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- c763abe9-bfe0-4d2e-935a-460d060a0ace
- true
- Digit Scroller
- TURN STEP
- false
- 0
- 12
- TURN STEP
- 2
- 0.0003419868
-
7974
28366
250
20
-
7974.39
28366.43
- fb6aba99-fead-4e42-b5d8-c6de5ff90ea6
- DotNET VB Script (LEGACY)
- A VB.NET scriptable component
- true
- a5d5a292-9ba5-4db7-87cc-0bb840e03f34
- true
- DotNET VB Script (LEGACY)
- Turtle
- 0
- Dim i As Integer
Dim dir As New On3dVector(1, 0, 0)
Dim pos As New On3dVector(0, 0, 0)
Dim axis As New On3dVector(0, 0, 1)
Dim pnts As New List(Of On3dVector)
pnts.Add(pos)
For i = 0 To Forward.Count() - 1
Dim P As New On3dVector
dir.Rotate(Left(i), axis)
P = dir * Forward(i) + pnts(i)
pnts.Add(P)
Next
Points = pnts
-
10116
28201
104
44
-
10171
28223
- 1
- 1
- 2
- Script Variable Forward
- Script Variable Left
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- true
- true
- Forward
- Left
- true
- true
- 2
- Print, Reflect and Error streams
- Output parameter Points
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- true
- true
- Output
- Points
- false
- false
- 1
- false
- Script Variable Forward
- 169a6bf9-7051-47c9-8af9-6d54359501ea
- true
- Forward
- Forward
- true
- 1
- true
- fafed710-e79d-472d-9b45-bedb0b22c125
- 1
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
10118
28203
41
20
-
10138.5
28213
- 1
- false
- Script Variable Left
- 2a3330da-d674-4b6a-a421-fc0cd3c74f7b
- true
- Left
- Left
- true
- 1
- true
- fcee0c3b-74ec-4be8-81f5-750eae6bcae3
- 1
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
10118
28223
41
20
-
10138.5
28233
- Print, Reflect and Error streams
- b03c6bec-85be-48be-b72b-ca5d2a557279
- true
- Output
- Output
- false
- 0
-
10183
28203
35
20
-
10200.5
28213
- Output parameter Points
- 770e8f58-8dfe-4f6f-905d-3f5cbadbdf1d
- true
- Points
- Points
- false
- 0
-
10183
28223
35
20
-
10200.5
28233
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
- true
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- true
- Point
- Point
- false
- 44cddb8b-ba4f-4eab-b3bd-08f5b804d82c
- 1
-
7924
27616
50
24
-
7949.7
27628.84
- dd8134c0-109b-4012-92be-51d843edfff7
- Duplicate Data
- Duplicate data a predefined number of times.
- true
- 3c11906b-2011-4aac-bb44-b0a8260f0bbd
- true
- Duplicate Data
- Duplicate Data
-
8623
28246
102
64
-
8686
28278
- 1
- Data to duplicate
- b9352246-308b-4a41-a51e-8d16471b4ff4
- true
- Data
- Data
- false
- c4650d06-e701-488c-9dbc-a658d92b263e
- 1
-
8625
28248
49
20
-
8649.5
28258
- Number of duplicates
- ba80eda7-39e8-4da0-85be-76dd9f3294e9
- true
- Number
- Number
- false
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- 1
-
8625
28268
49
20
-
8649.5
28278
- 1
- 1
- {0}
- 2
- Retain list order
- 25332cf5-26a4-42d3-83b4-0b5265331fcd
- true
- Order
- Order
- false
- 0
-
8625
28288
49
20
-
8649.5
28298
- 1
- 1
- {0}
- true
- 1
- Duplicated data
- 8b096aad-41f0-4c90-bdc2-44ece26f1604
- true
- Data
- Data
- false
- 0
-
8698
28248
25
60
-
8710.5
28278
- 797d922f-3a1d-46fe-9155-358b009b5997
- One Over X
- Compute one over x.
- true
- de29117b-9a5e-4a92-97ed-3c2864e3cbe8
- true
- One Over X
- One Over X
-
8392
28334
88
28
-
8435
28348
- Input value
- b7bef66a-1949-4a17-83b4-4eb52de9765c
- true
- Value
- Value
- false
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- 1
-
8394
28336
29
24
-
8408.5
28348
- Output value
- c4650d06-e701-488c-9dbc-a658d92b263e
- true
- Result
- Result
- false
- 0
-
8447
28336
31
24
-
8462.5
28348
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7b5f5b19-5616-42d8-ba58-288544f41550
- true
- Shift List
- Shift List
-
8770
28361
90
64
-
8827
28393
- 1
- List to shift
- aa9b1c36-5754-4429-b60c-d84826926824
- true
- List
- List
- false
- 1d9ca0e8-950e-46ce-8479-db13c1cd3229
- 1
-
8772
28363
43
20
-
8793.5
28373
- Shift offset
- b8123dc8-4417-4532-836d-1b3667eef304
- true
- Shift
- Shift
- false
- 0
-
8772
28383
43
20
-
8793.5
28393
- 1
- 1
- {0}
- 1
- Wrap values
- 712ba1ce-cc2a-4c2e-ab7f-c3dfb1e925db
- true
- Wrap
- Wrap
- false
- 0
-
8772
28403
43
20
-
8793.5
28413
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ed039296-6dd2-44c6-9e1a-c1e8dfc59069
- true
- List
- List
- false
- 0
-
8839
28363
19
60
-
8848.5
28393
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7f9d1c96-2fbd-4af5-9e4c-9dd734401acd
- true
- Shift List
- Shift List
-
8745
28255
90
64
-
8802
28287
- 1
- List to shift
- 9df69feb-1432-4fed-b436-f2fdcc9e6f5e
- true
- List
- List
- false
- 8b096aad-41f0-4c90-bdc2-44ece26f1604
- 1
-
8747
28257
43
20
-
8768.5
28267
- Shift offset
- 05577071-06fc-48b9-9ea0-95de0ac6cc56
- true
- Shift
- Shift
- false
- 0
-
8747
28277
43
20
-
8768.5
28287
- 1
- 1
- {0}
- 1
- Wrap values
- 1531b378-33ee-4cfb-96e9-50152c45e68c
- true
- Wrap
- Wrap
- false
- 0
-
8747
28297
43
20
-
8768.5
28307
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ab6779f5-8519-4c74-bf58-f285580cb58b
- true
- List
- List
- false
- 0
-
8814
28257
19
60
-
8823.5
28287
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
- true
- 6fcdde93-48bd-4eba-aff9-a0246408803c
- true
- Addition
- Addition
-
8658
28502
85
44
-
8698
28524
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for addition
- 66bca250-846f-4673-a9eb-159a32a2bd80
- true
- A
- A
- true
- 0
-
8660
28504
26
20
-
8673
28514
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 0
- Second item for addition
- 90e15842-1d83-4cd5-9f4b-9ba16be36eed
- true
- B
- B
- true
- 6a8dea11-5285-47df-9db4-ae7cd329914e
- 1
-
8660
28524
26
20
-
8673
28534
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Result of addition
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- true
- Result
- Result
- false
- 0
-
8710
28504
31
40
-
8725.5
28524
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 6fcdde93-48bd-4eba-aff9-a0246408803c
- 1
- 38226a8a-96d4-43f8-864a-454d3069644d
- Group
- POINT NUMBER
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7fac966d-75d3-4d85-b4ea-7a678a11276c
- true
- Shift List
- Shift List
-
10256
28203
90
64
-
10313
28235
- 1
- List to shift
- 53e4a544-1f0d-42c8-8181-edabc62890fb
- true
- List
- List
- false
- 770e8f58-8dfe-4f6f-905d-3f5cbadbdf1d
- 1
-
10258
28205
43
20
-
10279.5
28215
- Shift offset
- 8f9c061e-cd01-4348-99ea-9f0af62458bc
- true
- Shift
- Shift
- false
- 0
-
10258
28225
43
20
-
10279.5
28235
- 1
- 1
- {0}
- -1
- Wrap values
- ad18235a-a4ef-4d70-adcc-486461e889f1
- true
- Wrap
- Wrap
- false
- 0
-
10258
28245
43
20
-
10279.5
28255
- 1
- 1
- {0}
- false
- 1
- Shifted list
- db13a26a-6a2c-48a4-a5e3-a419afc7c1b7
- true
- List
- List
- false
- 0
-
10325
28205
19
60
-
10334.5
28235
- 9c007a04-d0d9-48e4-9da3-9ba142bc4d46
- Subtraction
- Mathematical subtraction
- true
- 8714601c-8d05-4922-a3e8-99ec5bee1bb8
- true
- Subtraction
- Subtraction
-
8243
28646
85
44
-
8283
28668
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- 2e5c86e5-e70a-4903-9d2b-95c6bcb6c57a
- true
- A
- A
- true
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
8245
28648
26
20
-
8258
28658
- Second operand for subtraction
- 6085835a-7965-4b8a-83c4-098ca7abca0e
- true
- B
- B
- true
- 0
-
8245
28668
26
20
-
8258
28678
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of subtraction
- ab54d613-8d13-4335-a8f4-c01221b4b1df
- true
- Result
- Result
- false
- 0
-
8295
28648
31
40
-
8310.5
28668
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- a7f6c94e-b5e4-4c5c-a6fc-1eb1aab9a9c6
- true
- Multiplication
- Multiplication
-
8240
28717
85
44
-
8280
28739
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- f18d75e7-d9af-44e1-bb5d-d0526569a9b0
- true
- A
- A
- true
- ab54d613-8d13-4335-a8f4-c01221b4b1df
- 1
-
8242
28719
26
20
-
8255
28729
- Second item for multiplication
- 80a36f12-5318-43fe-8a19-c5f8cea93e2a
- true
- B
- B
- true
- 0
-
8242
28739
26
20
-
8255
28749
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of multiplication
- b6aa70cd-ffce-47a3-a260-712054f216e7
- true
- Result
- Result
- false
- 0
-
8292
28719
31
40
-
8307.5
28739
- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- 5a82e036-1da3-46fc-bdb7-89e70238a8c5
- true
- Division
- Division
-
8649
28634
85
44
-
8689
28656
- Item to divide (dividend)
- 00d9aad6-1954-4e86-909c-12ed594c867c
- true
- A
- A
- false
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
8651
28636
26
20
-
8664
28646
- Item to divide with (divisor)
- 5971abd0-d534-469b-9280-deb118a30aab
- true
- B
- B
- false
- 0
-
8651
28656
26
20
-
8664
28666
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- The result of the Division
- 26ccf0cc-83e2-418a-8f4c-3a22dcee2db4
- true
- Result
- Result
- false
- 0
-
8701
28636
31
40
-
8716.5
28656
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
- true
- f3612ad2-8be3-46a2-b3c6-b260c7c8829f
- true
- Addition
- Addition
-
8768
28615
85
44
-
8808
28637
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for addition
- ae2bce56-0c27-47a9-845e-bcd3a3ec3adf
- true
- A
- A
- true
- 26ccf0cc-83e2-418a-8f4c-3a22dcee2db4
- 1
-
8770
28617
26
20
-
8783
28627
- Second item for addition
- 1f518679-1901-4e25-b47c-95c43779b806
- true
- B
- B
- true
- 0
-
8770
28637
26
20
-
8783
28647
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of addition
- 6ada5024-09f3-4903-bc95-bb9e58bfc140
- true
- Result
- Result
- false
- 0
-
8820
28617
31
40
-
8835.5
28637
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 69a46f6d-5884-4eb5-aed5-3b2d6e594ef6
- true
- Evaluate Length
- Evaluate Length
-
8094
27448
142
64
-
8172
27480
- Curve to evaluate
- ce38b61d-d6bd-4be1-9ba8-66ec9bf55379
- true
- Curve
- Curve
- false
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
8096
27450
64
20
-
8128
27460
- Length factor for curve evaluation
- 039927db-1f2e-44e5-822f-a8fc97e34554
- true
- Length
- Length
- false
- 0
-
8096
27470
64
20
-
8128
27480
- 1
- 2
- {0}
- 0
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 7005dea7-81ff-4270-bacf-d190d0643895
- true
- Normalized
- Normalized
- false
- 0
-
8096
27490
64
20
-
8128
27500
- 1
- 1
- {0}
- true
- Point at the specified length
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- true
- Point
- Point
- false
- 0
-
8184
27450
50
20
-
8209
27460
- Tangent vector at the specified length
- 72ce55c1-290d-4329-9208-b5c4d3190bc6
- true
- Tangent
- Tangent
- false
- 0
-
8184
27470
50
20
-
8209
27480
- Curve parameter at the specified length
- 930c51b6-8d37-4be0-9339-ccebaca39c9e
- true
- Parameter
- Parameter
- false
- 0
-
8184
27490
50
20
-
8209
27500
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 6a8dea11-5285-47df-9db4-ae7cd329914e
- true
- Relay
- false
- 6ada5024-09f3-4903-bc95-bb9e58bfc140
- 1
-
8455
28488
40
16
-
8475
28496
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- aaa5a334-801a-4f37-a832-229d9cc793e6
- true
- Relay
- false
- 236190cc-8c61-4e05-ad13-e2c8c13610f9
- 1
-
9169
28205
40
16
-
9189
28213
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- true
- Relay
- false
- 1fe668b1-ad7d-42fc-ba89-f43371616761
- 1
-
9144
28526
40
16
-
9164
28534
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fafed710-e79d-472d-9b45-bedb0b22c125
- true
- Relay
- false
- 08aafdf1-9cde-4d9a-a5c8-2f9081abd6d2
- 1
-
10036
28234
40
16
-
10056
28242
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fcee0c3b-74ec-4be8-81f5-750eae6bcae3
- true
- Relay
- false
- 58040f5e-60b6-45ff-8eaa-20ac9a1bc558
- 1
-
10076
28514
40
16
-
10096
28522
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 0675152f-f085-47f2-9154-4be9991ccfd5
- true
- Shift List
- Shift List
-
9327
28670
106
64
-
9384
28702
- 1
- List to shift
- 0a6f1940-14a0-4c11-8624-be6ebfe9a432
- true
- List
- List
- false
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- 1
-
9329
28672
43
20
-
9350.5
28682
- Shift offset
- ea53497d-2601-4b97-a4f1-ce79888ed6e4
- true
- Shift
- Shift
- false
- 0
-
9329
28692
43
20
-
9350.5
28702
- 1
- 1
- {0}
- -1
- Wrap values
- 1764e100-1227-4791-b676-d899f68c6060
- true
- Wrap
- Wrap
- false
- 0
-
9329
28712
43
20
-
9350.5
28722
- 1
- 1
- {0}
- false
- 1
- Shifted list
- c733a2e2-ed93-4f92-98e7-f6a908d64a92
- true
- List
- List
- false
- true
- 0
-
9396
28672
35
60
-
9405.5
28702
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 134af8dc-fd98-4279-ba9a-9b330f78353c
- true
- Merge
- Merge
-
9323
28608
106
64
-
9368
28640
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- a2d0a6fb-2703-40c6-af92-174831f5ba79
- true
- false
- Data 1
- D1
- true
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- 1
-
9325
28610
31
20
-
9340.5
28620
- 2
- Data stream 2
- f53a7097-cfde-42ef-b02f-408031044329
- true
- false
- Data 2
- D2
- true
- c733a2e2-ed93-4f92-98e7-f6a908d64a92
- 1
-
9325
28630
31
20
-
9340.5
28640
- 2
- Data stream 3
- 5c136c4f-69be-407f-a1b7-5e2fcf65926c
- true
- false
- Data 3
- D3
- true
- 0
-
9325
28650
31
20
-
9340.5
28660
- 2
- Result of merge
- 413ecb15-763e-4e83-90bf-3ffbecc8e2c0
- true
- 1
- Result
- Result
- false
- 0
-
9380
28610
47
60
-
9395.5
28640
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- true
- Relay
- false
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- 1
-
9362
28759
40
16
-
9382
28767
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fd8d01b6-550f-461d-bf89-7d885534636d
- true
- Relay
- false
- 413ecb15-763e-4e83-90bf-3ffbecc8e2c0
- 1
-
9358
28589
40
16
-
9378
28597
- 2576f657-2f0d-4e3e-9dfb-c79eb4cd13d7
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop Start
- Start the loop with this one. Double click to rerun.
- true
- ee8829f1-a69a-474f-ac63-380a98834db2
- true
- Loop Start
- Loop Start
-
10124
29784
118
84
-
10189
29826
- 4
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Number of repeats
- 3ca87afb-e6e9-4109-b4a2-70e62bad5866
- true
- Repeat
- Repeat
- true
- 0
-
10126
29786
51
20
-
10151.5
29796
- 1
- 1
- {0}
- 1
- 2
- If you want trigger loop to restart
- 48ad2736-1528-471c-914c-0958dcd53bf4
- true
- Trigger
- Trigger
- true
- 3dae4219-1a09-4c78-83fe-fafea0163300
- 1
-
10126
29806
51
20
-
10151.5
29816
- 2
- Contains a collection of generic data
- 6322e428-eca4-423b-a4b4-7a28c279addc
- true
- Data
- D0
- true
- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
-
10126
29826
51
20
-
10151.5
29836
- 2
- Contains a collection of generic data
- 10678145-91ad-4efa-b802-df158d8d0166
- true
- Data
- D1
- true
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- 1
-
10126
29846
51
20
-
10151.5
29856
- Connect to Loop End
- dba71230-81ce-4ad5-ad65-b40a07910eb0
- true
- >
- >
- false
- 0
-
10201
29786
39
20
-
10220.5
29796
- Counter
- 9d387d64-76a1-4df3-b7b6-8fa8c9cd26a9
- true
- Counter
- Counter
- false
- 0
-
10201
29806
39
20
-
10220.5
29816
- 2
- Contains a collection of generic data
- 6e3091e5-a7ac-4ae5-8dd8-482aad3c899f
- true
- Data
- D0
- false
- 0
-
10201
29826
39
20
-
10220.5
29836
- 2
- Contains a collection of generic data
- e5bf71f8-8f56-4764-8cb0-ff6b65c13310
- true
- Data
- D1
- false
- 0
-
10201
29846
39
20
-
10220.5
29856
- 15483310-2ce2-48c6-b803-9dee8cb7cc9b
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop End
- End the loop with this one. Double click to pause the loop.
- true
- 8e88c30a-54ad-4e0e-a86c-5a9cda0fd361
- true
- Loop End
- Loop End
- 0
- false
- Constant & Record
-
10327
29784
91
84
-
10372
29826
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- 2833f182-382c-4ec4-bab2-3c0ac238f8be
- true
- <
- <
- false
- dba71230-81ce-4ad5-ad65-b40a07910eb0
- 1
-
10329
29786
31
20
-
10344.5
29796
- Set to true to exit the loop
- 1f9ae913-365c-42e3-8e3f-cc69fed7e90b
- true
- Exit
- Exit
- true
- 0
-
10329
29806
31
20
-
10344.5
29816
- 1
- 1
- {0}
- false
- 2
- Contains a collection of generic data
- 3c417e2a-63b3-4784-bdb9-e29866396e66
- true
- Data
- D0
- false
- fa427076-9410-409a-a28f-ff2c773f6a9d
- 1
-
10329
29826
31
20
-
10344.5
29836
- 2
- Contains a collection of generic data
- 77f32577-d9af-4eb1-ada7-e225446be236
- true
- Data
- D1
- false
- fd8d01b6-550f-461d-bf89-7d885534636d
- 1
-
10329
29846
31
20
-
10344.5
29856
- 2
- Contains a collection of generic data
- fab7e2a7-7157-4003-b8e4-b15a9a4260d0
- true
- 1
- Data
- D0
- false
- 0
-
10384
29786
32
40
-
10392
29806
- 2
- Contains a collection of generic data
- 74f7012c-7fbd-4e26-8738-bbfa495bca3f
- true
- 1
- Data
- D1
- false
- 0
-
10384
29826
32
40
-
10392
29846
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 1d0c73ba-7b51-4bc7-8966-36d2b512a153
- true
- Shift List
- Shift List
-
9283
28075
106
64
-
9340
28107
- 1
- List to shift
- a78d97e7-8217-47e4-aa22-6304b88ce3d9
- true
- List
- List
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- 4eba5543-8aae-4c2a-972c-7fc31ea91b76
- 1
-
9285
28077
43
20
-
9306.5
28087
- Shift offset
- 850d7b43-afa3-4cf6-b5ca-c09fc145f711
- true
- Shift
- Shift
- false
- 0
-
9285
28097
43
20
-
9306.5
28107
- 1
- 1
- {0}
- -1
- Wrap values
- 010db27a-fcda-4212-a5d7-098305b3829a
- true
- Wrap
- Wrap
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- 0
-
9285
28117
43
20
-
9306.5
28127
- 1
- 1
- {0}
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- 1
- Shifted list
- 1cfa9398-84a0-4469-b446-2fb43cb74a8e
- true
- List
- List
- false
- true
- 0
-
9352
28077
35
60
-
9361.5
28107
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 305cdec8-fbd3-4861-bdfb-d54cf581c887
- true
- Merge
- Merge
-
9279
28013
106
64
-
9324
28045
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 8ab8be51-71e4-41b6-9171-f19d1d81d758
- true
- false
- Data 1
- D1
- true
- 4eba5543-8aae-4c2a-972c-7fc31ea91b76
- 1
-
9281
28015
31
20
-
9296.5
28025
- 2
- Data stream 2
- 03846402-d78d-4528-b02d-7e5dbe3e22be
- true
- false
- Data 2
- D2
- true
- 1cfa9398-84a0-4469-b446-2fb43cb74a8e
- 1
-
9281
28035
31
20
-
9296.5
28045
- 2
- Data stream 3
- c3a9f6af-05a9-4180-b959-03b902ced0ad
- true
- false
- Data 3
- D3
- true
- 0
-
9281
28055
31
20
-
9296.5
28065
- 2
- Result of merge
- 03d583ba-67b6-4697-afd1-3a5f24c931cf
- true
- 1
- Result
- Result
- false
- 0
-
9336
28015
47
60
-
9351.5
28045
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4eba5543-8aae-4c2a-972c-7fc31ea91b76
- true
- Relay
- false
- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
-
9312
28147
40
16
-
9332
28155
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fa427076-9410-409a-a28f-ff2c773f6a9d
- true
- Relay
- false
- 03d583ba-67b6-4697-afd1-3a5f24c931cf
- 1
-
9314
27994
40
16
-
9334
28002
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 6e5061e1-aa6f-42cf-93f2-4d449f23690c
- X/4
- true
- Number
- Number
- false
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
12656
28010
50
24
-
12689.63
28022.02
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
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- 25715f20-5ff7-4c61-9cc2-352c53d742af
- 3
- a0caceac-d6b4-4a28-9b82-8b165ea9f451
- Group
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
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- Panel
- X 1024
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- GraphMapper+
- External Graph mapper
You can Right click on the Heteromapper's icon and choose "AutoDomain" mode to define Output domain based on input domain interval; otherwise it'll be set to 0-1 in "Normalized" mode.
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- External curve as a graph
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- Curve
- false
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- 1
-
9229
29248
47
20
-
9252.5
29258
- Optional Rectangle boundary. If omitted the curve's would be landed
- b0339b52-7de2-4662-a003-50ccabe57648
- true
- Boundary
- Boundary
- true
- 915ca187-0684-4984-90e1-1f06c10f7133
- 1
-
9229
29268
47
20
-
9252.5
29278
- 1
- List of input numbers
- ce0ef573-9001-4e88-a7d9-d6c99e0ca0c1
- true
- Numbers
- Numbers
- false
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- 1
-
9229
29288
47
20
-
9252.5
29298
- 1
- 9
- {0}
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- (Optional) Input Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- 144027f2-4301-44ac-8786-7ab7b995b198
- true
- Input
- Input
- true
- f570df43-5009-430d-bfd1-27f65f985d30
- 1
-
9229
29308
47
20
-
9252.5
29318
- (Optional) Output Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- 0fb785c6-a8d7-4fe8-b1c6-d98c6ff80bec
- true
- Output
- Output
- true
- f570df43-5009-430d-bfd1-27f65f985d30
- 1
-
9229
29328
47
20
-
9252.5
29338
- 1
- Output Numbers
- d49245f3-5bf7-4e07-a2dc-594dca29df34
- true
- Number
- Number
- false
- 0
-
9300
29248
39
100
-
9319.5
29298
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- b129a78c-ce0b-4659-9392-e69777ed9c5c
- true
- End Points
- End Points
-
9180
29529
84
44
-
9224
29551
- Curve to evaluate
- 94a33f0c-dcb3-4361-ada3-e12df7594083
- true
- Curve
- Curve
- false
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- 1
-
9182
29531
30
40
-
9197
29551
- Curve start point
- 05980ff6-43ba-4938-bab8-2f2daec47ffe
- true
- Start
- Start
- false
- 0
-
9236
29531
26
20
-
9249
29541
- Curve end point
- 602db9d8-1f27-4fad-bab2-0fe9c4848923
- true
- End
- End
- false
- 0
-
9236
29551
26
20
-
9249
29561
- 575660b1-8c79-4b8d-9222-7ab4a6ddb359
- Rectangle 2Pt
- Create a rectangle from a base plane and two points
- true
- 31e437e2-63c4-4b78-aac5-4914c287fe8c
- true
- Rectangle 2Pt
- Rectangle 2Pt
-
9169
29398
198
101
-
9305
29449
- Rectangle base plane
- d5bfa5f9-7c76-478e-bc7a-ddb84429c3bf
- true
- Plane
- Plane
- false
- 0
-
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29400
122
37
-
9232
29418.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- First corner point.
- b818243e-e2de-44d0-af69-d029b2edee73
- true
- Point A
- Point A
- false
- 05980ff6-43ba-4938-bab8-2f2daec47ffe
- 1
-
9171
29437
122
20
-
9232
29447
- 1
- 1
- {0}
-
0
0
0
- Second corner point.
- 3f714117-1112-45d4-8770-7f2fa53939f9
- true
- Point B
- Point B
- false
- 602db9d8-1f27-4fad-bab2-0fe9c4848923
- 1
-
9171
29457
122
20
-
9232
29467
- 1
- 1
- {0}
-
10
5
0
- Rectangle corner fillet radius
- b4a33b7f-64f6-466a-acf2-773dc5713387
- true
- Radius
- Radius
- false
- 0
-
9171
29477
122
20
-
9232
29487
- 1
- 1
- {0}
- 0
- Rectangle defined by P, A and B
- 915ca187-0684-4984-90e1-1f06c10f7133
- true
- Rectangle
- Rectangle
- false
- 0
-
9317
29400
48
48
-
9341
29424.25
- Length of rectangle curve
- 1a0fa2db-8b1e-4c0c-a25e-46189cdeb411
- true
- Length
- Length
- false
- 0
-
9317
29448
48
49
-
9341
29472.75
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 54581da1-580d-4778-93ab-674f6e734ffb
- true
- Bounds
- Bounds
-
9069
29163
110
28
-
9127
29177
- 1
- Numbers to include in Bounds
- 61e1cd32-b63d-4ebe-90d8-1f22e5dfdbcf
- true
- Numbers
- Numbers
- false
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- 1
-
9071
29165
44
24
-
9093
29177
- Numeric Domain between the lowest and highest numbers in {N}
- f570df43-5009-430d-bfd1-27f65f985d30
- true
- Domain
- Domain
- false
- 0
-
9139
29165
38
24
-
9158
29177
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- true
- Number
- Number
- false
- 8b9ef3ba-f24f-4ab0-8eee-d5332f1092f5
- 1
-
9026
29257
50
24
-
9051.664
29269.73
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- true
- Curve
- Curve
- false
- 082832c7-f80b-4ab0-8cec-39daa2c6ee5b
- 1
-
9111
29608
50
24
-
9136.482
29620.62
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- db0c3f90-16aa-4bcb-ae4f-fc0bbeaa378f
- true
- Relay
- false
- ed039296-6dd2-44c6-9e1a-c1e8dfc59069
- 1
-
8900
28423
40
16
-
8920
28431
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 3dae4219-1a09-4c78-83fe-fafea0163300
- true
- True Only Button
- false
- 0
- neutral,N
-
9789
29811
66
22
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 236190cc-8c61-4e05-ad13-e2c8c13610f9
- true
- Relay
- false
- ab6779f5-8519-4c74-bf58-f285580cb58b
- 1
-
8834
28216
40
16
-
8854
28224
- 7cd2f235-466e-4d30-bd3c-3b9573ac7dda
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Fast Loop Start
- Loop Start
- true
- 6a0427dd-97fd-412a-be12-fe9558ccba8b
- true
- Fast Loop Start
- Fast Loop Start
-
9137
28323
127
84
-
9211
28365
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Loop iterations
- 62d27cfd-3b3f-45e5-aa28-62ccbed2e6b1
- true
- Iterations
- Iterations
- false
- 0
-
9139
28325
60
26
-
9169
28338.33
- 1
- 1
- {0}
- 1
- 2
- Contains a collection of generic data
- ed77f663-0b90-457c-afea-47cc55fafb50
- true
- Data
- D0
- true
- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
-
9139
28351
60
27
-
9169
28365
- 2
- Contains a collection of generic data
- 6157358f-b6ed-4b5e-b7de-1f696efcd3a7
- true
- Data
- D1
- true
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- 1
-
9139
28378
60
27
-
9169
28391.67
- Connect to Loop End
- 6dea6cc4-dc4e-4113-9e42-6c3693b206af
- true
- >
- >
- false
- 0
-
9223
28325
39
20
-
9242.5
28335
- Counter
- daaf5468-a976-4ef0-a518-fb036bd9cf70
- true
- Counter
- Counter
- false
- 0
-
9223
28345
39
20
-
9242.5
28355
- 2
- Contains a collection of generic data
- b601bd0c-ff52-4987-a6d9-cb9fc1bcc354
- true
- Data
- D0
- false
- 0
-
9223
28365
39
20
-
9242.5
28375
- 2
- Contains a collection of generic data
- 8c825e90-4b27-4bb3-9e7f-bcb80b27812f
- true
- Data
- D1
- false
- 0
-
9223
28385
39
20
-
9242.5
28395
- 4e5b891f-3e8d-4b3d-b677-996c63b3ac70
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Fast Loop End
- Loop End
- true
- aaea4aad-2963-4409-84b7-3990db27a71b
- true
- Fast Loop End
- Fast Loop End
- true
- 0
-
9432
28312
91
84
-
9477
28354
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- c3bc5aa8-1b46-4010-93bf-b4a248668950
- true
- <
- <
- false
- 6dea6cc4-dc4e-4113-9e42-6c3693b206af
- 1
-
9434
28314
31
20
-
9449.5
28324
- Set to true to exit the loop
- 2e52e7cf-2d99-4181-98d0-2711d19de7de
- true
- Exit
- Exit
- true
- 0
-
9434
28334
31
20
-
9449.5
28344
- 1
- 1
- {0}
- false
- 2
- Contains a collection of generic data
- 2355d77a-2930-4385-a1dd-414f4809c4c9
- true
- Data
- D0
- false
- fa427076-9410-409a-a28f-ff2c773f6a9d
- 1
-
9434
28354
31
20
-
9449.5
28364
- 2
- Contains a collection of generic data
- d95e8708-b9cf-4d9a-945e-5db46367d6c9
- true
- Data
- D1
- false
- fd8d01b6-550f-461d-bf89-7d885534636d
- 1
-
9434
28374
31
20
-
9449.5
28384
- 2
- Contains a collection of generic data
- 15aa5336-9858-4ec6-beda-c3a2d7f52046
- true
- 1
- Data
- D0
- false
- 0
-
9489
28314
32
40
-
9497
28334
- 2
- Contains a collection of generic data
- d7b42618-d2bc-436a-98d5-a8857d8b2666
- true
- 1
- Data
- D1
- false
- 0
-
9489
28354
32
40
-
9497
28374
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 1fe668b1-ad7d-42fc-ba89-f43371616761
- true
- Number
- Number
- false
- fb5477b8-182b-46c5-ac57-f253eb9baed8
- 1
-
9514
29273
50
24
-
9539.742
29285.28
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e62a82d8-3c92-4e2a-9aca-b526644e6c8b
- da33a5bd-afb6-4917-a2ad-7b78b6875928
- a962b382-2559-410e-b76c-266d28450a4a
- 3
- ac124fdd-467b-493a-8722-fa10321d6afc
- Group
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 0f23777f-356c-47ca-b703-f6f1e543bf2d
- true
- Panel
- X 128
- false
- 0
- 0
- 0,1/128,1/64,3/128,1/32,5/128,3/64,7/128,1/16,9/128,5/64,11/128,3/32,13/128,7/64,15/128,1/8,17/128,9/64,19/128,5/32,21/128,11/64,23/128,3/16,25/128,13/64,27/128,7/32,29/128,15/64,31/128,1/4,33/128,17/64,35/128,9/32,37/128,19/64,39/128,5/16,41/128,21/64,43/128,11/32,45/128,23/64,47/128,3/8,49/128,25/64,51/128,13/32,53/128,27/64,55/128,7/16,57/128,29/64,59/128,15/32,61/128,31/64,63/128,1/2,65/128,33/64,67/128,17/32,69/128,35/64,71/128,9/16,73/128,37/64,75/128,19/32,77/128,39/64,79/128,5/8,81/128,41/64,83/128,21/32,85/128,43/64,87/128,11/16,89/128,45/64,91/128,23/32,93/128,47/64,95/128,3/4,97/128,49/64,99/128,25/32,101/128,51/64,103/128,13/16,105/128,53/64,107/128,27/32,109/128,55/64,111/128,7/8,113/128,57/64,115/128,29/32,117/128,59/64,119/128,15/16,121/128,61/64,123/128,31/32,125/128,63/64,127/128,1
-
7620
29318
160
100
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7620.861
29318
-
255;255;255;255
- true
- true
- false
- false
- false
- false
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- eb4824b9-1b6a-4da7-afef-ca0073312fbf
- true
- Text Split
- Text Split
-
7837
29334
127
44
-
7919
29356
- Text to split.
- 162bd387-789a-4a1e-b1e2-dff8ebe83834
- true
- Text
- Text
- false
- 0f23777f-356c-47ca-b703-f6f1e543bf2d
- 1
-
7839
29336
68
20
-
7873
29346
- Separator characters.
- 6307c6e9-babd-4a85-bb23-641ced7a1e15
- true
- Separators
- Separators
- false
- 0
-
7839
29356
68
20
-
7873
29366
- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- d975738e-73d2-4393-a83a-2b9bf445bd2e
- true
- Result
- Result
- false
- 0
-
7931
29336
31
40
-
7946.5
29356
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 2d00a82a-689f-4535-a590-6ea8f4f00616
- true
- Panel
- Y 128
- false
- 0
- 0
- 0,583/179789679820800,1153/561842749440,10997359/179789679820800,19/33177600,105664189/35957935964160,29407171/2809213747200,5264015321/179789679820800,143/2073600,25686901721/179789679820800,753352771/2809213747200,16748792509/35957935964160,25219/33177600,211860341359/179789679820800,983043073/561842749440,450217958983/179789679820800,1/288,842215449017/179789679820800,3467317247/561842749440,1431724785041/179789679820800,334781/33177600,452428920131/35957935964160,43445431229/2809213747200,3373656816679/179789679820800,46657/2073600,4798686576679/179789679820800,88063341629/2809213747200,1311836172611/35957935964160,1396781/33177600,8666608497041/179789679820800,30786738047/561842749440,11124681522617/179789679820800,5/72,13933895269817/179789679820800,48344323967/561842749440,17094249738641/179789679820800,3470381/33177600,4121049919811/35957935964160,351427130429/2809213747200,24463182807079/179789679820800,305857/2073600,28656580541479/179789679820800,482385079229/2809213747200,6632699163971/35957935964160,6555581/33177600,37951503498641/179789679820800,126370418687/561842749440,42980421657017/179789679820800,73/288,48206851661383/179789679820800,159001316353/561842749440,53586921538159/179789679820800,10393219/33177600,11815446530749/35957935964160,966420578371/2809213747200,64637603087321/179789679820800,777743/2073600,70235607695321/179789679820800,1141272491971/2809213747200,15169859899069/35957935964160,14515219/33177600,81467209666159/179789679820800,263363789953/561842749440,87085626163783/179789679820800,1/2,92704053657017/179789679820800,298478959487/561842749440,98322470154641/179789679820800,18662381/33177600,20788076065091/35957935964160,1667941255229/2809213747200,109554072125479/179789679820800,1295857/2073600,115152076733479/179789679820800,1842793168829/2809213747200,24142489433411/35957935964160,22784381/33177600,126202758282641/179789679820800,402841433087/561842749440,131582828159417/179789679820800,215/288,136809258163783/179789679820800,435472330753/561842749440,141838176322159/179789679820800,26622019/33177600,29325236800189/35957935964160,2326828667971/2809213747200,151133099279321/179789679820800,1767743/2073600,155326497013721/179789679820800,2457786616771/2809213747200,31836886044349/35957935964160,29707219/33177600,162695430082159/179789679820800,513498425473/561842749440,165855784550983/179789679820800,67/72,168664998298183/179789679820800,531056011393/561842749440,171123071323759/179789679820800,31780819/33177600,34646099791549/35957935964160,2721150405571/2809213747200,174990993244121/179789679820800,2026943/2073600,176416023004121/179789679820800,2765768315971/2809213747200,35505507044029/35957935964160,32842819/33177600,178357955035759/179789679820800,558375432193/561842749440,178947464371783/179789679820800,287/288,179339461861817/179789679820800,560859706367/561842749440,179577819479441/179789679820800,33152381/33177600,35941187171651/35957935964160,2808460394429/2809213747200,179763992919079/179789679820800,2073457/2073600,179784415805479/179789679820800,2809184340029/2809213747200,35957830299971/35957935964160,33177581/33177600,179789668823441/179789679820800,561842748287/561842749440,179789679820217/179789679820800,1
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7619.861
29439
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255;255;255;255
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- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- fa29e628-2090-4c46-8c09-20615141542c
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
-
7492
30733
196
28
-
7635
30747
- Uri of file to read
- false
- All files|*.*
- b9508b12-2cc1-4f4d-9ca6-7f22a30c05a5
- true
- File
- File
- false
- 0
-
7494
30735
129
24
-
7558.5
30747
- 1
- 1
- {0}
- false
- C:\FABIUS 4096 X.TXT
- 1
- File content
- 12097910-805a-4ef6-998c-9e5ce5b09bc2
- true
- Content
- Content
- false
- 0
-
7647
30735
39
24
-
7666.5
30747
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- 51570009-3d5d-4bbd-b8b1-bdfbbf85115e
- 0da2aad4-444e-4d52-8274-d2fb3e5aaf1f
- 3
- f9dde7c6-699c-440c-a632-c24a8eefd133
- Group
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- b761c393-2730-4efa-a305-9443ef7597fe
- true
- Text Split
- Text Split
-
7899
30747
127
44
-
7981
30769
- Text to split.
- c7fab27f-5725-4cd5-8379-6b7d5e760f4d
- true
- Text
- Text
- false
- 8a536d62-0be0-4943-a59f-2d6466d0d509
- 1
-
7901
30749
68
20
-
7935
30759
- Separator characters.
- fd51762b-3e12-4500-b43e-6405505e5163
- true
- Separators
- Separators
- false
- 0
-
7901
30769
68
20
-
7935
30779
- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- true
- Result
- Result
- false
- 0
-
7993
30749
31
40
-
8008.5
30769
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- 364a8efd-eec6-404f-ab5c-e6e2078d6eb8
- true
- Text Split
- Text Split
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- Text to split.
- a662be09-6078-4b5f-8ec5-951f3dbe5db4
- true
- Text
- Text
- false
- b055e58f-3b57-49cf-ab76-33835accf6a7
- 1
-
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- Separator characters.
- c61c81d3-8364-4e61-85b5-46af31dd582e
- true
- Separators
- Separators
- false
- 0
-
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- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- true
- Result
- Result
- false
- 0
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- 87091d69-a60b-4a19-842b-a866901fe24c
- true
- Concatenate
- Concatenate
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- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- First text fragment
- b12325ed-1f6b-4983-bb39-a82a446015b6
- true
- Fragment A
- Fragment A
- true
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- 1
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- Second text fragment
- 0a3b9102-73a4-4b03-8763-e99531cb10ba
- true
- Fragment B
- Fragment B
- true
- eeaadcbc-e19f-4e7d-ad8f-797c7c321297
- 1
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- 1
- 1
- {0}
- false
- *65536
- Resulting text consisting of all the fragments
- 428b4b1c-8794-4258-a90a-711dd03be945
- true
- Result
- Result
- false
- 0
-
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- afc5ea2b-b28a-4c04-a477-8796a5939be3
- true
- Concatenate
- Concatenate
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- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- First text fragment
- 097ed67d-2e7b-4914-bdf3-f02afc65acc5
- true
- Fragment A
- Fragment A
- true
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
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- Second text fragment
- c4d40302-5b1d-42ec-8eac-05a22e88299e
- true
- Fragment B
- Fragment B
- true
- eeaadcbc-e19f-4e7d-ad8f-797c7c321297
- 1
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- 1
- {0}
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- *65536
- Resulting text consisting of all the fragments
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- true
- Result
- Result
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- 0
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- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- true
- Construct Point
- Construct Point
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- {x} coordinate
- 7fcc7372-e36e-4d5c-87d6-b659a531b31f
- true
- X coordinate
- X coordinate
- false
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- 1
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- 1
- 1
- {0}
- 0
- {y} coordinate
- b1fc1dda-00d4-451d-a8be-115616047918
- true
- Y coordinate
- Y coordinate
- false
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
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- 1
- 1
- {0}
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- {z} coordinate
- f2f55175-b244-43ae-8da9-079ef747bf7d
- true
- Z coordinate
- Z coordinate
- false
- 0
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- 1
- 1
- {0}
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- Point coordinate
- 1aaece72-b107-4823-9e6c-ca26b6b9397c
- true
- Point
- Point
- false
- 0
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- 1
- 51570009-3d5d-4bbd-b8b1-bdfbbf85115e
- Group
- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- 0da2aad4-444e-4d52-8274-d2fb3e5aaf1f
- true
- Construct Point
- Construct Point
-
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- {x} coordinate
- 510af284-b3c7-4070-a1be-cd410899d051
- true
- X coordinate
- X coordinate
- false
- 428b4b1c-8794-4258-a90a-711dd03be945
- 1
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- 1
- 1
- {0}
- 0
- {y} coordinate
- c44d4c56-b7dc-4b23-9a1a-7d69b7d37585
- true
- Y coordinate
- Y coordinate
- false
- 3ce54405-e2d2-4a5e-ac72-d0e4f4ca3f26
- 1
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- 1
- 1
- {0}
- 0
- {z} coordinate
- a7b31229-98f5-4b91-af59-735fbc1070e3
- true
- Z coordinate
- Z coordinate
- false
- 0
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- 1
- 1
- {0}
- 0
- Point coordinate
- dc56eb11-1ba6-4fdc-9332-a1688428a3bb
- true
- Point
- Point
- false
- 0
-
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- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 213f2fc8-3c62-4add-b084-ae87fdec816f
- true
- Panel
- false
- 1
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
- Double click to edit panel content…
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255;255;255;255
- true
- true
- true
- false
- false
- true
- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- 149afc02-a382-4ca6-9322-7a4f060b8f7f
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
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- Uri of file to read
- false
- All files|*.*
- 4e906bfc-2333-4718-8a8b-42b774beb5db
- true
- File
- File
- false
- 0
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- 1
- 1
- {0}
- false
- C:\FABIUS 4096 Y.TXT
- 1
- File content
- 3d097a6b-53b5-4f50-b948-3a177d2c8203
- true
- Content
- Content
- false
- 0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Data
- Contains a collection of generic data
- true
- b055e58f-3b57-49cf-ab76-33835accf6a7
- true
- Data
- Data
- false
- 0
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- {0;0}
- Grasshopper.Kernel.Types.GH_String
- false
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- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- f2aa309b-3dac-4084-aa45-453eaa9db884
- true
- Curve
- Curve
- false
- 0
-
8832
29645
50
24
-
8857.633
29657
- 1
- 1
- {0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0}
- -1
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zNx5PFR7/PjxsZQWsqRoNbRQylIJLd5jKUqFVi1qKJESKkmUiUJa0II2BhWpLEmEMpbQZt/XsY6dimj/zb33fc/H73sfv39+f3390fOe1zlnzpmzfObMIzeaAI1G+8P/+cu/fkQF+X/s2Gx76KiDvoO9vcPRRfTt1seOH3I4ulpTRX2pyhL1pcu0+P+hpqa+iK7vfOSE8zHr1UetnU8cszyyiG7qbHXk0H5ja9etDoetj67W0FiyREvdWltzv6aGhsZStTF/bUX27xdXMbR2sLc+ccxVxdThiKu+87GT1sL8mSIn/9nYBMtj+20PnbReesB+vIOj9dGjzsesjgsfsDxh+ddC48aNE/xrPyUUabQlfK//nCg6Xoj/H+J//VF+nkYT/O4hSHt7/p/39OOPIE0a3x+3rHKTYWepZEYbTcJLQGEgZmih70/+/EBcVkKY9j9/BuA/6Z+e8T/LmP8so8b4RwZqhJoy/trBX/T/7uA0ybi9ZhPLJDN+/7OD66e7yvy1g29wWQkhXPCvHRX697T9/+zsf9b9nz/x+FocNB8tQsvQKrQO5aLNaCvajnagXWgP2gf/93v4hH5Gv6CD6BD6FR1GR9Bv6Hf0B/oT/YX+Rv/8e+wYf//JQmkCOI3SBHEapQnhNEoTxmmUNganUdpYnEZpIjiN0sbhNEobj9MobQJOo7SJOI3SRHEapYnhNEqbhNMoTRynUZrEPzJQFspBaZI4H2WhHJQmhfNRFspBaZNxPspCOShNGuejLJSD0qbgfJSFclDaVJyPslAOSpPB+SgL5aA0WZyPslAOSpuG81EWykFp03E+ykI5KG0GzkdZKAelzcT5KAvloLRZOB9loRyUNhvnoyyUg9LkcD7KQjkojf6PdJSBMlEWykY5KBelyeP6KANloiyUjXJQLkpTwPVRBspEWSgb5aBclDYH10cZKBNloWyUg3JR2lxcH2WgTJSFslEOykVp83B9lIEyURbKRjkoF6XNx/VRBspEWSgb5aBclKaI66MMlImyUDbKQbkoTQnXRxkoE2WhbJSDclHaAlwfZaBMlIWyUQ7KRWkLcX2UgTJRFspGOSgXpSnj+igDZaIslI1yUC5KW4TrowyUibJQNspBuShtMa6PMlAmykLZKAflojQVXB9loEyUhbJRDspFaaq4PspAmSgLZaMclItSDy3E/z5nkJ+t7o6RsuYa/3nu0LG4cVpK0BTMFujZL5tou+rfzvi7M0Gp9Vbjx/EX0v/t9ZcakmcI2cL1zDch0y9G/o/lHcFszofUM1pZ1PL+J7SnBQueAK08kOz5w6WWb/j7dU7BmAnzD+en/KGWV4n02s4WcoeZkr873oXMWv1vh79fnwVn4o2tdO6tfPVv53W0v90q6AmHCtMSE7J3rv6/t3serKSDP9aPP0Utr0m7bFst6A32O3Y/i7APopbn/r0/vqDUfq5cuPc5tfwFGXWRvUJ+kKC2J2ahdym1vNrf+3kZTKSELXZpfqaWr1CpeNAsdBUMTPY+G/4tofNv1/17/wOgdIkf/d6xeVSXilwdsVQwELqjbRjp8hpU/+d9XQPFFfEBT7T0qP5CJeCTs+B1WCx+B2I3b6S6z9/v9wZckspY++r8dqqbpTYzUgRvQqKagtayF0yqT/77OATB9ONntibMtaX6uzUaAd8Fg0G1OvhQsZgT1Q/+fXxCQPTMY63ECBeq1xf5NK4SugVeRkOx9BksqstO/eu43QbJpV9elYVdoPrXXTUqHkJ3QCimZeOX+5epzgj763jehb1dFd/tXl2jenzzorOZQvcgMuva/HKdEKo3zv3rOIfCgikvbmpMDKP6cmuPj0LCYfAgQTX0a2wk1U+b/XX82TB7osf7hvRoqnv12U6a48kGN19eRURZLNX/+P51XsLBfj8jt1E8kerf5KSWG3iGg2RNAmfSwWSqL3v21/mKgM9Pl7xR9E4n51cnzcLaMwLEogUMBtdkUv1Mpj//PEbC95kSwsXvcqherH3ggrdnJBx7Ws5Wbs6nekKkFv/83oeuz2fje+99pHrvd9GnUZ73gb7udGGabzHVjVc08c/7A9gxKf5UZXQZ1XftTirL93wAFj7RIxdWVFFdZftF/vXwELKu+5qVrquj+iJ5i5+dng/hmW9IWpETl+oP4tX410kUMFfd+VYxoYXqQV+F5k70igKJffIXjYfbqK7VXMG/fqKhrbbIeECnk+p++x4ZL/KKhqCZNd9/dPZQ/ct2N/519QhOBuUIXmUNUD3wyYbjG70egU6C3LS03M9UL4BZ/OstBsr05gls2zBE9YCunttHvWLA0nWox3bqCNWjWGn86/AxGJQGDesu/EH1wQLfLH+vx6DmOnLu0JXfZLu3t/KvzyfwS2tleqmCABlH2bO74r2ewNEAJb1zi4SoLnat/Uym0FPIE7abyj04huq1sk8kS7yewg6jH85LykWonlJ0lH89x8K+nvGzak5PoHqzkYr2F69YSJAbXme+W4zqDMGuD0LCceAZs79x/moJqn+zD2dKn48DI6U+5qteSaoLfF3Av/7jYbuztv++zMlUzzxAy5muFw/6yy5LiaVOofq1sFKxOZ7xEPlecnt5tQzVEzQjdyhnxUNioIxvpcJ0qq97djR8qWAC5D5cfVsveCbVz/hodK/US4DCr8d1t2nLUX2L/PAyA88EaFN7+T12jDzVo2uend2QlQCb3K+51PsoUP3XL5v8rYLPQKz2kZT93LlU18mZImWh9wwEjLZF3q2bR/XALWm7rT2fgfDhaVXPEhSp3vRqxwP7rGfw7vN91d/3F1D93p/OPmfBRDiRNKW/LFmZ6qq/HbXO6iXC1OVyU252L6a6p3f3OW/PRBgj1Ti3hK5G9bPG5u+vZiXCGR+5tmQLdapbtyZJBws+Bz1emtLyp0uorvxecG+Y3nNIPyv1e4LEMqpn7VodFeX5HAySEqVHvMnntuXH/QNxWc+h41z84ywpTaonrjihnSKYBDuivp9Z+lyLXJ9BRzw5eknASmx4MvXICqrvfrL+fb5nErgcfRS9cuUqqscoiEoXZyWBTmSwjLOCDtXzj8fuqRZ8AQ70UIsNkgyqe/epPGjSewHq89fFwGxdqr9I9Ovt9HwBvf2n9T219Kiu9Py1xuesF3AilW7hxdQn5z0278x3wWRgHJt3NjHIgOqDiyPeCOonQ/bgd8fztWuonuS9XmyiVzI4GAsvO6RqSHWn8vStk7OTYdvNgc7ya0ZUd/k5eGeGUAq4JIq/g7HrqV4R3tc8Rz8F3g7cl5jlZ0z17YsfLFjklQLmXK3+1tkbqW6eO9lxWXYKdAZ3uYu/2UT1djONF6uEXoJaErPUT8eU6v6Owj8N9F/Cl2CBgJQ5ZlT3cnfT3ejFX37EeMEmqc2j7pcb3tuyX0Lz4jeKFydsoXq1+br3FkKpkOVXvy9KdCvVHxy+Ln5QPxU+Fzt2tctuo3p4z+EtR71SQYnpPstbdTvVWSnvg05mp0Ky9fQL2aY7qF6y83H1WaE0yJcvrqt3N6e6hYjQTB/9NHgbrT9e+vlOqs+KeGfh75UGPvYmUg++7qL6lcRvocHZaVB0IXRWkcEeqr887NMYJpQO340TD5WFWlD9RpidXLR+OgRccFj3SXgfuW7zbu2N90oH/8qJEokrmeR++THhXkp2OpRrdapo/yA9aDCxhiP0Cpy6zV4vzLSkusN4P5m3+q9AzeDT2agrVlR/pOy5pdjrFdiFSC4rZO6n+iJewNXq7FfQ4fI2InPFAbI/zJj8JqHXIKq9OzB0hjXV3UyzBLr0X0OxOSf3gtBBqu8S+aD92es17N6/c0LwZ9J51qmO37NfQ0Fq6pzPHTZUn9zg8VBQOAMmF16tedFuS/XbjpNqJxhkgEqg91fhnkNUn/p4x6TJ5zMg3H4L/Byxo7rCww2MGTkZsPBXpHu62BGqpwo4pEgKcsA0Ys5J64X25P4a+lU4RYEDN51Pf5lqcpTq9WPft0/T48DglI3pA24OVF/98ePPWVYc2LRu9oaL5o5Uvx/xS1LBkwMDAscVNw2T7sg2mz8/ggO2t/tLt992onpNKEd7YRYHZqw310jUPUb1sct0N6g0c2BqgZXq8V7Spye+tVgimAnlZ6IePLx3nOoGyqZHlytkwpWHPm4Wm09Qve3guzMr9DJB6uSYG1ETnake0rX4so5VJhxmXyy+8Zb0I4MOt/Q8M+HA9OtTNC6fJJ+bbhcerI3IhI5HGxkhW1yonrtof/z6rEwojhdVK5A7RXVw+PVyU3Mm0I9Gc9oHSN++1yhrs2AWxKWlv/uU60r15+81325XyALN2nyFP+Gnqa6tk1GwSy8Llmqphcz2dCPjw6fikr1WWRAvN3Nwn407+Xwptyq38swC5SCdkRKzM1QvvHKg4mBEFtwoP2nho3uW6puPvS23y8qC93fMSy4v96C67FWv0qPNWTBh7gd3V1kW1d+EnS88JpgND9erPj8QQrr/tNdvTypkA/uRfon4jHNUXyMvn3VaLxs+2tsEerJJZweEppy1yoZxYq4ROUqeVD83NP+pp2c2THdsflyfSLr5tZgw74hs0OtnG5XrelE9bu+0AL+sbOg5ZyySWDKqi+w/e7U5G5bLyh46e/A81SsHTtpdE8yBp4+5XJ1fpL9cZrA1SCEHRIyUSn4EXSDPCQ9errytlwPWs+kB6Uu9qZ5W+IYeapUDMx882eNbSnr88HahCM8cmFNlZ3PwpA/V9WfvbnkQkQN+9UkfLGb6knGVxuE8ysoBRtjTG85vSA+SPX7naXMOxGyDZ8+dLlI9g215PEHwDew5qC6oIO9HddPrp4ySFN5A1ppl63NKSZ/69P70l3pvgLX8u2bExUvkefJoSWe61RtQK97BzNK7TK43ub4kjucbyFzsoKP8h/QVH1rO5kS8gdhdvCUtr69Q/eDGMIP8rDeQfU7da+DcVXIe14iKfGh+AxUJdeY7jfypHjB3am6hYC6csXfnSo4PIM8tC6LPlSrkwu7QnPIYB9KVrZ9qV+rlwkVlL+fvlaTrpUr01Vjlwvenw7eE9ALJeNuUHtrgmQuuvhqT3j4lvezQXePmiFyALz+ubJxxjeqS6bcG27Jy4azlzTfX/Ug/OCPsVmdzLkh9fGUW+oN02eigFb2CeZAK/hkOR69T3djSrnJAIQ8G8o9fntBC+uf5wo6DenmQ/XXGfKedN8j+pG0UHrHKgyv1p7oeFJNun6d244dnHjzKSFF8bHyTfO5UBcn9iciDb65rZnrlke554NBDwew8uP4z+6vqmiCqPysIVBrbkgccI+mKxBzSJay/PRgvlA8ikWZvJdYGU32i9cXZYnPyob+4pNDoLenDPxdek9DPh0t7FlZbbAqhusmmPJr0/nywz5v/xqyc9FcOhnYyXvmwuqJk//y9t8h5cbhRMD0yH153OzvXd5CevzV48ezsfJj75kbMKefbVD81R9tHviUfQn9/jvwmdIfqH+qsaucKvYXLY4I+W94gfavnrwVKc97C+DXvZBLn36V6v8znY8r6b8H5hPKFvlTShx8seKGy/y1ofY+/O8XsHtXXrbzyRd3rLSzcnBG/oJP0nf1jlDUi38LhLSC8yCuU6qKt7nu0st+CoWT6u1lyYVR/aFjrs7LlLbg2+SjRXpF+ZPuEpzpC74B59MQ0OxU2uX/3fHmvO+cdFJ+bf2qjB+lHXni0Gui/A/GJ+k8WFpO+uSzkq+H+d6Aa4L1QcG441ddrKwkae72D7XUPmWUupDPPyIhsinwHB+zdk8I/jFp+k+kYs+x3IBOketFOIYLqCxzTf25peQeb5hzSUHUlfebrNb3bhd7DJU1vsYEi0jkLKyp2znkPLt8K9j5dEEn1A5wdL/fov4eayDhHGy/S14U/v7Fv/3tIOPPl/OwG0u+JVNpaeb2HHl2BqhLt+1Q/tOaRhnXke/C6IBt+Poj0vTlTfthkv4djqf5SywZJvzRG5KVdy3t4fl5qV9PmB+Q5h23jYC/0AXLVuezLz0ifukZhtuOcD+C0YoLo8skPyXX1Qv7NMf0PoP/mWXr9CdLXFJgecN7/ARKUjIu8Kknnnb79w8XrAwzalTCVVkZRvehVp9/pyA/g82LyhfdhpCs9XiB1JvsDHHjUamo/JprqobZrAj1aPkCYyf5ysSOk71ikNM5T6CP0uy+Vf1pKevTKVyfPz/kIJnPSGMarHlG9r7O/zlv/I0hrWOh0PCB9ZfDjFRf3f4TYW88UzkvEUF0urtb/ktdH+JnGGZztTvrhqMN1VyI/wlfG4tSUDtJLfq+lB2R/hEavoy5m2x9TfWTlzt3XWj7C7ssjqp05pE/ruXLlhlABmGw82O6x7Al5Xo0oehE0pwA+Tg67O+UB6XFDopUh+gUQPmNkS8zUp+R8ear03d5fAPFGm8V0LpLOaaP/vOtVAJwxy94W/SR9a2YhLSyyAGpMG32snGKprpM8/yc7uwCiJxxY96Wd9MmHJfsiWgpA9XmsmJdFHNW3nHOruC9UCIpN18sky0n/Hmqa9HBOIRzb21NQOD+e6qxD7n7R+oWQ43t3WdB+0qW9u7bF7C8ErwiNGXVs0p/f8ZZ54lUIwnaBnuENpKsbryp8GlkIbtm+du0zE6ges2HYPS67EITWD5bE7Cb9iEAkPaGlEJTPPU7ru0167L7f3iLfCsFB+IaA0xvSFT+u3FMtUARPXb0P5NWQPiF0za4/HoIs6n3+7/lFiP/+xcc/W0LpqBrKQE1RJuqIstAAlI3Goxy0COWiA/9uXx23j9JRNZSBmqJM1BFloQEoG41HOWgRykUHUNoS3D5KR9VQBmqKMlFHlIUGoGw0HuWgRSgXHUBpS3H7KB1VQxmoKcpEHVEWGoCy0XiUgxahXHQApS3D7aN0VA1loKYoE3VEWWgAykbjUQ5ahHLRAZSmgdtH6agaykBNUSbqiLLQAJSNxqMctAjlogMobTluH6WjaigDNUWZqCPKQgNQNhqPctAilIsOoDRN3D5KR9VQBmqKMlFHlIUGoGw0HuWgRSgXHUBpWrh9lI6qoQzUFGWijigLDUDZaDzKQYtQLjqA0rRx+ygdVUMZqCnKRB1RFhqAstF4lIMWoVx0AKWtwO2jdFQNZaCmKBN1RFloAMpG41EOWoRy0QGUthK3j9JRNZSBmqJM1BFloQEoG41HOWgRykUHUNoq3D5KR9VQBmqKMlFHlIUGoGw0HuWgRSgXHUBpq3H7KB1VQxmoKcpEHVEWGoCy0XiUgxahXHQApeng9lE6qoYyUFOUiTqiLDQAZaPxKActQrnoAEoD3D5KR9VQBmqKMlFHlIUGoGw0HuWgRSgXHUCp39ok/vWc8f96sDllNzKoIlIEw32n8mYNkK6r/HpujWQRWCnvFRua/ozq07cxeDXyRTBtjMjJ5N2km+26dr9WvQgsg3bu/XaX9NDuR3vqdItgapNybmoD6Upt7uL1ZkUgpLz16Q96ItVPywi8qrcsgqTJ0ZPT95NusH2RdYNTEVxz/Tny4yHp9icGRRrPFUFUxlyLtC7SV64xedAYWATckE/wXeU5+eJ/d8lqbngRzBJRDU85TnrihhuF3IQiCDEPZ31NIf2Ist2epswimNJGa0j8TfoWsZiWpuIiOLttMGXAIIl84c1fZ93cVAST14yXfHqJdNCApuZPRRA9/XFbRwnp4otZO1oEiiFBUHb5/ekvqF58WTC/RbIYfAS2CjRakZ63LH1Jq3wxHJaZvvbWY9J9x0cGt6oXw0eX94Klg6RPG3rytVW3GOaX7dG4rJNM9QpeoUmbWTG8fqVbm+NLelW1QGSbZTFMUdn+yb2UdLUPWgNtTsUgZ5x7/PnsFPKF4p2dZvu5YpjlP2hx2I70191XTrUHFkPghb0x4S9Iv7AtJLE9vBjct7I27xB6SfW5q1gd7QnFsNw0edNlU9LXtK2U4WUWQ3bZnCBGKOlPHmUCr7gYfEP9Zp/oIV1lWMSK11QMSSUadfNXppIvhpvHnOV9KobE+vJMcz/S6bvir/MESoAFVpzxNaRX5/6J4EmWwOPN33O1F6ZR3cOh6zFPvgTcpXKzOk6Tvme9TSxPvQT2NVWETv1AerCDfQxPtwTkTccZZM9Kp/rVGYNhPLMS8OnihvQ5kD474fNVnmUJhE85fi4ki3TJdKYLz6kEzsnoNHKmvCLH84vGTt65EnhkLx5oc4j03avslvECSyA3ovXY5VekP3k8NI4XXgLK9R8tVKVeky9WF4sq2hNKIIlZrGhqQ3q82Zd77ZklYK5XFNmXTvrul9v3theXAPf8kfAJkzPIF6jYLzLtTSWwtXigJ/IQ6cK7st+1fSoBiwFtk1QO6TLzMk62CZTCHvHi3PmiHKoXJHNntEmWwsK5w89VtEgf+imf2ipfCuNDZhefOEC6/5wzZq3qpaCp5z4yEkD6W3ZPU4tuKVwf2D827RXpMeqHD7eYlcKDOr2y1C7SX9V96W22LIVZEne0R2QyyfXz5dyhZqdSYD/9M/H4GtLvS0s2NJ0rBTUxKTnl46RXK98zbgosBfEbHgb0cNLjTyg844aXgu5i2obNhaTPdLsnyU0oBXODbUKZv0jnzJxo15hZCpfnrlt+ZFEWuU78bNMaikuhPjQ2dstu0lMME8c0NJXCpAbmMhc/0uepdhrVfyoF1hb9KxUvSV/iOO5CnUAZvIjTPePUSXproHhqrWQZqDaY5BpOy6b63eO/+ON/GWwQtFPauY70qZuKJ9Wol4H98RuWD1xJd3/up1KtWwZeL2sXL4oh/cDNBYZVZmXwyG+rYW8N6XUrY80rLcsgvHDGwY6JOVS3MJ22v8KpDAJStjNmrSY9r/rwwfJzZeD4ZYnfpaOkr9eJsioLLIOy6byhJWzSdQ0+7igNL4OIU4lLJ5eQPizFXVOSUAa+K1o+KQu/obrl0uZFxZll4L68oM59OelxARWiRcVl0LCnNnTMIdIzT3HaCprK4N0nL+6bO6RfvBuZ/PFTGShH7jB6VUC6osR5zw8C5eB0UcCtWyCX6mOMD659L1kOMTM2zTDVIP2xoonQO/lyEJu+5F2XLeluLfov89XL4ZBjyfy0u6Svmr3eNk+3HKZLXCngFJHOqraRyDUrh6WZghY/hPPI+O8SmZBjWQ5j2uWP2GmT3p4mtCHbqRxqlJbcEDtK+qo8/8bMc+UgL9x0uDWC9FnTTI5wAstBSNzEt6+S9OlX1n1+HV4OH7/MOqMslk/1Szt9nF4llEP857N1t/VI7xaT7ErLLIenxbqaq06RPi+wf3dqcTm0zmydKR5LeobcoryUpnLwvsOeMbmV9DHri5STP5VDactZjuH0t+Tz93PbxSSBChD6bRX8xJT00nUuTYmSFeAuNktZ14f0ScVXlzyTr4CrP06NGfOa9FVbNM/Eq1eAzJxNccODpB9tc8uM1a2AvT+vxssuekf1Oa02f56YVcCpfPMAm/2ki3waq/nYsgJiNIXKW26TnjFwwPaRUwVcElQTvlJCetC4q9ejzlXA5IM1EVYT3pPx/O7VlAeBFXDlyEGNA3qkbzI+XhkZXgELOuMg8DTpR/uNBsITKiBdZNqazmekR92aKcTOrIDQzSH5h7tJdwj4IR5aXAGWErkbZOd+oLr3xi9T7zZVQHBDx5a+PaQPuEnK3v5UAeOPCzB7b5Iu/nX/5BCBSog5Xv5ZupD0uuyRcUGSldCz+9uVA+M+Ul11WsPIdflKUDhc/axWl/TVWxVaAtUr4f3tzGZXN9Llfpbm+etWwqO7raE6SaT7ZQhEXTGrBI8mS9sF/aTfOp7KumRZCbQn6znaCwrIOCMltu2iE395zYeKDvtJH04bN9fnXCVk0Zzl3t4j/UFCeu/5wEpIWZOoZFhFuuJOrWee4ZWQW74rp0OqkJz3FZecWAmVcNz0wPGnG0k/9CtH+WxmJcBA3osbvqR72w9x3YorYQbtrHhoNunznRcFujZVwlsZj9/5v0mfI3d6lcunSpgyzcpzwqwicl5u9jWfEKgC8z2RxZwVpM+ac/v8MckqCNBlLfYxJ71R5Yq8o3wVfO1y3m5xkvTbUPXSXr0KguIFxPRvkL7v26WNh3WrwFUuXFLrGelnZ72sszWrArdvxXNXFZEu4Odoc9CyCj6tkBIx6SN9iXZ2736nKsibxz3lKFpMzq9uloPluSq4ti91BXsh6UKlZ3v3BlbBgkV0sQYj0l+umGCzJ7wKaKWB8QtsSBdpcK7bmVAFy3QC2zwvkN62snTjjswqCGmOONIZSTq7e2na1uIqMPyzaaxFFulVdx7N3dxUBfm6c47Xc0m3lVzrZ/KpCiZUPz9u94f0ufNn9GwQqAbP3xH5QrNLqM7MW7F+vWQ1CH+7teTRKtKPDb64byhfDTvvbD+2azfpvPTwHwbq1ZCqE2Mkc5r0xzpiJnq6/OW1PU42hpA+FDkxDMyqYVVRffqzZNLl5eO6V1lWw+6IT3UBFaRv+DxeY4VTNSz3FQ9xHSK92VzFTfNcNWhy0+KOSJeS1w9Reb0ssBoMViW0HVpKeuDXmb/Vw6vh0H7eD8fNpDc/m7hSNaEadoTcfn7OifRt48WcF2VWQ+CULSV3Akh/tGjpkwXF1cCM75HJiCO9Vz+AO7+pGsbdDDXqLiDd12a51NxP1XBZUkiJ3ke6WqimrrxADfQelDttIVZGznv1A/vZkjVQdvewUOQi0vsGrwXPkK8Bm201vgPGpH+MlciQVa+BD2xu4ZrDpOs9UmudolsDZkVnQiP8SF9lLSwy2awGAoz008bGkF4J9xQlLGvAynRPr9Nb0vc4iK4Vc6qBTVU3f7Z0kG5I22814VwNHFxyMGHPuHKqm5QkuIsE1oB/3GBZrSLpF26Ovykczt9PaXl1S0PSPfNOPxZIqIH4ar+AnoOkx8VP4fzm1MBTesjrM96kR1h2lfwoqoEju9x9pB+S/iR+XOsItwY6vXVS4t+Q7qrJ+jI0wN//8RmzN7eR3m3KFPhCq4WPY19dHBGuIJ8LMiliAxK1ILWhNj9yLum6lkGyvfRasE6+/2SLAemeWeMVutRqoXF+wNhxB0j/4kNfyGPUQnaX0COOF+nHkzvUWk1r4Xa6uc2ZyFF9kuPyJmYtvFpVN0Unm/QhWs6KBsdaCPxeclGwhfQHKZ9W17JqYf+k07feCVaS8VN6LKMqgL9dk3EzgxRIN34oplvOroVZGnGdB/RI70uS1i2JrwXTw3dql1uRrrxakVHIqYXjy4beT/QkfVGnqc6Holp4eZd7syWc9Npp91a+5daC9PUzU15nkn6zaapW7kAtLPjEU7zTRHq/8Nul2bQ6GOum+fi0QBXVXb6/UuFI1MGdWo+ze+RJZ3X9UXpFr4MT7KJzDF3S+2NDFFLV6uCyhkbQfEvSBUsDZyQz6mBl0/N7k86RrnZ9cPJz0zroz9jsNsImvafu7cQEZh38eCU2uZVDeuCm6UKxjnVQeYm7rphLurZm37cYVh1kXcgcw6FVk+eWoI0DUQF18Ph8xOJ4OumGsxjt99l1cPWS46NwBumqiz7WhsfXQZLeZKsbTNI3lv8oCuXUQaf6EV1fFum3akve3CmqA5+YbUvOsEn3SDRPDeHWwfMt4fTjHNJ3eV2PvTlQB7M3Tv12iEv67LkXI67R6uF049FHlrQacn4VIMhfoh5Ck7bRd9FJ3/A69eJlej0cvWO1cQuD9Hd9tDMX1eqhMnOq/EYm6R+ZUx29GfUQ6FN12ZBFeqbrHysv03r4ndvnqccm/Zc5ZxuLWQ8HYty+ruaQ7l29x+iMYz1Ejnep1eaSPnS9asVpVj1k7Iiev5x/H//bfbnLF7sE1EPqAvbHJXTS11efljvBroc5+xNyVRmkb98TJekUXw9BU7vGLWaSrj4pQ+gopx60FoheXsgifdGenCG7onrYnX/BSIlNev3Zlzwbbj1syjikOZ9Dur87u/rAQD3ce2mzeS6X9Hxlt/eWtAaY4JZzXYH6n8FptCwN41d7JRpAY/Lmr3Q66R2yUnG76Q3wVdzWWY5B+l7lYra5WgPci6sVnc0k/eS9i9e2MRpAbfJIykwW6cvdV53fbNoAw44nT85gk16T2OVswmyAQ0Yn9aZzSDeWummzwbEBXtx2nj6NS3rEulU717EaoGDxup8y/Ovo3379M3f92oAGqG+Rbp9KJ735qtcqfXYD+KkbVExhkJ58aa4KI74BvPI930szSe/Rz5FbzWmA7kNJOZNZpC8Q3C+5oqgB9m3/wpFik64nJCCkyW2AX11nMyQ5pIu6hA4uHWiAnonZGRJc0jd5r2xXozUC/QYjU5x/Hv7tvQZVlYslGuGz58vsSXTSGb0n3i6kN8Lrzy65YgzSz4+XTFNUa4TBsd3vRJmkmxg/fTKX0QjxMzoLJrJIF/NaFypv2gjtF8eWTmCT7vaqzX82k7984IzK8RzS1YfPnZvh2Ahx1Utqx3FJn6Y++7gsqxHW+axrFOG/j3/7oF3qgSkBjaC7l9kylk568f3t26XYjTBnoQtvDIP02IbPhuLxjfB75Eq3MJP0S7L+2qKcRpiUd79fiEW67WZl5fFFjbDlZtoXQTbpay7nzRzLbYRL+0uGBTikK+TunyQ00Ai56p0/aFzSmcEn4x5/bwS9tI2Ptg2R/s/Pv/8oApfqiqpL7P6X/iLEf//i42/GoRKoLEpHlVA1VAtloEaoKWqOMlFb1BE9hbJQXzQADUHZaDQaj6agHDQfLUKrUC7agQ6gI/++f91/HIdKoLIoHVVC1VAtlIEaoaaoOcpEbVFH9BTKQn3RADQEZaPRaDyagnLQfLQIrUK5aAc6gI6gNL1/HIdKoLIoHVVC1VAtlIEaoaaoOcpEbVFH9BTKQn3RADQEZaPRaDyagnLQfLQIrUK5aAc6gI6gNP1/HIdKoLIoHVVC1VAtlIEaoaaoOcpEbVFH9BTKQn3RADQEZaPRaDyagnLQfLQIrUK5aAc6gI6gNIN/HIdKoLIoHVVC1VAtlIEaoaaoOcpEbVFH9BTKQn3RADQEZaPRaDyagnLQfLQIrUK5aAc6gI6gtDX/OA6VQGVROqqEqqFaKAM1Qk1Rc5SJ2qKO6CmUhfqiAWgIykaj0Xg0BeWg+WgRWoVy0Q50AB1BaWv/cRwqgcqidFQJVUO1UAZqhJqi5igTtUUd0VMoC/VFA9AQlI1Go/FoCspB89EitArloh3oADqC0gz/cRwqgcqidFQJVUO1UAZqhJqi5igTtUUd0VMoC/VFA9AQlI1Go/FoCspB89EitArloh3oADqCUv9sFZE8Z/z3wcbkuYFSjCAX9insVN42hvS+mQWnfotwYZbNRM8/4qTXad/99JM/vbJgqvAfOdI/bLez+yHDhR0aCt6/VUlPO67V8o2/nOvdxeN+A+mPAsbuGVHkwjkhbb9fJqQHPy0r+8pfv9/OQPTXPtK930VsHNLkArfI5OpPB9KP8xxzv/Bfd8+q3RI/PUi3EQb4bMiFBdcPXvvhT7qevFjKAH97SprHpH+Eke6qU6vWv4MLYmnuQd/jSDff9ehRL38/lI5dkv2eQbqOm4tCjw0XvN39bn8rJJ15cc2dLv7+hY/NmfmtkfSL9ZOlO1244KMzJ3Skn/TqVc2Xefz9/pS0T27kD+mnc+LHtPtwYcLp2exh8Sbyheusx9lW/vvx9GPQh+VI7z67abg5mAvFW73DvqqSPr5hlmMT/31ONH4w6yuQPje1t6MxigsZd3RuD5mQflXrtWUD//2v5NVLD+0j/YW3f01dMhekrg5dHnQgXbXWckst/7hMO1QrMOhBes1JjQ/VeVx4sOTNsS/+pEs9nLCmin+8PtTmNHwOI70ts+lVRSUXLuTlGHyOI32Netrycv5xtP3qFfkpg3RTu+C4Uh4Xlihd+zZQSPqlLyeVSvjHd8yI8ZqBRtLlrHeFFw1z4eDXivP9/aTPsNObXsg/7m5Zs170/SE9JVP1+keRJlgy50NFr3gz1QMZc0Q/8M/HTrpxa48c6Z3Fsy68k2mC0hmvartVSeedov/O55+nA93fXnYB6WVmi1zyFJsgadDPrdOE9N3X9Qbe8M+fw6aomR37SE/3P3AoR7MJ5nar3mp3IH3Mi+vNWfzzKl/2uKfVg/TV14t3Zxo2gaqbgVSLP+nnSuXKM/jnu2BhlnBTGOly+qxNr3c0wbm7vq8b4ki/VTiYl86/DrTSr2vXZZB+x9dDN82mCaaEnXCoLiS9mq2Q9pJ/fax7tmlnReOo43OUuyzFpQnU55X3l/ST/sk+LfYF/7rRDzBSLvxD+hadF0pJPk3gVH1C6L14C/ki/LA0IpF/Pc3fHueQK0f60mtTZz0LboJXC8sPZqqSvnOKZ3A8/zoT5a1rTAPSOw9Nk4qLaoKHe78WJJmQvudT4+Wn/OtPO9VQOW4f6U+WVYs8SW6Cx69UOqMcSN/fOs4rhn9dyq2W+xXmQXpy1bHf0Xn845MqvjvYn3Q/yRmno/jXq5C869crYaTbvhjz9UFlE4xnb8/yiiP97FTNY/f51/F+/3kJpzJI941O7IvgNcEK67bnRwpJ50xgHQ7nX9+5cTIZ+xpJfyMY3hE23ARLpTgcs/5Rr3NmxsFQ/nV/Ru9AjN4f0jX8B1vuijTDERHRI0vEW6kudVzd6g7/fji5XHeILke63aVK7i2ZZrifIK4xSXVUt+zZF8K/T/Ksx0z/rkP6uAfOjUGKzWC+fsm11k2k1yxy3XeTf/8cs1a69HEv6Z+GfjZe12wGuaofn54fJT12jojlNf59VTCil3j7LOkX/txrDjBshhTPqWlnr5L+ZiTvgD//fotokhxihpK+9v4l3pUdzZAYvmWDbizpY9P77S7z78OwCWcfy70mPWP2jz4/m2YI7En++eMj6fsKnx+/yL8/N91/uqCinvRTg3O++bg0w/DOazNie0n3qzTx8Obft7fd5dO8fpGu3wpjL/g0w0439sB2sTaqx0T9uOLFv58vpXMjFWeRrlLoN9UzuBneleimDy0iPVpxKIzFv89j+hPpmatIh7t6Cz2imkHpemryxQ2kr9ZwSzrDv/9vOzvYmOwhvWpqlK57cjNoR1+YInWE9DqPgoLT/HGhoH1DVLEb6Zvzv+1xzWuG6slJAlcvkS7NVO9x4Y8XhZVm4w3vkG718Yz7ycpmeLl7b8TPGNL3PuaJOfPHkSqZzPjYVNJvRbuwj/Oa4U6cuKzFO9IvXli+7Bh/fNlYfi1NpIZ0scmL3zoON0OQ+vqzsZ2kd6gd2OfAH3cubhjQM/tG+qoPrV/tRVpgpcvv7v5x7VQf35Dsf4Q/Hrknxe/2kyX9yaH2BYdlWqAoavwJuhLp29xc3xzij1NazhVTn2mS7j//tJWtYguUJT6bB4akJ5//RLPhj18bNol65m0n3Tuxg22t2QINlopixgdHvU6prd4B/rjWJq4Q/daZ9Oqxbm1Whvy+cmSp/gXSHRyU/Cz5412pik9g8g3Sx6qcVmPuaIEWmcDw+fdJf8x0rdrLHwe37OcYBCSSfkVe1dPCpgUiuTG7B7NIz7twf/Ee/vi45VlZ7uYS0k3uNtfscmkBD6HEg4+bSO878vniTv64yWHFzvg9QPqG4boV5j4t4HZ9Xu56Go9cP0se927nj6cz9x1dGyhOutqEgxHbglvAglXlXjybdDGrqTu38sfZ51dj101UIf2nxBvJLVEtwGNqXtFZTfr95tMfzPjj77mpyYqHN5B+Nohx0TS5BXo6Hb4F7CbdsXG2kQl/XNYsimiOsyPdZv/s8ZvyWmBWr392nivpf1INP2zgj9c+zSfdq3xJ13WKDDSubAF9oeDepmDSTYVW7FzPH8cNHFWHWx6SvpQ7ec46Xgu8UPRwbUgiPcBWu9+QP75fmPBma3EO6U59z16tHW4B7UY4lF5K+rgk36tr+ON+mZlKcFgz6UcHsiwNRFrB+UvB69OfSLd/c0hTn/95MGkFk7OR+tdh+ePGugviejKt8M2D7i4rTrrxuVldDP7nxCehTSU1s0j/abUiDxRbobV7fuSNRaQfKW15qMP//Li6vrNgzUrSF0fJX1yt2QrXVUo1+taRLhzxw34VtEJhhkLKFXPS75503bbSsBXkj01dPteG9KW5EbDCpBUEtvX6JziTvpLusUh7RyuwfXgPNM6TPiAwdabWvlYor1prHn+N9Kbyo5M0bVph0y0TH/lw0m2/BAgtd2gFrQfrJl+MI10q1OvHMpdWGPPoXF37K9JHhDd9XerRClMi12ev+EC6iN7wlyU+rbA68k/U+ZpRx3mn96C6fyvszh9zOKeD9HxNwRG14FbocCvo+fZ11HFLdPqtGtYKO7urxeaN6aS6kW+tiGpUK0i+fhm7ZjLpO3etlVaJa4UXY6Tjd8uTzktImbM4uRXqDzz8fFCV9Oc/tJYvymgFt4PrdtisJp3t89FYOa8V9v758nqPMenuPu4HFha2wtQlGRMMd5LeJ7aBtaCyFVo+ds6Yb0P6OjG9MKXGVuhk1JV+O0G61fYDmYq8Vljhskg6y5N01+CU9vn9rTAzM/z12QDSp+42EJ8/3AoR6VpJqqGkj4wVWznvTyuwGIo1ZY9J/1UjYzdXpA1EDbniR1+STh84dHeOeBvMrpbR/pFL+lHNcSUKMm2QP5Kr5V5G+gTX4QkKcm1w85Lq54Em0ldsWWUor9gGW/W5Rjv7ST+uXetNV20DMa8UetJP0p2OV72V02wDWNVjITyhixyHmVoSctAGw69F2tbKkC6m8HvnbMM2eOf85bb7XNKlDVSiZpm0Act7+MADddIZkz8Mz9zRBokmGUqZOqQ3D9QYz9zXBt/T9nwoNCZdf9LeyBk2bcDbb7y82Jx05SPmv6c7tMEZ1+Mb31iTfqbmw57pLm0wxXXRt8fHSO8ZfvV6mkcbPLgH8hc8SE9TV5k7zacNNGS6nppeJj0sW+6KrH8bXBVq9Jl0i/To5BvfZIL571dpXcjrB6Rvar96SCasDSyPfchnPiP9/Ffx+qlRbbBX3Udo6DXpXItpW6fGtUGV/OSlbu9Jr2E+KZiS3AbG2t56XypJnzn53YYpGW0wV//4LItW0ot3HC+QzmuDOrOuuJQB0qWao7dIF7bBNFHX9jG/Ru2nxuG6yZVtsL1+YazB+G6qZz1ItZ3c2AZhkhcHT0whfdA8eESK1wbzW25HBcmTrr5W4LJUfxvYe7QlPVpM+iTNEQWp4TY4Me7IpFht0nl5bq8k/7SB1I04duQa0u1tL+2WFGkHeeW4PX5mpM/ZM/+XhHg7nMnnLbGyIP1TqnGEhEw7rDPfKq18iHS20/f1EnLtUP/C/nPrCdKP6akPiyu2Q1fswgx/FunRb/oeiqu2Q8LgnyPKl0mfbKe+S5z//PRzOrcvOZj0WOdhCXFoh+fuK7U0IklXHgvvJ/Gfq0KkaasjY0mPkBx7cZJJO3xfeeuTQOqo5W3Wr5+0ox0qjfrXm70h/U7cePFJ+9qhVshGJ7CIdK2jupViNu1wvJ+bmVlL+gWB/ggxh3b4vTPlfXM76bL3xY+JubTD1+VZmwc/kX7Cnm0g5tEOC9KNN339SfqvzaHTxXzaYTBT9kWHSA/Ve5TGDor6t0N5m6XneynSzSLLikSD2+GAQ8nj0FmkK+4YmyAa1g5JwxeUrZRIt0kLviEaxT/+pWN+TFlK+oKFF9xE49phl8Fa6dTVpJc0vbMWTW6H6MORTpuMSF891nqLaEY7bJBqECvdTPpwuImBaF47SKyWbTW0IN0pyltLtJC//L3i/ic2pGt9HqMmWtkOcc0tiwSPkb7M6O1C0Ub+eR86G2zoPmp/dn1QEuXxj8OceYvOeJOumz9hoWh/O8SvjuJFBJB+fSZLRXS4HWKS6Hkpt0kfKFFcLvqHv58pX/Je3yf9yfZfDFERHqw3eMN7Hkv6IeGfm0T5z50xa1zn3kkZddyU5ZiiMjxQfaLi7pRFuoWY1QlROR7YXljZq/mB9N6mjEuiijz4PmXByb7yUcezfOlDUVUeOA3FTbnZSLr8hJfZopo82KT6/J1yJ+nlt9e3igIPZh3VvfHsM+kdt1pExAx5cHe5j9OCn6RLT/ZQETPhgc6KcsuAMb1UnyIqay62gwfr8oMP8CaRfvzCo/Ni+3jgZr3VVUWW9JVuKs/FbHgwNvBhmLU86XfbwtvFHHgg/WpV5eWFpAe//D1jkgsPCj3K5e4vJf1UJ2yd5ME/nn9WuT5eRTrTmuk/yYcHj++ub4lYQ/qTGbs/TvLngUVlg4XfJtK3f1s4SZz/3Gzm3NRhuYP09V3vzMTDeLC3Bc4vYJL+sFojRDyKB71l3apNtqQPJxxsEo/jwUy5mm5fJ9KtLMwXSyTzoPWDQAr9NOlv34xxl8jgwUTb3TeiPUmvLzv0USKPBwWOXBb9Eun6JzzkJQt54PfL74zvddIPX9E9JVnJg/DT2/y4d0hXm/C4WLKRBw1eK6KU7pNeWfJisRSPBxofl5Uxn4w6X+X7+OM///3KgeTF56Tv62L3Sg3z4OaKrXvD00nPeed1wfYnD+SbJQx/ZpJuP63ZbPIfHrxTc5gclUO646Te9P+lvwjx37/4+JtxqAQqi9JRJVQN1UIZqBFqipqjTNQWdURPoSzUFw1AQ1A2Go3GoykoB81Hi9AqlIt2oAPoyL/vf90/jkMlUFmUjiqhaqgWykCNUFPUHGWitqgjegplob5oABqCstFoNB5NQTloPlqEVqFctAMdQEdQ2vp/HIdKoLIoHVVC1VAtlIEaoaaoOcpEbVFH9BTKQn3RADQEZaPRaDyagnLQfLQIrUK5aAc6gI6gNON/HIdKoLIoHVVC1VAtlIEaoaaoOcpEbVFH9BTKQn3RADQEZaPRaDyagnLQfLQIrUK5aAc6gI6gtA3/OA6VQGVROqqEqqFaKAM1Qk1Rc5SJ2qKO6CmUhfqiAWgIykaj0Xg0BeWg+WgRWoVy0Q50AB1BaRv/cRwqgcqidFQJVUO1UAZqhJqi5igTtUUd0VMoC/VFA9AQlI1Go/FoCspB89EitArloh3oADqC0jb94zhUApVF6agSqoZqoQzUCDVFzVEmaos6oqdQFuqLBqAhKBuNRuPRFJSD5qNFaBXKRTvQAXQEpZn84zhUApVF6agSqoZqoQzUCDVFzVEmaos6oqdQFuqLBqAhKBuNRuPRFJSD5qNFaBXKRTvQAXQEpZn+x7+eM/5fDzbStozZrwU64JjHx0azPNLvQ2XyZJEOqPP3U4r4QHrFoiy6tHgHZJwMf+BXRvrSXrXL0jIdEMiLXbK/jvTJO2d/l5brAE7J00LlVtLd9l6wm6LYAfHGt9xbu0lntzHrp6h2QMfRI9pXvpCuW/V481TNDlhyQmHs/B+kP5azfDcVOqAv80VzrGAf1Vc+cDOQMeyA19LzChUnkK62+StHxqQDtmcceh8gSXqM+AeQ3dEBXyZ4VnbKkh6QO8yR3dcB9zOOfFlCJ/30vhMG02w6wLl2odwRRdJvZK16N82hA9ae5ey6qUK6S6Xx5ukuHZAzafnDWA3Sv52/WzfdowOU79wSSFlFumDCgkMzfDpgpQvNPkGf9A2MvuEZ/h2QLXOx4/Z60udNbfOdGdwBn5QtTpwwI11LevzMWWEdoDuYKKFjTrr69G0Js6I64GBF2avhvaSfH5NjNDuuA+IWTXcPtyZ9aoJp8+zkDni/cdB45RHSuwaHzshldIB6fs/iN8dIr3oQO4Oe1wFj3z9SAFfSNW46p9ELO8Au6dPCRx6kXwpYYyFf2QEhObGGQt6kr7WcJqDQ2AFm1Z9dN14m/eiH7ocKPP7x3/gjy+ca6YevJW+a098BT0qXzX0WQnrqUZeROcMdsGsPhH0IJT1bZv79uX86oPXnJ43K+6Tf03ltNk+kE5Iq93YVx5DecXWFwHzxTtgpXPk6PZ70B7E3n82X6YRol76k4Beky+q8s1aU64Tmbo8Sq3TSn1aWTFdS7IR5+fEys7NI54nHFCupdkL2mCHft3mkmziv91ug2QmHJCYvtP5IumtArMFC6ASfu4p/BkpIH2op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- 00000000-0000-0000-0000-000000000000
- dde71aef-d6ed-40a6-af98-6b0673983c82
- Nurbs Curve
- Construct a nurbs curve from control points.
- true
- 5953c941-4736-4fdc-be71-5b01d5096fc8
- true
- Nurbs Curve
- Nurbs Curve
-
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- Curve control points
- e8a36df3-789b-4e83-a172-c94aab9f8a4b
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- Vertices
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- 8d8f2080-094e-4467-95f2-a8b6da5f1972
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- Curve degree
- a1808e6a-4721-4f1a-a284-1c1247923816
- true
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- 1
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- {0}
- 11
- Periodic curve
- 23a8e221-1a6b-4bde-a02e-514c56bba545
- true
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- Periodic
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- 0
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- 1
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- Resulting nurbs curve
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- Curve
- Curve
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- 0
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- Curve length
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- Curve domain
- 5da61cb6-d609-4f66-abc9-15278dfb1282
- true
- Domain
- Domain
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- 0
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 8d8f2080-094e-4467-95f2-a8b6da5f1972
- true
- Relay
- false
- 0089c2e3-9879-4f71-a687-a024344de1f1
- 1
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- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- 13aab24b-b036-4a08-a6ee-d32ebb1217ee
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
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- Uri of file to read
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- All files|*.*
- 64b96e62-3d7e-4959-893b-b1cb268333af
- true
- File
- File
- false
- 0
-
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- 1
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- {0}
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- C:\FABIUS 16384 X.TXT
- 1
- File content
- bf9d0fa0-6c87-413b-abf1-9a7fed38d319
- true
- Content
- Content
- false
- 0
-
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
- 5b00838f-4808-4364-bbcd-4705dea61ca6
- 8386555d-1604-4e1b-ae8f-630eff298486
- 9ec4a0af-799b-4e1f-a413-0ecab486e883
- 3
- be8005da-b6c8-4939-ae79-fcd9991bdca6
- Group
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- d4c354e4-6a25-40e4-b57c-0b9d21a35f38
- true
- Text Split
- Text Split
-
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- Text to split.
- a67e2d37-6782-4828-8780-a248f66e2fe8
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- Text
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- 150c505d-ca0d-4cd7-8862-2f22baf8add1
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- Separator characters.
- 47216bb8-a906-4cac-b6f9-27c8af000f08
- true
- Separators
- Separators
- false
- 0
-
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- 1
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- {0}
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- ,
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- Resulting text fragments
- a3fc0dec-53ca-4b10-9e78-ad3723aca7db
- true
- Result
- Result
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- 0
-
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- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- 07f4ba56-a85f-400d-9a35-83a531f8b2bd
- true
- Text Split
- Text Split
-
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- Text to split.
- 577015bd-4f82-4784-a345-940c0d3f96c2
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- c4a5c37c-b696-47db-8f86-ef64754026fe
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- Separator characters.
- cf445915-90e5-4a62-881f-587f4a096032
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- false
- 0
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- Resulting text fragments
- 840d554c-b279-4cbe-be56-996c05ad1dce
- true
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- 0
-
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
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- The bulge factor for Tangency and Curvature modes
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28858.99
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- Vector Display Ex
- Preview vectors in the viewport
- true
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- true
- Vector Display Ex
- Vector Display Ex
-
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27264
76
84
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27306
- Start point of vector
- 5550e5e9-4471-419b-8cdf-22d1a7c9f9f5
- true
- Point
- Point
- true
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- 1
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8433
27266
48
20
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8457
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- Vector to display
- d94d1c9a-40f8-44d6-80a8-c3050982aa56
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- Vector
- Vector
- true
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8433
27286
48
20
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- Colour of vector
- c4e5c9c0-483c-4478-8c2b-3a83f228b790
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- Colour
- true
- 0
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8433
27306
48
20
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8457
27316
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- 1
- {0}
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255;0;0;0
- Width of vector lines
- 426df84f-3d1e-4abc-8847-c8dee5fc0e74
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- Width
- Width
- true
- 0
-
8433
27326
48
20
-
8457
27336
- 1
- 1
- {0}
- 2
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 92df39c6-f1a0-40bf-be65-baededdefc8f
- true
- Format
- Format
-
7907
28592
130
84
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7999
28634
- 4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
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- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 2d7b5f1c-8d43-40f1-92e2-515dd21b4dac
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- Format
- Format
- false
- 0
-
7909
28594
78
20
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7948
28604
- 1
- 1
- {0}
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- {0:R}
- Formatting culture
- 6130ffb5-3b3e-468c-b86e-51b878a033c2
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- Culture
- Culture
- false
- 0
-
7909
28614
78
20
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7948
28624
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- d99ac31b-d785-487c-a2a1-375045f89430
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- Data 0
- 0
- true
- a16e0194-897c-4ae3-a86c-9b0a83b06ed2
- 1
-
7909
28634
78
20
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7948
28644
- Data to insert at {1} placeholders
- 054d532a-5ce9-4105-9642-75bacb9fe37f
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- Data 1
- 1
- true
- 0
-
7909
28654
78
20
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7948
28664
- Formatted text
- 1f21e48d-e605-4a50-ab07-e00f3c5b3303
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- Text
- Text
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- 0
-
8011
28594
24
80
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8023
28634
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- a16e0194-897c-4ae3-a86c-9b0a83b06ed2
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- Relay
- false
- 540742f6-f4da-4da9-8ecf-b5af184a14a7
- 1
-
7829
28579
40
16
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7849
28587
- 9abae6b7-fa1d-448c-9209-4a8155345841
- Deconstruct
- Deconstruct a point into its component parts.
- true
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- true
- Deconstruct
- Deconstruct
-
7757
27316
120
64
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27348
- Input point
- 954b8f10-7fc8-4419-93cc-941ce30c0ea8
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- Point
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7759
27318
27
60
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7772.5
27348
- Point {x} component
- c5098eba-f62f-4204-b86a-be1c52aae0ee
- true
- X component
- X component
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- 0
-
7810
27318
65
20
-
7842.5
27328
- Point {y} component
- 5da2d624-4c9e-4761-99f7-447ce0d151b3
- true
- Y component
- Y component
- false
- 0
-
7810
27338
65
20
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7842.5
27348
- Point {z} component
- 5c28713c-6330-4532-b78c-b6594dea3eb7
- true
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- Z component
- false
- 0
-
7810
27358
65
20
-
7842.5
27368
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
- f74eae17-b09c-46ae-a891-13e3f5c122a6
- true
- Explode Tree
- Explode Tree
-
7929
27283
78
44
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7984
27305
- 1
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to explode
- bf93038e-70a3-4294-8e4e-1255776bb924
- true
- 2
- Data
- Data
- true
- c5098eba-f62f-4204-b86a-be1c52aae0ee
- 1
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7931
27285
41
40
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7959.5
27305
- 2
- All data inside the branch at index: 0
- f2c449e8-8648-4fd0-89f4-d6b30aee160c
- true
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- Branch 0
- -
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- 0
-
7996
27285
9
20
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8000.5
27295
- 2
- All data inside the branch at index: 1
- 9d43af13-00f9-48eb-b21e-66c4781aff05
- true
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- Branch 1
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- 0
-
7996
27305
9
20
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8000.5
27315
- 9c007a04-d0d9-48e4-9da3-9ba142bc4d46
- Subtraction
- Mathematical subtraction
- true
- 740de8b6-5fb7-460e-8178-072c070ed481
- true
- Subtraction
- Subtraction
-
8092
27278
70
44
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8117
27300
- 2
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- f4ee9563-4697-4362-a46d-f2a88d9d99f8
- true
- A
- A
- true
- f2c449e8-8648-4fd0-89f4-d6b30aee160c
- 1
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8094
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11
20
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8099.5
27290
- Second operand for subtraction
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- true
- B
- B
- true
- 9d43af13-00f9-48eb-b21e-66c4781aff05
- 1
-
8094
27300
11
20
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8099.5
27310
- Result of subtraction
- 33c98b11-df16-46d3-b656-96b33d6aef91
- true
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- Result
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- 0
-
8129
27280
31
40
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8144.5
27300
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- fee30ed6-da8a-4110-8085-01d2b9e95ad0
- true
- Format
- Format
-
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130
64
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- 3
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- Text format
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- Format
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8073
27191
78
20
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8112
27201
- 1
- 1
- {0}
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- Formatting culture
- 6857890b-c6da-48dd-b132-9e47656b3e39
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- Culture
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- 0
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8073
27211
78
20
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8112
27221
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- c0f6caad-0e96-4cc7-8583-9de6fa452fab
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- Data 0
- 0
- true
- 33c98b11-df16-46d3-b656-96b33d6aef91
- 1
-
8073
27231
78
20
-
8112
27241
- Formatted text
- b9b225c0-4c70-4081-ac8a-96f9165ae9ee
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- Text
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- 0
-
8175
27191
24
60
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8187
27221
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 9e429655-c48d-4c69-a6df-97f0119bf853
- true
- Panel
- X0-X1
- false
- 0
- de99d806-0033-411c-be6e-993093e9e3ee
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- 0.0003419868677042794559
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226
71
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8004.624
28198.16
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255;255;255;255
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- false
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- false
- false
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
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- true
- Merge
- Merge
-
8201
27279
90
64
-
8246
27311
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 2
- Data stream 1
- f6b328d5-3e57-42dc-9c76-e27d45737586
- true
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- Data 1
- D1
- true
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- 1
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8203
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31
20
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8218.5
27291
- 2
- Data stream 2
- 8bc03a2d-699a-4702-bd83-32f9ec336d16
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- Data 2
- D2
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- 1
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8203
27301
31
20
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8218.5
27311
- 2
- Data stream 3
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- Data 3
- D3
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- 0
-
8203
27321
31
20
-
8218.5
27331
- 2
- Result of merge
- de99d806-0033-411c-be6e-993093e9e3ee
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- 0
-
8258
27281
31
60
-
8273.5
27311
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- d07e1734-c175-41dc-9d25-373919246eee
- true
- Evaluate Length
- Evaluate Length
-
9380
27619
142
64
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9458
27651
- Curve to evaluate
- 922fb345-dec3-4c66-a47c-cf1c70c4c06d
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- Curve
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- 029f8972-c08f-4c74-9db9-d1602083474e
- 1
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9382
27621
64
20
-
9414
27631
- Length factor for curve evaluation
- a5a41833-3de3-4e10-ad09-bb0d69af0e55
- true
- Length
- Length
- false
- 0
-
9382
27641
64
20
-
9414
27651
- 1
- 2
- {0}
- 0
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
- Normalized
- Normalized
- false
- 0
-
9382
27661
64
20
-
9414
27671
- 1
- 1
- {0}
- true
- Point at the specified length
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- true
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- Point
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- 0
-
9470
27621
50
20
-
9495
27631
- Tangent vector at the specified length
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- Tangent
- Tangent
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9470
27641
50
20
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9495
27651
- Curve parameter at the specified length
- 0b8eff06-2ff1-453a-ac98-75c220a7d25a
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- Parameter
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- 0
-
9470
27661
50
20
-
9495
27671
- 575660b1-8c79-4b8d-9222-7ab4a6ddb359
- Rectangle 2Pt
- Create a rectangle from a base plane and two points
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- true
- Rectangle 2Pt
- Rectangle 2Pt
-
9286
27498
198
101
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27549
- Rectangle base plane
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9288
27500
122
37
-
9349
27518.5
- 1
- 1
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-
0
0
0
1
0
0
0
1
0
- First corner point.
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- 1
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9288
27537
122
20
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9349
27547
- 1
- 1
- {0}
-
0
0
0
- Second corner point.
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- true
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- Point B
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- 1
-
9288
27557
122
20
-
9349
27567
- 1
- 1
- {0}
-
10
5
0
- Rectangle corner fillet radius
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- true
- Radius
- Radius
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- 0
-
9288
27577
122
20
-
9349
27587
- 1
- 1
- {0}
- 0
- Rectangle defined by P, A and B
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- Rectangle
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- 0
-
9434
27500
48
48
-
9458
27524.25
- Length of rectangle curve
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- Length
- Length
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- 0
-
9434
27548
48
49
-
9458
27572.75
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
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- true
- Explode Tree
- Explode Tree
-
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27624
78
44
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27646
- 1
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- Data to explode
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- 2
- Data
- Data
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- 1
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27626
41
40
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9593.5
27646
- 2
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- 0
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9630
27626
9
20
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9634.5
27636
- 2
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9630
27646
9
20
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9634.5
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- a10e8cdf-7c7a-4aac-aa70-ddb7010ab231
- Box Corners
- Extract all 8 corners of a box.
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- true
- Box Corners
- Box Corners
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94
164
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- Base box
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- 1
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27330
21
160
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- Corner at {x=min, y=min, z=min}
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- 0
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9438
27330
45
20
-
9460.5
27340
- Corner at {x=max, y=min, z=min}
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- true
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- Corner B
- false
- 0
-
9438
27350
45
20
-
9460.5
27360
- Corner at {x=max, y=max, z=min}
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- false
- 0
-
9438
27370
45
20
-
9460.5
27380
- Corner at {x=min, y=max, z=min}
- b4ccb984-448f-470a-80f3-02e69cdd354b
- true
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- Corner D
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- 0
-
9438
27390
45
20
-
9460.5
27400
- Corner at {x=min, y=min, z=max}
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- true
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- Corner E
- false
- 0
-
9438
27410
45
20
-
9460.5
27420
- Corner at {x=max, y=min, z=max}
- dfeea850-330d-4d9d-8319-0652cbc2403b
- true
- Corner F
- Corner F
- false
- 0
-
9438
27430
45
20
-
9460.5
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- Corner at {x=max, y=max, z=max}
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- true
- Corner G
- Corner G
- false
- 0
-
9438
27450
45
20
-
9460.5
27460
- Corner at {x=min, y=min, z=max}
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- true
- Corner H
- Corner H
- false
- 0
-
9438
27470
45
20
-
9460.5
27480
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
- true
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- true
- Point
- Point
- false
- b4ccb984-448f-470a-80f3-02e69cdd354b
- 1
-
9426
27304
50
24
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9451.633
27316.02
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 607647b9-d6f4-4c29-9f4d-93d739deeb34
- true
- Polar Array
- Polar Array
-
9440
27170
191
84
-
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27212
- Base geometry
- 6a69a647-aacb-48b8-ab0e-694504f42f0f
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- Geometry
- Geometry
- true
- 029f8972-c08f-4c74-9db9-d1602083474e
- 1
-
9442
27172
113
20
-
9498.5
27182
- Polar array plane
- 8b5aac2a-2c0b-4d67-90cb-023cbd588d4b
- true
- Plane
- Plane
- false
- 06ecc8ab-7209-4438-836b-119c5732583d
- 1
-
9442
27192
113
20
-
9498.5
27202
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- a3f39ccd-7156-4ea7-bcb5-6c7ccee91adf
- true
- Count
- Count
- false
- 0
-
9442
27212
113
20
-
9498.5
27222
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 420355a6-aff5-4db9-a9d5-990bea2c4892
- true
- Angle
- Angle
- false
- 0
- false
-
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113
20
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27242
- 1
- 1
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- 6.2831853071795862
- 1
- Arrayed geometry
- e68c5fe8-1fed-41da-98f7-f3dac4eb9545
- true
- Geometry
- Geometry
- false
- 0
-
9579
27172
50
40
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9604
27192
- 1
- Transformation data
- 534ccd7e-686f-40ce-936e-3a8bf42c0ed5
- true
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- Transform
- false
- 0
-
9579
27212
50
40
-
9604
27232
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
- 8ee13ade-d6bc-48c9-a10e-035cd34ec578
- true
- Explode Tree
- Explode Tree
-
7968
27090
78
44
-
8023
27112
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to explode
- f0706de4-e458-45ae-8fe4-2e2801f1a5ff
- true
- 2
- Data
- Data
- true
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- 1
-
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27092
41
40
-
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27112
- 2
- All data inside the branch at index: 0
- 15ba0a9e-7c13-47c9-a120-0c7ab3977abd
- true
- false
- Branch 0
- -
- false
- 0
-
8035
27092
9
20
-
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27102
- 2
- All data inside the branch at index: 1
- 49801c49-68b9-499a-8324-7a78a638a3e8
- true
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- Branch 1
- -
- false
- 0
-
8035
27112
9
20
-
8039.5
27122
- 9abae6b7-fa1d-448c-9209-4a8155345841
- Deconstruct
- Deconstruct a point into its component parts.
- true
- f3f58225-4602-49ba-91e6-6b555431f93f
- true
- Deconstruct
- Deconstruct
-
8100
27095
120
64
-
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27127
- Input point
- ef106332-e5b6-400b-9328-8410a73fba9d
- true
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- Point
- false
- 49801c49-68b9-499a-8324-7a78a638a3e8
- 1
-
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27097
27
60
-
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27127
- Point {x} component
- 3c6f247f-4c49-4f68-b5b5-0ff3d33ed74d
- true
- X component
- X component
- false
- 0
-
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65
20
-
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27107
- Point {y} component
- c349f021-de67-4c6a-85cc-018bf530b608
- true
- Y component
- Y component
- false
- 0
-
8153
27117
65
20
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- Point {z} component
- 331e46af-08fb-44cd-926d-c48814f1b83f
- true
- Z component
- Z component
- false
- 0
-
8153
27137
65
20
-
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27147
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- d58d961c-ae9c-4fab-832b-12998948c201
- true
- Mirror
- Mirror
-
8777
27527
126
44
-
8839
27549
- Base geometry
- b2a4d631-1ae1-430c-ac1f-6e7474481ae5
- true
- Geometry
- Geometry
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
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27529
48
20
-
8803
27539
- Mirror plane
- f5855df0-191f-4026-b8aa-26f9286fb056
- true
- Plane
- Plane
- false
- 4825d5c1-ae87-4bbc-96d9-f6813501ff2c
- 1
-
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27549
48
20
-
8803
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- 1
- 1
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-
0
0
0
0
1
0
0
0
1
- Mirrored geometry
- 1af07c62-ff38-4cdf-aee3-f6ec7a28a8a9
- true
- Geometry
- Geometry
- false
- 0
-
8851
27529
50
20
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8876
27539
- Transformation data
- 39ae8c27-b896-4798-a3b2-59a4b6329b04
- true
- Transform
- Transform
- false
- 0
-
8851
27549
50
20
-
8876
27559
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 3a0b8b19-f25c-4518-a98f-627474f69fab
- true
- List Item
- List Item
-
8051
27541
77
64
-
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27573
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 1001d769-275c-4259-b1ac-c87542504c18
- true
- List
- List
- false
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- 1
-
8053
27543
43
20
-
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27553
- Item index
- 097d2964-74f2-443f-a872-0e24902794a0
- true
- Index
- Index
- false
- 0
-
8053
27563
43
20
-
8074.5
27573
- 1
- 1
- {0}
- -1
- Wrap index to list bounds
- a14f2e60-f3b0-4b1f-9664-41adbbd76081
- true
- Wrap
- Wrap
- false
- 0
-
8053
27583
43
20
-
8074.5
27593
- 1
- 1
- {0}
- true
- Item at {i'}
- 4ed77016-2fe9-49fc-9c97-a8f70ec22370
- true
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- Item
- i
- false
- 0
-
8120
27543
6
60
-
8123
27573
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- b1a15299-df6f-41a0-bae3-3358fad867da
- true
- Line SDL
- Line SDL
-
8850
27409
111
64
-
8925
27441
- Line start point
- c1c4fc3b-1eec-4434-83fc-26979a82bcf3
- true
- Start
- Start
- false
- 4ed77016-2fe9-49fc-9c97-a8f70ec22370
- 1
-
8852
27411
61
20
-
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27421
- Line tangent (direction)
- 573f9951-0238-4b24-963e-4796a8be1751
- true
- Direction
- Direction
- false
- 0ad32c15-e0bb-438f-9a7c-fa7f5af22f77
- 1
-
8852
27431
61
20
-
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27441
- 1
- 1
- {0}
-
1
1
0
- Line length
- 6de70698-9aa8-4be6-af4b-a303befbc25f
- true
- Length
- Length
- false
- 0
-
8852
27451
61
20
-
8882.5
27461
- 1
- 1
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- 1
- Line segment
- 4825d5c1-ae87-4bbc-96d9-f6813501ff2c
- true
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- Line
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- 0
-
8937
27411
22
60
-
8948
27441
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 54492cdf-eec5-43f9-b305-c633663f407c
- true
- Merge
- Merge
-
8949
27561
90
64
-
8994
27593
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
- fd0b6619-1604-496d-ae9f-03fb46558d80
- true
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- Data 1
- D1
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
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27563
31
20
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27573
- 2
- Data stream 2
- f9761a1d-3802-42d1-bef0-f0706c242541
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- Data 2
- D2
- true
- 1af07c62-ff38-4cdf-aee3-f6ec7a28a8a9
- 1
-
8951
27583
31
20
-
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- 2
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- 3d143dcc-983f-4265-bbd5-3cca664fd9f5
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- D3
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-
8951
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31
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-
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- 2
- Result of merge
- 7b24f9ce-d158-4f9e-8e14-e345e0de6d31
- true
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- Result
- false
- 0
-
9006
27563
31
60
-
9021.5
27593
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- 0d824c3b-96fc-42d2-a484-6f796091f7f8
- true
- Join Curves
- Join Curves
-
8316
27636
132
44
-
8399
27658
- 1
- Curves to join
- 9c3fee6b-58aa-41ca-93bc-ef2f1243c2b2
- true
- 1
- Curves
- Curves
- false
- 7b24f9ce-d158-4f9e-8e14-e345e0de6d31
- 1
-
8318
27638
69
20
-
8360.5
27648
- Preserve direction of input curves
- cc5a0252-614e-4554-b451-d40d7f81c38e
- true
- Preserve
- Preserve
- false
- 0
-
8318
27658
69
20
-
8360.5
27668
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- fa54f823-8a2e-4f67-8c01-f0cd00a64ba4
- true
- Curves
- Curves
- false
- 0
-
8411
27638
35
40
-
8428.5
27658
- 75eb156d-d023-42f9-a85e-2f2456b8bcce
- Interpolate (t)
- Create an interpolated curve through a set of points with tangents.
- true
- 547daed3-e526-468b-800a-64b6209048bc
- true
- Interpolate (t)
- Interpolate (t)
-
7458
27907
244
84
-
7650
27949
- 1
- Interpolation points
- d1922547-7b3c-4853-8b35-dc9cf830798c
- true
- Vertices
- Vertices
- false
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- 1
-
7460
27909
178
20
-
7549
27919
- Tangent at start of curve
- d486fe76-ae79-45ad-8054-bac4bcefd8fc
- true
- Tangent Start
- Tangent Start
- false
- 0
-
7460
27929
178
20
-
7549
27939
- 1
- 1
- {0}
-
1
0
0
- Tangent at end of curve
- f1998f4b-2ddd-46c3-9feb-f37c4f3ece6d
- true
- Tangent End
- Tangent End
- false
- 0
-
7460
27949
178
20
-
7549
27959
- 1
- 1
- {0}
-
0
1
0
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- f99689a7-e708-475b-b74d-a577d35e724a
- true
- KnotStyle
- KnotStyle
- false
- 0
-
7460
27969
178
20
-
7549
27979
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 473f7647-6e58-4b9e-91d2-8f585d5a6649
- true
- Curve
- Curve
- false
- 0
-
7662
27909
38
26
-
7681
27922.33
- Curve length
- d2ed8027-a0e0-498f-a043-e358e6bb5ab0
- true
- Length
- Length
- false
- 0
-
7662
27935
38
27
-
7681
27949
- Curve domain
- 1f348736-b2e3-4af7-86af-c1a614441e90
- true
- Domain
- Domain
- false
- 0
-
7662
27962
38
27
-
7681
27975.67
- e9eb1dcf-92f6-4d4d-84ae-96222d60f56b
- Move
- Translate (move) an object along a vector.
- true
- 49641e2a-6345-4e2b-a88c-65b810efe4e3
- true
- Move
- Move
-
9544
27361
142
44
-
9622
27383
- Base geometry
- b507da92-7dc2-480a-9fa1-0f0e90fa2618
- true
- Geometry
- Geometry
- true
- e68c5fe8-1fed-41da-98f7-f3dac4eb9545
- 1
-
9546
27363
64
20
-
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- Translation vector
- 42a20604-cfcb-42de-99b2-15990d9215e3
- -X
- true
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- Motion
- false
- 06ecc8ab-7209-4438-836b-119c5732583d
- 1
-
9546
27383
64
20
-
9586
27393
- 1
- 1
- {0}
-
0
0
10
- Translated geometry
- 9f7378b6-9894-4b84-998a-f5226749112f
- true
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- Geometry
- false
- 0
-
9634
27363
50
20
-
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- Transformation data
- 3b7e5e45-5dae-4b9a-a940-d75a94b88f48
- true
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- Transform
- false
- 0
-
9634
27383
50
20
-
9659
27393
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 921a4c47-a14a-4ae8-a939-3fa685fa688d
- true
- End Points
- End Points
-
8738
27790
84
44
-
8782
27812
- Curve to evaluate
- c0dcc44b-e03a-4be2-b2ca-2d753dc405e7
- true
- Curve
- Curve
- false
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
8740
27792
30
40
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- Curve start point
- c475072e-1fe0-42c5-b3e5-ace9a4f477bc
- true
- Start
- Start
- false
- 0
-
8794
27792
26
20
-
8807
27802
- Curve end point
- 796038b0-8393-4141-a4f4-fa10cae2524d
- true
- End
- End
- false
- 0
-
8794
27812
26
20
-
8807
27822
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- be9b2731-1a06-4cce-84c1-1c4881f7601a
- true
- Line
- Line
-
8887
27790
102
44
-
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27812
- Line start point
- 3025a762-b90d-46e1-81c6-2d91538603f9
- true
- Start Point
- Start Point
- false
- c475072e-1fe0-42c5-b3e5-ace9a4f477bc
- 1
-
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27792
52
20
-
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- Line end point
- 950fbbca-eba8-46d3-b614-dfc70b04ce67
- true
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- End Point
- false
- 796038b0-8393-4141-a4f4-fa10cae2524d
- 1
-
8889
27812
52
20
-
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- Line segment
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- true
- Line
- Line
- false
- 0
-
8965
27792
22
40
-
8976
27812
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 98c446bc-5e7b-4949-bc4d-55a5abdcc6dc
- true
- Evaluate Length
- Evaluate Length
-
9031
27781
149
64
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- Curve to evaluate
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- true
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- Curve
- false
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
9033
27783
71
20
-
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- Length factor for curve evaluation
- a7c5e0af-e582-4ad0-93df-3660492d36df
- true
- Length
- Length
- false
- 0
-
9033
27803
71
20
-
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27813
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- d300cf4d-5b21-482f-98fb-a6424261ff24
- true
- Normalized
- Normalized
- false
- 0
-
9033
27823
71
20
-
9068.5
27833
- 1
- 1
- {0}
- true
- Point at the specified length
- 25200f80-2e95-4f38-ab66-a92c473cb11e
- true
- Point
- Point
- false
- 0
-
9128
27783
50
20
-
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- Tangent vector at the specified length
- aed17c8c-373a-4521-b837-4c123720e32f
- true
- Tangent
- Tangent
- false
- 0
-
9128
27803
50
20
-
9153
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- Curve parameter at the specified length
- d10df88d-d7b4-44a1-ba2c-423feaf79c00
- true
- Parameter
- Parameter
- false
- 0
-
9128
27823
50
20
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9153
27833
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 6702c62f-e4c0-49b2-83f6-4419cd923fb7
- true
- Line SDL
- Line SDL
-
9240
27793
94
64
-
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27825
- Line start point
- 2ef5a359-b0b1-41a3-982d-a20728a8dc11
- true
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- Start
- false
- 25200f80-2e95-4f38-ab66-a92c473cb11e
- 1
-
9242
27795
44
20
-
9264
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- Line tangent (direction)
- f4198ebb-ed97-4f14-93e1-dcf5e71fc811
- true
- Direction
- Direction
- false
- 3641d63f-f6a1-410a-bb98-c00fec3be173
- 1
-
9242
27815
44
20
-
9264
27825
- 1
- 1
- {0}
-
0
0
1
- Line length
- 932422c3-938f-4896-bfba-93e9dc63dd8e
- true
- Length
- Length
- false
- 9f3a6cd3-00a5-4f12-84f7-3a56eb5630da
- 1
-
9242
27835
44
20
-
9264
27845
- 1
- 1
- {0}
- 1
- Line segment
- 308c9394-dd98-4fc8-971a-a1b8bf4ce995
- true
- Line
- Line
- false
- 0
-
9310
27795
22
60
-
9321
27825
- b6d7ba20-cf74-4191-a756-2216a36e30a7
- Rotate
- Rotate a vector around an axis.
- true
- ea049eb4-e34b-4db1-971c-23f959a7c78a
- true
- Rotate
- Rotate
-
9005
27889
185
64
-
9143
27921
- Vector to rotate
- b8b25cd0-c4e0-4e97-a694-3999684b1fa1
- true
- Vector
- Vector
- false
- aed17c8c-373a-4521-b837-4c123720e32f
- 1
-
9007
27891
124
20
-
9077
27901
- Rotation axis
- 5738ea86-6bef-4d8a-821c-df3f2582e45e
- true
- Axis
- Axis
- false
- 0
-
9007
27911
124
20
-
9077
27921
- 1
- 1
- {0}
-
0
0
1
- Rotation angle (in degrees)
- 22b5c062-1d46-4959-bf7f-ce186f811a1c
- true
- Angle
- Angle
- false
- 0
- true
-
9007
27931
124
20
-
9077
27941
- 1
- 1
- {0}
- 90
- Rotated vector
- 3641d63f-f6a1-410a-bb98-c00fec3be173
- true
- Vector
- Vector
- false
- 0
-
9155
27891
33
60
-
9171.5
27921
- c75b62fa-0a33-4da7-a5bd-03fd0068fd93
- Length
- Measure the length of a curve.
- true
- 22c2fd8f-4f4b-486f-a523-4871ff61a4d0
- true
- Length
- Length
-
8837
27704
92
28
-
8881
27718
- Curve to measure
- baa1397b-52fd-4f3f-be30-f33ffcadbf13
- true
- Curve
- Curve
- false
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
8839
27706
30
24
-
8854
27718
- Curve length
- 0d72d33c-7529-4646-b0d3-e06c84ee7c1f
- true
- Length
- Length
- false
- 0
-
8893
27706
34
24
-
8910
27718
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*SQRT(3)/6
- true
- 3d1f2fa7-968c-4d68-8a1f-878b5c7ca144
- true
- Expression
- Expression
-
9011
27686
158
28
-
9080
27700
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- fd1f6b44-7166-48cf-a064-4545c7281f0f
- true
- Variable O
- O
- true
- 0d72d33c-7529-4646-b0d3-e06c84ee7c1f
- 1
-
9013
27688
11
24
-
9018.5
27700
- Result of expression
- 9f3a6cd3-00a5-4f12-84f7-3a56eb5630da
- true
- Result
- Result
- false
- 0
-
9136
27688
31
24
-
9151.5
27700
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 57393fcf-4116-4c07-92dd-e41339c0f525
- true
- Evaluate Length
- Evaluate Length
-
9400
27772
149
64
-
9485
27804
- Curve to evaluate
- ce65bcce-f09a-44b3-94cd-cc73bb237aaf
- true
- Curve
- Curve
- false
- 308c9394-dd98-4fc8-971a-a1b8bf4ce995
- 1
-
9402
27774
71
20
-
9437.5
27784
- Length factor for curve evaluation
- baafa833-4ef8-425f-b607-a7876121b49c
- true
- Length
- Length
- false
- 0
-
9402
27794
71
20
-
9437.5
27804
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- de9b5e2c-f3fc-426a-a76a-87c3039c08ba
- true
- Normalized
- Normalized
- false
- 0
-
9402
27814
71
20
-
9437.5
27824
- 1
- 1
- {0}
- true
- Point at the specified length
- 53ada397-2c9c-431e-8a96-ba407a255873
- true
- Point
- Point
- false
- 0
-
9497
27774
50
20
-
9522
27784
- Tangent vector at the specified length
- dd888f3a-4b87-4d6a-85e5-fb0aa6030ccb
- true
- Tangent
- Tangent
- false
- 0
-
9497
27794
50
20
-
9522
27804
- Curve parameter at the specified length
- cfa9c748-f17c-4de8-8706-d009df92c6cf
- true
- Parameter
- Parameter
- false
- 0
-
9497
27814
50
20
-
9522
27824
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 643548c7-e04c-46c8-a912-73b81340f60c
- true
- Polar Array
- Polar Array
-
9579
27711
191
84
-
9706
27753
- Base geometry
- 51b4c9be-a0a6-48b0-8a51-2b635cbf72ca
- true
- Geometry
- Geometry
- true
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
9581
27713
113
20
-
9637.5
27723
- Polar array plane
- 14495758-452f-4515-833d-6b411c69c0fe
- true
- Plane
- Plane
- false
- 53ada397-2c9c-431e-8a96-ba407a255873
- 1
-
9581
27733
113
20
-
9637.5
27743
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- eea66035-3fac-4d03-950f-8296730c879e
- true
- Count
- Count
- false
- 0
-
9581
27753
113
20
-
9637.5
27763
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 2123eff2-fbe6-4059-9ae7-dcce8ac7add1
- true
- Angle
- Angle
- false
- 0
- false
-
9581
27773
113
20
-
9637.5
27783
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- f9dcf267-1e15-4850-9ec4-8e7ad6d9f2ad
- true
- Geometry
- Geometry
- false
- 0
-
9718
27713
50
40
-
9743
27733
- 1
- Transformation data
- dd83b124-9569-4709-9a61-1a92bc7b736c
- true
- Transform
- Transform
- false
- 0
-
9718
27753
50
40
-
9743
27773
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- 5f125462-d0f8-4183-b286-475d3acf0b80
- true
- Join Curves
- Join Curves
-
9944
27725
116
44
-
10011
27747
- 1
- Curves to join
- 12e37bce-c053-4efd-a977-c0f522b26642
- true
- Curves
- Curves
- false
- f9dcf267-1e15-4850-9ec4-8e7ad6d9f2ad
- 1
-
9946
27727
53
20
-
9972.5
27737
- Preserve direction of input curves
- d117240c-4ab9-460f-bbfb-66dc61b43975
- true
- Preserve
- Preserve
- false
- 0
-
9946
27747
53
20
-
9972.5
27757
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- 313dc56d-5db5-4cb0-88da-248d848cf9d0
- true
- Curves
- Curves
- false
- 0
-
10023
27727
35
40
-
10040.5
27747
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 3cc94df5-d9f1-4979-a5ab-be1fac63184f
- true
- Polar Array
- Polar Array
-
9586
27833
191
84
-
9713
27875
- Base geometry
- e6740668-b9bc-4cec-88e7-68ca31ae6aee
- true
- Geometry
- Geometry
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
9588
27835
113
20
-
9644.5
27845
- Polar array plane
- 50d41db2-0be5-414a-a105-cf75d7ca3326
- true
- Plane
- Plane
- false
- 53ada397-2c9c-431e-8a96-ba407a255873
- 1
-
9588
27855
113
20
-
9644.5
27865
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- a4c562c2-1370-489a-8662-0f28f19bec21
- true
- Count
- Count
- false
- 0
-
9588
27875
113
20
-
9644.5
27885
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b42ad307-1e85-4873-992e-8cb29886ba06
- true
- Angle
- Angle
- false
- 0
- false
-
9588
27895
113
20
-
9644.5
27905
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- bc6ee7cc-dfce-484f-b2eb-2a5a4d0007c8
- true
- Geometry
- Geometry
- false
- 0
-
9725
27835
50
40
-
9750
27855
- 1
- Transformation data
- 914dfde9-23d3-4c32-8acf-801b3a0a96f7
- true
- Transform
- Transform
- false
- 0
-
9725
27875
50
40
-
9750
27895
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 74f760b9-aa8a-4167-9ec4-7a13306ccf56
- true
- Curve
- Curve
- false
- 0
-
7000
-3940
50
24
-
7025.612
-3928.156
- 1
- 4
- {0;0;1;0;0}
- -1
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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10743
27792
148
20
-
10825
27802
- Rotation angle in degrees
- 08234d50-5319-4eda-b011-e5a672193566
- true
- Angle
- Angle
- false
- 0
- true
-
10743
27812
148
20
-
10825
27822
- 1
- 1
- {0}
- 45
- Rotation plane
- 71cf7492-5d81-4727-b72d-dda2eb760d72
- true
- Plane
- Plane
- false
- 0
-
10743
27832
148
37
-
10825
27850.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Rotated geometry
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- true
- Geometry
- Geometry
- false
- 0
-
10915
27792
50
38
-
10940
27811.25
- Transformation data
- 897ce37d-d731-4fb4-b8fe-75df1d5dc9a2
- true
- Transform
- Transform
- false
- 0
-
10915
27830
50
39
-
10940
27849.75
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- e7a5cf4c-3f82-4f47-b79b-d8e2537d8afd
- 1
- a941ff94-f01d-41a5-8c0b-c7127477058b
- Group
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- 8c984148-7404-4d11-8d34-bca11770b24b
- true
- Rotate
- Rotate
-
11017
27792
226
81
-
11179
27833
- Base geometry
- 7f4e85e8-1d1c-48d7-8d91-6d18ec61aa57
- true
- Geometry
- Geometry
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11019
27794
148
20
-
11101
27804
- Rotation angle in degrees
- 7c6018ba-c804-42dc-9996-5cae1df22202
- true
- Angle
- Angle
- false
- 0
- true
-
11019
27814
148
20
-
11101
27824
- 1
- 1
- {0}
- 90
- Rotation plane
- 6f386100-34ea-43f2-b91b-92333417f7d4
- true
- Plane
- Plane
- false
- 0
-
11019
27834
148
37
-
11101
27852.5
- 1
- 1
- {0}
-
0
0
0
0
0
1
1
0
0
- Rotated geometry
- 187503ea-36dc-430c-b32c-9a0fc88ca815
- true
- Geometry
- Geometry
- false
- 0
-
11191
27794
50
38
-
11216
27813.25
- Transformation data
- 2edb102d-c38c-4b17-ad62-8b711fbd4fa7
- true
- Transform
- Transform
- false
- 0
-
11191
27832
50
39
-
11216
27851.75
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- f23308dc-6e0b-4773-8442-547e1fc6aa65
- true
- Rotate
- Rotate
-
11022
27886
226
81
-
11184
27927
- Base geometry
- 2c0ae8e6-3630-4763-8c31-b9bbfd2e3c67
- true
- Geometry
- Geometry
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11024
27888
148
20
-
11106
27898
- Rotation angle in degrees
- 92a62df3-18a7-497f-bad7-10c8f60f9a2d
- true
- Angle
- Angle
- false
- 0
- true
-
11024
27908
148
20
-
11106
27918
- 1
- 1
- {0}
- 90
- Rotation plane
- df893b4e-64c0-40e3-aab8-e58edaf6b4f6
- true
- Plane
- Plane
- false
- 0
-
11024
27928
148
37
-
11106
27946.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
0
0
1
- Rotated geometry
- 95df8731-1a7f-41e7-a9cb-ee4366bdc926
- true
- Geometry
- Geometry
- false
- 0
-
11196
27888
50
38
-
11221
27907.25
- Transformation data
- 185ac99e-4fd1-4677-b7ff-41c7d45269a5
- true
- Transform
- Transform
- false
- 0
-
11196
27926
50
39
-
11221
27945.75
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 0904875c-3233-4683-9546-caf8a1b3bca5
- true
- List Item
- List Item
-
10947
27613
77
64
-
11004
27645
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- ee418169-09f2-4e76-b5d5-545d268e3f85
- true
- List
- List
- false
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
10949
27615
43
20
-
10970.5
27625
- Item index
- 0b00e8eb-bba4-4229-85d7-4a747af6e274
- true
- Index
- Index
- false
- 0
-
10949
27635
43
20
-
10970.5
27645
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- fae23512-71a1-4420-9312-ebcf2925939a
- true
- Wrap
- Wrap
- false
- 0
-
10949
27655
43
20
-
10970.5
27665
- 1
- 1
- {0}
- true
- Item at {i'}
- 1e161022-56a4-4db7-b405-3a1b081e4b21
- true
- false
- Item
- i
- false
- 0
-
11016
27615
6
60
-
11019
27645
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e524ba89-65f4-457a-8f3b-566e3d69b338
- true
- Evaluate Length
- Evaluate Length
-
10915
27536
149
64
-
11000
27568
- Curve to evaluate
- f0ab2af7-69c9-43db-868b-caa852889764
- true
- Curve
- Curve
- false
- 1e161022-56a4-4db7-b405-3a1b081e4b21
- 1
-
10917
27538
71
20
-
10952.5
27548
- Length factor for curve evaluation
- fc420753-ba03-4fef-a0a8-a524c2294e69
- true
- Length
- Length
- false
- 0
-
10917
27558
71
20
-
10952.5
27568
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 8f83b134-0f2b-4506-a36b-358c77416dd0
- true
- Normalized
- Normalized
- false
- 0
-
10917
27578
71
20
-
10952.5
27588
- 1
- 1
- {0}
- true
- Point at the specified length
- ac15329e-7811-4638-9e02-958d44a78172
- true
- Point
- Point
- false
- 0
-
11012
27538
50
20
-
11037
27548
- Tangent vector at the specified length
- 68eeceaf-bc83-493a-bd93-69c0745eb406
- true
- Tangent
- Tangent
- false
- 0
-
11012
27558
50
20
-
11037
27568
- Curve parameter at the specified length
- e5f26acc-dc65-4f84-b199-bac1f44df9f2
- true
- Parameter
- Parameter
- false
- 0
-
11012
27578
50
20
-
11037
27588
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 17a07c24-0f69-4fa4-97bb-e3c74ef6d55c
- true
- List Item
- List Item
-
11236
27657
77
64
-
11293
27689
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- a7eca345-3aa0-4a12-8aa2-d6a39cf2468e
- true
- List
- List
- false
- 187503ea-36dc-430c-b32c-9a0fc88ca815
- 1
-
11238
27659
43
20
-
11259.5
27669
- Item index
- d14122b2-7acb-4746-a18e-74977033a79e
- true
- Index
- Index
- false
- 0
-
11238
27679
43
20
-
11259.5
27689
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- 54a61329-e56d-43ff-bc17-2fb9301f00ac
- true
- Wrap
- Wrap
- false
- 0
-
11238
27699
43
20
-
11259.5
27709
- 1
- 1
- {0}
- true
- Item at {i'}
- 8cb14055-5fd5-4d4c-bef3-3b128ef5471a
- true
- false
- Item
- i
- false
- 0
-
11305
27659
6
60
-
11308
27689
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a3a0987e-4742-48b6-afc7-5797464d4f9b
- true
- Evaluate Length
- Evaluate Length
-
11204
27580
149
64
-
11289
27612
- Curve to evaluate
- 30685dfe-7c69-42e5-8c42-242b51d3ca47
- true
- Curve
- Curve
- false
- 8cb14055-5fd5-4d4c-bef3-3b128ef5471a
- 1
-
11206
27582
71
20
-
11241.5
27592
- Length factor for curve evaluation
- 07212ece-558c-4b90-aab4-fa97e1419910
- true
- Length
- Length
- false
- 0
-
11206
27602
71
20
-
11241.5
27612
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 24e30027-61a0-4bf9-8e3d-aaabcf947974
- true
- Normalized
- Normalized
- false
- 0
-
11206
27622
71
20
-
11241.5
27632
- 1
- 1
- {0}
- true
- Point at the specified length
- d862f42d-b7d5-4961-8f17-2c24fd595947
- true
- Point
- Point
- false
- 0
-
11301
27582
50
20
-
11326
27592
- Tangent vector at the specified length
- f285b504-4093-46e2-9eb0-9a385df801db
- true
- Tangent
- Tangent
- false
- 0
-
11301
27602
50
20
-
11326
27612
- Curve parameter at the specified length
- 5a57e3ed-694c-4971-b6d3-c608b9faaea3
- true
- Parameter
- Parameter
- false
- 0
-
11301
27622
50
20
-
11326
27632
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- ed800b1a-87bc-41be-b147-fd8cf8fee48b
- true
- List Item
- List Item
-
11319
28039
77
64
-
11376
28071
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 7cdfb12e-b2df-4b62-9889-6b875368dc1c
- true
- List
- List
- false
- 95df8731-1a7f-41e7-a9cb-ee4366bdc926
- 1
-
11321
28041
43
20
-
11342.5
28051
- Item index
- 46a9e4b4-4ee0-4a14-8717-9ee715e06e09
- true
- Index
- Index
- false
- 0
-
11321
28061
43
20
-
11342.5
28071
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- 385de72d-084e-43f5-87e9-f9b7a9fd90b3
- true
- Wrap
- Wrap
- false
- 0
-
11321
28081
43
20
-
11342.5
28091
- 1
- 1
- {0}
- true
- Item at {i'}
- 1ba44e11-3244-4b08-8f5a-53473e7444b0
- true
- false
- Item
- i
- false
- 0
-
11388
28041
6
60
-
11391
28071
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 74d54793-b4ac-4902-b2db-7eb97fad4e83
- true
- Evaluate Length
- Evaluate Length
-
11287
27962
149
64
-
11372
27994
- Curve to evaluate
- bcac2eb2-1cf5-4798-b21c-3c1c4e53b1a4
- true
- Curve
- Curve
- false
- 1ba44e11-3244-4b08-8f5a-53473e7444b0
- 1
-
11289
27964
71
20
-
11324.5
27974
- Length factor for curve evaluation
- 942ec385-14c4-436d-82bf-254a62c4a81d
- true
- Length
- Length
- false
- 0
-
11289
27984
71
20
-
11324.5
27994
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- c507fc36-6518-440d-8b39-378189e13d72
- true
- Normalized
- Normalized
- false
- 0
-
11289
28004
71
20
-
11324.5
28014
- 1
- 1
- {0}
- true
- Point at the specified length
- 228ba4c9-f335-40d7-830a-930ba0b8f370
- true
- Point
- Point
- false
- 0
-
11384
27964
50
20
-
11409
27974
- Tangent vector at the specified length
- d66d6972-1966-4d7c-9727-8ccdb137e40d
- true
- Tangent
- Tangent
- false
- 0
-
11384
27984
50
20
-
11409
27994
- Curve parameter at the specified length
- ac5a3688-b5cc-4a0b-9013-606a50e82bfa
- true
- Parameter
- Parameter
- false
- 0
-
11384
28004
50
20
-
11409
28014
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e22a8212-4fbe-44d1-8960-60bce1b0633f
- true
- PolyLine
- PolyLine
-
11590
27769
116
44
-
11654
27791
- 1
- Polyline vertex points
- 1946d427-26c0-48d0-917c-d955ea38c046
- true
- Vertices
- Vertices
- false
- ba092d75-6ec4-47d7-beb9-6b24514697d2
- 1
-
11592
27771
50
20
-
11617
27781
- Close polyline
- 44054ace-1398-46bc-9f17-4f9d8eeb27bd
- true
- Closed
- Closed
- false
- 0
-
11592
27791
50
20
-
11617
27801
- 1
- 1
- {0}
- true
- Resulting polyline
- 05892abf-8ecd-4e8f-8e64-1a63af85f8a0
- true
- Polyline
- Polyline
- false
- 0
-
11666
27771
38
40
-
11685
27791
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 02c8e8c3-a797-4e87-96c5-9928bebed6f3
- true
- Merge
- Merge
-
11455
27717
90
84
-
11500
27759
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 60f109f9-2c6a-4f93-bf8b-8fb1a84cd617
- true
- false
- Data 1
- D1
- true
- 228ba4c9-f335-40d7-830a-930ba0b8f370
- 1
-
11457
27719
31
20
-
11472.5
27729
- 2
- Data stream 2
- 372d7189-edd9-4199-bcd3-a3c8ea2484c4
- true
- false
- Data 2
- D2
- true
- d862f42d-b7d5-4961-8f17-2c24fd595947
- 1
-
11457
27739
31
20
-
11472.5
27749
- 2
- Data stream 3
- 74aa7d1d-4920-4190-a60a-f45e0bd11a4b
- true
- false
- Data 3
- D3
- true
- ac15329e-7811-4638-9e02-958d44a78172
- 1
-
11457
27759
31
20
-
11472.5
27769
- 2
- Data stream 4
- 16d89d23-f403-40cf-869a-c47a5a6016e9
- true
- false
- Data 4
- D4
- true
- 0
-
11457
27779
31
20
-
11472.5
27789
- 2
- Result of merge
- ba092d75-6ec4-47d7-beb9-6b24514697d2
- true
- Result
- Result
- false
- 0
-
11512
27719
31
80
-
11527.5
27759
- 61d81100-c4d3-462d-8b51-d951c0ae32db
- Triangle Mapping
- Transform geometry from one triangle into another.
- true
- dc21fb8d-0ffb-45b1-aa92-8716354d0746
- true
- Triangle Mapping
- Triangle Mapping
-
11645
27648
126
64
-
11707
27680
- Base geometry
- 2746e58e-6745-45e5-bab3-d884e451357f
- true
- Geometry
- Geometry
- true
- bc6ee7cc-dfce-484f-b2eb-2a5a4d0007c8
- 1
-
11647
27650
48
20
-
11671
27660
- Triangle to map from
- e74900ea-b0f1-4464-9528-06aa310a52a1
- true
- Source
- Source
- false
- 313dc56d-5db5-4cb0-88da-248d848cf9d0
- 1
-
11647
27670
48
20
-
11671
27680
- Triangle to map into
- 909b36f8-16c1-4204-b306-99fd4cd11f04
- true
- Target
- Target
- false
- 05892abf-8ecd-4e8f-8e64-1a63af85f8a0
- 1
-
11647
27690
48
20
-
11671
27700
- Mapped geometry
- 311286dc-fe96-40a7-815b-24a54f71dd3c
- true
- Geometry
- Geometry
- false
- 0
-
11719
27650
50
30
-
11744
27665
- Transformation data
- e745e45c-567e-4db7-8ebc-2f3073131b2f
- true
- Transform
- Transform
- false
- 0
-
11719
27680
50
30
-
11744
27695
- c9785b8e-2f30-4f90-8ee3-cca710f82402
- Entwine
- Flatten and combine a collection of data streams
- false
- true
- 779daf5b-bb9f-4b0f-8250-d59d858f4457
- true
- Entwine
- Entwine
-
11461
27555
85
64
-
11501
27587
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to entwine
- d3f7a5c9-5e8b-471c-8ae6-8a3fb0d3b7f8
- true
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- Branch {0;x}
- {0;x}
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11463
27557
26
20
-
11476
27567
- 2
- Data to entwine
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26
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- 2
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26
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31
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11528.5
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85
44
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27500
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11619
27480
26
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11632
27490
- 2
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27500
26
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11632
27510
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11669
27480
31
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11684.5
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28175
226
81
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11694
28216
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11534
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148
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148
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28217
148
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11706
28177
50
38
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11731
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11706
28215
50
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27963
103
28
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27965
44
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27977
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27965
31
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172
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11085
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123
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123
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11011.5
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11097
28301
21
28
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11107.5
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28329
21
29
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11107.5
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77
84
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11053
28250
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11020
28210
21
80
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11030.5
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11065
28210
28
20
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11079
28220
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11065
28230
28
20
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11079
28240
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11065
28250
28
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11079
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11065
28270
28
20
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11079
28280
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210
121
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132
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132
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132
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132
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11244
28407
132
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11310
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50
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50
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108
44
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38
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42
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11205
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42
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11218
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70
44
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11302
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- 2
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11
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- Second item for addition
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11
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31
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70
44
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- Item to divide (dividend)
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11
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- Item to divide with (divisor)
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11379
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11
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11414
28174
31
40
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11429.5
28194
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
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-
11532
28357
226
81
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11694
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11534
28359
148
20
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11616
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11534
28379
148
20
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11616
28389
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11534
28399
148
37
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11616
28417.5
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0
0
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0
1
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11706
28359
50
38
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11731
28378.25
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11706
28397
50
39
-
11731
28416.75
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
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11538
28460
226
81
-
11700
28501
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11540
28462
148
20
-
11622
28472
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11540
28482
148
20
-
11622
28492
- 1
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11540
28502
148
37
-
11622
28520.5
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0
0
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0
0
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1
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-
11712
28462
50
38
-
11737
28481.25
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11712
28500
50
39
-
11737
28519.75
- c9785b8e-2f30-4f90-8ee3-cca710f82402
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27554
85
44
-
11900
27576
- 2
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11862
27556
26
20
-
11875
27566
- 2
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11862
27576
26
20
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11875
27586
- Entwined result
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-
11912
27556
31
40
-
11927.5
27576
- c9785b8e-2f30-4f90-8ee3-cca710f82402
- Entwine
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11862
28234
85
64
-
11902
28266
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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28236
26
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11877
28246
- 2
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11864
28256
26
20
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11877
28266
- 2
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11864
28276
26
20
-
11877
28286
- Entwined result
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-
11914
28236
31
60
-
11929.5
28266
- c9785b8e-2f30-4f90-8ee3-cca710f82402
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11990
27592
100
64
-
12045
27624
- 3
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11992
27594
41
20
-
12012.5
27604
- 2
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11992
27614
41
20
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12012.5
27624
- 2
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11992
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- true
- Merge
- Merge
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28499
90
64
-
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28531
- 3
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- Data stream 1
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- Data 1
- D1
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12400
28501
31
20
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12415.5
28511
- 2
- Data stream 2
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- Data 2
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12400
28521
31
20
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12415.5
28531
- 2
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- Data 3
- D3
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12400
28541
31
20
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12415.5
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-
12455
28501
31
60
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12470.5
28531
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- Create a polar array of geometry.
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- ba33b008-e040-47d1-8e6f-3b360b5bf43c
- true
- Polar Array
- Polar Array
-
12517
28406
207
84
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12644
28448
- Base geometry
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- 1
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12519
28408
113
20
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12575.5
28418
- Polar array plane
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- 8466f10c-3993-400e-8742-e7e3f179651f
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12519
28428
113
20
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12575.5
28438
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- 0
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12519
28448
113
20
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12575.5
28458
- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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-
12519
28468
113
20
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12575.5
28478
- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
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- 1
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12656
28408
66
40
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12681
28428
- 1
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- 0
-
12656
28448
66
40
-
12681
28468
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- Join Curves
- Join Curves
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12564
28289
116
44
-
12631
28311
- 1
- Curves to join
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- Curves
- Curves
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- acba9f12-7c5f-4b20-8140-fb2b4854a190
- 1
-
12566
28291
53
20
-
12592.5
28301
- Preserve direction of input curves
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- Preserve
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- 0
-
12566
28311
53
20
-
12592.5
28321
- 1
- 1
- {0}
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- 1
- Joined curves and individual curves that could not be joined.
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
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- Curves
- Curves
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- 0
-
12643
28291
35
40
-
12660.5
28311
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
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- 60b468ed-f005-442a-98a1-2f5f06f6910c
- true
- List Item
- List Item
-
12296
28677
77
64
-
12353
28709
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- Base list
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- List
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- 1
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12298
28679
43
20
-
12319.5
28689
- Item index
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- Index
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- 0
-
12298
28699
43
20
-
12319.5
28709
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
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- Wrap
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- 0
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12298
28719
43
20
-
12319.5
28729
- 1
- 1
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- true
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- Item
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- 0
-
12365
28679
6
60
-
12368
28709
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- 345e50d9-106f-48b0-8a5f-82619b7a42d8
- true
- Rotate
- Rotate
-
12430
28714
170
64
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12536
28746
- Base geometry
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- Geometry
- Geometry
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- 3914ac59-33d9-41bd-9611-37164936a031
- 1
-
12432
28716
92
20
-
12486
28726
- Rotation angle in degrees
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- Angle
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- 0
- true
-
12432
28736
92
20
-
12486
28746
- 1
- 1
- {0}
- 120
- Rotation plane
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- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
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12432
28756
92
20
-
12486
28766
- 1
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0
0
0
1
0
0
0
1
0
- Rotated geometry
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- Geometry
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- 0
-
12548
28716
50
30
-
12573
28731
- Transformation data
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- 0
-
12548
28746
50
30
-
12573
28761
- 75164624-395a-4d24-b60b-6bf91cab0194
- Sweep2
- Create a sweep surface with two rail curves.
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- 2b841695-b801-4232-8cec-df1e95b3ffb0
- true
- Sweep2
- Sweep2
-
12832
28253
125
84
-
12918
28295
- First rail curve
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- Rail 1
- Rail 1
- false
- 5ef63ff9-6730-42b3-b53c-8762ec52dae5
- 1
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12834
28255
72
20
-
12870
28265
- Second rail curve
- 77951b5e-c755-4586-93e1-b5073c2e9e8e
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- Rail 2
- Rail 2
- false
- 25b86b00-4b1e-44df-819e-b87ac8d0f104
- 1
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12834
28275
72
20
-
12870
28285
- 1
- Section curves
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- Sections
- Sections
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- 3b6ac9ce-f66a-47f3-8b74-010a93404a3e
- 1
-
12834
28295
72
20
-
12870
28305
- Create a sweep with same-height properties.
- 1e488029-c63b-4aef-bc34-8917303e40cc
- true
- Same Height
- Same Height
- false
- 0
-
12834
28315
72
20
-
12870
28325
- 1
- 1
- {0}
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- 1
- Resulting Brep
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- Brep
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- 0
-
12930
28255
25
80
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12942.5
28295
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
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- ed0799d7-3bc0-4ce1-9e3e-b4eafc3d5546
- true
- List Item
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12432
28860
77
64
-
12489
28892
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
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12434
28862
43
20
-
12455.5
28872
- Item index
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- Index
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- 0
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12434
28882
43
20
-
12455.5
28892
- 1
- 1
- {0}
- 12
- Wrap index to list bounds
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- 0
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12434
28902
43
20
-
12455.5
28912
- 1
- 1
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- Item
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- 0
-
12501
28862
6
60
-
12504
28892
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
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- true
- Rotate
- Rotate
-
12654
28749
226
81
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12816
28790
- Base geometry
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12656
28751
148
20
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12738
28761
- Rotation angle in degrees
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- 0
- true
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12656
28771
148
20
-
12738
28781
- 1
- 1
- {0}
- -90
- Rotation plane
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12656
28791
148
37
-
12738
28809.5
- 1
- 1
- {0}
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0
0
0
1
0
0
0
1
0
- Rotated geometry
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- 0
-
12828
28751
50
38
-
12853
28770.25
- Transformation data
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- 0
-
12828
28789
50
39
-
12853
28808.75
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- true
- Merge
- Merge
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12642
28599
90
64
-
12687
28631
- 3
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- Data stream 1
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- Data 1
- D1
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- 3914ac59-33d9-41bd-9611-37164936a031
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12644
28601
31
20
-
12659.5
28611
- 2
- Data stream 2
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- Data 2
- D2
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- a0df3237-16e5-4cbd-a199-50b04c6274bb
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12644
28621
31
20
-
12659.5
28631
- 2
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- Data 3
- D3
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- 0
-
12644
28641
31
20
-
12659.5
28651
- 2
- Result of merge
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- 0
-
12699
28601
31
60
-
12714.5
28631
- 22990b1f-9be6-477c-ad89-f775cd347105
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- Flip a curve using an optional guide curve.
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- Flip Curve
- Flip Curve
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12706
28501
88
44
-
12750
28523
- Curve to flip
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- 1
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12708
28503
30
20
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12723
28513
- Optional guide curve
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-
12708
28523
30
20
-
12723
28533
- Flipped curve
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- 0
-
12762
28503
30
20
-
12777
28513
- Flip action
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- Flag
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- 0
-
12762
28523
30
20
-
12777
28533
- 22990b1f-9be6-477c-ad89-f775cd347105
- Flip Curve
- Flip a curve using an optional guide curve.
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- Flip Curve
- Flip Curve
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12929
28778
88
44
-
12973
28800
- Curve to flip
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- 1
-
12931
28780
30
20
-
12946
28790
- Optional guide curve
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- Guide
- Guide
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-
12931
28800
30
20
-
12946
28810
- Flipped curve
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- Curve
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- 0
-
12985
28780
30
20
-
13000
28790
- Flip action
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- Flag
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-
12985
28800
30
20
-
13000
28810
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 9935447c-3f80-44d3-8052-01fa076971e7
- true
- List Item
- List Item
-
12388
27951
77
64
-
12445
27983
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- Base list
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- List
- List
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- 1
-
12390
27953
43
20
-
12411.5
27963
- Item index
- 005f07a2-8048-404f-883d-5a342c3566e4
- true
- Index
- Index
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- 0
-
12390
27973
43
20
-
12411.5
27983
- 1
- 1
- {0}
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- Wrap index to list bounds
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- Wrap
- Wrap
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-
12390
27993
43
20
-
12411.5
28003
- 1
- 1
- {0}
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- Item
- i
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- 0
-
12457
27953
6
60
-
12460
27983
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Get the point in the middle of a curve
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- true
- Curve Middle
- Curve Middle
-
13532
27996
101
28
-
13576
28010
- Curve for mid-point.
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- ff4b1356-82ea-4cf7-9d66-2ed9f409faef
- 1
-
13534
27998
30
24
-
13549
28010
- Point in the middle of the curve
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- 0
-
13588
27998
43
24
-
13609.5
28010
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
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- Point
- Point
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12962
28056
99
24
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13049.63
28068.02
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- 1
- {0}
-
0
0
0
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- Relay
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- A wire relay object
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-
11664
28034
40
16
-
11684
28042
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
12931
28356
207
84
-
13058
28398
- Base geometry
- fcd5c8ad-c3be-4e0f-aa7b-6a718f026e43
- true
- Geometry
- Geometry
- true
- 0490c4ad-b715-43e9-85d4-2fa26a0f17a7
- 1
-
12933
28358
113
20
-
12989.5
28368
- Polar array plane
- 1b718b59-fd18-44eb-b17c-1fd6a1a0c6a7
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
12933
28378
113
20
-
12989.5
28388
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 17c2c2bb-1438-410d-9450-05653a3d6610
- true
- Count
- Count
- false
- 0
-
12933
28398
113
20
-
12989.5
28408
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- cd9bc5d0-c344-4716-a064-eecf171207ef
- true
- Angle
- Angle
- false
- 0
- false
-
12933
28418
113
20
-
12989.5
28428
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 8417b745-f41f-4d9e-8bbb-9e5377f43932
- true
- 1
- Geometry
- Geometry
- false
- 0
-
13070
28358
66
40
-
13095
28378
- 1
- Transformation data
- 9beef5c1-f0e3-4213-8b40-a8de215f7c5b
- true
- Transform
- Transform
- false
- 0
-
13070
28398
66
40
-
13095
28418
- 75164624-395a-4d24-b60b-6bf91cab0194
- Sweep2
- Create a sweep surface with two rail curves.
- true
- 1df9d5e6-0ba1-4a1d-98c6-385bff3e9a5d
- true
- Sweep2
- Sweep2
-
12900
28616
125
84
-
12986
28658
- First rail curve
- b18cea78-d396-434a-b057-a5994b6649ae
- true
- Rail 1
- Rail 1
- false
- 788c609b-314a-42fc-9ea6-dd50e84c46d0
- 1
-
12902
28618
72
20
-
12938
28628
- Second rail curve
- 33b8c586-75e6-4631-828e-efad1f382d6b
- true
- Rail 2
- Rail 2
- false
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- 1
-
12902
28638
72
20
-
12938
28648
- 1
- Section curves
- 983cc157-3d94-43a5-9ddf-15500de2ac90
- true
- Sections
- Sections
- false
- 3914ac59-33d9-41bd-9611-37164936a031
- 1
-
12902
28658
72
20
-
12938
28668
- Create a sweep with same-height properties.
- 4f12b42c-ec4a-489b-887b-9f59ee1a5034
- true
- Same Height
- Same Height
- false
- 0
-
12902
28678
72
20
-
12938
28688
- 1
- 1
- {0}
- true
- 1
- Resulting Brep
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- true
- Brep
- Brep
- false
- 0
-
12998
28618
25
80
-
13010.5
28658
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- f9e9b3d3-0249-4fcd-9010-bda7192c49ec
- true
- List Item
- List Item
-
12550
28503
77
64
-
12607
28535
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- e3fa9389-8bb9-4073-bc9a-8fe79cbc3dc9
- true
- List
- List
- false
- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
-
12552
28505
43
20
-
12573.5
28515
- Item index
- 1f0c42fb-a12e-4e1e-a081-0ae5918b3e34
- true
- Index
- Index
- false
- 0
-
12552
28525
43
20
-
12573.5
28535
- 1
- 1
- {0}
- 6
- Wrap index to list bounds
- e30de5c8-e07a-4549-97aa-1294a3f1ea5c
- true
- Wrap
- Wrap
- false
- 0
-
12552
28545
43
20
-
12573.5
28555
- 1
- 1
- {0}
- false
- Item at {i'}
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- true
- false
- Item
- i
- false
- 0
-
12619
28505
6
60
-
12622
28535
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- 4b52ff38-2edb-42fc-ad3c-aad65645bfbf
- true
- Mirror
- Mirror
-
13151
28584
305
61
-
13392
28615
- Base geometry
- 505f36ba-5d42-4711-bb2f-12412b8d9067
- true
- Geometry
- Geometry
- true
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- 1
-
13153
28586
227
20
-
13266.5
28596
- Mirror plane
- f2f9db89-552e-445e-8378-f2fc9f019f55
- true
- Plane
- Plane
- false
- 0
-
13153
28606
227
37
-
13266.5
28624.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
-0.707106781186548
0
0.707106781186547
- Mirrored geometry
- 9e81018f-eb0e-422b-8b03-5fa6f29962ba
- true
- Geometry
- Geometry
- false
- 0
-
13404
28586
50
28
-
13429
28600.25
- Transformation data
- 9cd75d03-875f-4f14-a38a-33fee0ebdc03
- true
- Transform
- Transform
- false
- 0
-
13404
28614
50
29
-
13429
28628.75
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 2aa02528-07ad-4eb2-a14e-23480eb36571
- true
- Polar Array
- Polar Array
-
13242
28697
207
84
-
13369
28739
- Base geometry
- c7101f1b-5f11-4b5a-8ce4-aca0d3add6ab
- true
- Geometry
- Geometry
- true
- 060648e6-d9c2-477c-ba2f-71b14f63a036
- 1
-
13244
28699
113
20
-
13300.5
28709
- Polar array plane
- a8471fed-2546-4fb0-93a9-d9cebc0b92ea
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
13244
28719
113
20
-
13300.5
28729
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 0e17a2e0-16f2-4382-82e4-704ea4d7c239
- true
- Count
- Count
- false
- 0
-
13244
28739
113
20
-
13300.5
28749
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 5bc28fd2-567f-42d5-976a-afe024f38684
- true
- Angle
- Angle
- false
- 0
- false
-
13244
28759
113
20
-
13300.5
28769
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- b3e9652a-0589-4dbf-b8e1-243721b1bfc1
- true
- 1
- Geometry
- Geometry
- false
- 0
-
13381
28699
66
40
-
13406
28719
- 1
- Transformation data
- bbc36e0c-38f8-4c59-8ccd-b9ec863cf0e6
- true
- Transform
- Transform
- false
- 0
-
13381
28739
66
40
-
13406
28759
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- a1881539-51c5-48a1-b579-c1eeb39cdbdd
- true
- Merge
- Merge
-
13233
28480
90
64
-
13278
28512
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 38b8585d-bfe9-4a59-be1f-6f310459249a
- true
- false
- Data 1
- D1
- true
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- 1
-
13235
28482
31
20
-
13250.5
28492
- 2
- Data stream 2
- 6b0e7e6c-52be-48fb-934b-f4c80cd0c3fe
- true
- false
- Data 2
- D2
- true
- 9e81018f-eb0e-422b-8b03-5fa6f29962ba
- 1
-
13235
28502
31
20
-
13250.5
28512
- 2
- Data stream 3
- 264bee91-6031-4c1f-aae1-ef024f5be16e
- true
- false
- Data 3
- D3
- true
- 0
-
13235
28522
31
20
-
13250.5
28532
- 2
- Result of merge
- 060648e6-d9c2-477c-ba2f-71b14f63a036
- true
- Result
- Result
- false
- 0
-
13290
28482
31
60
-
13305.5
28512
- 57b2184c-8931-4e70-9220-612ec5b3809a
- Patch
- Create a patch surface
- true
- 896526e7-4b6f-49d0-9eba-8afd5bc1f034
- true
- Patch
- Patch
-
13037
28213
119
104
-
13113
28265
- 1
- Curves to patch
- 57e2c7ab-acb9-4ad3-98b6-2608f40034d6
- true
- Curves
- Curves
- true
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
- 1
-
13039
28215
62
20
-
13070
28225
- 1
- Points to patch
- 63afc207-44e8-434b-a8b5-07bc63a085f4
- true
- Points
- Points
- true
- 5cacee03-857e-4f27-8db3-fad6acaee1f8
- 1
-
13039
28235
62
20
-
13070
28245
- Number of spans
- 94205002-ff33-4d56-aa50-8c9de91b06d7
- true
- Spans
- Spans
- false
- 0
-
13039
28255
62
20
-
13070
28265
- 1
- 1
- {0}
- 16
- Patch flexibility (low number; less flexibility)
- fc501350-14e6-48eb-a9a6-29dedcd983f8
- true
- Flexibility
- Flexibility
- false
- 0
-
13039
28275
62
20
-
13070
28285
- 1
- 1
- {0}
- 8
- Attempt to trim the result
- 5159e24d-fc93-4859-a5c5-506c1538b080
- true
- Trim
- Trim
- false
- 0
-
13039
28295
62
20
-
13070
28305
- 1
- 1
- {0}
- true
- Patch result
- d636886e-6a7c-4eda-b4a4-ca364081a1e2
- true
- Patch
- Patch
- false
- 0
-
13125
28215
29
100
-
13139.5
28265
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- Curvature analysis
- Analyzes surface curvature
-
Dgva7o5MdBxh6ffAWXPPNJAy7sRtRKbicMvX5SX8WMHBAH39x104KL4LljbN5bT66X9MvUq3rFpnJek0kQoWLPiYB5rRYiPhXSpDhdptFKa22IUpk38BjRJJbWayiQM/IqWsrckG0u3neyIDB+vNV9gfwxw3xYacnqWl6buiR5MjUZqtmlfMl1V3CqI0H5r0yBdeefC9P8EqNGJCvJnw1a1YS2SV71vSGcSv8dPB0CPABJSGmuivV2FnQ9jidF94008wEsXLUyS5nOU1Dk1Qc01c8+EBpmJWSgLVnkuES4ixjYcJOS8MhPM24U/fe7Z6Nnw3AwvUrBTQQtyNvbALV6+da2btb3BxHA+gMfsKy3zO6my5QeQEXWISmkIi07l3HLcD42GzR9mr2hIaxbAcLujonUPL0QfVOohxSxVPl0TdUgf+yxcGnUg8nhTKUceklz42bU5uqyDFpHLkriYWBhuDO13c9DCDSBYpoDmKNQ873akOYIlLkLIiNlQpr42pQTW+Jqgprmurue/FlqPn5vXpXI15RxeZ7zgUXVa3TR1Rv3kQTlydekocJDSsTCnLSvbR1Zgv7BSoDVx01bcCdxWO8/E6TLL+scAM0VFzpuaO21UTs2S8dFcB0ZzjGdhQopTpCdcgPYzWnLc1pzwU2SJXflZvfDP8a3uyP5P62HZi6N3a757+lFtvWYd6ingE2jVA1Ahe/hN3KZgcre5PJU/MiYB/yjXGeUfBuVoWRkhey/N3yW1FTkwqCSP+AXxsXcG+ChRWt0b6vglVHD8Sz8GA17SEKgL/612JAeq0Wj9YDw9VevXiE5OXkf405M3etTYGHJya7X4r25Am+ug8Wl6TjMCV1RsKYVZJmzgPkvdLhfxs5nrYA3gWSrzWmooYWA1FOdRA1rYlklughEoNzrlwHt2Re5Mu9r39nHPmVO0aQWyqAkJunN++3c39WdWcRs1SyQIQJyx2+DelsY4AIQmWnI/hN2I+GQBMkpm0bKx9e7BCq0pDvcgJaDb0LnJnaPfVqNDaHt3UUPSmN0QwY1sgVOXl61w7zUUPmrdMX4/Jq4F7tLueSSeCRBh7MNBmAMeS6F6PAM8RMfY2oyfyunRv+dE8b0PSbKtNcDCBctcQ7UpUWEsisxYLHyW814ci4ujoinrNsaoYuNbejPlF3beBHiVl15ILItltUFjkAVv5XWzHAwcScTzNf0iloA4V76NQXpTpjlUcGfjP7Q7VV+I52aV/6rtmuCNeADTq7CKEpYWZHibaxhwEVpMCUE/t4aKr/8xUk9DoOJvNvS8gtdvvsFOk6HS3CHQztQzkfKxBSUmXw6Vihu9ETGp9jhALb6DrTZfFLpeEaJ/lZURi0TXhJ2wMDKjDHXTp9HwCR8bk4q8gA8QdqNZFV9zJ0Xg3o6EP33WdnOvjHZOXQGzcG7Ao3f5153utPmym1VNPJL0bEMWTr4J5Eh8404Sgr8OYGbI57svKELbHP66gFHZTUlY4DBW1PwGJoAZZse8FxRQ9+Lxj8Dn4ZULg9Ar+bZm29Mkrf00tdNy3LVbkE6la0keSVGfV4y0nigEkidW/a4YBojauVuWUEWiR/t3l3fmOjDWfRi7utdfBRYnUwdQLOeftegMw+UI568GB3+3Kei4aWlrfYiHGZXQwFCaUM60Mol2NfxGpkYqSt4XZLV8dyHCz1CZrvKgUgysMtdLjreI2L0CxQ0L7+JL27QrMigsFeJ2Vj/U3RlrEHQABc4goNqQoWTvClSY9yBrtvgeYzj196EycmSW4H/x3lji56Cg9J9uyYf4GU3YD7XCbiVhGtLI+uVMyx3iUHRQEr+2oy4GYTviR5vIcvi7tualfEMuG61dce84czN3KCBXa/KbfPqXl8/w8y62CBAnMzVxwfcAekM9QNAKqSTQlma6AJUHSKmMZd7DmJBM3aaLKR2Q5i5Li7JnUoE1t9fwCVJh10vFLMD3gqglGUwSQx5t2JaNPbg40IXZtiFaLyW444IciaW7V245k/rvN3nKpcM8LqbY6HDfWcBnmwdwjB3pnYJld03OQWRTTI0zhWVETBC/Hzi8u3v/WRQPQjY6e3XkJf+QfIxA5bn0IF4i6Kr2kaLDAs7did3bjQin0ruWLtl6tDf1eP/tVM9sxgDR+O3vfFzMsWP2gwe5Nd2jVU7bdtyzYCLJiAQ3uLGKwumfrOjQazACFoihok3Ed/rZqFQpkWVD0+SRxHiNYKHO7y+7vF3K1hIezX514Tk4lTg8jgFtPG1QeSVSk4gn7kYaXwylWDriugI2BIYb9Zj1Y0IRbbKRjNKYASIOt6qJUWPHa1sdiQPaQZ6+argVtpn8+Yd/pYH+ANNT4FykAEL6bs2ykACiTm8dBgYTwTxDuy0BJVEp9ZNdgZbdYUBpC96W54Umu2MNqLFTBFAqwydTebMoSY6gf5ZddIllpo+7CB9LZSA1qZvm0YvDXqfMvau2uXVdFfIg7eeVzXP1gWvHxSC9c7vJmWDI333KTYqBWaanK1OuAMY4MQ1XqEX9qcj/RIdQApB6/g+mj9GZclwsN0v1Ryt2RnimZaKW6dTjqvZ0yDEUMefbx+PWAj8Nly7+ls6rbIiYQbNpd8DG1N9vGFaiIr0z595y8l0HbqxqTkRTWgtwXkJfWTQHbiJ9TAruyHgJfBb7wP09IQRrf8r2lets8rUOVRtk77Ysw+fpLoGX/dKaiaxbmKUYIQEWmRVZ9N7p5KhuTfw8b/BEz2uBQRFCW6LAUOGi71aSsXZCwOtGLwSZccWF0W0YC6CeFEoH2Q2NScycr+84Xa5jfg4FOgHPFZHe1WMl5B1SqDDcAMywRnit+emd7BOnc5ZWDilrcjLhaMSXLW23LOOlpy3ex9tFRaK3fPsC0K6SUW8vrlmVfzsA7+MBSsS1UaHgERF71soPaJrEJkGjtfI1emx13dcuQB2PbgAXXHijArUkYhLFXT+Lrvx0RyZMt+WgAGZFscawvXPf8Po2y+RfqfMs40YlnA4BabAMXuRKWGb62UDpkFMCxZF+ppmAGgcv3u0efbPUVfrAUwzr6kVzpil5C19hRgmBkZ8nxH3k0wTEdLiqTckXAR3qixSoPzF1jLMhGL9v7VHXId+tWEiEEzLbO8TxjtJJLR8kg8pQqvllrT+kTx49HB/t2thwRkGZTFECE45X0G9VIGrg4Ss8GxC5TL7HCE3SRe7Z1dXXTH6nnZIKy3u2wqUuX/mU7l7PXeaycvqON3Lh7e89cR4SN41YBeCg5qP+9nob9M1TqctwFl6zfeOfqAneJ/Fvr7OaQtO/myYDK9oXk7zmklEpvb1zseiUrGGJ/we8kc5SAu4m/ei9LJxnu6aCnUVxwgC88PFDGrxSyxzaOxQd3RmC3XR/QtCgQ3Esnfqxq+jr+Sf7r4VnBHqrqYI2XwICGe8/wKzfMxcsiPLvr3xhIaOQ83LSjA4ljK77aLfSgDIADhydkgEUnrpbw2xzm8GTxJ8Ah9f2PT22E+re+wSO6g4dAYf8JKO8VIlgBzue55mg5TodX2kD9c7/288bd9rybFONufvKEJqo1Q1nR68Y+Nk/N0g38UIvqVX3hICwsyWe22ssdGk519bMO1xU8J7gHSPaTOSvGkQLvyp7iJg8RnGcFeaHOL4nUOlqmruK/l3onPldDd11467qO98672mTjm9LY4t7qeamNQuAHGDFxov3dkCCEoH9V8CVjfTiCBXC85+edhXeSAWq8J4n5DS2Xba20M2uqyG2EMszsTtzcOrpMrbxo4zblE5A9HOGjSwvoBnGL98lXByKnVHhSOneWSBKu6KcwQGom/bD3wbnArfHJyZsDB/wJq3TvxlA42LFNrZs0qhr2gFBhye5KFcd2gVa9fdwpsseVV4BXyKf2aoR4PWstTyksOm9XSdB3ZzNmyHvLxxXr5zi9aD0n7LXW/+ZlaX5npkW19ZmV0R3/8a5MyU/KOPiuLxrVASYPPuP4u8uad3/aMHFXfeYM9KwXTKzEgMgnupfcmsYvxgxQs2Jr2bBrxgCJY14tnM0mL4G7vlVUKpqwBJR+jnEPGjBpIjkY3+UtrFxaQ0jTrTlPE0XiZpKNGeRN+kxmxBf4pTcRyf4ox7+cJhPVZgtInvUFqmf3/jYB/FwjcJx6bj8UWSA1k5ShG7YnUxOky4q7pFnUl3CttisE+XbjzcEv51aPdKRdyr+qBbHe6A1wdjPN23CsAic5mnqUDW7jiT4ttXA+O5+s86l9+k7B24PCsVLH5oRpQztqu9PpMLXViyiDeE2E1jDLABu3fwwqCuLELA3iCG3md0DwGygxmfB1sFnsj6eAj/M3Fap15oYpKDL4frhqosxdS29DwwtAR3UWjXou0QXmdrH/fDcgiLoyG7Di7c7zqtfSJOGavgS0cY1iKGlCEsvCqIdSeu1SA5FnahMp5Q5S1Q2J5nuPmHOQg5RErgxox/2oQ5EU9V5DiXCO0vGUSttT+C0FLAiBlJDHl8/QytYWPCtSYAbVnsXVaEMBhPYcPC0/pbSuBUF9WUbz1A3e4+mtgfJp9hsOmWXtKeRi7CbxHuMnjrkVUiaGKg2T1quCpZRZ9eCvuZOaestY/DFdH3z34DYaAy8kyAl781guAVsECUDslLb/MEQvDuldd36HIt/85NeOLz5zDZC4B6CRCxGA8jpk7NT5jTz/eOTtgex01z8SuJP+y1tzEma2zL2Uebct3i8DiUta8B6mXw8DuTE0OzJ+BOGlLNAQQbvmCiltoegyFm6yJuhTMVfVeWJ6UDORR5mYV6X0EVggUDgCWQ+by5AQu9ltCxBTNFbGfMvrFx/qnETE6sUmGtxypz+byDFfaBQfy+gD6w0qtiQ2+NVw9qZHUyOcfOEcgG39TCqkDnndrTNs6kyq5wdswSWSx6eSHkbjPcTVg5EWjJy26zhIrtW5BNktdOCcl0OJ/LdlIT7C5x3E7/Wwhndo7JmmZKQkCtd+ROg+3ikiZtOxeiQ6gspISnTfZ2xI/ZFBGrZWm7L5Br6Iw1mOYy+SiT74eDCNdRUi3qofbrM3uJTSaiWmH2YGmr7wjVA4FxlDmj1BvY/JAreb8Pp7mhhymNs3cGoKiTQkyQ3vAHt+Gtl5qiIJDWVOMGd3RxOcWp1+Betq2+SXwGVsFqGWImiUHmit1EjtjFBT2fxpZZRvaSD+BLAA4rnnpGB12lFiedY7EBb8JiHuXT7p+xvIEKGa79gpFrRHCv+06+T7FZ/4tZ9MP+LQwLN74eWhuXVHQzAlBkrbUz7aM/IunpmqL6bRRS5vIC83ux1F0CAfyFivgQ7W8SVvUa6SRznzZIcOuP3QE2WF7LuSRlW5/DrXst+Qgmr3LBLQQ7w+Bgu5JQDSjxYHtBizA3cEuwkme822wtkejGOyZSLXHpr5KopDlrKD+1t90R02ROEl2DvRL7Sex7phWmxzZQqYrx3qWrdgtgHeyrYdzduVk1RJEYtP4xzDQz0B46d82TdmDVppxlha6tywTXkTeSCHZtSxQl96DpB8GoeGl3bZ8ugmmT0R/bZC9Chm1nVCwfJQd3pjEqoK49W1YkSPPL4j+U+EG+3Jg9J+Z/qGbhh7MNImdm0wpJH3zD3ET9V+gu9af2kEr1IY2xDQXM//X0oHSSAGeduF337QvGD3laKNAmsQ66X5QLWq5PI8etpO9M59SssrxTtAq6+djJTW/U3WIv6ixvBrQ5TWEmdVI9PMutfUcmxSepV/+lCxSLYwpvkh+WsxXEdhAaaeXEslMzFBXj5/QGewWU0ooHdFzIGvDHfWhzPPFgJw60srvVrdn3hAlGrvpByfn9cqlaNdAakNo+ZlO2UTNcye1OJ+7eYkGTuJPm6L2sz24cU43ct4UzTTG/4pnZR5UkzBE9BX8lF4AHlkats+UCWehs7OyaOj0pmCXggyuCRwqtLevDIOd2JBYL2SUoB6XNy8/PdEJbKFgdYmr/NBHgJ/z5Z13GHqsYC3LCXlXDsY5+tp+IGlzaIGmGmITat+acHduVsYrFUqj3vDKbnutqUJVScKZvlztLjzVQwqKmTxmLZfEm8PHpdUFAtPObmXMZwCNRpRfJRYagNq8pvQJI63qXWglmad43M6I88EKI2aL+NywbMX4F0Cepr2oKgnuFaGMdgAFnRUGM2SdQpl92kg1gdhSCaNnEZOhgWA9E9o3ZUT/jxCbA/8NcZVZDFvM7oEqss5iaqvbI1g7jyeTqQ4cAHtwMOYhNx5PBDh5mt2yMQQ8MXGQsh94uY2iabtAW4UZDKSpyf9Z12wDJnjiSN2M1PsvtU+MXNqVV8o4vlmgZjbkEoow0/clwezog8FLHroxGDFNaxt1nvf8NocbL86e7qpuub6Q7TGTMeDtxkFSM/BGSCQWchrr3G3uCpEORC6r6QHHFV1L+GLUq/oiqKFC/vYMXH5e2EL73fp4odGSb5FNGfRWb7uat+UTusbKisiQ3Y2PF9Rqx2/BWYKyMNvWWI6QHl1rLfZzU4XjY5N6Xcm+Kf92qxgIVfz4IgQ8Mb4PGQBrdXht06iESJhjpg5tUPwPbQ7rMI5z6cYcUkiP/9ECJ3vP0z5WajKu1UmnoUu5YHkjhUmEguwQv7EHnshhCNB8JJtvoj/bgAxxuSlEMwio16IVT+6BoQTjQId9UFpg8YOR4JskNwc/0ux/htq2VPJ0N1CA/tsXiltz1L6msGtY/vZ01FWXzqYEI7S/ACb7xus1cRHWVAgMNplkpU8TTQaac5yiMxtl1fqgwjKpkZKsOYWsHwPc5lznhFzStLjz98WJgu0VoFVxDx+ZMN1njhJLyLhbRoUjGgKBVSYJkqEuaMwyfqwQzh1ldYERl0hk+ZPxn9pqMvtbH6jbAucPP6f+oftTHIVNvBaEXNrizHXfguLUfQ13xDJX7J2TVbwH85fs/kzS71KsVGwoqhF3SCbcYMagRq+liAUSSTpmjEdE2WrQsioSDEcBe34jnQKTexK+w8h5yJ2Em8zb0PAaepE3mz1jIDIYS9tdEb/imsh6/Lj96B4vaYt7t060eDIDfwuD8ugUptT8YvdHrRiCYIQeHLRrn7AljXu8uPUH33EHHDbnODCQaTzbJihWOx6woDCU7v4RLbUa3TbGE+B9BN70afZbgjNxF8sakfu8UprzWjGoo+VmLVEdSMidcXJs5OWQ/tLH4YqI4XuM6aPcrZES2luMEL6vfP/d1ZXGgijD8A0VaOSvQLqv/HfE5i5eRDI5/PvHf0JBTvSFbaVKKm26mnV2J6tQ/GfZ6N1Wqk6dbQfRS4alk12AaeccqtYH61/GWgm0LQNBvG56YWXT/ZPp5l9QUwThzOrMGYzPbOy0Jh7QU3TgB7O4kDd4LYbDxsrS2tjFSIVw/TR84TihpJ9/SOAOICqYaO7EXf7AXz/RdQtEOvS1thSEfWAnLoxHaQVdZqyRdKxB2uFCPbJX8W63yQJnUA2aEMazmLuqSGNt8yU8RSfTtEVg+qHpk9/MtOqbnHWYXUrKP/QQkbm3UkN6ZbltWfRmAy/g/oaB7pCD/cCrLPhi+6wTGh6/0iHhg6NcvDfFsB6S9WqAoezZlwuNJPWsy1hwrxN2LGeRFYtcpQhU4ashOURjNpcp/Fk33tPCUk95FS8cCq4lpE1zckBSVypkxX0Kyqb42w+cJknh0JdHzDDFaSKbrvw9rOLIEBudL7iidsljuwakH1zOZaoZb70C/rVsFD73Ly8K0krhQORI4SSaDFXTjPeJK5N+V76EIkruezAjoGPUEZagHwIknCVcKKPcomIyQNxq9Nu0Xu64r/uaVV0bEe9I68PooJNCFhLdlnmyO9J0Ta7DBpnN4wSPLW47LvzrUwT0SC91CYNghlUl+/LguoUqhCzL+zR6YUmk3riB6RTqLhxC6ULZakm0sIhRCpfe1haX7dlvpbLrK6JVeAE9qGchHdx0mlODRDtyJKSBjcgGqME0XuVb+UG/ObYoByeU6WkxhkWT9TPVoKdTfVsFXG9qaysp7wG+22wcExIKvrZ8OKWhZfA3oqqTiEljdJLafzqpY1pd36TEnggsDaSM6HNpiwhV2AsjZ5rJ7ZZgWxiuPxf5hlB9YFemMSXO0Js3nZ/JAGove1lHXTD4FvHcBydqKwhJML167x5Qis0POs35jTpFEGtGl4KHa/44TCA8u2qSL5i0vJh2mVVwLpdcfikkAwz1etwfll93B94qbHbYQ8OS5bMsTHEs7NyIoQ2V8Lvgtxt6RmR+2Fi5g7ogitfwwgJ+HWxp/zK97TtaVqMzH3FAjrqBI/K4c3lwlzCp3bCwwEIhG4tdrgAPEWPVIe63qyxKCIDdag51oCqpzJBpu/ij5IqgAzNINnVACg0IBTN3EEGGXOvWkA1BvjEAOvEcpEP1fEloVcSKoJPTkUvfVqzJ/3PjR5JKWol7RP1A8xYhpx6Nd84lXcA1YQbE+Qp3gBDPW3qx6KEY9rcPAbkTRF52y1tLmjK2B9ziBAWtpYA1ul4Bgu7LqhhuwJV16hHxj6mutYZyhb5IYjSw6Snlldpg5ZUIHveqM5eaHsAhHu5UWIkJL6qkqp3PNG2JnVwn5T0ABp6m6yJxblf7Kp2jwJ5+Op90/ELmYXIVop4XDxvruj3gzrB7dr/MthjcFgeFBEIjxC4fzpmc8xEbZ/ACvOxr3e00ZK/7vzlbj/DIVXvOzbya8QRT7oXHTvHnX6ksP1n2ztNUpM/eHMd2EUZjqoiBqZvvnBJ1OR4ZBGz3lW6UkEzBRFz81bgDZenh9J7vK4uGaNK3GQrvj8T7QYo4v+nXwNr5AI4qFpmEX9tBAeW8KuZF4Hmf55TLkbRaAj7ZMaXkNIzt4WkIk/nQlDEUIUu1OOaT6tqMVnIuKyx7lWAo3DNgAw+AXZ4Y5osbILWUq3TovGFIDTU+sglqD9e6l4b/fhfNTKvH7XvTYZoHiPXkPQ/Q+Qch2g+hikEo9UfSzY6gDv7CxHe1yYuPkPESLHKPY0wX10BtcIu/8wyJwzZmSBrjXC7HILWHwUpLwSDsWBt0gPJ+Oep5R8rEnn1lXEjFCcbuynQOkM7YMutu1ICAwfCtAjcpyc3fAIfvtA9RAWVz+98XusyN/p6/Mwg/+W7V0nccQ/I0Edix2FHRy95oIyH6bzArX0aT5ztUMXt2uDO8dXbK6FcMb2dzdVm50fNqzWvh1wwhWq1ukJLKMn6MXmtdPOPi6RueJ8fN0BHaKqPzAFE0NA8m4sNj7ovZHkZo2aXR+PmtlmUV1jWnil/XotI0HTZsA5v2nYU9s89nYvjpDByaJ5RbkjmOfkPa0WmqOeir/ywDCBcg7KgG4DgVdcXfFfid6AIRcQBpmzUb3y/97IqAZdN6nvHbrDljBNSf8PeWqJiuYARHSlp6iJcWVlA5tesrRaryp7Pljty/UrAdpCy5aGq/yD4O4s2JcGe95XOGmfhv+8C/HH9RrJPAhnWqJiOEz6lx/Qb3GTuXXEMeT8YXNDDoNVt2Mah1YsglguWjt7yXo6su3Opn4CY7elim1ptXYoXu0tQ0TfpGdM09iD/qDjNOo/fPOZ0LHU/MpSfJnrbNNK9qhINOZ9XbXmYg1dnGB+ZDjORdKNzMTHsQfAf9Opwd/EmNF5Xe9RUWDlKa+DxNH16b/kXaOVDjOgVuOEFPH3u/hc4OxlmEdFPXRwIbbK+cH1JkgSy/dCR+FLDQaFR2DnVq4EMcbj/EP7IwjlXlz40rlAdSFYmyuuoaTzsFnPixY8RwgQwn7WC6IQPyzQM7XMhol7oc8dvUREtnuvcCMPUodmnE45rFbUA9jgV+O74GZR6O8fqyGx0wVGvLmhzvyTwjkj2KUyHQRCpok+p5Xwt3f9dAckvhEfvERQXM2wwt1ogk3KLaGmEU0m7O7pPstUbGku0NHFrr4UElmTcQ6xoJy/Sn1FhOEQbrj/6KlpahrNlVkgdLr5xEeyMEYN+U+VVcToT2KqKnQ+XDD+Ca4Xx9ocDu4ftSGaJxTNW6sXrAQUDmX5iy8m1lHZo5E/IarmKd/dmYGa6cxwb9Fbr5Bsi7Ltkkdya0y0sBUUsYPwHwpEIs/NM8OsB3ugdQyDSoph8By4L2TDOQ66LCt4RWziZZPAQ2pdWLDpLOUFcqjCxDLSE7gcQLw7Ml/WqJDeHozExwqPlikwA6ZBBpp3LtMZ9gfrnYk8rRUAFJE2N0iW76lavzw/oEG9RuSn8fNUsgDnt8DSAvZ6e0SLVWlMak9H7rIV6fYq162nW0SMc340PlhvKcI7RO1WVGky1QIaPW3dWvM/fKtSMtpShGzzHZKM1Zt1UEcwLwZn+UiF3vZh/HIzJbWY/Rfu+dUz5nCa/Z8MGxmbaLmw8bsALtzchPDyKBivTNZeaFC0ow/fAPmzi4Ug6xy3iULQxoQHhiWLns4KwqfCLvm+mJgC0S2eXLlniIt/bxuyHKMfbmzBCeeTRvlrRRfTjvQfg/wFemk0Lhu9I6KBteJKOSrcUKwV0CMlpynnLlfQHn+kvUKGFsVevjFrEfWlYX8JNi4ifWCaSP9VaxoU+54sE3tFE6BNHJU6B3Rc7ZoM6jaHG+99AGT2s9YZJ+mLISiywAsQCnk1N27MKojmOGpYVz4ZqtMbySQUU9BoVMoMHEHw5iB8c/Arl1pXixUPKo2swJ0to9g6PnW1J7a/so08paKE4rNJ367Uzr8oV5zRWqdDefxYkNT22D8jWfSzNuZp2879iKVoOjVBN9T9jqj+Lnp2qw/Vic3XmYlcXXBBtf+Va6nsNN3wltm/Si8zEReYRddnr+s5FbF4je4xWYyYMLIzEQYYSgk/0R/pPqnC1ByPBqiUJcWSYKIP+GxnqySfTMuugYNViB+lVe/LJYpm4XDQii+uzqPHuHuxQs4NM6ZKw59WLZauD/h2+PF+/mCnRJRLGJTeNmrZym+XN9k/ljwAogfvo7l/RMcPB6k8pxATO7e39yZCPTMV3uBVtfnqQqOa6nj7wRmIRH0yk+BCEYRU8JfocItc5GZXlsZAEoAsOxg3xbV0oFrNmtqyjZpUpuBoSe96ErcGeCN4l9wZrgSbf/cDXOOjtN8EVSKe21Is5VhbhOPiHaNi49X1GxVVtSCB6Y3hoY8WLYK4pf7LueEunQV4Y54AdojBifCzq7On0UYy0ij2Fcu3+M7XUzsqRs6rSJICB2TnEebjhbD9LpBtk0tr3kM5KKFf2nCyitSCSOaQpk3JfNKEVGcX3EJQl7SZb/wzjRFrwG2miZxLVpuNBvVHZdkdpbbMEwlhuczV2mHyjzTmTK0T4XIYADTM2G1/7v0g/RtNIWuAvYGRnDz5DYgGqF2C6NbPKA4LK5uG7l0LnyXWVRPVDdwv7vksr3YC1EjPXIVkjD9ycZrtKiUU5ujMgdQZkDrjesT9nQoL4TVLpeY4SpFMp0wznhR/4oHRtj9MX57rJRuGAp/Vlgng+3opm1nfhBVjdo7WXCeif1Bvai900XlCQYyoWYZe/ZWAYXGQySaTEbtV2ltKktifqQQDLWn+CNprKEkITXqeHkd6QNGuixWXqmJ5qLg3qWNbPBDxZguJ4z+LgCNxVYQYmAbTM4nKhmsmKrJKA5hl/mbJY0jEK3hrdNFjMgeJR6tMj14C6P7gsXe7DmOtnlacaoLW7xUGiQDgflJKxuDJhroao//plfaPQadBNx4lFO+J3ilRl9xyH6fsUN9WAYg4gxscXWOkHJ/dXffmtvq1ShgtNY4HQDfYQ/Fxh60oamLXGX5aI+GkteYtZ6VZJsVfD1lztC/YU49YEw/5O9+hUtzQglh6adxwvF9ljQe/JftNuLXYPCohciZpw9HgTWV2O9qlbufrIVKHhyRynsQJz50FeFuAWIhl6t+pIt/nZOEXDOUHZ25W0tK+n+hE+eAZUXK6Rim77lXGLQK6hDqjmUWmsax7250wa/3TmyXA/X+UEDM/AIKOl38ckiEKfXGGz5UpyveB5fuPqN5051jMpbF4Ev8YACgaZDZNoegPgOTcB0dOCcYCUsfQLLYPEPOq5u1clPKRbUCNONNp/v94ZAzNWCzmq7/EwzO8PhLdfFD6AZ9iqu05WMUwljOw5dWvLrkOCUb1MQKnz7N6qDvrj7lDDK0dlDaitM3ZeoGETYt3DqJHTxNgpVf2srdNQE9rJ4NmTDr+tVRuAJZdrHqU1mkrwQZKAgR4CmS2PgXazu0pTt1eG4CxTuJkWQeGh40Cw093bk4zM5Tj50ZDgQ7jBgUyfg+dQe/bqiHlm1V/TjPpy7nlXX8rmN509uER2JaPlHkaAZMLrQ1W8XdxHIsVnU+L87PCoa53mcXXEsM2/25W9LHeE57ZE8NMnOjGezctEhbPrWdryfcrrKCgaIBY1AuEQXit7qYWIEaIn5fWOSHJLwRQu7mB8jKh9axfIJCBbhsH1jlZbMSCLSzhfj+E7K5ThwTTMIhe1xNvBfVDE+Bqgp23A61C0jNl2mv7z5gjSVZonVikcNT3pfm1D9HLEmwOz8KOi0uQJc6mIzrd7q3T8Tmh/9rWDSz2Ta3Jgk5MshF9V6RZG2YHN/SU5r5cTf8rCF3kKKIgFIIC0LSCOcVkzWuk6dcKVPUiJZMnHrUBcrcD7UUBdFKiUWfzTieuBQfuI1NmiE3KWuuE8DgeXHjXX2OxCJQo3wMQIODmqFvPd6SrbMlOE0XudzWJ0iRxv+njM8nLzgB7RW1qWNjLINmnRsXsWPqFCWWSLV0GBu9Ji+7q8qQkwhqMg0BhQUkFvvZhN+RxmL+sZLLirRrQQHQ8UDK3MLxFxvX0D5NSGCrczVSuvxU8BAVFYbEBO81b01wMYsSyK1T9UbPnAQImBWajfZ8n6fLD95dDuPepbRXr8d3iwl96dxbufs+6SZreiX5AaLsiGddBm/7oRo5JM2NA1lZehAjuzXEULAXZalN7zagjWxDqBcpCLf/dq6kZ/mLjHKBIXjWfV7Pop8bvxg7rVDP7F3fIuJFl2rOV6T/dftQxTYgb8SburxI7kipbud159KlgmtioRByhhAYNoPwJyM2vZ1qggLgV3fB9mebC74+zy/WT9smC5lwrWUru07WYSW++dDajxs9wPo5JXJdNpk+pFYs5OuwUrYjrwzp9YWL2mlgC0/Jb0cwCIWYO7q12KZ/qEfNjx8A5nqkACIY5Gg+LOmk09qJAfmlb6h4ZakMCh2nolxCDE8SaO0bTVCZZRwkViHYbpEyYfNfEgt8JP+ajH5XsBMbwlktqh/6IO3g/0AjYwrMIwZTPjtSElANih92QI8vu5jxcbfQCaMKECfH6NOGYBWp58+hzO9rGCxN0WRRStus92q5LVnY7TLWqUP7MNFT1XUtfWi9GPz3jwjcJW9WfkgwTJnrhb8fJvuoLOJbRdiL5qurWiWro8gJ/ax8pipeH7EQTvpIuQMWJaR8K3LOJux6GPTaOcDnmoQF3DQ4WoSYEY73nvRh1Q1jO5vu1z9kH/PBAZLvYZc4czMON+WBdttfk/dAUx3ZkN0fZOOyrbnKdcc91DTn0vJ8JeKHVSyUhGPm2HZeYtuUBB8sApWxJmLkrPuGgQBFOxdecFCLPp0DC+XjsGM+CVQZl8zwsUljCa8esedjG6pcmbNL8cDukRgFhQq/LbcdumKH5FiIVxT1D6LvnQfEFkHBRYLwxtyxY083YhOoSx41/+aUbwVnb2VME7JdjqoxJ6URgGbmK8OWfQMw7sPApWIb0O57H0TaRXLmNZXgI2m8q2xuPiXOU95eKRNBYBKBZAxgMMm86/pkyG2cpebg7t9PtvaKD4Hw9aUT5gKpGiLZLV6wvZYQghpUgpumbeLmTYCGfMskv5qOdtHZVlFyLtjxN5I7KCpQZgP3BHrU9p7xEWJUnAMAiK+jQpDuf488UyBNvCvs6nX2jyb5XQGMtjgJnbo6oYaVrr/dI/iX7Q7sSUotPpW/hpmitV3aOOIHReYq3rupDd4Wm+22X9ZcPaM4a3uv1rOdlcbvNq/ubkn0newgX1VRt/g5h0+Chj1L7zD88ikWvCGdukYMx0wx1NKrWF//18bJxF7NaGi1Diy9qpL7yNDgg3kMrqR6PG/YZ28zJ8xFtQIGtejN1o33M70t2+bYpAuQcwIX5VSERB3rvwvZy78GE1Gqjlh6wqxvzwQGEKfB5N4bTLadOf2YarkAQJO7x5+4awEkl46e+jg4S8D124ukD+xC3FpfzvkvZmfsfNHZiXCGP0epfE+aPgg7MMdV65Jz/CYjH2RmxM3Oc32BOEHO9Vv8jvR8s7CD4hR3YJk76ki7v4FmFTh7DYpmRSHu9x8SELM7Gp2et0fqxUMgfdQAIqOe8daC4K8UGEXlbetNIgVX+q/atA9Yl8rWREOJohrX/98wO2XpLr+EHUEJnQYIndjSSEpWEdF/WP/SkL5+MZCr8AlGuButqWRVRcgAOpe9CszwTLeyQvAq5Xq9UsKzhixm+vxuW/BJEnZFWoGCU4BplM2PHSpWq0z/jSQ34m9DQbX9h5zx94nkHU2gqnniZWOpeJaKsOZJN48u8dOPllUgp/KAywyR45cjCf8oSgU434HGsBj/QlcEc/Fw57BrWu2rlQ5Kl+xDeuShgH4G0CxefTg8JjWKspV36t/vSIwGqNaQkxQieSHbjqcef4+Zt4hib87aAlvzgYmlffNK4LkqJUnE/nrkTaYBdWC4/ZoelGIgXjUvvWCV6JqhCPtCMQGQbxHa2+2+aBDb4S0rClGWurusZrFeiOPv1+it6qU2mHmooc/XwSaDiWb8bSWgvwRkx8P9dRu5212IPWn5M2f3bqW2z6DEc+ndZpe8EQC1cF6RuUGbI7d8V+8gX1FpBf4pbdfYTillPkoc6gnS2XbH+4Z2R0EEgniR8dyVU5iZxwoq8GcN66LZT5HYkRv4kqivdFbtlveo8aMvqzNc2SDvofMweHxQ2xApb0mjidWp1YI59Oif2+iwYXGtrZVy+Ti6UVaNuulxT7xEkVhjN5ry6X6xAn+HAtgRdn0oqAcSast3FcVCVCcCF1v8cQgntYHfjLKFCROfsNbnPTc5rmL6gdKM/dj/MvytFKk59vjo2CTSdRUY2krRPQppAyGhw8EZUKDB4IAir1njSm9H0V72eunJcTsB92Jue/q5nTNw9L+CeMF07L02x0oSRGAwCl+g0xVvMbAFiM6YNhuhVD27fHiafvFztiuWtQKNeYsi704y6k1Mzhdg+a1E82OhoUTQ7dAl7DWN6LqLhnlv9wJguQirZ2hfaaR73qfYbgcmvYKhnAjSbwd3SaLHkXhHA0AtVhjlGk+0ZZZ/TkMd5S8cHjmC7NtIer1KF0J8KEHWlXbDowLR14FuBSgclqWLPI3ON1CKc6C5uqDIW5VJSu67rHZXVITFIAifVwJgmRYDOWemal8E5DwY/4/BBKzzTgVy0N+dE8BPkHueHChvo3TYJjBwRwK6/A5c+u4Biavfk0TApG8io9uo3dsziQInVyJ+p+vW07+q8+xXx793xZSzBkfb3LEp5fxr32NQ15zj2BbUfry1hXVmlLut0gHZmp0kl0/7h01LOyGhUWwSnNX52O1VgT4ivBXRqsMCttEw4+ZXlJ/liVyaubfDLkOfcrX+ACcpp2aGHfmA4TTm0Bk/66ewKbn1S7pSMy9AVcaI4Z3q8udRy+Aoy9Y0JwiRclXPkdC940fo3p/aXiZG0DUVZgGhP+BtWxgkjjUu3xwI8ddXHqV6YHBAvNOp36FiwPGjeUdDgM/Jr6NBdeH7f7BdICbI0RiQqUfmnLj3cQPqe/q0VNjQhgYrd1NBBQ0Y3krpWDLWOE4+7O9SHYyOqAnybAbe4tL24WfIbWn++gxysoHz+z+HT8wp3Iw8su1uy2N+6wgiRUmoisFM0S+Cm1F9JTs0EBqPlNDxUqEyq7asWXYNbftWowE21fz1EN18GBl4SPu4k9+7/nh0AQPa/4c06w0kEpYN6F3viPzjzZ71QP9GBWsNBGnEQFk+v5NSJwgfYWeQ71374ezDZRm2V8UMSIuuV0+PrslYA8QcqjVyGHZuCHGmBoEuw7Fm8AT8WAM/DGGG6vZDn8tg+KgK30+cmRH2pF2Unlsm5XQULLIVVfL0HL73U33OSrBs2sNx4wDXzS+JaUdkMiIt5HkKuzakzFRZswFY3/ltYHwUKceS8Pl9xrBRBPnPe0T8IcV4rARmwYc/P4S2NdQDivHCkcOjPwiokjsU3O7AUSLhz4gOmL/PY68LriPPwNUl8emWtZvn5xyTAD7QusQllg5+p6tSnhv0kGc3ZrGdW0BpjSjWovxoHBwgqF2eOHmBSooK+wZq4w3qVD0XtqmNR7lE5xdvNDeX7Q15eUOCqj0wJ7vMmZMIUnnjsd3ZvuUNqVRlAXqkf79t+mrk5zoK6ZaqCeto4k6W3sBbLq3P9gR/YfAdkpY+ZCMuWagRnAtbbqWqAUlfIypZiFY8QfAcmLkfGk1lZWNPBif28FnEQoT8bz1u95WTNXdoKzlNKALCX3cHjafWXK4zG1hHmnSPEACJvqbNV7i+v7DGQkvEWkUuYkdjc0nWUN8m0gBQ4WGdY6tlO1IjVyU7+m9CIMxl75uDWuTBPleLP14kcaF4rPfInw0Ls2gytgZ3H7V2nLHraCKYo+4JVkBs7Thjg/OOPrXcDaf+9O3EQV8ZV/NkJVKORsB9BACkafuzpjkq9k7nboDVHBzXvEwIFujTEy52ZMZuDJZWM70J6nVJt1YqVCy1NFkFYyU0AUhbLHSU5xRrnaIIsifwkTEiTzVbL0aTEJYiE1TSGwt/Rdsaiowboe34+G3yUrsqtMPHBio0S2yli0P+lXHgBpJ5qNyRtmmXsSi45eeyXultbDwl+zrEOJRfpYPGtVWydSDi/iIVf+rWveXsAgoSijJfSU35LASsgiYRA35Qne4IceE34e3oS9/9Tb5QXRBzER4nIJHjFq5vaNW648S6yVIPMSA8pfQThTC3xl3fVLuSklUIFdpxUb2Vyz0wODSV1fYAVWJOSt6iD1wQ70wYmmm2pO1zVV+kjOy4CUoPnBHkD8sVABGe7s2Iup3rI0fyQOgHYQ82G7CABt5NLQFqdQwyZ/s+iRMoZc2QgiVJ3wZYrA/QqtQ86GT7sdr3LN2WqYMpMhxXT3IljWTD06DuIYxmOFhk2/koBgw4pFbQhM+3J/FAzkQqIlUgg07GqlIBRFOiIqkFl1H1FOmz/8vY2/tbENgDZYG3rGmEI4UqW9WHeTukRMRWDWutxuiutnK7fQRbHfmUwBFd+J3yGA7yayUgHFlKh0tiYAi+8aLGbkfXKco6Oc5vVk+u/mpZ4+C/yHjNRLvsohkdoGCOH9X7X5SyRpbzYm5QddQuQDcmvHB+u8F+iUF5wFdipBo1BV4WUjqK7yJ2Us473AP/Rfwe5FE9HcN9tjF2t1Tjt9WtoO6bUSp9wyPq65gfUURJIeGvE2rHYYKIiKh1zYIlZk3iQhO+97g/C54BhkKh5WurBCrr4vq0lbWQUy9MrI3CzYYoHcDjLdLeaYY458b6tJUilWoZHcL+FpCPs3RHqdr0FTQH34SPxWY3aIx8ZPMAIm3j5KTYSwO6bU9dBrHSkFl9s/e7Q2StqiAy5TPwkYjTNhpL6QLfVIqwSCq7aIaVEHNyFdX7tfGB6WaVD91KCMENFogU3xXgERceJUijXXuaPxAcikK3/0udmYf/eseOAwixELD0yuhL9aHUOI1gkF53fAkIOQQefRvvzzxVGiPN3Jy24P7YyQ89EtTVihxWF8hMtjyatlOQEqzx8YJm5j5yv6f9OCTVudG6qpmcmbwLkGU4nUnLy3Q9n1IWZwFzIyX60pMHzrdcb+vC0yhWzApglmVi0uSDKviHCNVajjPAE59qAnYg2AKz2cgXoXPbGlzzyCSOASaoSLtXNnZjMQTc2S+C127Xm7w2UY7u0ug1yVxgdc1Q3asjjD3CetFENtWNmwbLxv2Z9quorzWPWrL3zz3OA9iV4kJ66S2WWlL70qqSnBaW1NYG5TXMXnJ1XkRWtitCvEXIlA4sMCfu770sB4YApiqjR6yHez32G58lI9tDkU9HPOw4tkSZ+hzMfHlKEjK5+hK4eRUyBPUiJppNsDeATGZabpkq5gBlSYt2r9DQAoHfk8PVXT/ZDmrXXmEOtCE+Ph5ZS3K4JvIngclSLr7XQxqDlfHuZIlGca2qaXmXNrY8OiK/ZmMeLbdLBXVLewWaQ33eoEpsNjD+2RewzdmRXwbc4hNUe+kQSZEjlTlQIExmUqDgAAvnDy3V6l5WYSBI9cUqhVzIGVIfE/RQ+JDWjOtRthIbU9L5LloBq4RXzb3JGKVvEMZLjhWgB5HhYY1CnBZqYZiF7EKLyP4x3/j1LtlSY0FOoZoV2pBw1vWYVkIBK4DVupdLiT3V/WlGnzJrpbpf0RQ5wxscktxOTKqX9c8WHWli2kO7Qw286lrFDNNSbG4rLq45TbTEvqmVGGLWCFEFp5YHQNVolfnEx9hI3wStevIaH+LYG0NYetxGaD62LfPzfwFinWphvhVDen1uRLKpJkOBHUMI9PY06gK04hgsKgwaAzySA2LUzr2eZ2iu0t9YpcrjxuqQyFTr/Kef8r/s9RjM6R2FRtievUCRCat73MPn3VX82/V6BENIOFuwmLXAEWbsgGYjQJFm3TutCv5UoFsbHxvENaGG+4q+OyOR+m8zPJeEYRXldh7eEaky+Vj7jDC8wCrffxRDTR7saIh6oP64+FtDI83Jtp9p7WAodBaWYmzlOohChkAHx4N0l7ydhjbqqxtAorZCPpAOK30zlnZqQkBNISwSwniFExsk18F42NLYkgFdQUyoyBfqK7tUQBfthY4req90SkMz+dCsnENivo8/YZ8lRdSQyW8onoL8H/rxY7l+gjVrSg6rQ44k1BXdReJbJEqfn2IUiKvqx5yNBpef/b6poXzdYWkJIIboxvA+DZpdm4Vn/wfRYhaAxckvepWKI+pi7Naw+ni6lkKFMwTht6poU5tBz40ldu8tIM01oQv0HkXstkD+5Li8QKNJWIKgDTLV1WbHJxtuwusS4Bh6L/7Hht7GzcXPHHuF8wbhklxUelRbL3HBvwyiw5+kAfVNRWI1hyjg/sTDtYYstj4DU+iMK/43x2mM5EbTlwjHIQn7buJydSLq0VTfEyGvJ9btO2XiDxNV6ZYCTtKxJ2I9axioXziBGAshbVJaGq9qBRTF6/ut4JOzbmjT69Rs4mGqg7mM2REy4OY0pZYA5JYzUVDJGJiosTxfEiAPW4z8cA2LtEI/3PZ0UaU356y8qyHmbQlf50AgbjhWbnqtn0jmQXJ8tsAUQIwNMx/FjJwXNC3sTOR5QkRpH/NAuKnYPCRFgg4Gt6kRDNs5W6SfspR38jwT6/TMsl2fhZVsjzOcsDMc2l/lnfnNU6pllxjtwxQLmTow/0vZ5YXyo1z3ir5LuAnKp4DEG5a8cpqZB6SyNDi62ATRcE+lkd7uh31zA7Br+5Jw1EUGTj/5M5QpULckP8lPZ0yD0DHBwYSlrgZuZnKn5R/Q8K0pf7pv1CmHamXONaOfFtFTwumWQpF+iBpz5yf02HXUMvYZYOi0UkxGm90W1uuzPoulU2l8GuyJLh2G4S9BS30648fR97d5zuTGFFZC6W3iHYhEIoi5++Pf9fQsdLjO3SiJNmwT6cqqqNJIapEOGn42iid6kVveJVnzaxtoStohjWeQVSLNdqvfzqKdxzwkYLj5BCKdHQcfdUxwjOUALVgvOC+OALxyiAC4cRzAJ1JJ+OYouJ+ir8cAtrYQ0IZQ8KKv9CYSUbjSNZUuiAiYbUgMhx4Uphmb9KThovz4D+A/aAJj/AQq3caT1s3SaOEQ9CsZBvDvRqv+3pMyWUrsYw1GsXtm97TGLw7lOqwINVQ1agu9iM5WTpKsxOlLCx958KX3+1CW1P/FYAENHGfh498G5sKs74Bplal3y3c2Reyfqwr96cxgVO7cLoIdrGP3CM/H815T8W7iBxrgQzilRLQgvIDueYxtSjqtj3MeKoufwVbW12VyNJem6mpT1Y0BRuZvDTWBQ32zmLAD88Z+P4YP6iL0wWplsMfcYZ0MiRkPW+gNTPQhae/6jlSnceHnAyutvI5/EefPSgE17T8VCK9+WzEDvK7sM5IA+085pi4dfKB+2zpEFlZ4W3q6jZIE4V5NrYLhMoPr/zYeA7eD3DoJF6ktNH3RBjJS7t3E5QZPJtJStSUXFakoBK0yBFMwIF8kERqCdnrrYs+JRDvxEaJXOlp+eFn1+StwAeRaetPyVoA2GFXW5S2A8gtzFSJBDefmgrSyFTBr/hUuLuND19YSgiwtznoSjzp3iKVzTmLadw82DZTZ2haKvNgqe/QGI5GXfz2M/jHca7hhY6Y8J66+m4UsSgWVCFwz2ApPm8hlBgu/O7Rjs3B1+yG6HQPQAwiD/IPHB2Mt2A4a2g1WqDoCmpRGH8DFh37KNfIvtP0V1n4Tt0WIVMNchfRoc0c6Q3TVT84CidPMA0Hh3odRZfJ1BVsz220DnSlpXjYn8TVdYOrjDonUJo/sZgdiE9rYFyb6kdGnrL57cMEN1xo+XMssN1NTj12/1G5ZYNVod85gnKdU6WcS4QaiphZBWyLa4VYdnEVI1LQyamDdIcasteR8SEAjFak5w/OWx+sYUseaUMfbHRw0d3n6WrvZeCG+F9ZWsqN/sKmh2N5boWqKqPNMTKHkEEu45yaxKL4+jlD8hE++/Vzot6fnSCWo7C/U3BjaiTs8NC+OLym1v37YvAORRBifdywfRruNfM7vM5KzKljgEthHgTbLXFbCOej2gtfcgUC8TUmaN8GlENYc+VRatqeT4bMFMB8dw0uohEIpXAYfxbrgl/pZMlWan8gyLJfiTGDlS9xeH0k44P88afbdcGvb8VaXyJiOYtAPoJIZ91XLkMzkeHWOwsNhSCvq6GFG7F4RFTeXPFXHR33dhF96G5khNLXShT0S9dEuxxMtwvWB+GpxV9AlB2r0ZYERuYutxJJ9Y4EPI583Vh0OqZGY3tbRM7JgINxOVR+OfMeqVsJyIOpeatUINdRBnOuN/kF9kAGqAFDhh0utK38ou4Lm7YOqpB87wHX2yDDE1g2BegIGvfVEkofR/9BGNy6qIwAFVclKYYlL/gyhWQ2XYzAZXeuA9D3+0nKAWWlRQP1CrcNCzslFwdhUFLfmqYruyBL2hp9wvbxe/b6sLrKjeVX3uqxm4+05nh35gG6aGjnsk03SDtZ5x7pweiTqMJIexi91VwcwEjHdePbfG82nP41FjUJg1/GocLAp6nkeI+IzgauDd9A0xQkwDYyseGg38GvTTin6S3rB5fkts9fBTs9wxyGnLyNWt2bohYFjgM51AM9obWKRBRnfyf9XsxjI/S8yxjKfsXoIijKYOMeNDyJvfAftn0thRF6NGa9ODQ9Pl0qzGJNMEB7/tRGlrU1nYEJnHch1et4ZgF9R+SoMuJoWbXMdXlPMdTfjji6f6ZlySZvCLsvR3UpMw+k0yAF/IMb5Eaeg4JIPENuSx8c4EovfcWVXEyuGV7TbirfpU3oAKidRGBlfjrst2CladThWq8wHHAqYi/idNH3ylBxzgECpii/i+xOy923uRUAcfo1IKDpgJRIBs1/SVsC1nzk55gHsLED+kFq3nLL6U9UjdsoOh9JYS/2n4J4RyUWbm9NKBM179G2eo8SLT9qurYxPe1KNEkfE4tc5LnW7JB2PoMwzqcBug+VYCpp2/BtFRPRq153uNdP38TD8two7X1Um+LtRveOguXOlTU1pnOYM/tD2B+weE3soNONoiC5WGdVkhm5o/0cQakwvfSswIaURp2cciR73EfRJm0csXT5gFKL6hZUeQUg8eXRCfPZhsNBipp9BDwrv/JBff/L7uYTenm2CAoWkNmsmC75V/i0Is/I2dpVSqtYV73V0u+rj65OuXlMimDGHr1RWrMIGcm28lvgiS8lhXrHYxbHBMJg3zm1mBa8hPm98njUQeeVSgY0rEfkzvcq+3plGEMnPcppWSBoUc/qNYUTVtLSy9FTrMB8vfns1VPGeEcgVSJeKq3r9G9oyJgt/oYv3PEVkRpqRGaHCNHRzuMKAsdctagK/a/GIqRbYBTSd0C8iq33pK8lgwJ/qRJpIarACktz+r0aObFMFwrT0vPSRydzjJexrQh/SLfl0P3cESGEiWXIZnJ9ESeDpbzzhYzD/3/vfxudHViBy9tQ9Z6hxACD8+h0zhy7XxlXDL7Pb7XYqLIgSm43hkESKdCznTlSR+JxZwO3/4b+S/RWkQcR2FRZ3Le0sOIsSfpSk4BXBAIL07S2zJjRcoBildAHUtTb+306g/1eVQJ9mmIXjzCycaXJCAhGQU6Is1Gj+4S3/M4YBu0x+dd01a5YEMIPOryXqYo8yH3Sp8PlhYRqWz4EtbUn3nkYhXRGPYN/WcXciLxj/EqLgE9c61oYWae9NUaK481ke6sHYbBCqubt9GvkBgfkAVxeSE5GopuigORW0QMbZWuIb14ATb3CH1iLtiR2N6ue9UJWMVf0VHssaPWvj7f403EnJ29C5QRigxM+4ESwKEmsshyHEHtqJ9svWtCqi7/LsUoSe6mx2KYCG5hntiCgCecNO4+qJdUfPMZO4y8Z/GplfBrFTvJK4Ea2dNLmKfIjrrH8H8xLmT5YGdgZjTFYTUxwxxIgbvZ7uz2zszYOXZtzy3UvEwq6uy8VzndeL7mfywz37cgMU/+GlFAaEx4sDQR1JD6w2UiJ+aXf/H/xt0Cd1m0HOZhQ/AWd5iQe3JiKYJ8dvKP5VGXhhvq5ZagDA63qGcoGBHGHpkzyxsNYuwYCowqb10GQ3pLgELQkWNaU7WMRT6DGRnAiN2l7+dje/GbR/rhnAmVNp6FHTE0bg9r7CdkTgDZLnJP721hi67wC2dCw0/ncoZcfLF7JqHuGdjv8plsN3dMlPBGGQlOSo3hjMI2A1B3FJ2G5rq0dJ5FwVewKoRcISX2w1FbYf3uRbrI9rYVOeMiVkHcK2uPFNOVPJkJxmkhViPLbz4fIptiv93a16NQh9oUQWTnGjzS2yeDWTjXKqE19pFwPad8h1+SpvOvqOBq1cTM0CH6V6R0fgaoaFooS+XHp/6aZIL7tRU6QucqC036fTqPn79PtCpYHfQ7wEu3KtBWXstpvXTiKXnf7RWrqpZDmtQ9ZCP7J+F368eBuX6JerduD0VEPtWZXzlVL753prlcvROvBhGfRC2FEL8xhi8ObobCS9kAnTLqBq+kxT10H1158SbvW90EAkE/I+2kFok2JcSDuLJlWJuy9fOz2fPUIEzkRq/BUCXQKoc7SGe38Shum0HOf4qYq0IAnI14KEIFR4+8MJDCewWeLbYEiCjArZBLYcba8Csw0pJOKZmWA6QeQKHk4OFSl9vVraA22b6JP+AyPJQKlVjho7NPAon0sMNi4jR5p+5JxXk6jCX+BQTHYH/Zta766u7Mp/t5pVo3NbsyEQNrXhtyN3FaVT8M+pD+tcDW3076qCwMJV+acPSQtb7WzsU1MHHyPYszXfdNtOcvAkozjEulKnXSYojb/tK2tLXkWeIMIN6kTrD9aWEL9Muau+m7BDoTVafzj8RoaM5w8rIFv8qc+PAY9EOxX9Bqs6k47NlynRwgZW4WobWhovs+ILt0UBmKAuTqgDNh1fzC+U0vsNm8prCEd+3Hl4DWOYLpZmwVB22A/YkTzU72T7A3BkFAxY9ipANs2lZX0uJXF9hym5alc0q/fJyJ4tAFoBJdqz8l1efwZMyLLMti/Eq6TlfR4uvTfuCKvpMDfYF+/0W2ZZi3k5nuIxeZkgAz9NWE4phjoGdPHjXVWPBtO5mhTC7mnIGPS/h0E/nlD30gts/rgLAbdLZlBvmJKJ8bkPBdn97HGC3YiGqQluO+zCPLH+ehi/V0Jix/nVO+okrMRLtR3kYuuCwlN8+bOGae6DWHo5VZhLzYHzc5EBL7Pamyt6UPjgAcOuclmIv2JBfo6h5UGRKsF2mXbVx67btqVBLd/JK8c/sKJzM0/5bHrhPLT5ILmmeZB0QP4D9oegX8KL4fH0YthOd0oEK9lIN7Ip62Yb2wLq4LWCZUTuaIO9u3CZ03wxqSlybijOGdQDp59MqJWRtjPtq0/7UnlguuBCXuDTmlCY+0of3avFvehcZRALSgM0VL+NG/Y3QqUv8ydCyUZF+TFodTsUv6x5RnCJbg6lI0tVOrlpJjC7XO1zaiwxU0dnRDk2nGB+bh0PTKYcv78it0B1DcK2pL0atkgOLWTCVFF3bK5IWGBjCSFRRMDOhgqtLm/eiLN5Z8dcpayS0QqP8UbM5I3wb5I2GRgS2S1iKXpNiREidscs3zIZPbXd1yFtsmRDEo14gZEnoKwYwfprFhMA7bHbpRbmZT4p0gNcR0ws6K3Z8Q2Adc4xl0kS9kVnB+YotEbObiEBKDpbPY9TlwBAqSi4+m7nr95xXzBBAzuPtJofbCRGZmrgxRvo9bLzen2cS/Kv1NkCD4ZfhcxtbXI+vumeh3LekjXajczhZxPiHssrfz7h2D8YUDp1hAAKlzp9+zBf3JcAnqvtMlCHtEheFgNco7Wwer2yWHgscISn3n7LmwAc+7Fd5EJYFwHsA4vuNXw3Xrkx4aiRojLTl2NOBmfOKLtfmGtHricfNFwwUGZxaFLll4MQDfz7TFQSmggOdYmOLFZedAWAsRRPRCZ8y6UiCZLkxkH0tXcBEDsxgIOeZXjYdtree4hmkwPn3+Rq3mbe1j7We1nQvO/4d9Tdl6bHjRvZf7G2Z9+l0hBfuiHxW6ZD7O/mWDDepJ5EkXtqWdBDcvINpR68nSEtU9Wg58NyRzvvKMAqyfgf+vttt3B29r1oaJ5Qm/nT7wLmDJuUXRt/z2jz+4Z6u2xB8iWmqbO6MeNMBG1ZVdzvXN+xsL/DCAUy+4X4Op5LWQxD6Zpw13qVqAyzAxlvWDfuwgOoGxAPLPhdC0IE99Fzw1MCsWwPFxuz5SMUBX0hNaVQ32yGG5JGYpOjmgGNUR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T4fUA/K0cC3QWjo0THlaTA==
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- Curvature analysis
- Curvature analysis
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- SEEDstudio | www.studioseed.net
- dga_3@hotmail.com
- Daniel Abalde
- www.studioseed.net
- 5
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167
64
-
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28392
- 3
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- 2
- ac2bc2cb-70fb-4dd5-9c78-7e1ea97fe278
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Base surface, brep, mesh or curve
- true
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- Geometry
- Geometry
- true
- d636886e-6a7c-4eda-b4a4-ca364081a1e2
- 1
-
13169
28362
91
20
-
13214.5
28372
- Number of divisions in UV directions
Note * Only subdivided surfaces, breps, and curves
- 80f3a926-2bb6-4559-ab18-aa854690d208
- true
- Divisions
- Divisions
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- 0
-
13169
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91
20
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13214.5
28392
- 1
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- {0}
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- False = Mean; True = Gaussian
Note * For surfaces and breps
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- Curvature type
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20
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13214.5
28412
- 1
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-
13284
28362
48
30
-
13308
28377
- Values of curvature
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- Values
- Values
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- 0
-
13284
28392
48
30
-
13308
28407
- 66d2a68e-2f1d-43d2-a53b-c6a4d17e627b
- Control Polygon
- Extract the nurbs control polygon of a curve.
- true
- e4d2c833-667c-4dc0-ad59-020f542c6d20
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- Control Polygon
- Control Polygon
-
12887
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98
44
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12931
28173
- Curve to evaluate
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12889
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30
40
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12904
28173
- Control polygon curve for input curve adjusted for periodicity.
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40
20
-
12963
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- 1
- Control polygon points.
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- Points
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- 0
-
12943
28173
40
20
-
12963
28183
- ac750e41-2450-4f98-9658-98fef97b01b2
- Brep Wireframe
- Extract the wireframe curves of a brep.
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- Brep Wireframe
- Brep Wireframe
-
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130
44
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13273
28245
- Base Brep
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52
20
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- Wireframe isocurve density
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- Density
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52
20
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- Wireframe curves
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- 0
-
13285
28225
50
40
-
13310
28245
- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- 8607557e-920d-44ea-897a-c3388ebae07b
- true
- Construct Point
- Construct Point
-
13097
28112
117
64
-
13173
28144
- {x} coordinate
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- X coordinate
- X coordinate
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- 1
-
13099
28114
62
20
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13130
28124
- 1
- 1
- {0}
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- {y} coordinate
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- true
- Y coordinate
- Y coordinate
- false
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- 1
-
13099
28134
62
20
-
13130
28144
- 1
- 1
- {0}
- 0
- {z} coordinate
- 17551570-925d-489c-8f4a-c7e1fe2c3dbb
- true
- Z coordinate
- Z coordinate
- false
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- 1
-
13099
28154
62
20
-
13130
28164
- 1
- 1
- {0}
- 0
- Point coordinate
- 51179561-239d-4312-82e0-f4e7f66516de
- true
- Point
- Point
- false
- 0
-
13185
28114
27
60
-
13198.5
28144
- 9445ca40-cc73-4861-a455-146308676855
- Range
- Create a range of numbers.
- true
- c9a8dc4b-abf3-4367-b392-ec2e73e5858f
- true
- Range
- Range
-
13104
28046
144
44
-
13202
28068
- Domain of numeric range
- b84b7aad-7c57-4840-9ae9-d3962839170d
- true
- Domain
- Domain
- false
- 0
-
13106
28048
84
20
-
13148
28058
- 1
- 1
- {0}
-
0
1
- Number of steps
- aaafd565-907f-48bc-9256-389f9fbad5aa
- true
- Steps
- Steps
- false
- 0
-
13106
28068
84
20
-
13148
28078
- 1
- 1
- {0}
- 6
- 1
- Range of numbers
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- true
- Range
- Range
- false
- 0
-
13214
28048
32
40
-
13230
28068
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 450ec7d6-6e26-4b9a-970b-d0cbf1772eec
- true
- List Item
- List Item
-
12225
28194
77
64
-
12282
28226
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- c4d83e97-6acf-4921-9e15-25465eddb845
- true
- List
- List
- false
- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
-
12227
28196
43
20
-
12248.5
28206
- Item index
- 3c027a27-2646-4367-9902-c20adeb5f6af
- true
- Index
- Index
- false
- 0
-
12227
28216
43
20
-
12248.5
28226
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 58f4d409-cc2a-44ed-849a-d0442067a074
- true
- Wrap
- Wrap
- false
- 0
-
12227
28236
43
20
-
12248.5
28246
- 1
- 1
- {0}
- false
- Item at {i'}
- 04070efd-05f8-4658-8331-40f0368aa8fa
- true
- false
- Item
- i
- false
- 0
-
12294
28196
6
60
-
12297
28226
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 15462838-16ed-45b2-ae57-bf3140d2a0c4
- true
- Evaluate Length
- Evaluate Length
-
12369
28106
149
64
-
12454
28138
- Curve to evaluate
- 765a521b-aa26-4ea8-bd44-2d1ac48c4a29
- true
- Curve
- Curve
- false
- 04070efd-05f8-4658-8331-40f0368aa8fa
- 1
-
12371
28108
71
20
-
12406.5
28118
- Length factor for curve evaluation
- 89441ced-3308-4968-9a08-ca77e5fff5ca
- true
- Length
- Length
- false
- 0
-
12371
28128
71
20
-
12406.5
28138
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 554ae01c-34f4-406a-9d3f-a64da5656529
- true
- Normalized
- Normalized
- false
- 0
-
12371
28148
71
20
-
12406.5
28158
- 1
- 1
- {0}
- true
- Point at the specified length
- f37cb892-e085-4d02-b622-0cf629b13abf
- true
- Point
- Point
- false
- 0
-
12466
28108
50
20
-
12491
28118
- Tangent vector at the specified length
- ccaef106-f7ec-4a61-955b-726eba10cb0f
- true
- Tangent
- Tangent
- false
- 0
-
12466
28128
50
20
-
12491
28138
- Curve parameter at the specified length
- 4158be2d-5059-4c52-9111-20bb07143d0e
- true
- Parameter
- Parameter
- false
- 0
-
12466
28148
50
20
-
12491
28158
- 269eaa85-9997-4d77-a9ba-4c58cb45c9d3
- Discontinuity
- Find all discontinuities along a curve.
- true
- 787bc2e4-45a8-4f65-ba4a-1370065d5bd7
- true
- Discontinuity
- Discontinuity
-
12493
28182
196
44
-
12620
28204
- Curve to analyze
- c620e97d-b1df-43da-84e2-a8167399f250
- true
- Curve
- Curve
- false
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
- 1
-
12495
28184
113
20
-
12551.5
28194
- Level of discontinuity to test for (1=C1, 2=C2, 3=Cinfinite)
- 0ba9154e-97dd-41b5-8079-8af2e09ec5d7
- true
- Level
- Level
- false
- 0
-
12495
28204
113
20
-
12551.5
28214
- 1
- 1
- {0}
- 1
- 1
- Points at discontinuities
- df6e61e1-1184-4a91-97bf-62962510ac96
- true
- Points
- Points
- false
- 0
-
12632
28184
55
20
-
12659.5
28194
- 1
- Curve parameters at discontinuities
- c974fe53-cc46-49c9-963d-cc9c7e724e14
- true
- Parameters
- Parameters
- false
- 0
-
12632
28204
55
20
-
12659.5
28214
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 413dab6f-30ff-4b34-9f67-90b9f0ff1ee3
- true
- List Item
- List Item
-
12603
28105
77
64
-
12660
28137
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- b430cc72-3de3-4425-bb1c-86715c095b3c
- true
- List
- List
- false
- df6e61e1-1184-4a91-97bf-62962510ac96
- 1
-
12605
28107
43
20
-
12626.5
28117
- Item index
- 4a487015-cb96-43bd-9f37-765100234d74
- true
- Index
- Index
- false
- 0
-
12605
28127
43
20
-
12626.5
28137
- 1
- 1
- {0}
- 4
- Wrap index to list bounds
- d8cac58f-189f-498d-8607-9f7a513a1b26
- true
- Wrap
- Wrap
- false
- 0
-
12605
28147
43
20
-
12626.5
28157
- 1
- 1
- {0}
- false
- Item at {i'}
- c0156a88-eddd-4204-a1a9-6d6859b95655
- true
- false
- Item
- i
- false
- 0
-
12672
28107
6
60
-
12675
28137
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 2b4ed57e-fb00-43dc-8e5f-783398616385
- true
- List Item
- List Item
-
12596
28027
77
64
-
12653
28059
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 5f3a2d0d-f2d2-4ee0-8ed5-2c4dbae31185
- true
- List
- List
- false
- df6e61e1-1184-4a91-97bf-62962510ac96
- 1
-
12598
28029
43
20
-
12619.5
28039
- Item index
- dff5cd65-cb06-41b2-b199-a1946585a002
- true
- Index
- Index
- false
- 0
-
12598
28049
43
20
-
12619.5
28059
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- e7e6673d-186e-4a1a-9466-639bf1eeddd1
- true
- Wrap
- Wrap
- false
- 0
-
12598
28069
43
20
-
12619.5
28079
- 1
- 1
- {0}
- false
- Item at {i'}
- 330006fd-b3f1-44f3-8f7d-9b4cca70cab1
- true
- false
- Item
- i
- false
- 0
-
12665
28029
6
60
-
12668
28059
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 2ac16693-cfbb-413e-95aa-4f61e4c28f43
- true
- Merge
- Merge
-
12720
28025
106
84
-
12781
28067
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 4aa7a97a-2fa1-43b2-971f-37891cd5c08c
- true
- 1
- false
- Data 1
- D1
- true
- 330006fd-b3f1-44f3-8f7d-9b4cca70cab1
- 1
-
12722
28027
47
20
-
12753.5
28037
- 2
- Data stream 2
- cf5915bf-66c0-4066-92ac-d3d1b8b959eb
- true
- 1
- false
- Data 2
- D2
- true
- f37cb892-e085-4d02-b622-0cf629b13abf
- 1
-
12722
28047
47
20
-
12753.5
28057
- 2
- Data stream 3
- 8e0e32cb-a4ba-4c66-b3e7-461cba5c8d0b
- true
- 1
- false
- Data 3
- D3
- true
- c0156a88-eddd-4204-a1a9-6d6859b95655
- 1
-
12722
28067
47
20
-
12753.5
28077
- 2
- Data stream 4
- 5703caee-1e91-455a-b652-9f6cfe30e0f8
- true
- false
- Data 4
- D4
- true
- 0
-
12722
28087
47
20
-
12753.5
28097
- 2
- Result of merge
- 7c15dd75-0fb5-4a70-8968-035294646203
- true
- Result
- Result
- false
- 0
-
12793
28027
31
80
-
12808.5
28067
- 75eb156d-d023-42f9-a85e-2f2456b8bcce
- Interpolate (t)
- Create an interpolated curve through a set of points with tangents.
- true
- 4f97cf3f-ae0c-4d3c-9f34-ce92704918f5
- true
- Interpolate (t)
- Interpolate (t)
-
12077
27979
244
84
-
12269
28021
- 1
- Interpolation points
- d554d29a-fd6e-4dd5-8e2b-3e23c028de73
- true
- Vertices
- Vertices
- false
- 7c15dd75-0fb5-4a70-8968-035294646203
- 1
-
12079
27981
178
20
-
12168
27991
- Tangent at start of curve
- dadee473-b312-46ba-8f68-cd9361f1f948
- true
- Tangent Start
- Tangent Start
- false
- 0
-
12079
28001
178
20
-
12168
28011
- 1
- 1
- {0}
-
0
1
0
- Tangent at end of curve
- 30e48b0d-5118-47d5-a050-92e2ccd4925f
- true
- Tangent End
- Tangent End
- false
- 0
-
12079
28021
178
20
-
12168
28031
- 1
- 1
- {0}
-
1
0
-1
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- cc4486c6-435b-494a-90b6-38e39bf80feb
- true
- KnotStyle
- KnotStyle
- false
- 0
-
12079
28041
178
20
-
12168
28051
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 0ad4a801-5c37-4f86-b0c9-cfa2810fbeed
- true
- Curve
- Curve
- false
- 0
-
12281
27981
38
26
-
12300
27994.33
- Curve length
- f19d34d8-952c-4b7b-9d1c-7cff6f55186e
- true
- Length
- Length
- false
- 0
-
12281
28007
38
27
-
12300
28021
- Curve domain
- 03e24465-d0af-4b53-bf1d-8f60b8c8be45
- true
- Domain
- Domain
- false
- 0
-
12281
28034
38
27
-
12300
28047.67
- 14cf43b6-5eb9-460f-899c-bdece732213a
- Blend Curve Pt
- Create a blend curve between two curves that intersects a point.
- true
- 81c31b9d-d9f4-48ac-8b75-2e11cf294f83
- true
- Blend Curve Pt
- Blend Curve Pt
-
11740
27031
167
84
-
11864
27073
- First curve for blend
- a4c7118a-7572-41be-b304-670fa4f0336a
- true
- Curve A
- Curve A
- false
- 5a30bc9c-1f0b-4a38-8546-68bfff78fe07
- 1
-
11742
27033
110
20
-
11797
27043
- Second curve for blend
- b9be3c42-571a-4365-b65c-6eb712673f9e
- true
- Curve B
- Curve B
- false
- 781927c7-3272-460b-af8b-3107b52db860
- 1
-
11742
27053
110
20
-
11797
27063
- Point for blend intersection
- 56da942a-7d64-4a15-a453-bd453c33c962
- true
- Point
- Point
- false
- f37cb892-e085-4d02-b622-0cf629b13abf
- 1
-
11742
27073
110
20
-
11797
27083
- Continuity of blend (1=tangency, 2=curvature)
- c921ac17-e66d-495f-b864-733f670a6de1
- true
- Continuity
- Continuity
- false
- 0
-
11742
27093
110
20
-
11797
27103
- 1
- 1
- {0}
- 2
- Blend curve connecting the end of A to the start of B, ideally coincident with P
- e7179353-b7a9-4734-995e-1ac6997baecc
- true
- Blend
- Blend
- false
- 0
-
11876
27033
29
80
-
11890.5
27073
- 62cc9684-6a39-422e-aefa-ed44643557b9
- Extend Curve
- Extend a curve by a specified distance.
- true
- 78bea16c-c7ca-42a2-8f5a-2cbb175c6b39
- true
- Extend Curve
- Extend Curve
-
12152
27754
124
84
-
12232
27796
- Curve to extend
- cb01bec1-5994-48f1-bdcc-f6c296ef31f8
- true
- Curve
- Curve
- false
- 0ad4a801-5c37-4f86-b0c9-cfa2810fbeed
- 1
-
12154
27756
66
20
-
12187
27766
- Type of extension (0=Line, 1=Arc, 2=Smooth)
- cea346a1-d619-486a-907c-9d9c84e216d8
- true
- Type
- Type
- false
- 0
-
12154
27776
66
20
-
12187
27786
- 1
- 1
- {0}
- 0
- Extension length at start of curve
- 2cc7cbe5-f621-4395-9528-fb47068a8b5f
- true
- Start
- Start
- false
- 0
-
12154
27796
66
20
-
12187
27806
- 1
- 1
- {0}
- 0.0625
- Extension length at end of curve
- 3bcb9a0c-7d15-470d-b3db-f84b1b79ace3
- true
- End
- End
- false
- 0
-
12154
27816
66
20
-
12187
27826
- 1
- 1
- {0}
- 0.0625
- Extended curve
- b7ece470-8963-4e98-b9fc-c87e811ab6a6
- true
- Curve
- Curve
- false
- 0
-
12244
27756
30
80
-
12259
27796
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 8ffd48b3-48cf-434f-9acc-297e520858bf
- true
- Explode
- Explode
-
12131
27691
134
44
-
12202
27713
- Curve to explode
- d9fa462d-da4f-4ce6-92e7-51395c617b2d
- true
- Curve
- Curve
- false
- b7ece470-8963-4e98-b9fc-c87e811ab6a6
- 1
-
12133
27693
57
20
-
12161.5
27703
- Recursive decomposition until all segments are atomic
- 16058c48-486f-427a-802c-3b8a1a421834
- true
- Recursive
- Recursive
- false
- 0
-
12133
27713
57
20
-
12161.5
27723
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- b6507732-c5c5-43eb-bc89-4c7b87a994c4
- true
- Segments
- Segments
- false
- 0
-
12214
27693
49
20
-
12238.5
27703
- 1
- Vertices of the exploded segments
- b55cf522-ec7a-460d-b821-829569c85064
- true
- Vertices
- Vertices
- false
- 0
-
12214
27713
49
20
-
12238.5
27723
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 8a512fa1-3acb-436d-b89c-8cb084c66169
- true
- List Item
- List Item
-
12147
27563
77
64
-
12204
27595
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- eeb4e85f-0bf6-474e-88c8-cc8acc779e91
- true
- List
- List
- false
- b6507732-c5c5-43eb-bc89-4c7b87a994c4
- 1
-
12149
27565
43
20
-
12170.5
27575
- Item index
- 0eb903a7-7ee6-43b4-944b-4f4e6ad99965
- true
- Index
- Index
- false
- 0
-
12149
27585
43
20
-
12170.5
27595
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 99da5bf6-85bd-4a71-abf4-b7e058ad3f67
- true
- Wrap
- Wrap
- false
- 0
-
12149
27605
43
20
-
12170.5
27615
- 1
- 1
- {0}
- true
- Item at {i'}
- 36f43267-27de-4174-8fa7-7181d7f6dbfa
- true
- false
- Item
- i
- false
- 0
-
12216
27565
6
60
-
12219
27595
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 50b2e22f-d285-4505-b5fb-8235c2d94057
- true
- List Item
- List Item
-
12163
27628
77
64
-
12220
27660
- 3
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12186.5
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12232
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- ae4835db-ae71-4361-8536-1a5e50386819
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- Smooth Curve
- Smooth Curve
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- Curve to smooth
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12116
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2 = Preserve first three points
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12046
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158
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12125
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- Degree to fit the curve to (if omitted input curve degree is used)
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- Degree
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12046
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158
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12125
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- Tolerance distance the fit curve is allowed to deviate from the curve to fit (if omitted document tolerance is used)
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12046
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158
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12125
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- Tolerance angle in degrees for kink smoothing (if omitted document angle tolerance is used)
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12125
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- Resulting fitted curve
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- Fit Curve
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- Curve to fit
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12015
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113
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12071.5
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- Optional degree of curve (if omitted, input degree is used)
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- Degree
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12015
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113
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12071.5
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12015
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12071.5
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- Fitted curve
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- Rebuild PolyCurve
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
- Rebuild a curve preserving the kinks in the polycurves
- true
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- Rebuild PolyCurve
- Rebuild PolyCurve
- false
- dga_3@hotmail.com
- Daniel Abalde
- https://www.facebook.com/DanielAbaldeDesigner
- 4
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198
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12141
27145
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- Polycurve to rebuild
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11989
27115
140
20
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12059
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- Factor that multiplies the length of each curve segment to determine the number of control points for that segment.
Control points for each segment = length of the segment * Division factor.
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140
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12059
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11989
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140
20
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12059
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- Resulting curve
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12153
27115
30
60
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12168
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- Digit Scroller
- Numeric scroller for single numbers
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-
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11918
28092
250
20
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11918.63
28092.02
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- Join Curves
- Join as many curves as possible
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- Join Curves
- Join Curves
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116
44
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11849
27449
- 1
- Curves to join
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11784
27429
53
20
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11810.5
27439
- Preserve direction of input curves
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11784
27449
53
20
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11810.5
27459
- 1
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- Joined curves and individual curves that could not be joined.
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11861
27429
35
40
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11878.5
27449
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- ca78e54f-2c7c-4550-9fbf-85e4695e34e4
- true
- Evaluate Length
- Evaluate Length
-
11691
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149
64
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11776
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- Curve to evaluate
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11693
27238
71
20
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11728.5
27248
- Length factor for curve evaluation
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- Length
- Length
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11693
27258
71
20
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11728.5
27268
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
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11693
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71
20
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11728.5
27288
- 1
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- Point at the specified length
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11788
27238
50
20
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11813
27248
- Tangent vector at the specified length
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11788
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50
20
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11813
27268
- Curve parameter at the specified length
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11788
27278
50
20
-
11813
27288
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 34c4c1ac-606a-4181-b6ea-85caebd18dee
- true
- Evaluate Length
- Evaluate Length
-
11687
27348
149
64
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11772
27380
- Curve to evaluate
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11689
27350
71
20
-
11724.5
27360
- Length factor for curve evaluation
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- Length
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11689
27370
71
20
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11724.5
27380
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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11689
27390
71
20
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11724.5
27400
- 1
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- Point at the specified length
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11784
27350
50
20
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11809
27360
- Tangent vector at the specified length
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27370
50
20
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11809
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- Curve parameter at the specified length
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- 0
-
11784
27390
50
20
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11809
27400
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- Line SDL
- Line SDL
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11889
27341
111
64
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11964
27373
- Line start point
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11891
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61
20
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27353
- Line tangent (direction)
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11891
27363
61
20
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11921.5
27373
- 1
- 1
- {0}
-
0
0
1
- Line length
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- 0
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11891
27383
61
20
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11921.5
27393
- 1
- 1
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- 1
- Line segment
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-
11976
27343
22
60
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11987
27373
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- true
- Line SDL
- Line SDL
-
11864
27246
116
64
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11944
27278
- Line start point
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11866
27248
66
20
-
11899
27258
- Line tangent (direction)
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- 1
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11866
27268
66
20
-
11899
27278
- 1
- 1
- {0}
-
0
0
1
- Line length
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- Length
- Length
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- 0
-
11866
27288
66
20
-
11899
27298
- 1
- 1
- {0}
- -1
- Line segment
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- true
- Line
- Line
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- 0
-
11956
27248
22
60
-
11967
27278
- 22990b1f-9be6-477c-ad89-f775cd347105
- Flip Curve
- Flip a curve using an optional guide curve.
- true
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- true
- Flip Curve
- Flip Curve
-
11759
27171
88
44
-
11803
27193
- Curve to flip
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- Curve
- Curve
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- 1
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11761
27173
30
20
-
11776
27183
- Optional guide curve
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- 0
-
11761
27193
30
20
-
11776
27203
- Flipped curve
- 5a30bc9c-1f0b-4a38-8546-68bfff78fe07
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- Curve
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- 0
-
11815
27173
30
20
-
11830
27183
- Flip action
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- Flag
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-
11815
27193
30
20
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11830
27203
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- true
- Polar Array
- Polar Array
-
11726
26919
207
84
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11853
26961
- Base geometry
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- Geometry
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26921
113
20
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11784.5
26931
- Polar array plane
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11728
26941
113
20
-
11784.5
26951
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
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- 0
-
11728
26961
113
20
-
11784.5
26971
- 1
- 1
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- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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-
11728
26981
113
20
-
11784.5
26991
- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
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- Geometry
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11865
26921
66
40
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11890
26941
- 1
- Transformation data
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11865
26961
66
40
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11890
26981
- 4c0d75e1-4266-45b8-b5b4-826c9ad51ace
- 00000000-0000-0000-0000-000000000000
- Divide Curves on Intersects
- Divide curves on all of their intersects.
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- Divide Curves on Intersects
- Divide Curves on Intersects
-
11726
26862
174
44
-
11853
26884
- 1
- curves to be divided
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- curves
- curves
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11728
26864
113
20
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11784.5
26874
- ZeroTolerance
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- Tolerance
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- 0
-
11728
26884
113
20
-
11784.5
26894
- 1
- 1
- {0}
- 4.768E-07
- 1
- aligned curves
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- curves
- curves
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-
11865
26864
33
40
-
11881.5
26884
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
- Merge
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12407
29509
106
64
-
12468
29541
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
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- Data 1
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- acba9f12-7c5f-4b20-8140-fb2b4854a190
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12409
29511
47
20
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12440.5
29521
- 2
- Data stream 2
- b3c3dc20-91ea-42ab-a774-508a452de635
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- 1
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- Data 2
- D2
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- f53f20a5-69ef-4f15-910d-10163e12842b
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12409
29531
47
20
-
12440.5
29541
- 2
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- 3e8e5b08-c7e2-44f7-a27c-3d7901e0ea27
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- Data 3
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-
12409
29551
47
20
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12440.5
29561
- 2
- Result of merge
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-
12480
29511
31
60
-
12495.5
29541
- 22990b1f-9be6-477c-ad89-f775cd347105
- Flip Curve
- Flip a curve using an optional guide curve.
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- c8952bed-4df0-4f17-9d79-43e809adecfd
- true
- Flip Curve
- Flip Curve
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12596
28903
88
44
-
12640
28925
- Curve to flip
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- Curve
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- aeaf0dce-3d62-4791-b43d-941eeac6c2dd
- 1
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12598
28905
30
20
-
12613
28915
- Optional guide curve
- d6ab2f4f-8592-4046-9f38-14d9c0c86934
- true
- Guide
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- 0
-
12598
28925
30
20
-
12613
28935
- Flipped curve
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-
12652
28905
30
20
-
12667
28915
- Flip action
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- Flag
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-
12652
28925
30
20
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12667
28935
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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12825
28880
90
84
-
12870
28922
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
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- 1
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12827
28882
31
20
-
12842.5
28892
- 2
- Data stream 2
- da9945ce-59f7-4a96-b705-16a66625fadb
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- Data 2
- D2
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- 1
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12827
28902
31
20
-
12842.5
28912
- 2
- Data stream 3
- 2c15933c-ed2d-41f2-b118-69a74a250e27
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- Data 3
- D3
- true
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- 1
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12827
28922
31
20
-
12842.5
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- 2
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- a2635cde-6a9b-4bbf-8847-e4ee58b9bccf
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- Data 4
- D4
- true
- 0
-
12827
28942
31
20
-
12842.5
28952
- 2
- Result of merge
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-
12882
28882
31
80
-
12897.5
28922
- 4f8984c4-7c7a-4d69-b0a2-183cbb330d20
- Plane
- Contains a collection of three-dimensional axis-systems
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-
12822
29795
50
24
-
12847.63
29807
- 962034e9-cc27-4394-afc4-5c16e3447cf9
- Extrude
- Extrude curves and surfaces along a vector.
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- true
- Extrude
- Extrude
-
12934
29770
133
44
-
13008
29792
- Profile curve or surface
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-
12936
29772
60
20
-
12974
29782
- Extrusion direction
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- -X
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- Direction
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-
12936
29792
60
20
-
12974
29802
- Extrusion result
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- Extrusion
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-
13020
29772
45
40
-
13042.5
29792
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- Relay
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-
12756
29756
40
16
-
12776
29764
- 4f8984c4-7c7a-4d69-b0a2-183cbb330d20
- Plane
- Contains a collection of three-dimensional axis-systems
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- Plane
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- bc6cb778-3b9d-4212-b11d-dc534e071d3b
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-
12837
29898
50
24
-
12862.63
29910
- 962034e9-cc27-4394-afc4-5c16e3447cf9
- Extrude
- Extrude curves and surfaces along a vector.
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- true
- Extrude
- Extrude
-
12949
29873
133
44
-
13023
29895
- Profile curve or surface
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- bc6cb778-3b9d-4212-b11d-dc534e071d3b
- 1
-
12951
29875
60
20
-
12989
29885
- Extrusion direction
- 3615e3e8-527c-484d-bab7-357debff0c3d
- -X
- true
- Direction
- Direction
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- b61abf08-a492-40ae-a5bd-8b6987016bfc
- 1
-
12951
29895
60
20
-
12989
29905
- Extrusion result
- c9f55136-fb6f-40a6-819e-aba3e906f9c8
- true
- Extrusion
- Extrusion
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- 0
-
13035
29875
45
40
-
13057.5
29895
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- true
- Relay
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- 1
-
12771
29859
40
16
-
12791
29867
- 4f8984c4-7c7a-4d69-b0a2-183cbb330d20
- Plane
- Contains a collection of three-dimensional axis-systems
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- 347017c1-2ff4-494f-9650-d789a20b9830
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-
12832
29674
50
24
-
12857.63
29686
- 962034e9-cc27-4394-afc4-5c16e3447cf9
- Extrude
- Extrude curves and surfaces along a vector.
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- true
- Extrude
- Extrude
-
12959
29648
117
44
-
13017
29670
- Profile curve or surface
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-
12961
29650
44
20
-
12983
29660
- Extrusion direction
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-
12961
29670
44
20
-
12983
29680
- Extrusion result
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- Extrusion
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-
13029
29650
45
40
-
13051.5
29670
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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12765
29634
40
16
-
12785
29642
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
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11334
29809
50
24
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11359.63
29821
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- List
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26558
38
20
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11829
26568
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- Index
- Index
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- 0
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11810
26578
38
20
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26588
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- Wrap index to list bounds
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11810
26598
38
20
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11829
26608
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- 1
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26558
6
60
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26588
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- Retrieve a specific item from a list.
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26571
72
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26603
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26573
38
20
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11724
26583
- Item index
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11705
26593
38
20
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11724
26603
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11705
26613
38
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26623
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26573
6
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26603
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- Merge a bunch of data streams
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- Merge
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31
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31
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31
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31
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- Join as many curves as possible
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- Join Curves
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116
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- Curves to join
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53
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- Preserve direction of input curves
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- Preserve
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53
20
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- Joined curves and individual curves that could not be joined.
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26473
35
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- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- true
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- Join Curves
-
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26518
116
44
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11744
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- 1
- Curves to join
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- Curves
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- f63e2038-e99c-4ba8-bdcb-667e1ffc18a9
- 1
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26520
53
20
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- Preserve direction of input curves
- dc69c91d-b4d8-473d-80c9-ccbca9c4442e
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- Preserve
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11679
26540
53
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- 1
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- 1
- Joined curves and individual curves that could not be joined.
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26520
35
40
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- 046b132a-5362-439b-a57a-d4dbb32ff590
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- Solve the arithmetic weighted average for a set of curves.
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- Weighted Average Curve
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186
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- Set of curves for averaging
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79
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- Collection of weights for each curve
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- Weights
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79
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11837.5
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- Optional Refit match method.
(No Integer or 0 = Off, Integer greater than 0 = On and curve degree of refit)
If an integer greater than zero, Refit match method is used if possible. When input curves are refit their control points are redistributed, added to, and removed from based on the curves curvature and the input integer degree, while trying to maintain their shapes. Refit results in tighter shaped averages, with curvature based control point distribution.
- 343200ae-fb51-4440-b046-591d01e6148b
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11798
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79
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- Optional Point Sample match method.
(No Integer or 0 = Off, Integer greater than 0 = On and amount of sample points)
If an integer greater than zero, Point Sample match method is used. When input curves are sampled their control points are recreated by equally dividing the curve by the input integer point count. Point Sample results in looser shaped averages, with uniform control point distribution.
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- Point Sample
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- 0
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11798
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79
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- Arithmetic mean (average) of all input curves
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- Arithmetic mean
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79
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- Numeric slider for single values
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275
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- Numeric slider for single values
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275
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- Create a polar array of geometry.
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- Polar Array
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- Geometry
- Geometry
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113
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- Polar array plane
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- Number of elements in array.
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113
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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- Geometry
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66
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- Transform
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- Divide curves on all of their intersects.
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- Divide Curves on Intersects
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174
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- curves to be divided
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- curves
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113
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113
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33
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- Retrieve a specific item from a list.
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43
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- Numeric scroller for single numbers
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- 12
- Digit Scroller
- 11
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29924
250
20
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- Retrieve a specific item from a list.
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77
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- Contains a collection of generic surfaces
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- Group
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- A group of Grasshopper objects
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- Group
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- Relay
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- A wire relay object
- 30377d3c-57fd-4ec7-9de3-54b95b3a7509
- true
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- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
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- Simple Mesh
- Simple Mesh
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- Brep to mesh, only breps with triangle or quad faces are supported.
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- Brep
- Brep
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- Weaverbird's Catmull-Clark Subdivision
- Calculates the type of mesh-based recursive subdivision described by Edwin Catmull and Jim Clark, at first in their 1978 paper. The resulting mesh always consists of quad faces.
Provided by Weaverbird 0.9.0.1.
- 2
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- Weaverbird's Catmull-Clark Subdivision
- Weaverbird's Catmull-Clark Subdivision
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- The open or closed mesh, or closed curves list, to subdivide
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- The number of subdividing iterations for each face
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- Level
- Level
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- Defines how to treat the naked edges
0: Fixed. Naked edges will not move or be modified.
1: Smooth. The naked edge will tend toward a spline.
2: Corner Fixed. Corners (2-sided vertices) will be fixed, while other naked vertices will tend toward a spline.
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- The mesh after the subdividing process
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- Output Mesh/Curves
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- ba2d8f57-0738-42b4-b5a5-fe4d853517eb
- Deconstruct Mesh
- Deconstruct a mesh into its component parts.
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- Deconstruct Mesh
- Deconstruct Mesh
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- Mesh vertices
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- Vertices
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- Mesh faces
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- Mesh vertex colours
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- Mesh normals
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- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
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- Pull a point to a variety of geometry.
- true
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- Pull Point
- Pull Point
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- Point to search from
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- Point
- Point
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- Geometry that pulls
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- Geometry
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- Point on [G] closest to [P]
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- Closest Point
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- Distance between [P] and its projection onto [G]
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- Distance
- Distance
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- e2c0f9db-a862-4bd9-810c-ef2610e7a56f
- Construct Mesh
- Construct a mesh from vertices, faces and optional colours.
- true
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- Construct Mesh
- Construct Mesh
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- Vertices of mesh object
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- Vertices
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- Faces of mesh object
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- Optional vertex colours
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- Colours
- Colours
- true
- 0
-
11851
29575
52
20
-
11877
29585
- Constructed mesh
- e2eb27fa-4759-4c6b-b0e2-999e4b9cb9f0
- true
- Mesh
- Mesh
- false
- 0
-
11927
29535
28
60
-
11941
29565
- 079bd9bd-54a0-41d4-98af-db999015f63d
- Fan+3
- Private Function appendprepend(ByVal i As Integer)
Dim srsEnum As IEnumerable(Of Integer) = Enumerable.Range(0, i + 1)
Dim arrVal As New list(Of Integer)
arrVal = srsEnum.tolist()
arrVal.add(0)
arrVal.insert(0, i)
Return arrVal.toarray()
End Function
Private Function matchDbl(ByVal a As list(Of Double), ByVal t As Integer)
Dim i,k As Integer
k = a.count()
For i = 0 To ((t + 1) - k) - 1 Step 1
a.add(a.item(k - 1))
Next
Return a
End Function
Private Function matchClr(ByVal a As list(Of Color), ByVal t As Integer)
Dim i,k As Integer
k = a.count()
For i = 0 To ((t + 1) - k) - 1 Step 1
a.add(a.item(k - 1))
Next
Return a
End Function
Private Function evalP(ByVal op As point3d, ByVal tp As Point3d, ByVal t As Double)
Return New point3d(op + (tp - op) * t)
End Function
Private Function evalV(ByVal ov As vector3d, ByVal tv As vector3d, ByVal t As Double)
Return New vector3d(ov + (tv - ov) * t)
End Function
Private Function evalN(ByVal u As Double, ByVal v As Double, ByVal t As Double)
Return u + (v - u) * t
End Function
Private Function avgVec(ByVal v() As vector3f)
Dim i As Integer
Dim tv As Vector3d
For i = 0 To ubound(v) Step 1
tv += v(i)
Next
tv /= (ubound(v) + 1)
tv.Unitize()
Return New vector3f(tv.X, tv.Y, tv.Z)
End Function
Private Function roundClr(ByVal r As Integer, ByVal g As Integer, ByVal b As Integer, ByVal i As Integer)
r = CInt(r / i)
g = CInt(g / i)
b = CInt(b / i)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
Private Function avgClr(ByVal c() As color)
Dim r,g,b As Integer
Dim i,k As Integer
k = ubound(c) + 1
For i = 0 To k - 1 Step 1
r += CInt(c(i).R)
g += CInt(c(i).G)
b += CInt(c(i).B)
Next
r = CInt(r / k)
g = CInt(g / k)
b = CInt(b / k)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
Private Function evalC(ByVal oc As color, ByVal tc As color, ByVal t As Double)
Dim r,g,b As Integer
r = CInt(CInt(oc.R) + (CInt(tc.R) - CInt(oc.R)) * t)
g = CInt(CInt(oc.G) + (CInt(tc.G) - CInt(oc.G)) * t)
b = CInt(CInt(oc.B) + (CInt(tc.B) - CInt(oc.B)) * t)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
- true
- Replaces selected faces of a mesh or the interior of a curve with a frame around the edge by creating 3 new points along the edge and removing the face's vertex.
-
251
91
- true
-
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
- d83cd624-e7c4-45b5-b4d0-2a3985556ca5
- true
- Fan+3
- Fan+3
- true
- 0
-
Component.Params.Input(0).Name = "Mesh or Curve"
Component.Params.Input(0).Description = "Open or closed mesh or curve"
Component.Params.Input(1).Name = "Index [Face]"
Component.Params.Input(1).Description = "An optional integer or list of integers which specify the faces to be modified if the input is a mesh. If no value is supplied then all faces will be modified"
Component.Params.Input(2).Name = "Along Edge"
Component.Params.Input(2).Description = "Evaluates a new vertex along the input geometry's edge"
Component.Params.Input(3).Name = "Close"
Component.Params.Input(3).Description = "If true then additional faces and if needed vertices will be added to the mesh, covering the complete areas of the existing mesh"
Component.Params.Input(4).Name = "Color [Vertex]"
Component.Params.Input(4).Description = "(If applied to a mesh a list of colors corresponding to each mesh face, if applied to a curve, a list of colors corresponding to each control point plus an additonal color value for the new averaged center"
Component.Params.Output(1).Name = "Mesh"
Component.Params.Output(1).Description = "If successful, a valid mesh"
If G IsNot Nothing Then
Dim bM, bP,bmC,biC As Boolean
bM = g.ObjectType = ObjectType.Mesh
bP = g.ObjectType = ObjectType.Curve
If (bM Or bP) Then
Dim msh As New mesh
Dim crv As curve
Dim av As point3d
Dim ac As color
Dim h,j,jj,k,u,v,w As Integer
Dim cv,cf,ce As Integer
Dim x(),y() As Integer
Dim mv,fv,ep,tv As New list(Of Point3d)
Dim mev As New dictionary(Of String, Integer)
Dim mf As Rhino.Geometry.Collections.MeshFaceList = Nothing
Dim mtv As Rhino.Geometry.Collections.MeshTopologyVertexList = Nothing
Dim mte As Rhino.Geometry.Collections.MeshTopologyEdgeList = Nothing
Dim ev As New list(Of vector3d)
Dim ed,en As New list(Of Double)
Dim mc,ec,tc,cc,fc As New list(Of color)
Dim xf As New list(Of meshface)
If clr.count() = 0 Then clr.add(color.LightGray) Else biC = True
If bm Then
'Start Deconstruct if Mesh
msh = g
If msh.Normals.Count() = 0 Then msh.Normals.ComputeNormals()
If msh.FaceNormals.Count() = 0 Then msh.FaceNormals.ComputeFaceNormals()
If i.count() = 0 Then I = Enumerable.Range(0, msh.Faces.Count()).ToList()
mv = msh.Vertices().ToPoint3dArray().tolist()
mte = msh.TopologyEdges()
mtv = msh.TopologyVertices()
mf = msh.Faces()
cf = I.Count() - 1
ce = mte.count() - 1
'Assign Colors
If msh.VertexColors.Count() < 1 Then
msh.VertexColors.CreateMonotoneMesh(color.LightGray)
bmC = biC
Else
bmC = True
End If
'Assign fake edges
mc = msh.VertexColors().ToArray().ToList()
Else
'Start Deconstruct if Curve
crv = g
I.clear()
I.add(0)
Dim nc As nurbscurve
Dim pc As polyline
Dim nps As Rhino.Geometry.Collections.NurbsCurvePointList
nc = crv.ToNurbsCurve()
nps = nc.Points
pc = nc.Points.ControlPolygon
If (Not pc.IsClosed) Then pc.add(pc(0))
av = pc.CenterPoint
msh.Vertices.AddVertices(pc.ToArray())
msh.faces.addfaces(pc.TriangulateClosedPolyline())
msh.Vertices.Remove(pc.count() - 1, True)
msh.FaceNormals.ComputeFaceNormals()
mv = msh.Vertices.ToPoint3dArray().tolist()
mte = msh.TopologyEdges()
mtv = msh.TopologyVertices()
'Assign Colors
If bic Then bmC = True
mc = clr
If (clr.count() - 1) < (mv.count() - 1) Then mc = matchClr(mc, mv.count() - 1)
ac = avgClr(mc.toarray())
cf = 0
End If
cv = mv.count() - 1
ce = mte.count() - 1
x = appendprepend(cv)
'Match variables and colors to vertex count
If (T0.count() - 1) < cv Then T0 = matchDbl(T0, cv)
If (clr.count() - 1) < cv Then clr = matchClr(clr, cv)
If biC Then fc = clr Else fc = mc
'Edge based vertices
k = 0
For j = 0 To mte.count() - 1 Step 1
If (bm Or (bp And (mte.GetConnectedFaces(j).Count() < 2))) Then
u = mtv.MeshVertexIndices(mte.GetTopologyVertices(j).I)(0)
v = mtv.MeshVertexIndices(mte.GetTopologyVertices(j).J)(0)
ep.add(evalP(mv(u), mv(v), T0(u) / 2))
ec.add(evalC(mc(u), mc(v), T0(u) / 2))
mev.add(u & "," & v & "," & 0, k)
ep.add(evalP(mv(u), mv(v), 0.5))
ec.add(evalC(mc(u), mc(v), 0.5))
mev.add(u & "," & v & "," & 1, k + 1)
mev.add(v & "," & u & "," & 1, k + 1)
ep.add(evalP(mv(v), mv(u), T0(v) / 2))
ec.add(evalC(mc(v), mc(u), T0(v) / 2))
mev.add(v & "," & u & "," & 0, k + 2)
k += 3
End If
Next
'Face based vertices
Dim xv(),mt(),ei() As Integer
Dim xc() As color
Dim xn As Double
ReDim ei(3)
u = 0
v = ep.count() + cf + 1
For jj = 0 To I.count() - 1 Step 1
Dim tcv As New point3d
j = I(jj)
w = v + tv.count()
xn = 0
If bm Then
If mf(j).isquad() Then h = 4 Else h = 3
ReDim xv(h - 1)
ReDim xc(h - 1)
mt = mf.GetTopologicalVertices(j)
For k = 0 To h - 1 Step 1
xv(k) = mtv.MeshVertexIndices(mt(k))(0)
xc(k) = fc(xv(k))
Next
av = mf.GetFaceCenter(j)
ac = avgClr(xc)
Else
h = mv.count()
xv = Enumerable.Range(0, h).ToArray()
End If
y = appendprepend(h - 1)
Dim tev As New list(Of Integer)
For k = 1 To h Step 1
ei(0) = mev.item(xv(y(k)) & "," & xv(y(k + 1)) & "," & 0)
ei(1) = mev.item(xv(y(k)) & "," & xv(y(k + 1)) & "," & 1)
ei(2) = mev.item(xv(y(k + 1)) & "," & xv(y(k)) & "," & 0)
ei(3) = mev.item(xv(y(k)) & "," & xv(y(k - 1)) & "," & 0)
'Define new faces
tev.add(ei(1))
xf.add(New meshface(ei(0), ei(1), ep.count() + jj))
xf.add(New meshface(ei(1), ei(2), ep.count() + jj))
xf.add(New meshface(ei(3), ei(0), ep.count() + jj))
If c Then xf.add(New meshface(ei(0), ei(3), v + xv(y(k))))
Next
fv.add(av)
cc.add(ac)
Next
Dim om As New mesh
om.Vertices.AddVertices(ep.toarray())
If bmC Then om.VertexColors.AppendColors(ec.toarray())
om.Vertices.AddVertices(fv)
If bmC Then om.VertexColors.AppendColors(cc.toarray())
If c Then
om.Vertices.AddVertices(mv)
If bmC Then om.VertexColors.AppendColors(mc.toarray())
End If
om.Faces.AddFaces(xf.toarray())
If i.count() > 1 Then om.Vertices.CullUnused()
A = om
End If
End If
- Imports System.IO
Imports System.Linq
Imports System.Data
Imports System.Drawing
Imports System.Reflection
Imports System.Windows.Forms
Imports System.Xml
Imports System.Xml.Linq
Imports Microsoft.VisualBasic
Imports System.Runtime.InteropServices
Imports Rhino.DocObjects
Imports Rhino.Collections
Imports GH_IO
Imports GH_IO.Serialization
-
11680
29761
72
104
-
11719
29813
- 5
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- true
- Script Variable G
- 02277887-37da-43cd-9045-2ab622639ff1
- true
- G
- G
- true
- 0
- true
- 979517f2-242e-4e4d-bb88-dd2fc0fa6486
- 1
- c37956f4-d39c-49c7-af71-1e87f8031b26
-
11682
29763
25
20
-
11694.5
29773
- 1
- true
- Script Variable I
- 8bd25a8a-91d9-4eb6-9e52-e603199172cb
- true
- I
- I
- true
- 1
- true
- 0
- efe48ae7-2987-421b-a33a-1f7be1c3f050
-
11682
29783
25
20
-
11694.5
29793
- 1
- true
- Script Variable T0
- f73ae574-ad64-4c32-ae83-7e8f37868e39
- true
- T0
- T0
- true
- 1
- true
- 0
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
11682
29803
25
20
-
11694.5
29813
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Number
- 0.00390625
- true
- Script Variable C
- 541f6166-b28c-4953-9587-28afbe302f37
- true
- C
- C
- true
- 0
- true
- 0
- 3cda2745-22ac-4244-9b04-97a5255fa60f
-
11682
29823
25
20
-
11694.5
29833
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Boolean
- false
- 1
- true
- Script Variable clr
- 14fbe32e-4185-4da3-b3dc-3e17bbd88a35
- true
- clr
- clr
- true
- 1
- true
- 0
- 24b1d1a3-ab79-498c-9e44-c5b14607c4d3
-
11682
29843
25
20
-
11694.5
29853
- 1
- Print, Reflect and Error streams
- ee0a4ed3-d78c-40ef-847e-90017eeb7dc0
- true
- out
- out
- false
- 0
-
11731
29763
19
50
-
11740.5
29788
- Output parameter A
- 16e90cf5-2746-46b7-bcf2-2c1b43dfacf2
- true
- A
- A
- false
- 0
-
11731
29813
19
50
-
11740.5
29838
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 5fa3dc85-5552-4797-8ef8-852841306048
- true
- Relay
- false
- e2eb27fa-4759-4c6b-b0e2-999e4b9cb9f0
- 1
-
11840
29391
40
16
-
11860
29399
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- cfcc5b9b-e104-430a-a736-e9cfea660979
- true
- Relay
- false
- 979517f2-242e-4e4d-bb88-dd2fc0fa6486
- 1
-
11684
29944
40
16
-
11704
29952
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- 8ca2ca44-079d-4e4e-83d9-78c3dacd6aa1
- true
- Mirror
- Mirror
-
11571
28774
305
61
-
11812
28805
- Base geometry
- f0451bfd-6b26-4476-a72d-80f6e314bf50
- true
- Geometry
- Geometry
- true
- 8ad5c4e2-d150-4afc-a797-fd8b0b4ef95e
- 1
-
11573
28776
227
20
-
11686.5
28786
- Mirror plane
- bdda47f8-b994-4250-b1b5-b26f29b09a23
- true
- Plane
- Plane
- false
- 0
-
11573
28796
227
37
-
11686.5
28814.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
-0.707106781186548
0
0.707106781186547
- Mirrored geometry
- 3b6274c6-0db1-455b-9b83-56ddcc437d14
- true
- Geometry
- Geometry
- false
- 0
-
11824
28776
50
28
-
11849
28790.25
- Transformation data
- c350c7c4-7044-46b5-b160-4695143dbec2
- true
- Transform
- Transform
- false
- 0
-
11824
28804
50
29
-
11849
28818.75
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- b05b3657-d031-4156-a0f9-5d9aa404e206
- true
- Merge
- Merge
-
11945
28874
90
64
-
11990
28906
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 343f6de4-eecf-4785-b593-7aaf75b8cc9e
- true
- false
- Data 1
- D1
- true
- 3b6274c6-0db1-455b-9b83-56ddcc437d14
- 1
-
11947
28876
31
20
-
11962.5
28886
- 2
- Data stream 2
- bd4c1892-0bf0-4db4-a530-98e1456b3833
- true
- false
- Data 2
- D2
- true
- 8ad5c4e2-d150-4afc-a797-fd8b0b4ef95e
- 1
-
11947
28896
31
20
-
11962.5
28906
- 2
- Data stream 3
- d82bb646-e7ea-4620-a4e6-a21543407c90
- true
- false
- Data 3
- D3
- true
- 0
-
11947
28916
31
20
-
11962.5
28926
- 2
- Result of merge
- feee9bed-0a55-4a71-bbe4-7083862058a6
- true
- Result
- Result
- false
- 0
-
12002
28876
31
60
-
12017.5
28906
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 4b3c5c37-6f6a-4f2d-90a7-ad7b24cb571c
- true
- Polar Array
- Polar Array
-
12065
28758
207
84
-
12192
28800
- Base geometry
- 035d7fb3-c2cf-4600-bfd9-842d930e39d5
- true
- Geometry
- Geometry
- true
- feee9bed-0a55-4a71-bbe4-7083862058a6
- 1
-
12067
28760
113
20
-
12123.5
28770
- Polar array plane
- 1786f70d-6c1f-4d8e-8097-e7d5e5b74c63
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
12067
28780
113
20
-
12123.5
28790
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f62765ec-b9fe-48ee-8fff-50fd1b505801
- true
- Count
- Count
- false
- 0
-
12067
28800
113
20
-
12123.5
28810
- 1
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12204
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66
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12229
28820
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- A wire relay object
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11798
28939
40
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11818
28947
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- Brep Join
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29246
92
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30
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29248
34
20
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13113
29268
34
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255;255;255;255
- A group of Grasshopper objects
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Extract the end points of a curve.
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26
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27883
26
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27893
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- Create a polyline connecting a number of points.
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27794
116
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50
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- Close polyline
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13592
27816
50
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27826
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27796
38
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27816
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- Create a polyline connecting a number of points.
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13597
27919
116
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13661
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27921
50
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- Close polyline
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13599
27941
50
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27951
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27921
38
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27941
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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90
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31
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31
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31
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31
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- Join as many curves as possible
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116
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- Preserve direction of input curves
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35
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- Number of items in L
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- c75b62fa-0a33-4da7-a5bd-03fd0068fd93
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- Measure the length of a curve.
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- Curve to measure
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- Curve length
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- Item to divide (dividend)
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- Item to divide with (divisor)
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- Item to divide (dividend)
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- Item to divide with (divisor)
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31
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66
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66
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66
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66
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66
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120
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- Curve to explode
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65
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- Mesh join result
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- The open or closed mesh
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110
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- Weld threshold value for Vertices
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110
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- The constructed mesh
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80
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- The material override
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255;255;255;255
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- Colour of the diffuse channel
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255;255;255;255
- Colour of the specular highlight
- 28cee4bd-1a24-43e1-868f-385a08024a2e
- true
- Specular
- Specular
- false
- 0
-
14332
27756
81
20
-
14372.5
27766
- 1
- 1
- {0}
-
255;255;255;255
- Emissive colour of the material
- ef1c2dee-aefd-4179-97bf-7712dadef0fe
- true
- Emission
- Emission
- false
- 0
-
14332
27776
81
20
-
14372.5
27786
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 426b9a64-97a9-44e8-9e95-0216b51823b8
- true
- Transparency
- Transparency
- false
- 0
-
14332
27796
81
20
-
14372.5
27806
- 1
- 1
- {0}
- 0
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 1796cfa4-59c9-4dd0-ab45-9d85a728a169
- true
- Shine
- Shine
- false
- 0
-
14332
27816
81
20
-
14372.5
27826
- 1
- 1
- {0}
- 0
- Resulting material
- 326fbc08-dea2-43c0-83cd-c5852522fa30
- true
- Material
- Material
- false
- 0
-
14437
27736
40
100
-
14457
27786
- 12bb406c-41bc-4c8a-9b96-6924df61b6d6
- d2580c41-5c48-4997-87c5-b6333b5e21d7
- Mesh Rebuild Normals
- Rebuilds Mesh Normals
- true
- 4ad1e8d2-5eec-4a0b-ab32-27566d3371b2
- true
- Mesh Rebuild Normals
- Mesh Rebuild Normals
-
14267
27571
84
28
-
14309
27585
- The Input Mesh
- 67d0048a-9807-4193-bec0-59a715e5ae19
- true
- Mesh
- Mesh
- false
- b013ce48-f199-40ec-bce6-4f6f401e0259
- 1
-
14269
27573
28
24
-
14283
27585
- The Mesh with Rebuilt Normals
- 4c36b0a7-9a92-4045-9c7b-9705ffc8e3a1
- true
- Mesh
- Mesh
- false
- 0
-
14321
27573
28
24
-
14335
27585
- 4bfe1bf6-fbc9-4ad2-bf28-a7402e1392ee
- c2ea695e-1a09-6f42-266d-113498879f60
- MultiPipe
- Create a branching pipe around a network of lines/curves
- true
- e65bd057-1477-4024-bf3f-a43c107821f5
- true
- MultiPipe
- MultiPipe
-
14427
27177
186
184
-
14576
27269
- 1
- The curves to pipe. Also accepts meshes
- 9d5ac057-127f-4e4b-b6df-8548a8e2f2de
- true
- Curves
- Curves
- false
- c6bade99-c83e-413c-befb-c3d58ce01183
- 1
-
14429
27179
135
20
-
14504.5
27189
- 1
- Pipe radius. If one value given, it is applied to all. Alternatively, provide a list of radii corresponding to each point in SizePoints
- 8799a98a-0c75-4383-b675-a8bdd2e6b449
- X*65536
- true
- NodeSize
- NodeSize
- false
- d2521a95-eb69-45eb-8202-b014e1e92713
- 1
-
14429
27199
135
20
-
14504.5
27209
- 1
- 1
- {0}
- 0.5
- 1
- If you are supplying multiple radii for NodeSize, these points identify which node to set as which radius. If only some of the nodes have their radius set this way, the values will be interpolated across the shape
- 176f6124-ddbd-40b8-97e7-372416d6976a
- true
- SizePoints
- SizePoints
- true
- 0
-
14429
27219
135
20
-
14504.5
27229
- The distance of the first edge loop away from the node as a multiplier of NodeSize. If this is set to zero, no intermediate edge loop is added, to give a smoother shape.
- 4833559f-205f-4c7b-8c61-5a9d655a6a5d
- true
- EndOffset
- EndOffset
- false
- 0
-
14429
27239
135
20
-
14504.5
27249
- 1
- 1
- {0}
- 1
- The size of the struts between nodes as a multiplier of NodeSize. <1 gives tapering struts, >1 gives bulging struts
- 13260dff-63c9-4a5a-a106-7475f418b115
- true
- StrutSize
- StrutSize
- false
- 0
-
14429
27259
135
20
-
14504.5
27269
- 1
- 1
- {0}
- 1
- Approximate spacing of edge loops along each strut. If set to zero, no additional edge loops are added
- 441666d9-3257-4d33-94db-64e10261e09e
- true
- Segment
- Segment
- false
- 0
-
14429
27279
135
20
-
14504.5
27289
- 1
- 1
- {0}
- 0
- When the input to 'Curves' are smooth curves, this sets the maximum angle between consecutive segments when discretizing
- c77d7fd1-e082-41c9-ae77-a131386c9277
- true
- KinkAngle
- KinkAngle
- false
- 0
-
14429
27299
135
20
-
14504.5
27309
- 1
- 1
- {0}
- 90
- If >0 this attempts to fit a cube at each node. Should be a value between 0 and 1, where 0 = never, and 1 = always, depending on how close to orthogonal its connected lines are.
- 1cdffb78-f04a-4d16-9fed-7de9da78bb39
- true
- CubeFit
- CubeFit
- false
- 0
-
14429
27319
135
20
-
14504.5
27329
- 1
- 1
- {0}
- 0
- Cap option - 0:None, 1:Round, 2:Flat
- 5811a0ea-ed73-4508-ab04-c5f12074a47b
- true
- Caps
- Caps
- true
- 0
-
14429
27339
135
20
-
14504.5
27349
- 1
- 1
- {0}
- 1
- Resulting Pipe SubD
- 1867f002-ba43-453d-9003-2fa07903686d
- true
- Pipe
- Pipe
- false
- 0
-
14588
27179
23
180
-
14599.5
27269
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- d98270ba-9afb-47d3-9937-cf8259edcdee
- true
- Merge
- Merge
-
13791
28090
90
84
-
13836
28132
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 86ac1872-92ab-4b63-a9e4-484713be52be
- true
- false
- Data 1
- D1
- true
- 960f7236-e5a9-422d-a2d2-dbf7ecde4556
- 1
-
13793
28092
31
20
-
13808.5
28102
- 2
- Data stream 2
- 179555f5-43af-48e9-9fc2-4f3b7acfb0fe
- true
- false
- Data 2
- D2
- true
- 0
-
13793
28112
31
20
-
13808.5
28122
- 2
- Data stream 3
- fcc88034-d9de-4584-9e6a-4b7aaab42489
- true
- false
- Data 3
- D3
- true
- c4c58973-5656-4a93-b5f4-7f922145a19f
- 1
-
13793
28132
31
20
-
13808.5
28142
- 2
- Data stream 4
- 65b533b7-98c2-47f6-a1cd-017b3924e9a2
- true
- false
- Data 4
- D4
- true
- 0
-
13793
28152
31
20
-
13808.5
28162
- 2
- Result of merge
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- true
- Result
- Result
- false
- 0
-
13848
28092
31
80
-
13863.5
28132
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- fd92a202-6283-4250-8b87-a63ec2749b47
- true
- Join Curves
- Join Curves
-
13923
28165
116
44
-
13990
28187
- 1
- Curves to join
- 81a540c7-0c42-4b17-ae37-fcc96a189b33
- true
- Curves
- Curves
- false
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- 1
-
13925
28167
53
20
-
13951.5
28177
- Preserve direction of input curves
- 8c16c48d-153e-4180-ab2f-c3f6b58158c7
- true
- Preserve
- Preserve
- false
- 0
-
13925
28187
53
20
-
13951.5
28197
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- 54ebf683-fd9d-4ded-8395-0a2c3898d0ef
- true
- Curves
- Curves
- false
- 0
-
14002
28167
35
40
-
14019.5
28187
- c3f9cea5-6fd4-4db5-959b-08cd08ed9fe1
- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
- cdeb0ed4-1a13-4341-9034-684797145956
- true
- Simple Mesh
- Simple Mesh
-
14130
28051
81
28
-
14169
28065
- Brep to mesh, only breps with triangle or quad faces are supported.
- 3948c631-d998-4834-bfdc-3fc92eb3b4ed
- true
- Brep
- Brep
- false
- 0
-
14132
28053
25
24
-
14144.5
28065
- Mesh
- 49844cd2-dce1-4c0c-bd49-b5e0b6dd8e38
- true
- Mesh
- Mesh
- false
- 0
-
14181
28053
28
24
-
14195
28065
- 9266a2bb-918f-4675-9c91-f67d0dd33eac
- Quadrangulate
- Quadrangulate as many triangles as possible in a mesh
- true
- 8665abfd-c7fc-4786-bc40-b494c4bfa4bc
- true
- Quadrangulate
- Quadrangulate
-
14130
27970
148
64
-
14234
28002
- Mesh to quadrangulate
- 2f0e53af-4c1f-4ce1-bb65-8ce06ec8be50
- true
- Mesh
- Mesh
- false
- 54ebf683-fd9d-4ded-8395-0a2c3898d0ef
- 1
-
14132
27972
90
20
-
14177
27982
- Angle threshold. Triangles that exceed this kink-angle will not be merged.
- 7dd61ecc-f1dd-424a-958c-4cdac6b8c9e0
- true
- Angle
- Angle
- false
- 0
-
14132
27992
90
20
-
14177
28002
- 1
- 1
- {0}
- 0.034906585039886591
- Ratio threshold. Quads that have a ratio (shortest diagonal/longest diagonal) that exceed the threshold, will not be considered.
- d6e66e82-f7a2-44db-84b9-4e87f8830fd1
- true
- Ratio
- Ratio
- false
- 0
-
14132
28012
90
20
-
14177
28022
- 1
- 1
- {0}
- 0.875
- Quadrangulated mesh (not all triangles are guaranteed to be converted).
- a7da4a92-991c-4900-b5d1-360021364e54
- true
- Mesh
- Mesh
- false
- 0
-
14246
27972
30
30
-
14261
27987
- Number of triangles that were quadrangulated
- 9700fcbf-be9e-450e-b55e-ba2b4a83e357
- true
- Count
- Count
- false
- 0
-
14246
28002
30
30
-
14261
28017
- 4c0d75e1-4266-45b8-b5b4-826c9ad51ace
- 00000000-0000-0000-0000-000000000000
- Divide Curves on Intersects
- Divide curves on all of their intersects.
- true
- 2f177179-4697-4a93-a401-219c588e7391
- true
- Divide Curves on Intersects
- Divide Curves on Intersects
-
14066
28166
174
44
-
14193
28188
- 1
- curves to be divided
- e220dfce-a878-44d3-8a16-63de991c5b32
- true
- curves
- curves
- false
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- 1
-
14068
28168
113
20
-
14124.5
28178
- ZeroTolerance
- 00c0f45e-ba64-4d33-9e88-f6c1deb34897
- true
- Tolerance
- Tolerance
- false
- 0
-
14068
28188
113
20
-
14124.5
28198
- 1
- 1
- {0}
- 4.768E-07
- 1
- aligned curves
- 6da19130-89a1-437b-b23f-cb65a54edfae
- true
- curves
- curves
- false
- 0
-
14205
28168
33
40
-
14221.5
28188
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 2f9c982a-f0ff-467e-ac38-6065e3546417
- true
- List Item
- List Item
-
14137
28223
77
64
-
14194
28255
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- fec5ed95-cdff-42cf-889b-c85d2af22ad9
- true
- List
- List
- false
- 6da19130-89a1-437b-b23f-cb65a54edfae
- 1
-
14139
28225
43
20
-
14160.5
28235
- Item index
- 0e1643b4-dc6c-4a34-9c1e-50d0d823a23e
- true
- Index
- Index
- false
- 0
-
14139
28245
43
20
-
14160.5
28255
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 3b1b18e4-5dbf-4177-a14b-2f72fd73de68
- true
- Wrap
- Wrap
- false
- 0
-
14139
28265
43
20
-
14160.5
28275
- 1
- 1
- {0}
- true
- Item at {i'}
- 2f6f0afd-993f-47a5-8a5f-5b97369eb913
- true
- false
- Item
- i
- false
- 0
-
14206
28225
6
60
-
14209
28255
- c3f9cea5-6fd4-4db5-959b-08cd08ed9fe1
- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
- 916b40c9-fae5-4a15-b308-c086513aa6ed
- true
- Simple Mesh
- Simple Mesh
-
13537
27486
81
28
-
13576
27500
- Brep to mesh, only breps with triangle or quad faces are supported.
- a3400c94-1368-45d9-919d-f308d19cb831
- true
- Brep
- Brep
- false
- 02d977a4-4efe-4e2d-8407-51dd988709ae
- 1
-
13539
27488
25
24
-
13551.5
27500
- Mesh
- c141638f-f968-4458-8a65-656377164c14
- true
- Mesh
- Mesh
- false
- 0
-
13588
27488
28
24
-
13602
27500
- 8307c31e-e307-48e9-b7c3-f970591e86d2
- 2cd3c35a-cada-1a81-ddba-5b184219e513
- ggNetworkPolygons
- Polygon from Curve network
- true
- 03dad908-8250-4fe7-9faf-aac50ee62be7
- true
- ggNetworkPolygons
- ggNetworkPolygons
-
13615
27745
134
44
-
13710
27767
- 1
- Input Curves
- 0124ecba-9dc2-4ca3-80ff-7428af38b8cc
- true
- Curves
- Curves
- false
- 4cb9ae17-9c50-4f01-abc2-ce86d43083b0
- 1
-
13617
27747
81
20
-
13657.5
27757
- Number of edges considered to be a void or perimeter location
- 5e4caa1c-831b-487e-bdd5-a88cf6ee8f05
- true
- Perim or Void
- Perim or Void
- true
- 0
-
13617
27767
81
20
-
13657.5
27777
- 1
- 1
- {0}
- 4
- 1
- Resultant Polygons
- c3015044-b271-488b-bb89-63d99aa97c9b
- true
- Cells
- Cells
- false
- 0
-
13722
27747
25
40
-
13734.5
27767
- 3c5edcba-b7a5-4710-b076-4b19a7080a2b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Center
- Returns the center of a geometry and the Diameter of it's bounding box as the Dimension
You can Right Click on the component's icon and choose "ForAll" option to have center point of a group of geometries.
Besides You can Right click on the component's icon and choose one of three provided options (Spacial/ Planar/ Basement ) to have Desired type of center.
- true
- 6ec8f57d-f6b6-4f61-9fa6-ea4d3930062b
- true
- Center
- Center
-
13723
27607
129
44
-
13787
27629
- 1
- Geometric
- 25a6dac4-741b-4cf2-b6c4-46916348ea4c
- true
- Geometric
- Geometric
- false
- 83c37836-d997-40ad-b3dd-9f1c8098cd80
- 1
-
13725
27609
50
40
-
13750
27629
- 1
- Center
- 5be92eb5-02c1-4a50-802c-7ab01a573a0e
- true
- Center
- Center
- false
- 0
-
13799
27609
51
20
-
13824.5
27619
- 1
- Diagonal size of geometry's bounding box
- 8fe3d4fd-0f58-4b7a-8a93-086ba2ce3425
- true
- Dimension
- Dimension
- false
- 0
-
13799
27629
51
20
-
13824.5
27639
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- 22249883-3dfd-42f2-938f-5dbb9209cffb
- true
- Scale
- Scale
-
13523
27550
191
64
-
13650
27582
- Base geometry
- add7ea7e-611e-4934-b67e-62bdab122d97
- true
- Geometry
- Geometry
- true
- 83c37836-d997-40ad-b3dd-9f1c8098cd80
- 1
-
13525
27552
113
20
-
13581.5
27562
- Center of scaling
- 15215e10-f506-4266-8884-84f12e90ff86
- true
- Center
- Center
- false
- 5be92eb5-02c1-4a50-802c-7ab01a573a0e
- 1
-
13525
27572
113
20
-
13581.5
27582
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- 9bb0c08c-8fbe-4370-9fac-438da46c2bd9
- true
- Factor
- Factor
- false
- 0
-
13525
27592
113
20
-
13581.5
27602
- 1
- 1
- {0}
- 0.33333333333333331
- Scaled geometry
- 02d977a4-4efe-4e2d-8407-51dd988709ae
- true
- Geometry
- Geometry
- false
- 0
-
13662
27552
50
30
-
13687
27567
- Transformation data
- 4354deec-6b6e-4a5c-b887-e54017812829
- true
- Transform
- Transform
- false
- 0
-
13662
27582
50
30
-
13687
27597
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
- true
- fef8f6d8-5af6-4935-8408-78241f7e4d7b
- true
- Surface
- Surface
- false
- cbd6bf4a-bfcb-42e9-b3ba-b33cb2875e0a
- 1
-
13617
27436
50
24
-
13642.63
27448.02
- ba2d8f57-0738-42b4-b5a5-fe4d853517eb
- Deconstruct Mesh
- Deconstruct a mesh into its component parts.
- true
- 2b056227-09bd-4857-a416-66e816e2af0b
- true
- Deconstruct Mesh
- Deconstruct Mesh
-
13708
27437
97
84
-
13750
27479
- Base mesh
- 2f090a6d-532a-430f-aed9-fb570dbc2522
- true
- Mesh
- Mesh
- false
- c141638f-f968-4458-8a65-656377164c14
- 1
-
13710
27439
28
80
-
13724
27479
- 1
- Mesh vertices
- fd84477c-fe0f-4f05-9828-1aa854d22749
- true
- Vertices
- Vertices
- false
- 0
-
13762
27439
41
20
-
13782.5
27449
- 1
- Mesh faces
- 3a3c7504-af86-4050-b2f7-9453abe99352
- true
- Faces
- Faces
- false
- 0
-
13762
27459
41
20
-
13782.5
27469
- 1
- Mesh vertex colours
- 67e990b8-5886-40d8-8adb-301eb5ef3b69
- true
- Colours
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- Scale an object with non-uniform factors.
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- Scale NU
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- Deconstruct a numeric domain into its component parts.
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108
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11
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31
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64
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60
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44
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- Contains a collection of floating point numbers
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- Evaluate the curvature of a curve at a specified parameter.
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50
30
-
9263
-2362
- Parameter on curve domain to evaluate
- 2b184f5f-60fe-48a2-84af-24f1707371c9
- true
- Parameter
- Parameter
- false
- 9b047484-149a-4c2c-bc3b-133bf8a16042
- 1
-
9238
-2347
50
30
-
9263
-2332
- Point on curve at {t}
- 27d02d99-f186-4f18-959f-fb55050714ad
- true
- Point
- Point
- false
- 0
-
9312
-2377
47
20
-
9335.5
-2367
- Curvature vector at {t}
- aeb40292-7614-4530-8cb6-cb15afc4abd7
- true
- Curvature
- Curvature
- false
- 0
-
9312
-2357
47
20
-
9335.5
-2347
- Curvature circle at {t}
- ac4108b8-b50c-4b2f-9d58-db3abf48d468
- true
- Curvature
- Curvature
- false
- 0
-
9312
-2337
47
20
-
9335.5
-2327
- 2162e72e-72fc-4bf8-9459-d4d82fa8aa14
- Divide Curve
- Divide a curve into equal length segments
- true
- 1c788573-d7bf-4f72-a121-cbf3b62252c6
- true
- Divide Curve
- Divide Curve
-
9237
-2293
123
64
-
9291
-2261
- Curve to divide
- 7bb740f1-89a7-41ba-908d-6172c795d802
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-2291
40
20
-
9259
-2281
- Number of segments
- 31973aa3-a6c4-40e2-8334-3d5983744459
- true
- Count
- Count
- false
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- 1
-
9239
-2271
40
20
-
9259
-2261
- 1
- 1
- {0}
- 32
- Split segments at kinks
- f686c8ca-6a0f-4056-b538-82d1db5c6c23
- true
- Kinks
- Kinks
- false
- 0
-
9239
-2251
40
20
-
9259
-2241
- 1
- 1
- {0}
- false
- 1
- Division points
- 6c829d37-82dc-4ac3-941d-503e2491d515
- true
- Points
- Points
- false
- 0
-
9303
-2291
55
20
-
9330.5
-2281
- 1
- Tangent vectors at division points
- 1c759179-d2dd-4f1d-8b1b-e5fb56023536
- true
- Tangents
- Tangents
- false
- 0
-
9303
-2271
55
20
-
9330.5
-2261
- 1
- Parameter values at division points
- 9b047484-149a-4c2c-bc3b-133bf8a16042
- true
- Parameters
- Parameters
- false
- 0
-
9303
-2251
55
20
-
9330.5
-2241
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- true
- Curve
- Curve
- false
- 506f2123-b521-4a52-9165-68e803a30009
- 1
-
9282
-811
50
24
-
9307.541
-799.8869
- 23862862-049a-40be-b558-2418aacbd916
- Deconstruct Arc
- Retrieve the base plane, radius and angle domain of an arc.
- true
- f3a56189-a559-47f2-af99-08d4a3d06a47
- true
- Deconstruct Arc
- Deconstruct Arc
-
9248
-2462
102
64
-
9282
-2430
- Arc or Circle to deconstruct
- 6cec1ee5-525e-453b-ad11-20021ffb74ad
- true
- Arc
- Arc
- false
- ac4108b8-b50c-4b2f-9d58-db3abf48d468
- 1
-
9250
-2460
20
60
-
9260
-2430
- Base plane of arc or circle
- b86f8283-6c12-49a0-bd2b-33920875eaa4
- true
- Base Plane
- Base Plane
- false
- 0
-
9294
-2460
54
20
-
9321
-2450
- Radius of arc or circle
- e440447f-77d2-4617-ba70-c50ae59a1c77
- true
- Radius
- Radius
- false
- 0
-
9294
-2440
54
20
-
9321
-2430
- Angle domain (in radians) of arc
- b91b85ff-7309-4c95-aa1c-b70e2d0d927c
- true
- Angle
- Angle
- false
- 0
-
9294
-2420
54
20
-
9321
-2410
- 797d922f-3a1d-46fe-9155-358b009b5997
- One Over X
- Compute one over x.
- true
- e5e088e3-6608-44e6-a7d7-7eb73fb9b2c8
- true
- One Over X
- One Over X
-
9255
-3051
88
28
-
9298
-3037
- Input value
- af3506ed-2063-459e-aa23-5a1fdc8a363f
- true
- Value
- Value
- false
- 2cd82ac7-4de3-4efd-b21c-bb675514f953
- 1
-
9257
-3049
29
24
-
9271.5
-3037
- Output value
- c1491a51-714b-4cb9-85b6-34a38ca75a1f
- true
- Result
- Result
- false
- 0
-
9310
-3049
31
24
-
9325.5
-3037
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 52fc7e98-c167-43e7-87c2-59064227472a
- true
- Quick Graph
- Quick Graph
- false
- 0
- 9ffa872c-e479-408b-8f5c-98a77c7ef2dd
- 1
-
9232
-3288
150
150
-
9232.541
-3287.887
- -1
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c95358a1-3288-48df-a244-8bf7e0c6385d
- true
- Line
- Line
-
9248
-2987
102
44
-
9314
-2965
- Line start point
- dda79b74-b3e3-445d-8e48-4096cd5b33ec
- true
- Start Point
- Start Point
- false
- 27d02d99-f186-4f18-959f-fb55050714ad
- 1
-
9250
-2985
52
20
-
9276
-2975
- Line end point
- ebc36594-9c20-4f70-988a-0ab4624f67fd
- true
- End Point
- End Point
- false
- b86f8283-6c12-49a0-bd2b-33920875eaa4
- 1
-
9250
-2965
52
20
-
9276
-2955
- Line segment
- 7785f9df-f096-491f-964e-599a2aec932f
- true
- Line
- Line
- false
- 0
-
9326
-2985
22
40
-
9337
-2965
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 39e437ab-17e0-4324-8544-cb86abbc9e57
- true
- Line SDL
- Line SDL
-
9244
-4871
110
64
-
9318
-4839
- Line start point
- 41670e9e-038a-4b55-9192-201b8ad9b7af
- true
- Start
- Start
- false
- 27d02d99-f186-4f18-959f-fb55050714ad
- 1
-
9246
-4869
60
20
-
9284
-4859
- Line tangent (direction)
- 7a745369-90e9-483d-ae37-86261addbb34
- true
- Direction
- Direction
- false
- 2fcc79ac-e62a-4a44-84e2-59411080f035
- 1
-
9246
-4849
60
20
-
9284
-4839
- 1
- 1
- {0}
-
0
0
1
- Line length
- 8ebf383f-28be-4dbc-9a3f-e05ca0ef3e02
- -X
- true
- Length
- Length
- false
- 37bb12ea-34eb-418f-9b39-ae27a2fe2897
- 1
-
9246
-4829
60
20
-
9284
-4819
- 1
- 1
- {0}
- 1
- Line segment
- 2158b91e-623b-4f9d-8297-f4edb0d6540d
- true
- Line
- Line
- false
- 0
-
9330
-4869
22
60
-
9341
-4839
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- c6073d46-269e-471f-9961-e21811a07752
- true
- Evaluate Length
- Evaluate Length
-
9224
-5784
149
64
-
9309
-5752
- Curve to evaluate
- af95f296-ac3c-495a-9314-f578c0929d0c
- true
- Curve
- Curve
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9226
-5782
71
20
-
9261.5
-5772
- Length factor for curve evaluation
- 082891a2-5a2f-4b4c-b46b-91e2da8ce77d
- true
- Length
- Length
- false
- 0
-
9226
-5762
71
20
-
9261.5
-5752
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 71ea8ef3-18b4-4e5c-ab66-8d3bbe633f6e
- true
- Normalized
- Normalized
- false
- 0
-
9226
-5742
71
20
-
9261.5
-5732
- 1
- 1
- {0}
- true
- Point at the specified length
- 58715e09-1461-47aa-b311-c9878cbef364
- true
- Point
- Point
- false
- 0
-
9321
-5782
50
20
-
9346
-5772
- Tangent vector at the specified length
- 78cd4516-cf88-4c55-b855-7036ef090b35
- true
- Tangent
- Tangent
- false
- 0
-
9321
-5762
50
20
-
9346
-5752
- Curve parameter at the specified length
- 0351b476-a056-45f8-868d-0f74aeb0b6bd
- true
- Parameter
- Parameter
- false
- 0
-
9321
-5742
50
20
-
9346
-5732
- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- 93569eee-4485-4e75-b081-b5a4f7d2e796
- true
- Interpolate
- Interpolate
-
9186
-6115
225
84
-
9359
-6073
- 1
- Interpolation points
- dde1eac0-839e-45a9-a2e5-3f21c6dc288e
- true
- Vertices
- Vertices
- false
- 043ef658-425b-4fc2-a0ed-57be30e7b117
- 1
-
9188
-6113
159
20
-
9267.5
-6103
- Curve degree
- 08e55262-47e4-4f8d-bebd-c3a698f87d4e
- true
- Degree
- Degree
- false
- 0
-
9188
-6093
159
20
-
9267.5
-6083
- 1
- 1
- {0}
- 1
- Periodic curve
- 2ad1ddf0-9cf3-4806-837a-41b2fddf6642
- true
- Periodic
- Periodic
- false
- 0
-
9188
-6073
159
20
-
9267.5
-6063
- 1
- 1
- {0}
- false
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- eae7757e-1299-4541-a34c-bcc676de11c9
- true
- KnotStyle
- KnotStyle
- false
- 0
-
9188
-6053
159
20
-
9267.5
-6043
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 098a4c87-ff22-4643-a81f-d1664572e52a
- true
- Curve
- Curve
- false
- 0
-
9371
-6113
38
26
-
9390
-6099.667
- Curve length
- 54263cd0-b37d-47d9-868f-db90f9b3858d
- true
- Length
- Length
- false
- 0
-
9371
-6087
38
27
-
9390
-6073
- Curve domain
- ad91ff97-0733-42e1-ab10-73c9b30777cd
- true
- Domain
- Domain
- false
- 0
-
9371
-6060
38
27
-
9390
-6046.333
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 9d77a9be-7ee4-404f-b9d9-0b021cd89431
- true
- Number
- Number
- false
- b22d0187-dac5-4128-a6af-18259df683c4
- 1
-
9282
-6145
50
24
-
9307.541
-6133.887
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 61019724-eb0d-4b80-ba89-1f6601b8fba6
- true
- Curve
- Curve
- false
- 098a4c87-ff22-4643-a81f-d1664572e52a
- 1
-
9282
-6242
50
24
-
9307.541
-6230.887
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 9ffa872c-e479-408b-8f5c-98a77c7ef2dd
- true
- Relay
-
- false
- c1491a51-714b-4cb9-85b6-34a38ca75a1f
- 1
-
9279
-3070
40
16
-
9299
-3062
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 09c6c5c2-7cc1-43ae-a3a3-04ac393041d8
- true
- Create Material
- Create Material
-
9223
-5631
152
104
-
9321
-5579
- Colour of the diffuse channel
- f7a4b8b1-069c-43a0-b602-1833de12db7e
- true
- Diffuse
- Diffuse
- false
- 0
-
9225
-5629
84
20
-
9267
-5619
- 1
- 1
- {0}
-
255;248;248;248
- Colour of the specular highlight
- 0cdf7eb3-a2e9-4b8c-80df-5796a2c42d29
- true
- Specular
- Specular
- false
- 0
-
9225
-5609
84
20
-
9267
-5599
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- f9ec374b-4e7e-425e-80dc-7d1913f5d442
- true
- Emission
- Emission
- false
- 0
-
9225
-5589
84
20
-
9267
-5579
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 7d73c7ec-e469-48b9-9f6c-3af7d21e5a0a
- true
- Transparency
- Transparency
- false
- 0
-
9225
-5569
84
20
-
9267
-5559
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- f29297e6-80ae-4e98-8057-425ad865e68a
- true
- Shine
- Shine
- false
- 0
-
9225
-5549
84
20
-
9267
-5539
- 1
- 1
- {0}
- 100
- Resulting material
- 1ce09a68-c1f4-44f0-990c-4d96308dc9e1
- true
- Material
- Material
- false
- 0
-
9333
-5629
40
100
-
9353
-5579
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- e286f87e-7fc1-43eb-b9a4-a2366f90ae24
- true
- Custom Preview
- Custom Preview
-
9265
-5701
76
44
-
9327
-5679
- Geometry to preview
- true
- 366ececa-ed22-4724-b989-f09e6937697d
- true
- Geometry
- Geometry
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9267
-5699
48
20
-
9291
-5689
- The material override
- 027c3144-be54-484e-975d-ce396e8b251f
- true
- Material
- Material
- false
- 1ce09a68-c1f4-44f0-990c-4d96308dc9e1
- 1
-
9267
-5679
48
20
-
9291
-5669
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 3f7e06d6-03e2-4aa1-b86d-542eceeb31ee
- true
- Create Material
- Create Material
-
9223
-1711
152
104
-
9321
-1659
- Colour of the diffuse channel
- 7f94db8a-e3ab-4ce3-9b03-f3ec7b4f851b
- true
- Diffuse
- Diffuse
- false
- 0
-
9225
-1709
84
20
-
9267
-1699
- 1
- 1
- {0}
-
255;211;211;211
- Colour of the specular highlight
- 77a29782-5647-44c5-a815-16be8fea0af6
- true
- Specular
- Specular
- false
- 0
-
9225
-1689
84
20
-
9267
-1679
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 46d73d35-3d8f-4a3a-af59-d7f2aff6c5e4
- true
- Emission
- Emission
- false
- 0
-
9225
-1669
84
20
-
9267
-1659
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- fa2a385c-186e-442f-8652-d241044e2bdc
- true
- Transparency
- Transparency
- false
- 0
-
9225
-1649
84
20
-
9267
-1639
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- a1f22685-5539-4143-83f0-28d6fea1c703
- true
- Shine
- Shine
- false
- 0
-
9225
-1629
84
20
-
9267
-1619
- 1
- 1
- {0}
- 100
- Resulting material
- 71d2a512-f0b5-4c06-9af5-6682789399fe
- true
- Material
- Material
- false
- 0
-
9333
-1709
40
100
-
9353
-1659
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- fd34a320-94b5-40d0-945e-128f98958485
- true
- Custom Preview
- Custom Preview
-
9270
-1797
76
44
-
9332
-1775
- Geometry to preview
- true
- e50fc350-2355-4f9b-a8ca-f8fa8ee0fe7a
- true
- Geometry
- Geometry
- false
- f1cb17b7-ee0e-49ec-95f6-e24ed89eb56e
- 1
-
9272
-1795
48
20
-
9296
-1785
- The material override
- 88a7d6cf-88b3-401f-879c-b7f3a4cd2820
- true
- Material
- Material
- false
- 71d2a512-f0b5-4c06-9af5-6682789399fe
- 1
-
9272
-1775
48
20
-
9296
-1765
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- e2e12ca1-f11f-496f-af7e-060e0185e0e7
- true
- Create Material
- Create Material
-
9223
-6402
152
104
-
9321
-6350
- Colour of the diffuse channel
- aa7be633-bc1c-4774-8b07-82401abd26bf
- true
- Diffuse
- Diffuse
- false
- 0
-
9225
-6400
84
20
-
9267
-6390
- 1
- 1
- {0}
-
255;223;223;223
- Colour of the specular highlight
- 75c45dd2-9c4f-4900-9e26-43c55a421435
- true
- Specular
- Specular
- false
- 0
-
9225
-6380
84
20
-
9267
-6370
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- f5341123-f1a4-4536-a36e-d2cb025ab991
- true
- Emission
- Emission
- false
- 0
-
9225
-6360
84
20
-
9267
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- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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- Allows for customized geometry previews
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- Custom Preview
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- Geometry to preview
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- The material override
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48
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Curvature Graph
- Draws Rhino Curvature Graphs.
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- Curvature Graph
- Curvature Graph
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80
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- Curve for Curvature graph display
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- Sampling density of the Graph
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250
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- Remap Numbers
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149
64
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- Value to remap
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- Value
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81
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- Source domain
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81
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81
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- Remapped number
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9331
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40
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9331
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40
30
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- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
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110
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- Numbers to include in Bounds
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44
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- Numeric Domain between the lowest and highest numbers in {N}
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- 0
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38
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40
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- A wire relay object
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70
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- First item for multiplication
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11
20
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- Second item for multiplication
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11
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31
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40
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255;255;255;255
- A group of Grasshopper objects
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200
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40
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30
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- Curve length
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34
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- Multiplication
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70
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11
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- Second item for multiplication
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11
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- Result of multiplication
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31
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40
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- Recursive decomposition until all segments are atomic
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- Length factor for curve evaluation
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50
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- Line start point
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60
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- Line tangent (direction)
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60
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0
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- Line length
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60
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22
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- Compute relative differences for a list of data
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116
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- List of data to operate on (numbers or points or vectors allowed)
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9363
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38
26
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9382
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- Curve length
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- Length
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- 0
-
9363
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38
27
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9382
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- Curve domain
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- Domain
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- 0
-
9363
-9805
38
27
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9382
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- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
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- true
- Create Material
- Create Material
-
9215
-9997
152
104
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9313
-9945
- Colour of the diffuse channel
- 207b8415-27f7-42c6-8c64-3adb873fcfd8
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- false
- 0
-
9217
-9995
84
20
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9259
-9985
- 1
- 1
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-
255;219;219;219
- Colour of the specular highlight
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- true
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- Specular
- false
- 0
-
9217
-9975
84
20
-
9259
-9965
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 6f9a8ba2-dd2e-4732-95dd-5d9316fff397
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- Emission
- false
- 0
-
9217
-9955
84
20
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9259
-9945
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- e715ae77-2790-4464-a60f-20723da9f4a8
- true
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- Transparency
- false
- 0
-
9217
-9935
84
20
-
9259
-9925
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 7ce4fc74-7bad-4ffe-8f64-8bef1035495d
- true
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- Shine
- false
- 0
-
9217
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84
20
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9259
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- Resulting material
- 6836f515-706a-4c69-8769-5d7de637fb53
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- 0
-
9325
-9995
40
100
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9345
-9945
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
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- true
- Custom Preview
- Custom Preview
-
9241
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76
44
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9303
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- Geometry to preview
- true
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- Geometry
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- c32bd525-2467-45e9-a83b-330bd9f9b05a
- 1
-
9243
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48
20
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9267
-10056
- The material override
- d553ab6a-7371-4cea-9568-4cd00d85c970
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- 6836f515-706a-4c69-8769-5d7de637fb53
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9243
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48
20
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9267
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- 1
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Quick Graph
- 1
- Display a set of y-values as a graph
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- Quick Graph
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- dd7ae928-e56d-4423-b7b1-b1999182a279
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-
9223
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150
150
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9223.633
-8189
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
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255;255;255;255
- A group of Grasshopper objects
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- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
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- true
- Explode
- Explode
-
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-10388
134
44
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9295
-10366
- Curve to explode
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- c32bd525-2467-45e9-a83b-330bd9f9b05a
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9226
-10386
57
20
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9254.5
-10376
- Recursive decomposition until all segments are atomic
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- 0
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9226
-10366
57
20
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9254.5
-10356
- 1
- 1
- {0}
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- 1
- Exploded segments that make up the base curve
- 657f9a26-0555-40a8-85a2-d714bd1df761
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- Segments
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9307
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49
20
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9331.5
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- Vertices of the exploded segments
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- Vertices
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9307
-10366
49
20
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9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 31841e7d-30a7-4a57-896b-1f20e5587acb
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- Evaluate Length
- Evaluate Length
-
9216
-10471
149
64
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9301
-10439
- Curve to evaluate
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9218
-10469
71
20
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9253.5
-10459
- Length factor for curve evaluation
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- true
- Length
- Length
- false
- 0
-
9218
-10449
71
20
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9253.5
-10439
- 1
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
- Normalized
- Normalized
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9218
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71
20
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9253.5
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- 1
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- Point at the specified length
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- Point
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-
9313
-10469
50
20
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9338
-10459
- Tangent vector at the specified length
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- Tangent
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9313
-10449
50
20
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9338
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- Curve parameter at the specified length
- 572b8234-c8fb-4fcc-b7ec-a320da596eeb
- true
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- Parameter
- false
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-
9313
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50
20
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9338
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- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9236
-12191
110
64
-
9310
-12159
- Line start point
- c9666999-2358-4b17-8320-a71d84c28fa9
- true
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- Start
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9238
-12189
60
20
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9276
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- Line tangent (direction)
- 2f910283-5649-449c-be0c-b136a4148d2e
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- Direction
- Direction
- false
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- 1
-
9238
-12169
60
20
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9276
-12159
- 1
- 1
- {0}
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0
0
1
- Line length
- 3f7a29c7-d6dd-43e5-a2bc-9d2174148239
- ABS(X)
- true
- Length
- Length
- false
- 9f9eae92-60c1-4f4c-87f5-b8931d6fd9c9
- 1
-
9238
-12149
60
20
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9276
-12139
- 1
- 1
- {0}
- 0.015625
- Line segment
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- true
- Line
- Line
- false
- 0
-
9322
-12189
22
60
-
9333
-12159
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- d78b1c8d-4c32-45a1-9cd0-3f1c128e80c8
- true
- Relative Differences
- Relative Differences
-
9233
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116
28
-
9280
-10800
- 1
- List of data to operate on (numbers or points or vectors allowed)
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- Values
- Values
- false
- 36b3a4ab-79e8-4ae2-bcf6-59f01b423655
- 1
-
9235
-10812
33
24
-
9251.5
-10800
- 1
- Differences between consecutive items
- 7338c244-af88-4723-b45a-08577283c18b
- true
- Differenced
- Differenced
- false
- 0
-
9292
-10812
55
24
-
9319.5
-10800
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 60ac2b1a-ed32-485c-b398-5132c0ce38c7
- true
- Replace Nulls
- Replace Nulls
-
9221
-10758
139
44
-
9316
-10736
- 1
- Items to test for null
- 8b748710-2523-4d4d-a9f8-7949b3dbbaec
- true
- Items
- Items
- false
- 55a89bb9-1cb3-4508-a64e-593c4f56d389
- 1
-
9223
-10756
81
20
-
9263.5
-10746
- 1
- Items to replace nulls with
- 78bf5914-83e2-4bf8-abe7-ef8d3f6c72a5
- true
- Replacements
- Replacements
- false
- 0
-
9223
-10736
81
20
-
9263.5
-10726
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 36b3a4ab-79e8-4ae2-bcf6-59f01b423655
- true
- Items
- Items
- false
- 0
-
9328
-10756
30
20
-
9343
-10746
- Number of items replaced
- f2ac4a82-0586-43fd-ac95-daa25658f827
- true
- Count
- Count
- false
- 0
-
9328
-10736
30
20
-
9343
-10726
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 55a89bb9-1cb3-4508-a64e-593c4f56d389
- true
- Relay
- false
- d8ad52e1-09c5-4d42-8086-8d7eedd452d8
- 1
-
9271
-10695
40
16
-
9291
-10687
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7054797c-3a92-4321-8597-127654b4ca6c
- true
- Relay
- false
- 95512bec-3e3b-4a1e-968f-fdd54a0ed3fb
- 1
-
9271
-11059
40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- d78b1c8d-4c32-45a1-9cd0-3f1c128e80c8
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- a7355444-5015-436e-931d-6d44c0532770
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- dc265006-688d-45d2-a2b8-861a06b4a669
- true
- Curve Closest Point
- Curve Closest Point
-
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108
64
-
9281
-10527
- Point to project onto curve
- 59eb5142-8d20-4b58-9832-b73d38c01f5e
- true
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- Point
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9239
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30
30
-
9254
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- Curve to project onto
- 4e26aed9-39d5-4a12-91ee-5be2f0b044cb
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-10527
30
30
-
9254
-10512
- Point on the curve closest to the base point
- 40443f53-c592-445e-a339-a109be0a51bb
- true
- Point
- Point
- false
- 0
-
9293
-10557
50
20
-
9318
-10547
- Parameter on curve domain of closest point
- a0713c1c-c26e-441e-93b3-f8edf5c233b2
- true
- Parameter
- Parameter
- false
- 0
-
9293
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50
20
-
9318
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- Distance between base point and curve
- b2882fd2-b8b7-4172-8f26-363ace0aa2a4
- true
- Distance
- Distance
- false
- 0
-
9293
-10517
50
20
-
9318
-10507
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- a4a2e4fe-4294-43c1-8033-d508439ba3f1
- true
- Line
- Line
-
9240
-10638
102
44
-
9306
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- Line start point
- 223c6b86-f150-4be0-be87-6066ca661b45
- true
- Start Point
- Start Point
- false
- 40443f53-c592-445e-a339-a109be0a51bb
- 1
-
9242
-10636
52
20
-
9268
-10626
- Line end point
- 9b417723-48ba-4f1a-a0a5-971d61bf310e
- true
- End Point
- End Point
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9242
-10616
52
20
-
9268
-10606
- Line segment
- 509ce120-a6c6-472d-a7ba-325df3973ff0
- true
- Line
- Line
- false
- 0
-
9318
-10636
22
40
-
9329
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- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
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- true
- Remap Numbers
- Remap Numbers
-
9214
-11889
154
64
-
9314
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- Value to remap
- 4388d5aa-717b-4e61-958d-f0267b4a896b
- true
- Value
- Value
- false
- ef3c8bc1-7cba-4c60-9fcc-d378b603bd10
- 1
-
9216
-11887
86
20
-
9259
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- Source domain
- 6255db04-e743-411d-bd22-b9b95f602d3c
- true
- Source
- Source
- false
- 94bf725f-3745-4e94-93fa-23d17c538a20
- 1
-
9216
-11867
86
20
-
9259
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- 1
- 1
- {0}
-
0
1
- Target domain
- 5c9dd6aa-a9b2-4bb6-bf8c-c95a44b4a77b
- true
- Target
- Target
- false
- 0
-
9216
-11847
86
20
-
9259
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- 1
- 1
- {0}
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-1
1
- Remapped number
- 7fde5602-5527-4b53-9098-bc2f764c30ec
- true
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- 0
-
9326
-11887
40
30
-
9346
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- Remapped and clipped number
- c83d928d-275e-4779-8baf-744d80d2b95e
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- false
- 0
-
9326
-11857
40
30
-
9346
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- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 8c5b608e-fe4b-4be4-ae7d-a2f8720579a9
- true
- Bounds
- Bounds
-
9236
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110
28
-
9294
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- 1
- Numbers to include in Bounds
- fc76b9e6-26e3-4e91-b5a1-e62e80c88332
- true
- Numbers
- Numbers
- false
- ef3c8bc1-7cba-4c60-9fcc-d378b603bd10
- 1
-
9238
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44
24
-
9260
-11793
- Numeric Domain between the lowest and highest numbers in {N}
- 94bf725f-3745-4e94-93fa-23d17c538a20
- true
- Domain
- Domain
- false
- 0
-
9306
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38
24
-
9325
-11793
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- ef3c8bc1-7cba-4c60-9fcc-d378b603bd10
- true
- Relay
-
- false
- 7054797c-3a92-4321-8597-127654b4ca6c
- 1
-
9271
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40
16
-
9291
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 7b233811-8adf-47e6-9487-409c1062dec0
- true
- Evaluate Length
- Evaluate Length
-
9216
-13891
149
64
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9301
-13859
- Curve to evaluate
- 3ba71f4d-c6e6-488f-b9dd-2c03ba6069ba
- true
- Curve
- Curve
- false
- 371443ac-3136-42c3-8360-f83d4c4c61ed
- 1
-
9218
-13889
71
20
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9253.5
-13879
- Length factor for curve evaluation
- 855c025c-5286-44a9-a0a4-0c354b5e7bb8
- true
- Length
- Length
- false
- 0
-
9218
-13869
71
20
-
9253.5
-13859
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 038af75f-2a62-499e-a4b2-3c06ef0bfa9a
- true
- Normalized
- Normalized
- false
- 0
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9218
-13849
71
20
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9253.5
-13839
- 1
- 1
- {0}
- true
- Point at the specified length
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- true
- Point
- Point
- false
- 0
-
9313
-13889
50
20
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9338
-13879
- Tangent vector at the specified length
- 17de63ad-5524-45df-8781-f5ead83a2f49
- true
- Tangent
- Tangent
- false
- 0
-
9313
-13869
50
20
-
9338
-13859
- Curve parameter at the specified length
- fc254605-90a0-4a19-a769-ae1d5782ef45
- true
- Parameter
- Parameter
- false
- 0
-
9313
-13849
50
20
-
9338
-13839
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- f61e5a6d-a81d-45cf-a7d9-36b9d5fab315
- true
- Line SDL
- Line SDL
-
9236
-15757
110
64
-
9310
-15725
- Line start point
- 4c0b0d3c-c86a-4490-96a1-f64f940d644e
- true
- Start
- Start
- false
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9238
-15755
60
20
-
9276
-15745
- Line tangent (direction)
- 859e964a-4ec0-48de-9c45-4b6c6cf6d6cb
- true
- Direction
- Direction
- false
- a43ca145-0b7a-4245-a9fd-9ee3155f0628
- 1
-
9238
-15735
60
20
-
9276
-15725
- 1
- 1
- {0}
-
0
0
1
- Line length
- 0cd5a2e9-100e-4e88-a8be-29455a703651
- ABS(X)
- true
- Length
- Length
- false
- 25faccb1-b1d4-451a-8577-baa88375614a
- 1
-
9238
-15715
60
20
-
9276
-15705
- 1
- 1
- {0}
- 0.015625
- Line segment
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- true
- Line
- Line
- false
- 0
-
9322
-15755
22
60
-
9333
-15725
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 5f35fc89-309b-4e17-88a9-16b8cfb9fabb
- true
- Relative Differences
- Relative Differences
-
9233
-14234
116
28
-
9280
-14220
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 5e22cf88-33d8-4bad-930c-c1a842b9fc93
- true
- Values
- Values
- false
- 472f4653-0d63-489f-aa1e-78a685ed3cd5
- 1
-
9235
-14232
33
24
-
9251.5
-14220
- 1
- Differences between consecutive items
- 72af1623-98b2-41a3-b5a9-7e1bda1d7111
- true
- Differenced
- Differenced
- false
- 0
-
9292
-14232
55
24
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9319.5
-14220
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 2e7e46e0-8bb4-4ff2-bc33-167650346f6e
- true
- Replace Nulls
- Replace Nulls
-
9221
-14178
139
44
-
9316
-14156
- 1
- Items to test for null
- aa88ba3d-75ba-449c-b1af-976060979fcf
- true
- Items
- Items
- false
- 25c15167-43ce-4ca0-b325-c34d67039fe4
- 1
-
9223
-14176
81
20
-
9263.5
-14166
- 1
- Items to replace nulls with
- 2b4280b4-b88d-4417-a5c2-cd0b4441600d
- true
- Replacements
- Replacements
- false
- 0
-
9223
-14156
81
20
-
9263.5
-14146
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 472f4653-0d63-489f-aa1e-78a685ed3cd5
- true
- Items
- Items
- false
- 0
-
9328
-14176
30
20
-
9343
-14166
- Number of items replaced
- 0721411f-5db7-4c73-913e-6c87d11faa2e
- true
- Count
- Count
- false
- 0
-
9328
-14156
30
20
-
9343
-14146
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 25c15167-43ce-4ca0-b325-c34d67039fe4
- true
- Relay
- false
- 7054797c-3a92-4321-8597-127654b4ca6c
- 1
-
9271
-14115
40
16
-
9291
-14107
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- bfc69fd4-c68c-40ea-b4e6-b6f9c5550d3e
- true
- Relay
- false
- 5fcafa9d-43c7-4d8e-b1fa-7217ab260d93
- 1
-
9271
-14479
40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 5f35fc89-309b-4e17-88a9-16b8cfb9fabb
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- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- b9c7f1c6-2f5e-4c3d-b929-a89603c04f14
- true
- Curve Closest Point
- Curve Closest Point
-
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108
64
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9281
-13947
- Point to project onto curve
- eb35bf93-9f3b-47cb-88b9-37c7e236dd69
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- Point
- Point
- false
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9239
-13977
30
30
-
9254
-13962
- Curve to project onto
- db893065-426f-4a58-92a7-236e0193d82c
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-13947
30
30
-
9254
-13932
- Point on the curve closest to the base point
- 2d839212-b8d4-4812-98d8-b6368d1ce218
- true
- Point
- Point
- false
- 0
-
9293
-13977
50
20
-
9318
-13967
- Parameter on curve domain of closest point
- 3c21d431-d450-4778-9e83-e0e5c534de56
- true
- Parameter
- Parameter
- false
- 0
-
9293
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50
20
-
9318
-13947
- Distance between base point and curve
- 8ee23322-d45f-45c7-a334-0d6117e065d5
- true
- Distance
- Distance
- false
- 0
-
9293
-13937
50
20
-
9318
-13927
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- e95f78aa-eafb-4329-9993-de6cbe543737
- true
- Line
- Line
-
9240
-14058
102
44
-
9306
-14036
- Line start point
- 85df0df4-eafa-4d92-af84-501c0c3f6b89
- true
- Start Point
- Start Point
- false
- 2d839212-b8d4-4812-98d8-b6368d1ce218
- 1
-
9242
-14056
52
20
-
9268
-14046
- Line end point
- 4f8840e6-cde4-4eeb-82fd-27ff532598eb
- true
- End Point
- End Point
- false
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9242
-14036
52
20
-
9268
-14026
- Line segment
- a43ca145-0b7a-4245-a9fd-9ee3155f0628
- true
- Line
- Line
- false
- 0
-
9318
-14056
22
40
-
9329
-14036
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 659f6427-1e0c-4b4a-b76b-5960c7fe394d
- true
- Remap Numbers
- Remap Numbers
-
9214
-15455
154
64
-
9314
-15423
- Value to remap
- babfbfbd-b943-43e7-94d0-48b810e96707
- true
- Value
- Value
- false
- b1f209e2-7620-47ec-8679-406efde82380
- 1
-
9216
-15453
86
20
-
9259
-15443
- Source domain
- 7e5a984f-1c76-4f46-9bac-02510837c41c
- true
- Source
- Source
- false
- d6f9116b-a2e0-49bb-840d-45e874d72f8e
- 1
-
9216
-15433
86
20
-
9259
-15423
- 1
- 1
- {0}
-
0
1
- Target domain
- aaa645f7-2720-4872-bd9c-becfeabba234
- true
- Target
- Target
- false
- 0
-
9216
-15413
86
20
-
9259
-15403
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 1470d22a-da01-48d1-9419-1724f78ad190
- true
- Mapped
- Mapped
- false
- 0
-
9326
-15453
40
30
-
9346
-15438
- Remapped and clipped number
- 6942278c-6594-4d60-9732-8e188c38310c
- true
- Clipped
- Clipped
- false
- 0
-
9326
-15423
40
30
-
9346
-15408
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 8999696a-74f0-4557-97f6-38fc25e0e737
- true
- Bounds
- Bounds
-
9236
-15373
110
28
-
9294
-15359
- 1
- Numbers to include in Bounds
- d965d7d1-9aee-406b-93c4-18f3199264c5
- true
- Numbers
- Numbers
- false
- b1f209e2-7620-47ec-8679-406efde82380
- 1
-
9238
-15371
44
24
-
9260
-15359
- Numeric Domain between the lowest and highest numbers in {N}
- d6f9116b-a2e0-49bb-840d-45e874d72f8e
- true
- Domain
- Domain
- false
- 0
-
9306
-15371
38
24
-
9325
-15359
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- b1f209e2-7620-47ec-8679-406efde82380
- true
- Relay
-
- false
- bfc69fd4-c68c-40ea-b4e6-b6f9c5550d3e
- 1
-
9271
-15326
40
16
-
9291
-15318
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 2dbc970d-71e3-4f0d-8142-558c895fcd12
- true
- Multiplication
- Multiplication
-
9256
-15654
70
44
-
9281
-15632
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- a4c5348c-e748-41ef-98ab-8ce70441ac52
- true
- A
- A
- true
- 6a969140-0075-4523-a327-0427abb39edd
- 1
-
9258
-15652
11
20
-
9263.5
-15642
- Second item for multiplication
- a60361f7-90d9-488c-8408-62be9d12b55a
- true
- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9258
-15632
11
20
-
9263.5
-15622
- Result of multiplication
- 25faccb1-b1d4-451a-8577-baa88375614a
- true
- Result
- Result
- false
- 0
-
9293
-15652
31
40
-
9308.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 2b0c3eae-72c9-4057-a9f2-0b7a17dbdaaa
- true
- Multiplication
- Multiplication
-
9256
-15526
70
44
-
9281
-15504
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- d84fe2b4-a233-4c1f-b392-fb3a114b2e59
- true
- A
- A
- true
- 5828018c-2ca6-4a08-80ec-15d609092e7a
- 1
-
9258
-15524
11
20
-
9263.5
-15514
- Second item for multiplication
- 7f19a3fd-9268-4d35-923b-1f1b4d34063d
- true
- B
- B
- true
- 1470d22a-da01-48d1-9419-1724f78ad190
- 1
-
9258
-15504
11
20
-
9263.5
-15494
- Result of multiplication
- 6a969140-0075-4523-a327-0427abb39edd
- true
- Result
- Result
- false
- 0
-
9293
-15524
31
40
-
9308.5
-15504
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 5828018c-2ca6-4a08-80ec-15d609092e7a
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- Relay
- false
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-
9271
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40
16
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9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 659f6427-1e0c-4b4a-b76b-5960c7fe394d
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- b1f209e2-7620-47ec-8679-406efde82380
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- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- d6599ced-fd64-4798-b31a-cfa70f5fa710
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- Group
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- Panel
- A panel for custom notes and text values
- cc56ef11-96b9-4530-972f-8cbc81a613c9
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- 3d034f31-d797-4424-8cef-9499e7099fc1
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- Double click to edit panel content…
-
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185
271
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9205.633
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255;255;255;255
- true
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- Relay
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- A wire relay object
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-
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- cc56ef11-96b9-4530-972f-8cbc81a613c9
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-
9271
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40
16
-
9291
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- e9df2d08-5a93-4bb4-9361-d5b6b5a545a5
- true
- Relay
-
- false
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-
9271
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40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 07602edd-99d6-4400-93a3-3b8afb259584
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- Group
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
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- Create Material
- Create Material
-
9215
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152
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9313
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- Colour of the diffuse channel
- 88a35608-9071-40f7-a0b5-6328887e6dde
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- 0
-
9217
-16475
84
20
-
9259
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- 1
- 1
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255;236;236;236
- Colour of the specular highlight
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9217
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84
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9259
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255;0;255;255
- Emissive colour of the material
- 3c4de844-d373-4abb-bfa6-d5934b78fb76
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9217
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84
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9259
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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9217
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84
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9259
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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9217
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84
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9259
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- Resulting material
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100
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
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- Allows for customized geometry previews
- true
- true
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- Custom Preview
- Custom Preview
-
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76
44
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- Geometry to preview
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- The material override
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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149
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- Curve to evaluate
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9218
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- Length factor for curve evaluation
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- Length
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- 0
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9218
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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9218
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71
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-
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- Tangent vector at the specified length
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9313
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50
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- Create an interpolated curve through a set of points.
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- Interpolate
- Interpolate
-
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- Curve degree
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159
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9180
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159
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9259.5
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- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
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9180
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159
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9259.5
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- Resulting nurbs curve
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38
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- Create an OpenGL material.
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152
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84
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- Colour of the specular highlight
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9217
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84
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9259
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255;0;255;255
- Emissive colour of the material
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9217
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9259
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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9259
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84
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9325
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100
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- Allows for customized geometry previews
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76
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9255
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48
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9279
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Display a set of y-values as a graph
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150
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255;255;255;255
- A group of Grasshopper objects
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- Explode a curve into smaller segments.
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57
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9254.5
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- Exploded segments that make up the base curve
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9307
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49
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
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9216
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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9218
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71
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9253.5
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9218
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71
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50
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- Line SDL
- Line SDL
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- Line start point
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60
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22
60
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- Replace nulls or invalid data with other data
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139
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81
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- Items to replace nulls with
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9223
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81
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9263.5
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- List without any nulls
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30
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9343
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30
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- A wire relay object
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40
16
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- Relay
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40
16
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255;255;255;255
- A group of Grasshopper objects
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- Find the closest point on a curve.
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108
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- Point to project onto curve
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30
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- Curve to project onto
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- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 09024d99-a87c-4956-b0e1-7bc86894ca46
- true
- Quick Graph
- Quick Graph
- false
- 0
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9223
-18980
150
150
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9223.633
-18980
- -1
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- b5568a68-fe32-424e-8c33-57bdb7be33cd
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- 6fae5acb-1d7f-46ec-a1bd-b4f0011792bd
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- 05be53c1-a657-4588-ae4a-a119edd7ca8d
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- b5568a68-fe32-424e-8c33-57bdb7be33cd
- true
- Explode
- Explode
-
9224
-21025
134
44
-
9295
-21003
- Curve to explode
- c96c9a02-1f26-40a5-9026-8ac73a753ab8
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- Curve
- Curve
- false
- 92df9f80-016f-455d-a9c3-bbe35cffa3bc
- 1
-
9226
-21023
57
20
-
9254.5
-21013
- Recursive decomposition until all segments are atomic
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- true
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- 0
-
9226
-21003
57
20
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9254.5
-20993
- 1
- 1
- {0}
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- 1
- Exploded segments that make up the base curve
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9307
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49
20
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9331.5
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- 1
- Vertices of the exploded segments
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- Vertices
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- 0
-
9307
-21003
49
20
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9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 6f1a677f-deb5-4ba0-84a4-eebb8827de33
- true
- Evaluate Length
- Evaluate Length
-
9216
-21108
149
64
-
9301
-21076
- Curve to evaluate
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- Curve
- Curve
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-
9218
-21106
71
20
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9253.5
-21096
- Length factor for curve evaluation
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- true
- Length
- Length
- false
- 0
-
9218
-21086
71
20
-
9253.5
-21076
- 1
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
- Normalized
- Normalized
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- 0
-
9218
-21066
71
20
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9253.5
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- 1
- 1
- {0}
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- Point at the specified length
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- Point
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- 0
-
9313
-21106
50
20
-
9338
-21096
- Tangent vector at the specified length
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- Tangent
- Tangent
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-
9313
-21086
50
20
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9338
-21076
- Curve parameter at the specified length
- 1e9137ad-19c0-44de-93b0-ed22758d1b72
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- Parameter
- Parameter
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-
9313
-21066
50
20
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9338
-21056
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9236
-22902
110
64
-
9310
-22870
- Line start point
- cccde99e-d1bb-42cb-9308-b60adc13598e
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- Start
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- 1
-
9238
-22900
60
20
-
9276
-22890
- Line tangent (direction)
- 8d269f2f-2e46-408a-b010-ea591ec9a0cd
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- Direction
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-
9238
-22880
60
20
-
9276
-22870
- 1
- 1
- {0}
-
0
0
1
- Line length
- 10f261f6-bdba-47f2-88ae-420dc21f40c9
- ABS(X)
- true
- Length
- Length
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- 1
-
9238
-22860
60
20
-
9276
-22850
- 1
- 1
- {0}
- 0.015625
- Line segment
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- true
- Line
- Line
- false
- 0
-
9322
-22900
22
60
-
9333
-22870
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 865c8066-5247-4b0a-96a1-4424156c0cb8
- true
- Relative Differences
- Relative Differences
-
9233
-21451
116
28
-
9280
-21437
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 22bbf386-4b21-4caa-b85a-18d67d6107e9
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- Values
- Values
- false
- 5be97c92-8ae7-4d99-a8a3-607079460d5e
- 1
-
9235
-21449
33
24
-
9251.5
-21437
- 1
- Differences between consecutive items
- f3da83a8-552c-4482-9825-f165df6fa732
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- Differenced
- Differenced
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- 0
-
9292
-21449
55
24
-
9319.5
-21437
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- dc8e38ea-6a83-4745-9d49-e94867a156af
- true
- Replace Nulls
- Replace Nulls
-
9221
-21395
139
44
-
9316
-21373
- 1
- Items to test for null
- 8156fbf8-f136-40c5-b535-ed951f9d17f7
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- Items
- Items
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- 362fefaa-7013-4c74-8cf7-e74beaf18bce
- 1
-
9223
-21393
81
20
-
9263.5
-21383
- 1
- Items to replace nulls with
- 5e913941-5ebb-4f96-9c6d-9694825347d8
- true
- Replacements
- Replacements
- false
- 0
-
9223
-21373
81
20
-
9263.5
-21363
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 5be97c92-8ae7-4d99-a8a3-607079460d5e
- true
- Items
- Items
- false
- 0
-
9328
-21393
30
20
-
9343
-21383
- Number of items replaced
- 2f70f5c7-6a5d-4968-9d65-4ba70ef85dca
- true
- Count
- Count
- false
- 0
-
9328
-21373
30
20
-
9343
-21363
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 362fefaa-7013-4c74-8cf7-e74beaf18bce
- true
- Relay
- false
- 0928c206-a25e-4834-9a06-eb4c248c6ef7
- 1
-
9271
-21332
40
16
-
9291
-21324
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- bced28c6-c3d6-4c77-97c8-51f4de83d178
- true
- Relay
- false
- f63f83de-17f7-454a-bc36-895bc7488c7e
- 1
-
9271
-21696
40
16
-
9291
-21688
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 096e1e94-cef1-45dd-9170-91b3022799a9
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-21196
108
64
-
9281
-21164
- Point to project onto curve
- bf711b90-da21-4a31-83ef-a5fae2b85980
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- Point
- Point
- false
- c117a95c-6877-440a-be04-f9bf41059d4b
- 1
-
9239
-21194
30
30
-
9254
-21179
- Curve to project onto
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- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-21164
30
30
-
9254
-21149
- Point on the curve closest to the base point
- 26daa500-5e3a-4c10-b67b-5c34dbb5336e
- true
- Point
- Point
- false
- 0
-
9293
-21194
50
20
-
9318
-21184
- Parameter on curve domain of closest point
- 2457c44a-4724-4030-877f-29aa2ae799f0
- true
- Parameter
- Parameter
- false
- 0
-
9293
-21174
50
20
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9318
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- Distance between base point and curve
- c0d86339-7732-4312-a9a6-a9647a257181
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- Distance
- Distance
- false
- 0
-
9293
-21154
50
20
-
9318
-21144
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 1691d791-4089-4e1a-b6a9-744569a38353
- true
- Line
- Line
-
9240
-21275
102
44
-
9306
-21253
- Line start point
- 70841617-86dd-46b4-a70d-871f1e7eb6d5
- true
- Start Point
- Start Point
- false
- 26daa500-5e3a-4c10-b67b-5c34dbb5336e
- 1
-
9242
-21273
52
20
-
9268
-21263
- Line end point
- 8a193f72-6e7c-4093-a705-db8675e7aa97
- true
- End Point
- End Point
- false
- c117a95c-6877-440a-be04-f9bf41059d4b
- 1
-
9242
-21253
52
20
-
9268
-21243
- Line segment
- 9b8925fa-9a9d-4705-8727-ff9576da78bc
- true
- Line
- Line
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- 0
-
9318
-21273
22
40
-
9329
-21253
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- a1441e70-b9c0-4e1f-8831-9ef3c2ef0635
- true
- Remap Numbers
- Remap Numbers
-
9214
-22600
154
64
-
9314
-22568
- Value to remap
- cad3e760-fb48-4120-9d69-67f35f3611ad
- true
- Value
- Value
- false
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- 1
-
9216
-22598
86
20
-
9259
-22588
- Source domain
- b3b78e1b-c8d1-4754-b6fa-ff02d55ecc97
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- Source
- Source
- false
- 530027ad-30c9-438e-8038-d5cadaa47365
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9216
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86
20
-
9259
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- 1
- 1
- {0}
-
0
1
- Target domain
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- Target
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- 0
-
9216
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86
20
-
9259
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- 1
- 1
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-1
1
- Remapped number
- 74f8d46b-5e69-4fb0-8e31-ece17f0b35f6
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-
9326
-22598
40
30
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9346
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- Remapped and clipped number
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- 0
-
9326
-22568
40
30
-
9346
-22553
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- e3b23a7d-af34-4738-bc62-f9f3409c8db3
- true
- Bounds
- Bounds
-
9236
-22518
110
28
-
9294
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- 1
- Numbers to include in Bounds
- beb8a25a-99b8-4e6f-b2e8-7ea93528c19d
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- Numbers
- Numbers
- false
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- 1
-
9238
-22516
44
24
-
9260
-22504
- Numeric Domain between the lowest and highest numbers in {N}
- 530027ad-30c9-438e-8038-d5cadaa47365
- true
- Domain
- Domain
- false
- 0
-
9306
-22516
38
24
-
9325
-22504
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- true
- Relay
-
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-
9271
-22471
40
16
-
9291
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
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- true
- Multiplication
- Multiplication
-
9256
-22799
70
44
-
9281
-22777
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- d88e451c-a221-4a3c-bb80-172596ebe09f
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- A
- A
- true
- f4a5a11b-11a6-4bd1-bad5-e11c598ba2ee
- 1
-
9258
-22797
11
20
-
9263.5
-22787
- Second item for multiplication
- b35a5238-7c06-430d-822d-ed17cada8dd5
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- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9258
-22777
11
20
-
9263.5
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- Result of multiplication
- 47728caf-51cd-404e-8626-f3bf6658ad3e
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- 0
-
9293
-22797
31
40
-
9308.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 3ccaaeb7-75c9-4925-99f4-b7474381c81c
- true
- Multiplication
- Multiplication
-
9256
-22692
70
44
-
9281
-22670
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 2e7c606c-8fa0-4a11-862c-21f4feb71673
- true
- A
- A
- true
- 9264f0ff-aad0-4d8f-9480-080924b6c884
- 1
-
9258
-22690
11
20
-
9263.5
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- Second item for multiplication
- ca71652b-8a23-4fd1-ba1a-4ab427df4118
- true
- B
- B
- true
- 74f8d46b-5e69-4fb0-8e31-ece17f0b35f6
- 1
-
9258
-22670
11
20
-
9263.5
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- Result of multiplication
- f4a5a11b-11a6-4bd1-bad5-e11c598ba2ee
- true
- Result
- Result
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- 0
-
9293
-22690
31
40
-
9308.5
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 9264f0ff-aad0-4d8f-9480-080924b6c884
- true
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- 1a924b4b-4576-4ca9-9ace-b4586f3dbb90
- 1
-
9271
-22627
40
16
-
9291
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a1441e70-b9c0-4e1f-8831-9ef3c2ef0635
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60
20
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0
0
1
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60
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22
60
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33
24
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139
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81
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- Items to replace nulls with
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81
20
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- List without any nulls
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30
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- Number of items replaced
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30
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40
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40
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255;255;255;255
- A group of Grasshopper objects
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- Find the closest point on a curve.
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- Point to project onto curve
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30
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- Curve to project onto
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30
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- Point on the curve closest to the base point
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50
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- Parameter on curve domain of closest point
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- Line end point
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52
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- Line segment
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- Remap Numbers
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- Value to remap
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- Source domain
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86
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40
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- Remapped and clipped number
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40
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- Create a numeric domain which encompasses a list of numbers.
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- Numbers to include in Bounds
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44
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- Numeric Domain between the lowest and highest numbers in {N}
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38
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- Relay
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- A wire relay object
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- Mathematical multiplication
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11
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- Second item for multiplication
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11
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11
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31
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255;255;255;255
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255;255;255;255
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Length factor for curve evaluation
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- Tangent vector at the specified length
- d4ad06af-261d-480c-9b76-80b8b35af349
- true
- Tangent
- Tangent
- false
- 0
-
9313
-27149
50
20
-
9338
-27139
- Curve parameter at the specified length
- c971b7a0-0366-4c4c-9464-7f4df888cb5a
- true
- Parameter
- Parameter
- false
- 0
-
9313
-27129
50
20
-
9338
-27119
- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- 8fa8d1cd-72e4-49a9-ac87-2091af68c9c5
- true
- Interpolate
- Interpolate
-
9178
-27547
225
84
-
9351
-27505
- 1
- Interpolation points
- 1503e6d5-6140-42c5-a21b-4dba42363436
- true
- Vertices
- Vertices
- false
- 9e6fc360-1810-4da7-a170-2f0668ae3de2
- 1
-
9180
-27545
159
20
-
9259.5
-27535
- Curve degree
- 5f85b622-d830-4a07-bff0-f8530b2c4a57
- true
- Degree
- Degree
- false
- 0
-
9180
-27525
159
20
-
9259.5
-27515
- 1
- 1
- {0}
- 1
- Periodic curve
- 58ad891d-4a3c-47c1-9618-6af0908ce9a4
- true
- Periodic
- Periodic
- false
- 0
-
9180
-27505
159
20
-
9259.5
-27495
- 1
- 1
- {0}
- false
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- 388ab5d7-428d-418b-90c0-96bd92120498
- true
- KnotStyle
- KnotStyle
- false
- 0
-
9180
-27485
159
20
-
9259.5
-27475
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- ff468b81-65e8-4cdf-b877-b88d817f1f2d
- true
- Curve
- Curve
- false
- 0
-
9363
-27545
38
26
-
9382
-27531.67
- Curve length
- bea94d63-6267-4a46-a8cc-af7392801828
- true
- Length
- Length
- false
- 0
-
9363
-27519
38
27
-
9382
-27505
- Curve domain
- dd30a448-ca31-4e64-90d5-cc9c40a7c8b3
- true
- Domain
- Domain
- false
- 0
-
9363
-27492
38
27
-
9382
-27478.33
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 5124b1bb-140f-4743-8c53-2e30544ed43f
- true
- Create Material
- Create Material
-
9215
-27674
152
104
-
9313
-27622
- Colour of the diffuse channel
- cc1605ca-daf4-460a-b0a4-67130800bed4
- true
- Diffuse
- Diffuse
- false
- 0
-
9217
-27672
84
20
-
9259
-27662
- 1
- 1
- {0}
-
255;199;199;199
- Colour of the specular highlight
- 626b5cae-5f16-4066-9743-736557a29475
- true
- Specular
- Specular
- false
- 0
-
9217
-27652
84
20
-
9259
-27642
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 5869d24e-a5b5-410d-82a1-847611623bed
- true
- Emission
- Emission
- false
- 0
-
9217
-27632
84
20
-
9259
-27622
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 3b1b263e-3d61-47b4-95c4-821fcef67b0b
- true
- Transparency
- Transparency
- false
- 0
-
9217
-27612
84
20
-
9259
-27602
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- d4f5488e-4a4f-4c05-a6b7-8bd31d59b4c7
- true
- Shine
- Shine
- false
- 0
-
9217
-27592
84
20
-
9259
-27582
- 1
- 1
- {0}
- 100
- Resulting material
- 1bed5aa6-f478-4993-a204-8cfa72a07424
- true
- Material
- Material
- false
- 0
-
9325
-27672
40
100
-
9345
-27622
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- c4521450-b023-4163-9d6b-30e587776f8e
- true
- Custom Preview
- Custom Preview
-
9253
-27740
76
44
-
9315
-27718
- Geometry to preview
- true
- 472a7ba1-052c-4737-85e3-2e7db5b49ee0
- true
- Geometry
- Geometry
- false
- ff468b81-65e8-4cdf-b877-b88d817f1f2d
- 1
-
9255
-27738
48
20
-
9279
-27728
- The material override
- 2808fa60-8978-4b6d-ae88-09a8be1d2563
- true
- Material
- Material
- false
- 1bed5aa6-f478-4993-a204-8cfa72a07424
- 1
-
9255
-27718
48
20
-
9279
-27708
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- fd00589e-5724-4407-aa46-ebe1d9f1b38d
- true
- Quick Graph
- Quick Graph
- false
- 0
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9223
-25917
150
150
-
9223.633
-25917
- -1
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- e55852e6-434c-4d81-ab8c-e702dfd1db4f
- e41c1b6a-7e1e-47d5-ab71-6b7f6f04b606
- 444edb66-366a-4115-b54d-07922398f854
- f6594335-7ff6-4c1e-aeb7-c9c8948883d4
- fd47e2e2-6481-4a34-a847-a0d1a632bc53
- 99c7fe47-7a69-4ff0-8cd8-12aa4d14e36a
- 729637d9-ea91-4c07-8b5a-52ac9c43759a
- a189e3aa-b04e-41b2-af57-783026734fbd
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- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
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- e555088f-a229-4d25-a883-c447edfca1c2
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- ba7905ed-fef6-48c1-8baf-dc7e08645b2a
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- 8fe511eb-1233-498f-a8f7-d34dd4f617ff
- 158188ab-8318-49ab-bbb3-3b4c147e50a1
- 1529fdbf-9759-4d95-a555-19007f500439
- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1ffd60e1-d5b8-48d2-85e8-77a63ab7786b
- 943c2602-b35d-4dea-b150-9f279be49248
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- 56934943-a19b-4a05-becd-bb3668f0a912
- 607e639e-e8c3-4263-aa73-c9a6384689bc
- 5bd5d6db-12a2-4550-8b71-deb45f3888b0
- 5f214b8c-7d05-4368-8735-afd3d68a4fce
- 87aee7ec-7851-4cc6-8c7c-6d39908c9364
- 33
- a6960d2a-4824-4efb-81eb-96c9415b7919
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- e55852e6-434c-4d81-ab8c-e702dfd1db4f
- true
- Explode
- Explode
-
9224
-27877
134
44
-
9295
-27855
- Curve to explode
- fde358cc-c101-4588-9436-44d67db87bad
- true
- Curve
- Curve
- false
- ff468b81-65e8-4cdf-b877-b88d817f1f2d
- 1
-
9226
-27875
57
20
-
9254.5
-27865
- Recursive decomposition until all segments are atomic
- 4ce8a128-9d38-4d5f-a8bf-02afc1631152
- true
- Recursive
- Recursive
- false
- 0
-
9226
-27855
57
20
-
9254.5
-27845
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- cfe0de88-5b8a-4ce6-9bc2-9c9bfa54cc0b
- true
- Segments
- Segments
- false
- 0
-
9307
-27875
49
20
-
9331.5
-27865
- 1
- Vertices of the exploded segments
- 551c18cf-2aef-4fe0-a831-c8f2defa03b1
- true
- Vertices
- Vertices
- false
- 0
-
9307
-27855
49
20
-
9331.5
-27845
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e41c1b6a-7e1e-47d5-ab71-6b7f6f04b606
- true
- Evaluate Length
- Evaluate Length
-
9216
-27960
149
64
-
9301
-27928
- Curve to evaluate
- 3b337348-6b71-448c-900a-d9054ef19368
- true
- Curve
- Curve
- false
- cfe0de88-5b8a-4ce6-9bc2-9c9bfa54cc0b
- 1
-
9218
-27958
71
20
-
9253.5
-27948
- Length factor for curve evaluation
- 652c5ab2-febc-4340-94df-6611e53df831
- true
- Length
- Length
- false
- 0
-
9218
-27938
71
20
-
9253.5
-27928
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 9ec37965-bbaa-472e-adc1-1aa463e2e77f
- true
- Normalized
- Normalized
- false
- 0
-
9218
-27918
71
20
-
9253.5
-27908
- 1
- 1
- {0}
- true
- Point at the specified length
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- true
- Point
- Point
- false
- 0
-
9313
-27958
50
20
-
9338
-27948
- Tangent vector at the specified length
- ed55b185-60fb-40cd-ad46-0842867be581
- true
- Tangent
- Tangent
- false
- 0
-
9313
-27938
50
20
-
9338
-27928
- Curve parameter at the specified length
- a5197d5c-aa87-4482-aaba-20779b7b231e
- true
- Parameter
- Parameter
- false
- 0
-
9313
-27918
50
20
-
9338
-27908
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 444edb66-366a-4115-b54d-07922398f854
- true
- Line SDL
- Line SDL
-
9236
-29740
110
64
-
9310
-29708
- Line start point
- 71f5a683-8e56-4a2f-81f8-5f9808eddf57
- true
- Start
- Start
- false
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9238
-29738
60
20
-
9276
-29728
- Line tangent (direction)
- ec34afb2-cc43-4614-b556-168228e82c6d
- true
- Direction
- Direction
- false
- be3b8f9c-1ae0-439a-bdb8-a5dd226cecc3
- 1
-
9238
-29718
60
20
-
9276
-29708
- 1
- 1
- {0}
-
0
0
1
- Line length
- 45490cfc-ec73-4dfd-a9b5-496410006025
- ABS(X)
- true
- Length
- Length
- false
- 139422c8-a710-487e-bbe0-ea2b6259e8e1
- 1
-
9238
-29698
60
20
-
9276
-29688
- 1
- 1
- {0}
- 0.015625
- Line segment
- 1c102dcf-a427-4f9a-93eb-d8fa6673d9fa
- true
- Line
- Line
- false
- 0
-
9322
-29738
22
60
-
9333
-29708
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- f6594335-7ff6-4c1e-aeb7-c9c8948883d4
- true
- Relative Differences
- Relative Differences
-
9233
-28303
116
28
-
9280
-28289
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 043e55bf-142c-4061-bcd6-66fad571d11f
- true
- Values
- Values
- false
- 5f33bac4-8ad0-4ac6-a703-b653e22e896d
- 1
-
9235
-28301
33
24
-
9251.5
-28289
- 1
- Differences between consecutive items
- 2d37b54a-d252-4d91-af08-37f5c09e7e4a
- true
- Differenced
- Differenced
- false
- 0
-
9292
-28301
55
24
-
9319.5
-28289
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- fd47e2e2-6481-4a34-a847-a0d1a632bc53
- true
- Replace Nulls
- Replace Nulls
-
9221
-28247
139
44
-
9316
-28225
- 1
- Items to test for null
- bcfd659f-ade9-4f4d-b929-0f87d1db74db
- true
- Items
- Items
- false
- 9fba3251-1d1c-4127-a406-05630ef73176
- 1
-
9223
-28245
81
20
-
9263.5
-28235
- 1
- Items to replace nulls with
- a3f4d718-1001-4437-b607-f5fed9eff18a
- true
- Replacements
- Replacements
- false
- 0
-
9223
-28225
81
20
-
9263.5
-28215
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 5f33bac4-8ad0-4ac6-a703-b653e22e896d
- true
- Items
- Items
- false
- 0
-
9328
-28245
30
20
-
9343
-28235
- Number of items replaced
- 29929c88-87bc-4ed9-a28e-5f9a48da5860
- true
- Count
- Count
- false
- 0
-
9328
-28225
30
20
-
9343
-28215
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 9fba3251-1d1c-4127-a406-05630ef73176
- true
- Relay
- false
- ff917474-e27a-48ee-86c6-2399e98eb9b3
- 1
-
9271
-28184
40
16
-
9291
-28176
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
- true
- Relay
- false
- d57b5cda-0b57-4731-b527-b630d209be02
- 1
-
9271
-28548
40
16
-
9291
-28540
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- f6594335-7ff6-4c1e-aeb7-c9c8948883d4
- fd47e2e2-6481-4a34-a847-a0d1a632bc53
- 99c7fe47-7a69-4ff0-8cd8-12aa4d14e36a
- 729637d9-ea91-4c07-8b5a-52ac9c43759a
- a189e3aa-b04e-41b2-af57-783026734fbd
- 9fba3251-1d1c-4127-a406-05630ef73176
- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
- ff2559cf-18b3-4cad-b391-315893967bf2
- 8
- 2c7854ff-ba1a-4fcd-9046-0142fe519f22
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- e555088f-a229-4d25-a883-c447edfca1c2
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-28048
108
64
-
9281
-28016
- Point to project onto curve
- 2fc6035a-a04a-413f-baf6-93f6cb789341
- true
- Point
- Point
- false
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9239
-28046
30
30
-
9254
-28031
- Curve to project onto
- 36e46100-a361-4382-a21f-dd07040a60fa
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-28016
30
30
-
9254
-28001
- Point on the curve closest to the base point
- 22edc7d2-47d5-4d3c-a9fb-41003038da00
- true
- Point
- Point
- false
- 0
-
9293
-28046
50
20
-
9318
-28036
- Parameter on curve domain of closest point
- 679c843b-31f4-4e05-b990-e840a91b4713
- true
- Parameter
- Parameter
- false
- 0
-
9293
-28026
50
20
-
9318
-28016
- Distance between base point and curve
- 6fa34270-3ef8-41fd-a4a1-154817bd8fb9
- true
- Distance
- Distance
- false
- 0
-
9293
-28006
50
20
-
9318
-27996
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c157fa6a-b9b5-4759-829e-44e742af0c34
- true
- Line
- Line
-
9240
-28127
102
44
-
9306
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- Line start point
- 532c7d06-0798-454c-b064-4aa4fde692f2
- true
- Start Point
- Start Point
- false
- 22edc7d2-47d5-4d3c-a9fb-41003038da00
- 1
-
9242
-28125
52
20
-
9268
-28115
- Line end point
- 3e6668db-752b-441c-b990-86c413d3d4fc
- true
- End Point
- End Point
- false
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9242
-28105
52
20
-
9268
-28095
- Line segment
- be3b8f9c-1ae0-439a-bdb8-a5dd226cecc3
- true
- Line
- Line
- false
- 0
-
9318
-28125
22
40
-
9329
-28105
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 4bfb41bf-3699-4f84-abbf-207c269d8b11
- true
- Remap Numbers
- Remap Numbers
-
9214
-29438
154
64
-
9314
-29406
- Value to remap
- aed1de46-96e2-40d5-b0dc-907537d31c19
- true
- Value
- Value
- false
- ea2d8131-d849-464b-991d-b7545490c298
- 1
-
9216
-29436
86
20
-
9259
-29426
- Source domain
- 15c453f5-b34f-4aaf-a5aa-9fba87008cbe
- true
- Source
- Source
- false
- 0fea1294-960c-4c43-acef-e8daa16a43a9
- 1
-
9216
-29416
86
20
-
9259
-29406
- 1
- 1
- {0}
-
0
1
- Target domain
- fef59a1b-601a-49d7-bc54-e0b0a37dd6b1
- true
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- Curve Degree
- Get the degree value of a curve.
- true
- dd4f9b33-eb2f-4c2c-a9da-2d65d6783044
- true
- Curve Degree
- Curve Degree
-
9252
-1079
94
28
-
9296
-1065
- Curve to get the degree value of
- 6a0046e4-5b4d-448f-b2b4-cade479dcad1
- true
- Curve
- Curve
- false
- ee782a63-64f0-4f70-a960-95d38003cbb3
- 1
-
9254
-1077
30
24
-
9269
-1065
- Degree value of the curve
- 272db34b-cb01-4ac1-bae9-e94d23c75f3c
- true
- Degree
- Degree
- false
- 0
-
9308
-1077
36
24
-
9326
-1065
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- A-B+1
- true
- d2d17992-1f6a-41ce-a0e5-0a8d83ef92d2
- true
- Expression
- Expression
-
9245
-1275
108
44
-
9289
-1253
- 2
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 9756e426-55fb-4678-a28c-dee3f43c22e5
- true
- Variable A
- A
- true
- a927a6be-3516-43fe-8365-bf443ef1923b
- 1
-
9247
-1273
11
20
-
9252.5
-1263
- Expression variable
- 211996a5-6e8a-4a9c-88db-d132592dde1e
- true
- Variable B
- B
- true
- 272db34b-cb01-4ac1-bae9-e94d23c75f3c
- 1
-
9247
-1253
11
20
-
9252.5
-1243
- Result of expression
- 82cdb6c5-d11c-4816-899a-ec7feeb75410
- true
- Result
- Result
- false
- 0
-
9320
-1273
31
40
-
9335.5
-1253
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 12e4c4ab-282e-49fd-8fbc-2e50fd9bf37a
- true
- B
- B
- false
- 0
-
9261
-12026
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- fba3b68f-f744-41d4-b4d2-9d899b5a7f88
- true
- B
- B
- false
- 0
-
9261
-15586
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 8b4a365c-1645-430f-8be6-7fb0019a20f5
- true
- B
- B
- false
- 0
-
9262
-19286
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 3d196e4e-a427-48b3-a97c-9aae81c0ab45
- true
- B
- B
- false
- 0
-
9261
-22740
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- ab1ac911-2029-4ebc-a2e6-4e954cd90453
- true
- B
- B
- false
- 0
-
9259
-26232
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 899223b6-df9a-403e-bae3-eb7c226d4aab
- true
- B
- B
- false
- 0
-
9261
-29565
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 62804d7b-bdd9-4ed1-b6e5-f970e801b6a3
- true
- Relay
-
- false
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9261
-18356
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 55512720-2a0e-47cd-b00a-dc2b37b30de5
- true
- Relay
-
- false
- 7af0cade-f743-4780-907e-050ed9fcd4f9
- 1
-
9261
-21791
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- a7aa0c22-62a5-48d9-8db9-35e295bd33c0
- true
- Relay
-
- false
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9261
-25268
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 2f70e9a1-868c-4cc1-a692-dd23505afa99
- true
- Relay
-
- false
- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1
-
9261
-28628
60
24
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 532c0140-0dbd-4867-a53d-0a5b1e3f1497
- true
- Shift List
-
-
9264
-7434
53
64
-
9297
-7402
- 1
- List to shift
- 7d76ee9a-e8ec-4986-8d85-406e5c4305d4
- true
- List
-
- false
- 0184d168-0386-49c1-b31a-26709654c038
- 1
-
9266
-7432
19
20
-
9275.5
-7422
- Shift offset
- a96c7aa5-08ee-40cc-a832-e9d67163b5a8
- true
- Shift
-
- false
- 0
-
9266
-7412
19
20
-
9275.5
-7402
- 1
- 1
- {0}
- 1
- Wrap values
- 40b4295e-9407-40bf-80d0-c4d99f8a0aeb
- true
- Wrap
-
- false
- 0
-
9266
-7392
19
20
-
9275.5
-7382
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 738d8220-3b26-49b2-a359-0fc4d671538d
- true
- List
-
- false
- 0
-
9309
-7432
6
60
-
9312
-7402
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 46418f77-df32-4b35-861e-15218fba9785
- true
- Shift List
-
-
9264
-10955
53
64
-
9297
-10923
- 1
- List to shift
- 109e878a-7998-4679-b117-34d7b6cf17de
- true
- List
-
- false
- 7338c244-af88-4723-b45a-08577283c18b
- 1
-
9266
-10953
19
20
-
9275.5
-10943
- Shift offset
- 0544d4a8-798d-4542-bf03-ac1d99f27a76
- true
- Shift
-
- false
- 0
-
9266
-10933
19
20
-
9275.5
-10923
- 1
- 1
- {0}
- 1
- Wrap values
- 2533a264-171f-404e-a1c6-c06a3b9b8e6f
- true
- Wrap
-
- false
- 0
-
9266
-10913
19
20
-
9275.5
-10903
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 95512bec-3e3b-4a1e-968f-fdd54a0ed3fb
- true
- List
-
- false
- 0
-
9309
-10953
6
60
-
9312
-10923
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 8fd33484-455a-46bc-a886-7e889984cd34
- true
- Shift List
-
-
9264
-14390
53
64
-
9297
-14358
- 1
- List to shift
- be257533-ca89-454e-b4ba-f9b6b4680c16
- true
- List
-
- false
- 72af1623-98b2-41a3-b5a9-7e1bda1d7111
- 1
-
9266
-14388
19
20
-
9275.5
-14378
- Shift offset
- 2d8260d3-7cf6-48ff-a5e8-331b238050bf
- true
- Shift
-
- false
- 0
-
9266
-14368
19
20
-
9275.5
-14358
- 1
- 1
- {0}
- 1
- Wrap values
- 600f582c-be8c-4052-b082-957c3db424ca
- true
- Wrap
-
- false
- 0
-
9266
-14348
19
20
-
9275.5
-14338
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 5fcafa9d-43c7-4d8e-b1fa-7217ab260d93
- true
- List
-
- false
- 0
-
9309
-14388
6
60
-
9312
-14358
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 03e206f6-06e3-45a0-bd1b-462b7509ec07
- true
- Format
- Format
-
9234
-2581
130
64
-
9326
-2549
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 60aa4b83-1c3e-42c0-a0fc-3958ecd7d990
- true
- Format
- Format
- false
- 0
-
9236
-2579
78
20
-
9275
-2569
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 961c16c0-6ded-4a47-a9b4-6bac4a3ee77c
- true
- Culture
- Culture
- false
- 0
-
9236
-2559
78
20
-
9275
-2549
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- a12fa6e2-f7e6-44db-89fd-2ee48c469cd2
- true
- false
- Data 0
- 0
- true
- 2cd82ac7-4de3-4efd-b21c-bb675514f953
- 1
-
9236
-2539
78
20
-
9275
-2529
- Formatted text
- ad720d66-d245-44d9-b76a-dafa2c256b04
- true
- Text
- Text
- false
- 0
-
9338
-2579
24
60
-
9350
-2549
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 939ec527-c895-4c10-8020-fc9e4da28bdd
- true
- Format
- Format
-
9234
-3425
130
64
-
9326
-3393
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- b40b6ba6-8d3b-4054-a253-f920a6f3f288
- true
- Format
- Format
- false
- 0
-
9236
-3423
78
20
-
9275
-3413
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 6e07828a-1ec4-4e71-8198-90b5c6d06fdd
- true
- Culture
- Culture
- false
- 0
-
9236
-3403
78
20
-
9275
-3393
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 2cfebbbe-71fe-4a4a-acdc-4ef62d2bc7f4
- true
- false
- Data 0
- 0
- true
- 94c91859-db24-4e5a-aaa7-9df679d51de2
- 1
-
9236
-3383
78
20
-
9275
-3373
- Formatted text
- 2ee62344-eed2-47d2-aae3-277cb264e100
- true
- Text
- Text
- false
- 0
-
9338
-3423
24
60
-
9350
-3393
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- f7c23408-ec08-4cd6-9afd-7fd502247d57
- true
- Format
- Format
-
9226
-7698
130
64
-
9318
-7666
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 5dc2652c-c8e1-468a-b333-c5da7a8fe3b3
- true
- Format
- Format
- false
- 0
-
9228
-7696
78
20
-
9267
-7686
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 618ca455-8d0f-4f78-befe-37c22b75ce12
- true
- Culture
- Culture
- false
- 0
-
9228
-7676
78
20
-
9267
-7666
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 06eab3da-eb92-49cc-8526-a9f59c60cae8
- true
- false
- Data 0
- 0
- true
- dd7ae928-e56d-4423-b7b1-b1999182a279
- 1
-
9228
-7656
78
20
-
9267
-7646
- Formatted text
- e96b0bfa-693f-4be8-bcb4-c9e4a7df9692
- true
- Text
- Text
- false
- 0
-
9330
-7696
24
60
-
9342
-7666
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 318a5c49-4892-4094-b625-e4cbecc814eb
- true
- Format
- Format
-
9226
-11218
130
64
-
9318
-11186
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 1c5694f5-cf69-4c42-a1bb-3da554b0635c
- true
- Format
- Format
- false
- 0
-
9228
-11216
78
20
-
9267
-11206
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- c5c61685-06d4-441e-9a4c-b2d1b2631663
- true
- Culture
- Culture
- false
- 0
-
9228
-11196
78
20
-
9267
-11186
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 09e97d28-ec29-4afe-8e36-634ce9ae03a8
- true
- false
- Data 0
- 0
- true
- 05a6550e-e7dc-41fc-8983-e7c430ad5012
- 1
-
9228
-11176
78
20
-
9267
-11166
- Formatted text
- 5a745073-b64d-4e12-bfb6-7d824ab5280e
- true
- Text
- Text
- false
- 0
-
9330
-11216
24
60
-
9342
-11186
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 8e870804-f0af-411f-a9d2-ed416c5c6187
- true
- Format
- Format
-
9226
-14674
130
64
-
9318
-14642
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 520f052e-3f14-4220-ac0e-0b03931a1266
- true
- Format
- Format
- false
- 0
-
9228
-14672
78
20
-
9267
-14662
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 19f9fdd9-7ac8-42d6-978d-356e3e565021
- true
- Culture
- Culture
- false
- 0
-
9228
-14652
78
20
-
9267
-14642
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- dd7860ba-e2ad-44a8-a3cf-a0d9a45c0842
- true
- false
- Data 0
- 0
- true
- e9df2d08-5a93-4bb4-9361-d5b6b5a545a5
- 1
-
9228
-14632
78
20
-
9267
-14622
- Formatted text
- 3d034f31-d797-4424-8cef-9499e7099fc1
- true
- Text
- Text
- false
- 0
-
9330
-14672
24
60
-
9342
-14642
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 7ce3ce15-850b-45e1-ad59-92f757c03b5c
- true
- Format
- Format
-
9226
-18461
130
64
-
9318
-18429
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 40164056-ab05-4230-b49c-dd067f9305d2
- true
- Format
- Format
- false
- 0
-
9228
-18459
78
20
-
9267
-18449
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 2db5bc1b-d60e-4c5c-8b12-9a60741a0086
- true
- Culture
- Culture
- false
- 0
-
9228
-18439
78
20
-
9267
-18429
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- de3f0b39-9873-400d-b1b9-85a5e16c03e0
- true
- false
- Data 0
- 0
- true
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9228
-18419
78
20
-
9267
-18409
- Formatted text
- 84721e9b-8e00-4fcb-9746-ae1b23e91d8d
- true
- Text
- Text
- false
- 0
-
9330
-18459
24
60
-
9342
-18429
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 1ef06ab7-bb52-421b-9d4f-0f74a7b338d7
- true
- Format
- Format
-
9226
-21883
130
64
-
9318
-21851
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- c23477a4-43c8-4198-a584-157e995bc70d
- true
- Format
- Format
- false
- 0
-
9228
-21881
78
20
-
9267
-21871
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- abd47b9e-8af3-4412-b330-03721da886d7
- true
- Culture
- Culture
- false
- 0
-
9228
-21861
78
20
-
9267
-21851
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 31b965f4-66e2-43d6-bc73-414c25ca61bd
- true
- false
- Data 0
- 0
- true
- 7af0cade-f743-4780-907e-050ed9fcd4f9
- 1
-
9228
-21841
78
20
-
9267
-21831
- Formatted text
- 9ea884c7-deed-4580-b340-ef5d5dc73681
- true
- Text
- Text
- false
- 0
-
9330
-21881
24
60
-
9342
-21851
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 3971560d-877c-4cb3-9aad-0356911759f5
- true
- Format
- Format
-
9226
-25385
130
64
-
9318
-25353
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- ea427ec3-5a35-4520-8ccf-18df23fc6a20
- true
- Format
- Format
- false
- 0
-
9228
-25383
78
20
-
9267
-25373
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 933deb80-43d7-4dd9-b413-0db54ca26dd1
- true
- Culture
- Culture
- false
- 0
-
9228
-25363
78
20
-
9267
-25353
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- b0eac621-7855-4073-b49b-fa4116b4784d
- true
- false
- Data 0
- 0
- true
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9228
-25343
78
20
-
9267
-25333
- Formatted text
- e7099fe1-9f7c-49ca-bf44-6736df5e3b63
- true
- Text
- Text
- false
- 0
-
9330
-25383
24
60
-
9342
-25353
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- c4c5c32f-2de8-427e-a283-c44a57d51434
- true
- Format
- Format
-
9226
-28732
130
64
-
9318
-28700
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- bbd9f5ee-62b0-4987-bce7-1fe240ab5162
- true
- Format
- Format
- false
- 0
-
9228
-28730
78
20
-
9267
-28720
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- e20d6918-7775-473e-a0be-b717596cb7dd
- true
- Culture
- Culture
- false
- 0
-
9228
-28710
78
20
-
9267
-28700
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- ce53e26b-c513-4d62-be4c-647c68ce1540
- true
- false
- Data 0
- 0
- true
- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1
-
9228
-28690
78
20
-
9267
-28680
- Formatted text
- d93f190c-e272-4223-ac4d-69ddd085d784
- true
- Text
- Text
- false
- 0
-
9330
-28730
24
60
-
9342
-28700
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 81eaa78b-b49c-4af4-a9e1-8ed2469b4e8c
- a03f91ac-0515-47e3-b1da-acb30c73ba6d
- 72305306-f2af-43c4-9fd0-d3e8e9bc541b
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- 8fa1b443-91a1-419e-a698-39f89d98c35f
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- 33
- 215e0185-7f41-4f11-9037-ea048af906f5
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 81eaa78b-b49c-4af4-a9e1-8ed2469b4e8c
- true
- Explode
- Explode
-
9224
-31204
134
44
-
9295
-31182
- Curve to explode
- 757b62fd-392a-4568-8b6b-502c736a7d1a
- true
- Curve
- Curve
- false
- 82d46f90-f3a3-4dc9-bab4-8b7484395e05
- 1
-
9226
-31202
57
20
-
9254.5
-31192
- Recursive decomposition until all segments are atomic
- 0baeb68c-d1b8-42b0-96d5-9fadc48e843b
- true
- Recursive
- Recursive
- false
- 0
-
9226
-31182
57
20
-
9254.5
-31172
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- fe3f9ab1-bf7b-4288-8d97-e7946294e33c
- true
- Segments
- Segments
- false
- 0
-
9307
-31202
49
20
-
9331.5
-31192
- 1
- Vertices of the exploded segments
- e0fac1f1-e34c-460c-bca6-4d652b5d1e7c
- true
- Vertices
- Vertices
- false
- 0
-
9307
-31182
49
20
-
9331.5
-31172
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a03f91ac-0515-47e3-b1da-acb30c73ba6d
- true
- Evaluate Length
- Evaluate Length
-
9216
-31287
149
64
-
9301
-31255
- Curve to evaluate
- dd3f8489-93cb-466e-a726-1d6ce1c1fa21
- true
- Curve
- Curve
- false
- fe3f9ab1-bf7b-4288-8d97-e7946294e33c
- 1
-
9218
-31285
71
20
-
9253.5
-31275
- Length factor for curve evaluation
- 71c1961c-f265-4c01-a5d9-26dc87f04220
- true
- Length
- Length
- false
- 0
-
9218
-31265
71
20
-
9253.5
-31255
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 59c6efa1-7240-4201-bc6c-5c31a378fbcf
- true
- Normalized
- Normalized
- false
- 0
-
9218
-31245
71
20
-
9253.5
-31235
- 1
- 1
- {0}
- true
- Point at the specified length
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- true
- Point
- Point
- false
- 0
-
9313
-31285
50
20
-
9338
-31275
- Tangent vector at the specified length
- 421d155b-e6ee-493b-b76e-514be889455d
- true
- Tangent
- Tangent
- false
- 0
-
9313
-31265
50
20
-
9338
-31255
- Curve parameter at the specified length
- 86747235-7923-4162-bf80-d06ce685768a
- true
- Parameter
- Parameter
- false
- 0
-
9313
-31245
50
20
-
9338
-31235
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 72305306-f2af-43c4-9fd0-d3e8e9bc541b
- true
- Line SDL
- Line SDL
-
9236
-33067
110
64
-
9310
-33035
- Line start point
- 921670be-6896-4871-8936-b58984df4f0a
- true
- Start
- Start
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9238
-33065
60
20
-
9276
-33055
- Line tangent (direction)
- 73b544b6-a2ee-4c7a-9bdd-d84c5868e8e7
- true
- Direction
- Direction
- false
- b236cb6d-586e-4db4-8608-bc3cfb183bfb
- 1
-
9238
-33045
60
20
-
9276
-33035
- 1
- 1
- {0}
-
0
0
1
- Line length
- 51d28f88-0bc1-4904-8e9f-c19e3e5f0f68
- ABS(X)
- true
- Length
- Length
- false
- 8e9b755e-d14d-45f3-810d-0016d1bc6909
- 1
-
9238
-33025
60
20
-
9276
-33015
- 1
- 1
- {0}
- 0.015625
- Line segment
- 0788f4f1-f5fb-4cbe-9fa5-9ccae96bc71e
- true
- Line
- Line
- false
- 0
-
9322
-33065
22
60
-
9333
-33035
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- dd9ded7c-395b-47d9-ac3c-e415673778cb
- true
- Relative Differences
- Relative Differences
-
9233
-31630
116
28
-
9280
-31616
- 1
- List of data to operate on (numbers or points or vectors allowed)
- bbe33525-f6e6-4c7a-ac43-89d73b365178
- true
- Values
- Values
- false
- af79ac58-6083-46fb-bd71-4571d4768b45
- 1
-
9235
-31628
33
24
-
9251.5
-31616
- 1
- Differences between consecutive items
- b0b2a1b6-2a67-466d-9bdf-e8b50dccde48
- true
- Differenced
- Differenced
- false
- 0
-
9292
-31628
55
24
-
9319.5
-31616
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 22fcc540-2869-4d46-b91a-7baf5b3b0523
- true
- Replace Nulls
- Replace Nulls
-
9221
-31574
139
44
-
9316
-31552
- 1
- Items to test for null
- 0d06677d-66cc-4a32-8338-5014731a3e32
- true
- Items
- Items
- false
- 43a91f6e-e3b9-4aad-adac-77d060886b47
- 1
-
9223
-31572
81
20
-
9263.5
-31562
- 1
- Items to replace nulls with
- 5531ecac-6e38-48ea-8b2d-03e1ad1d5b28
- true
- Replacements
- Replacements
- false
- 0
-
9223
-31552
81
20
-
9263.5
-31542
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- af79ac58-6083-46fb-bd71-4571d4768b45
- true
- Items
- Items
- false
- 0
-
9328
-31572
30
20
-
9343
-31562
- Number of items replaced
- 5fb3744d-0f50-472a-b0f5-33274cdac75c
- true
- Count
- Count
- false
- 0
-
9328
-31552
30
20
-
9343
-31542
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 43a91f6e-e3b9-4aad-adac-77d060886b47
- true
- Relay
- false
- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
- 1
-
9271
-31511
40
16
-
9291
-31503
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- true
- Relay
- false
- 628a45ae-3f38-4501-9306-b3bfe07a4a69
- 1
-
9271
-31875
40
16
-
9291
-31867
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- dd9ded7c-395b-47d9-ac3c-e415673778cb
- 22fcc540-2869-4d46-b91a-7baf5b3b0523
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
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- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- 27b1909a-f125-4246-82be-4d422422f56c
- 8
- f27ff281-d697-4da1-a47c-31749f573a6d
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 471229c7-3a45-429f-b0fa-94a45dae9b20
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-31375
108
64
-
9281
-31343
- Point to project onto curve
- a22e5dc2-7aea-41cc-bc34-0af6fd6dff09
- true
- Point
- Point
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9239
-31373
30
30
-
9254
-31358
- Curve to project onto
- fe5ffe52-63f4-4054-b970-a8cd10e33174
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-31343
30
30
-
9254
-31328
- Point on the curve closest to the base point
- 47b0dbfd-13d8-4a67-86d8-a24e8f565729
- true
- Point
- Point
- false
- 0
-
9293
-31373
50
20
-
9318
-31363
- Parameter on curve domain of closest point
- 6ac0259f-1c38-4ef5-94f5-eec70f4d8db9
- true
- Parameter
- Parameter
- false
- 0
-
9293
-31353
50
20
-
9318
-31343
- Distance between base point and curve
- c71ef2fb-fa1a-46b7-9f20-bd7f75e661ca
- true
- Distance
- Distance
- false
- 0
-
9293
-31333
50
20
-
9318
-31323
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c354b686-ceeb-4f9b-967c-89b7a10a2e8d
- true
- Line
- Line
-
9240
-31454
102
44
-
9306
-31432
- Line start point
- 6149bcaa-82a0-4690-a0bd-5813e840ea42
- true
- Start Point
- Start Point
- false
- 47b0dbfd-13d8-4a67-86d8-a24e8f565729
- 1
-
9242
-31452
52
20
-
9268
-31442
- Line end point
- 718fc483-7ccd-484f-a141-81ad5db06e46
- true
- End Point
- End Point
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9242
-31432
52
20
-
9268
-31422
- Line segment
- b236cb6d-586e-4db4-8608-bc3cfb183bfb
- true
- Line
- Line
- false
- 0
-
9318
-31452
22
40
-
9329
-31432
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 16a99370-5eb6-4fce-aeec-d7680f2fe05d
- true
- Remap Numbers
- Remap Numbers
-
9214
-32765
154
64
-
9314
-32733
- Value to remap
- a6e1fcd6-e49f-46e9-a872-7e47b8af5ea9
- true
- Value
- Value
- false
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- 1
-
9216
-32763
86
20
-
9259
-32753
- Source domain
- af14e9d0-e86c-496c-b6f9-9f6bc2814eef
- true
- Source
- Source
- false
- b22c79a2-0d33-46d7-9284-57f3b4abbb8f
- 1
-
9216
-32743
86
20
-
9259
-32733
- 1
- 1
- {0}
-
0
1
- Target domain
- d4fccc4e-bf36-471c-9b81-ba3f8d701373
- true
- Target
- Target
- false
- 0
-
9216
-32723
86
20
-
9259
-32713
- 1
- 1
- {0}
-
-1
1
- Remapped number
- f42a7e48-9398-409b-8a64-da1367bb2942
- true
- Mapped
- Mapped
- false
- 0
-
9326
-32763
40
30
-
9346
-32748
- Remapped and clipped number
- 689f688b-07fe-4428-9c4e-370f641273b0
- true
- Clipped
- Clipped
- false
- 0
-
9326
-32733
40
30
-
9346
-32718
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 5fe01426-5385-4a08-b8ea-7640aed5ecfb
- true
- Bounds
- Bounds
-
9236
-32683
110
28
-
9294
-32669
- 1
- Numbers to include in Bounds
- 5554d382-be36-4514-8504-a01372c39b80
- true
- Numbers
- Numbers
- false
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- 1
-
9238
-32681
44
24
-
9260
-32669
- Numeric Domain between the lowest and highest numbers in {N}
- b22c79a2-0d33-46d7-9284-57f3b4abbb8f
- true
- Domain
- Domain
- false
- 0
-
9306
-32681
38
24
-
9325
-32669
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- true
- Relay
-
- false
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- 1
-
9271
-32636
40
16
-
9291
-32628
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- c97695d5-8e09-472d-bde7-20c54a6299fe
- true
- Multiplication
- Multiplication
-
9256
-32964
70
44
-
9281
-32942
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 4bcc7d6b-5c4e-4433-b135-a07aa4aa0a5b
- true
- A
- A
- true
- 3946cb2b-8c1a-4e2c-a3b8-0a68992f993b
- 1
-
9258
-32962
11
20
-
9263.5
-32952
- Second item for multiplication
- d30a8b1c-7836-41e1-98be-ea095a5c6c05
- true
- B
- B
- true
- cd09c2ab-8662-4079-bdab-9e16238ac1e2
- 1
-
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9297
-25053
- 1
- List to shift
- 5499e5b9-8cb2-49eb-9c30-f42c02160bb0
- true
- List
-
- false
- 53cd2fb9-04f7-425c-aaa0-2f8eff8d768a
- 1
-
9266
-25083
19
20
-
9275.5
-25073
- Shift offset
- 1729daa5-e944-4ea1-b8b3-d12f2997dc4e
- true
- Shift
-
- false
- 0
-
9266
-25063
19
20
-
9275.5
-25053
- 1
- 1
- {0}
- 1
- Wrap values
- 8d1dfbee-0649-4ac4-af78-b408219fcce4
- true
- Wrap
-
- false
- 0
-
9266
-25043
19
20
-
9275.5
-25033
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ab4f4689-c6b1-486b-8d63-2934c6b34e6f
- true
- List
-
- false
- 0
-
9309
-25083
6
60
-
9312
-25053
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- ff2559cf-18b3-4cad-b391-315893967bf2
- true
- Shift List
-
-
9264
-28449
53
64
-
9297
-28417
- 1
- List to shift
- 273f5044-a2c4-4e53-b232-745a3aba44a6
- true
- List
-
- false
- 2d37b54a-d252-4d91-af08-37f5c09e7e4a
- 1
-
9266
-28447
19
20
-
9275.5
-28437
- Shift offset
- 5b25285d-2173-464a-b270-22bf8a418ba0
- true
- Shift
-
- false
- 0
-
9266
-28427
19
20
-
9275.5
-28417
- 1
- 1
- {0}
- 1
- Wrap values
- 4a0100fa-492c-44ed-8efd-286b52e4296b
- true
- Wrap
-
- false
- 0
-
9266
-28407
19
20
-
9275.5
-28397
- 1
- 1
- {0}
- false
- 1
- Shifted list
- d57b5cda-0b57-4731-b527-b630d209be02
- true
- List
-
- false
- 0
-
9309
-28447
6
60
-
9312
-28417
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 27b1909a-f125-4246-82be-4d422422f56c
- true
- Shift List
-
-
9264
-31775
53
64
-
9297
-31743
- 1
- List to shift
- bfcc7bea-5c84-4cb4-9ff7-0de9927cd430
- true
- List
-
- false
- b0b2a1b6-2a67-466d-9bdf-e8b50dccde48
- 1
-
9266
-31773
19
20
-
9275.5
-31763
- Shift offset
- 4f2a1b86-0f17-49bd-9fca-cbdc3d33ec14
- true
- Shift
-
- false
- 0
-
9266
-31753
19
20
-
9275.5
-31743
- 1
- 1
- {0}
- 1
- Wrap values
- b943df66-5f34-449f-a95b-f9c2d9811644
- true
- Wrap
-
- false
- 0
-
9266
-31733
19
20
-
9275.5
-31723
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 628a45ae-3f38-4501-9306-b3bfe07a4a69
- true
- List
-
- false
- 0
-
9309
-31773
6
60
-
9312
-31743
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 55fcfa84-e04c-40ca-ae46-cc937e27bc97
- 3472779d-20db-40dc-8dba-0814a38b261e
- 9b318109-1854-4397-bf67-7f973c203aaa
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- e027a95f-405b-4d15-be30-520d91dbc5fc
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- a2874c09-6237-43a6-9770-654bb457fea2
- eef9bfc4-b532-42a0-bd17-b8664766f22d
- dc8cf255-b505-46bc-b318-2ae7c8c46b35
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- 0343763a-82b3-483e-8d95-68ddd2c05938
- 8951eabd-7737-4a9d-88fc-d15ea0349bc1
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 7bc36f90-e59b-4ccb-9ddb-02043549301b
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- 87a2227f-c42b-4756-b84e-5cb0c48ee4fa
- a9701972-e21e-4da9-9c28-b38c5fd5ee91
- c192e380-8d44-4588-9699-871bb46e733f
- 8fe511eb-1233-498f-a8f7-d34dd4f617ff
- ec2ad91e-428d-4859-a2f4-c060e48f0123
- 6cec9000-baec-41ef-973b-b71a94f021fc
- c6ae0cff-05a7-4886-8aec-979f2907fe15
- e255ea20-b4ac-48b1-9e1b-0980e7594d5c
- 4a75522d-3e59-45b0-a235-b3d518b6df35
- cd5303fe-9c39-4150-8623-a6ac735d2876
- 0ef4bcf5-e770-4833-ad57-d7559ac0cfa8
- e328ed3a-fdf2-475b-930e-eac036796207
- 31d327cb-78e9-4772-9b77-ece7f5772c9a
- 4b4766df-9c4a-478a-a5ec-86bcf578667e
- ddda8bc0-631e-4735-96ff-a584cfbe1986
- 33
- 69a821a3-8a73-4cec-baac-b9a13a42017b
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 55fcfa84-e04c-40ca-ae46-cc937e27bc97
- true
- Explode
- Explode
-
9224
-34107
134
44
-
9295
-34085
- Curve to explode
- 7da04cc2-bf5d-4d0e-bcab-169bff54c587
- true
- Curve
- Curve
- false
- 88c9d358-2164-494c-93cd-620bfe195f0b
- 1
-
9226
-34105
57
20
-
9254.5
-34095
- Recursive decomposition until all segments are atomic
- 4bf6b70a-6c34-468c-aa86-94afd01fb357
- true
- Recursive
- Recursive
- false
- 0
-
9226
-34085
57
20
-
9254.5
-34075
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 6c4a04a3-a43f-457d-983f-5cf6e15c55b3
- true
- Segments
- Segments
- false
- 0
-
9307
-34105
49
20
-
9331.5
-34095
- 1
- Vertices of the exploded segments
- 4cbdd9d2-e4c9-48ca-a29a-60721e988124
- true
- Vertices
- Vertices
- false
- 0
-
9307
-34085
49
20
-
9331.5
-34075
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 3472779d-20db-40dc-8dba-0814a38b261e
- true
- Evaluate Length
- Evaluate Length
-
9216
-34190
149
64
-
9301
-34158
- Curve to evaluate
- 61ed4f99-0318-4550-9b89-e471060e49cd
- true
- Curve
- Curve
- false
- 6c4a04a3-a43f-457d-983f-5cf6e15c55b3
- 1
-
9218
-34188
71
20
-
9253.5
-34178
- Length factor for curve evaluation
- 9f2f27a2-8d4e-4115-b063-8157dc5bc3c7
- true
- Length
- Length
- false
- 0
-
9218
-34168
71
20
-
9253.5
-34158
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 5a640dfc-16bc-4d45-9299-3990b3d869ea
- true
- Normalized
- Normalized
- false
- 0
-
9218
-34148
71
20
-
9253.5
-34138
- 1
- 1
- {0}
- true
- Point at the specified length
- 83d865c2-6775-4675-9f8a-220e22ddae31
- true
- Point
- Point
- false
- 0
-
9313
-34188
50
20
-
9338
-34178
- Tangent vector at the specified length
- 93b233c7-cc87-47af-a8da-a31536701d3a
- true
- Tangent
- Tangent
- false
- 0
-
9313
-34168
50
20
-
9338
-34158
- Curve parameter at the specified length
- c83c9c3e-20cb-4973-90a0-33613bc0b9bf
- true
- Parameter
- Parameter
- false
- 0
-
9313
-34148
50
20
-
9338
-34138
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 9b318109-1854-4397-bf67-7f973c203aaa
- true
- Line SDL
- Line SDL
-
9236
-35970
110
64
-
9310
-35938
- Line start point
- 7517af86-db7e-4c90-b088-ebb63aeb9947
- true
- Start
- Start
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9238
-35968
60
20
-
9276
-35958
- Line tangent (direction)
- 2a40b560-e61e-43ee-857d-4d109c9e2564
- true
- Direction
- Direction
- false
- d3dbebd8-864a-42c4-a1e6-9bde8c219738
- 1
-
9238
-35948
60
20
-
9276
-35938
- 1
- 1
- {0}
-
0
0
1
- Line length
- 9a51e0da-5a90-4c2f-a539-6f1169e6adcf
- ABS(X)
- true
- Length
- Length
- false
- 7feacf97-94fa-4c5e-b845-893325d06a8a
- 1
-
9238
-35928
60
20
-
9276
-35918
- 1
- 1
- {0}
- 0.015625
- Line segment
- 6760dc6d-999e-4284-b361-b5cb2b5a6f55
- true
- Line
- Line
- false
- 0
-
9322
-35968
22
60
-
9333
-35938
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- true
- Relative Differences
- Relative Differences
-
9233
-34533
116
28
-
9280
-34519
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 8bdef77b-f99e-4151-baaa-1479ad4fb2a0
- true
- Values
- Values
- false
- cfb237b9-cda4-451f-88cf-681e8c1a12e1
- 1
-
9235
-34531
33
24
-
9251.5
-34519
- 1
- Differences between consecutive items
- 8945d4e1-f472-463e-8ed0-f9b54de13e94
- true
- Differenced
- Differenced
- false
- 0
-
9292
-34531
55
24
-
9319.5
-34519
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- e027a95f-405b-4d15-be30-520d91dbc5fc
- true
- Replace Nulls
- Replace Nulls
-
9221
-34477
139
44
-
9316
-34455
- 1
- Items to test for null
- 50e47417-d5fa-4fd6-80cb-1cd3825f090d
- true
- Items
- Items
- false
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- 1
-
9223
-34475
81
20
-
9263.5
-34465
- 1
- Items to replace nulls with
- 49bb910e-eb21-4eb7-a7f1-549dcb632f72
- true
- Replacements
- Replacements
- false
- 0
-
9223
-34455
81
20
-
9263.5
-34445
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- cfb237b9-cda4-451f-88cf-681e8c1a12e1
- true
- Items
- Items
- false
- 0
-
9328
-34475
30
20
-
9343
-34465
- Number of items replaced
- a42bf3d3-1e96-403d-b483-d487b33f5cb5
- true
- Count
- Count
- false
- 0
-
9328
-34455
30
20
-
9343
-34445
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- true
- Relay
- false
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- 1
-
9271
-34414
40
16
-
9291
-34406
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- a2874c09-6237-43a6-9770-654bb457fea2
- true
- Relay
- false
- f50a8f1c-4788-43be-b2e2-986396a4b91f
- 1
-
9271
-34778
40
16
-
9291
-34770
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- e027a95f-405b-4d15-be30-520d91dbc5fc
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- a2874c09-6237-43a6-9770-654bb457fea2
- cce0cf82-c2e4-4967-b2d7-8d1450f4e4ff
- 8
- eef9bfc4-b532-42a0-bd17-b8664766f22d
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- dc8cf255-b505-46bc-b318-2ae7c8c46b35
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-34278
108
64
-
9281
-34246
- Point to project onto curve
- 9f2045f7-84db-41a3-80a7-b78554fc6dc3
- true
- Point
- Point
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9239
-34276
30
30
-
9254
-34261
- Curve to project onto
- 53c74feb-bd8c-4934-b455-c4061c58e591
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-34246
30
30
-
9254
-34231
- Point on the curve closest to the base point
- 3800975a-d9c1-4d01-8d3c-5fe396f11ea9
- true
- Point
- Point
- false
- 0
-
9293
-34276
50
20
-
9318
-34266
- Parameter on curve domain of closest point
- 802dfdfc-00c0-4e0d-88cd-b70ffb31a626
- true
- Parameter
- Parameter
- false
- 0
-
9293
-34256
50
20
-
9318
-34246
- Distance between base point and curve
- 3a8aa4d2-6fcc-4120-8b54-3111253d7cb2
- true
- Distance
- Distance
- false
- 0
-
9293
-34236
50
20
-
9318
-34226
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 76231faf-dae2-4926-9f6b-2c8077bcac89
- true
- Line
- Line
-
9240
-34357
102
44
-
9306
-34335
- Line start point
- 2b14c6a3-4ad6-47d8-87b3-1587dd6eecf0
- true
- Start Point
- Start Point
- false
- 3800975a-d9c1-4d01-8d3c-5fe396f11ea9
- 1
-
9242
-34355
52
20
-
9268
-34345
- Line end point
- 1672f208-89e5-473d-a789-52bcc3c501c6
- true
- End Point
- End Point
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9242
-34335
52
20
-
9268
-34325
- Line segment
- d3dbebd8-864a-42c4-a1e6-9bde8c219738
- true
- Line
- Line
- false
- 0
-
9318
-34355
22
40
-
9329
-34335
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 0343763a-82b3-483e-8d95-68ddd2c05938
- true
- Remap Numbers
- Remap Numbers
-
9214
-35668
154
64
-
9314
-35636
- Value to remap
- fbb75435-dbda-4a99-b5de-a7f860bb107d
- true
- Value
- Value
- false
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 1
-
9216
-35666
86
20
-
9259
-35656
- Source domain
- bda3bd9e-69c4-4252-8fbd-8445a285ec60
- true
- Source
- Source
- false
- 4cc59e7a-388e-4875-939d-e051a56dbf0a
- 1
-
9216
-35646
86
20
-
9259
-35636
- 1
- 1
- {0}
-
0
1
- Target domain
- 6ed6b452-6999-4bc0-9d9b-1edae4d23e5e
- true
- Target
- Target
- false
- 0
-
9216
-35626
86
20
-
9259
-35616
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 0eaed2fe-a667-4ec0-bd86-4b5c20e158fe
- true
- Mapped
- Mapped
- false
- 0
-
9326
-35666
40
30
-
9346
-35651
- Remapped and clipped number
- 43ee08e0-34ae-4987-87d2-49bd6063b895
- true
- Clipped
- Clipped
- false
- 0
-
9326
-35636
40
30
-
9346
-35621
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 8951eabd-7737-4a9d-88fc-d15ea0349bc1
- true
- Bounds
- Bounds
-
9236
-35586
110
28
-
9294
-35572
- 1
- Numbers to include in Bounds
- b2d1db6e-815f-4c6e-adc4-7c0cdab96b4d
- true
- Numbers
- Numbers
- false
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 1
-
9238
-35584
44
24
-
9260
-35572
- Numeric Domain between the lowest and highest numbers in {N}
- 4cc59e7a-388e-4875-939d-e051a56dbf0a
- true
- Domain
- Domain
- false
- 0
-
9306
-35584
38
24
-
9325
-35572
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- true
- Relay
-
- false
- a2874c09-6237-43a6-9770-654bb457fea2
- 1
-
9271
-35539
40
16
-
9291
-35531
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 7bc36f90-e59b-4ccb-9ddb-02043549301b
- true
- Multiplication
- Multiplication
-
9256
-35867
70
44
-
9281
-35845
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Group
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- Explode
- Explode a curve into smaller segments.
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- Explode
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134
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- Curve to explode
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57
20
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- Recursive decomposition until all segments are atomic
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57
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- Exploded segments that make up the base curve
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49
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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149
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- Curve to evaluate
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- Length factor for curve evaluation
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Point at the specified length
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50
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- Tangent vector at the specified length
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- Curve parameter at the specified length
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- Line SDL
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- Line start point
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- Line tangent (direction)
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60
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0
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60
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- Line segment
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22
60
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- Compute relative differences for a list of data
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116
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- List of data to operate on (numbers or points or vectors allowed)
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- Items to replace nulls with
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81
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9263.5
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- Grasshopper.Kernel.Types.GH_Integer
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- List without any nulls
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30
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- Number of items replaced
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30
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Curve Closest Point
- Find the closest point on a curve.
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- Point to project onto curve
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- Curve to project onto
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30
30
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- Point on the curve closest to the base point
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- Parameter on curve domain of closest point
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- Distance between base point and curve
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50
20
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- Line
- Create a line between two points.
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- Line
- Line
-
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102
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- Line start point
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52
20
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- Line end point
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52
20
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- Line segment
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9318
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22
40
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- Remap Numbers
- Remap numbers into a new numeric domain
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- Remap Numbers
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154
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9314
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- Value to remap
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86
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- Source domain
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9216
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86
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0
1
- Target domain
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9216
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86
20
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-1
1
- Remapped number
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40
30
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- Remapped and clipped number
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9326
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40
30
-
9346
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- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
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110
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- Numbers to include in Bounds
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44
24
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- Numeric Domain between the lowest and highest numbers in {N}
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- Domain
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-
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38
24
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9325
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- Relay
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- A wire relay object
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40
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
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70
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- 2
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- First item for multiplication
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11
20
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- Second item for multiplication
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11
20
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- Result of multiplication
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- Multiplication
- Mathematical multiplication
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70
44
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- 2
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- First item for multiplication
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11
20
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- Second item for multiplication
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11
20
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- Result of multiplication
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31
40
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- A wire relay object
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40
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255;255;255;255
- A group of Grasshopper objects
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255;255;255;255
- A group of Grasshopper objects
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185
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22
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81
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40
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38
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40
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70
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11
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-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 13d1fa05-10a0-4e49-9f5c-d4be788f3bf7
- true
- Evaluate Length
- Evaluate Length
-
9216
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149
64
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9301
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- Curve to evaluate
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- Curve
- Curve
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- 1
-
9218
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71
20
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9253.5
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- Length factor for curve evaluation
- 3d38be95-53d7-42c7-bf78-b328a61d1004
- true
- Length
- Length
- false
- 0
-
9218
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71
20
-
9253.5
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 6083f354-e506-4938-8073-5ae19c9a0bcb
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- Normalized
- Normalized
- false
- 0
-
9218
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71
20
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9253.5
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- 1
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- Point at the specified length
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- true
- Point
- Point
- false
- 0
-
9313
-41758
50
20
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9338
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- Tangent vector at the specified length
- ac75852c-1840-42f1-a45c-a1340843b1f6
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- Tangent
- Tangent
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- 0
-
9313
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50
20
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9338
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- Curve parameter at the specified length
- 69a8f266-7c26-4dd5-ae0a-ce7f3038267c
- true
- Parameter
- Parameter
- false
- 0
-
9313
-41718
50
20
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9338
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- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- 1f826159-9b93-496e-a901-3569ec3f0529
- true
- Interpolate
- Interpolate
-
9178
-41865
225
84
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9351
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- 1
- Interpolation points
- 845c8ca5-93f1-4359-9c95-2955e582f673
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- Vertices
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- a7f000f7-077a-429b-9fd2-3461a60688ce
- 1
-
9180
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159
20
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9259.5
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- Curve degree
- af999c4e-9762-4d4d-84b3-529b4cdf1786
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- Degree
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- 0
-
9180
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159
20
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9259.5
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- Periodic curve
- 82797a82-ed5b-4939-a849-81dc5005e2f1
- true
- Periodic
- Periodic
- false
- 0
-
9180
-41823
159
20
-
9259.5
-41813
- 1
- 1
- {0}
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- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- 0002170b-0e61-4a14-921d-19fcde0ed3c1
- true
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- KnotStyle
- false
- 0
-
9180
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159
20
-
9259.5
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- 1
- {0}
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- Resulting nurbs curve
- 49ba7b32-079b-49b9-b959-c2d6bfd13254
- true
- Curve
- Curve
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- 0
-
9363
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38
26
-
9382
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- Curve length
- 8d874e72-0d60-47cc-a1c0-ecc588d0d3fc
- true
- Length
- Length
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-
9363
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38
27
-
9382
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- Curve domain
- 2a775b02-d107-44ba-858c-2046ed1c6795
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- Domain
- Domain
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-
9363
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38
27
-
9382
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- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
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- true
- Create Material
- Create Material
-
9215
-41992
152
104
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9313
-41940
- Colour of the diffuse channel
- 558b211b-9805-46c1-ba2c-9ec0d4ddc247
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- Diffuse
- false
- 0
-
9217
-41990
84
20
-
9259
-41980
- 1
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255;138;138;138
- Colour of the specular highlight
- 242fc3cc-4394-4ece-9bc2-200e01d9d80d
- true
- Specular
- Specular
- false
- 0
-
9217
-41970
84
20
-
9259
-41960
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 1e6c6da7-cc89-4938-998e-31b29107fa58
- true
- Emission
- Emission
- false
- 0
-
9217
-41950
84
20
-
9259
-41940
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- a1000b0b-f2eb-48b6-87d4-ce732f817a64
- true
- Transparency
- Transparency
- false
- 0
-
9217
-41930
84
20
-
9259
-41920
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- b98344ef-66c6-43b0-9504-cbb0bafb4a02
- true
- Shine
- Shine
- false
- 0
-
9217
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84
20
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9259
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- 1
- 1
- {0}
- 100
- Resulting material
- 556a7f51-dac7-4aa7-92e2-bf4ef5bb5c94
- true
- Material
- Material
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- 0
-
9325
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40
100
-
9345
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
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- true
- Custom Preview
- Custom Preview
-
9253
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76
44
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9315
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- Geometry to preview
- true
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- true
- Geometry
- Geometry
- false
- 49ba7b32-079b-49b9-b959-c2d6bfd13254
- 1
-
9255
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48
20
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9279
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- The material override
- 27318ca8-9375-4bb8-945e-1d98fced9ce8
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- Material
- Material
- false
- 556a7f51-dac7-4aa7-92e2-bf4ef5bb5c94
- 1
-
9255
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48
20
-
9279
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- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
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- Quick Graph
- 1
- Display a set of y-values as a graph
- 79de9cf0-fcdc-4bba-bc24-572fecdc1cd8
- true
- Quick Graph
- Quick Graph
- false
- 0
- f5764a3d-7ce6-4d28-831b-482fcc350345
- 1
-
9223
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150
150
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9223.633
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- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- e1a9abe3-f7cd-446d-828c-eb66e5fcbf81
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- B
- B
- false
- 0
-
9261
-41306
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 710b7f25-69d0-40c4-8e80-8af6e2e0161c
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-
- false
- f5764a3d-7ce6-4d28-831b-482fcc350345
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-
9261
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60
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- Format
- Format some data using placeholders and formatting tags
- true
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- true
- Format
- Format
-
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130
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- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- ed06f458-55d6-4614-838f-8cda3f23c651
- true
- Format
- Format
- false
- 0
-
9228
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78
20
-
9267
-40455
- 1
- 1
- {0}
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- {0:R}
- Formatting culture
- bb43e128-d580-4b54-ac41-7398752044d5
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- Culture
- Culture
- false
- 0
-
9228
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78
20
-
9267
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- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 519b6b8e-3606-4e7a-a870-bafdb95e3276
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- Data 0
- 0
- true
- f5764a3d-7ce6-4d28-831b-482fcc350345
- 1
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9228
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78
20
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9267
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- Formatted text
- 8c3b5a7e-88ac-4a85-aff3-496ee1f2fd94
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- Text
- Text
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- 0
-
9330
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24
60
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9342
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- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 344dc1b1-9c93-405e-b50c-435fc88b1393
- true
- Shift List
-
-
9264
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53
64
-
9297
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- 1
- List to shift
- 38028c4f-01b1-448b-971a-aeac3bdce801
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- List
-
- false
- f1a4fd75-be6b-426f-94b9-028e696a8d4e
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-
9266
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19
20
-
9275.5
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- Shift offset
- fa831690-2c1c-4038-9c05-76b4f05ad5f2
- true
- Shift
-
- false
- 0
-
9266
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19
20
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9275.5
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- 1
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- 1
- Wrap values
- 8eb8ab7b-f0bb-4609-b9db-45bf19bb7513
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- Wrap
-
- false
- 0
-
9266
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19
20
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9275.5
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- 1
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- 1
- Shifted list
- b16fb91f-43f8-48d3-85b5-411ce00f8e92
- true
- List
-
- false
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-
9309
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6
60
-
9312
-40151
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- f12dfdaf-a911-4905-b859-d8a9f4e0eedb
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- Group
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- Explode
- Explode a curve into smaller segments.
- true
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- true
- Explode
- Explode
-
9224
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134
44
-
9295
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- Curve to explode
- 21819ae5-0104-4cd0-b1a2-20a8c9437dac
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- Curve
- false
- 49ba7b32-079b-49b9-b959-c2d6bfd13254
- 1
-
9226
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57
20
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9254.5
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- Recursive decomposition until all segments are atomic
- 9b758182-5867-4d95-a7c9-7ce9ece6d472
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- Recursive
- Recursive
- false
- 0
-
9226
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57
20
-
9254.5
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- 1
- 1
- {0}
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- 1
- Exploded segments that make up the base curve
- 96fd8efe-b267-4f01-ae1d-95fa6f36f03d
- true
- Segments
- Segments
- false
- 0
-
9307
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49
20
-
9331.5
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- 1
- Vertices of the exploded segments
- 89f21f30-c523-446e-a993-0473c39c98b4
- true
- Vertices
- Vertices
- false
- 0
-
9307
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49
20
-
9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- ddec3c63-c1ce-4b98-bd8d-23dd34771bc1
- true
- Evaluate Length
- Evaluate Length
-
9216
-42494
149
64
-
9301
-42462
- Curve to evaluate
- e65aea05-b30b-4426-a83f-27f48a8fc4c9
- true
- Curve
- Curve
- false
- 96fd8efe-b267-4f01-ae1d-95fa6f36f03d
- 1
-
9218
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71
20
-
9253.5
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- Length factor for curve evaluation
- f4853285-4b14-4799-9792-998cce733eb1
- true
- Length
- Length
- false
- 0
-
9218
-42472
71
20
-
9253.5
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- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- ae68e25f-27c2-404d-9cea-27e2b3859708
- true
- Normalized
- Normalized
- false
- 0
-
9218
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71
20
-
9253.5
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- 1
- 1
- {0}
- true
- Point at the specified length
- eeb3326c-8c7d-4ee2-b604-1674c4e8b8a8
- true
- Point
- Point
- false
- 0
-
9313
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50
20
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9338
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- Tangent vector at the specified length
- b7be6e78-611a-4818-9515-b244d669269f
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- Tangent
- false
- 0
-
9313
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50
20
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9338
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- Curve parameter at the specified length
- 6349ae4e-3f8f-42c5-8fa4-eca0d9b289bb
- true
- Parameter
- Parameter
- false
- 0
-
9313
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50
20
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9338
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9236
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110
64
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9310
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- Line start point
- 4c1ef802-cc97-4f47-a2fc-8bf547ad8b77
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9238
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60
20
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9276
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- Line tangent (direction)
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- 1
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9238
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60
20
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9276
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0
0
1
- Line length
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- ABS(X)
- true
- Length
- Length
- false
- 24b005f9-d046-4d64-bb62-797fb722cb35
- 1
-
9238
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60
20
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9276
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- 1
- 1
- {0}
- 0.015625
- Line segment
- c7e0c241-90cc-496e-a87d-4b724bc0890a
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- Line
- Line
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- 0
-
9322
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22
60
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9333
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- dd17d442-3776-40b3-ad5b-5e188b56bd4c
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- Compute relative differences for a list of data
- true
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- true
- Relative Differences
- Relative Differences
-
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116
28
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9280
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- List of data to operate on (numbers or points or vectors allowed)
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9235
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33
24
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9251.5
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- 1
- Differences between consecutive items
- 7d62d328-5af4-4783-a10c-8dd6cb2e9a4a
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- 0
-
9292
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55
24
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9319.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- true
- Replace Nulls
- Replace Nulls
-
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139
44
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9316
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- Items to test for null
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- 1
-
9223
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81
20
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9263.5
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- Items to replace nulls with
- b3c8a56f-0cd4-4c51-a87c-5b8dd989b025
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- 0
-
9223
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81
20
-
9263.5
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- 1
- 1
- {0}
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- 0
- 1
- List without any nulls
- 6ef3022d-c15d-4be5-a48d-24d97fc6c710
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- Items
- Items
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- 0
-
9328
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30
20
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9343
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- Number of items replaced
- 507078d7-5473-44f8-867b-cde6bf18fdb1
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- Count
- Count
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- 0
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9328
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- A group of Grasshopper objects
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52
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9216
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- Numbers to include in Bounds
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38
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- A wire relay object
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- Mathematical multiplication
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31
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255;255;255;255
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- Group
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- A group of Grasshopper objects
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- Emissive colour of the material
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255;255;255;255
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- Length factor for curve evaluation
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- Point at the specified length
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255;130;130;130
- Colour of the specular highlight
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9217
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84
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9259
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255;0;255;255
- Emissive colour of the material
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- Emission
- Emission
- false
- 0
-
9217
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84
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9259
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Transparency
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9217
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84
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9259
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- 1
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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84
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- Resulting material
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9325
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40
100
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
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- Custom Preview
- Custom Preview
-
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76
44
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9315
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- Geometry to preview
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- Geometry
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- 2ade3e09-9450-4cf7-9dab-808a7e057067
- 1
-
9255
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48
20
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9279
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- The material override
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- Material
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- 4fe71d5e-bfd7-441d-8b41-fe4cb1b2c049
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9255
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48
20
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9279
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Quick Graph
- 1
- Display a set of y-values as a graph
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150
150
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9223.633
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- 448de216-3a12-43cf-a135-e3bfafc87744
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- Second item for multiplication
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-
9261
-44105
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
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-
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9261
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60
24
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- Format
- Format some data using placeholders and formatting tags
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- Format
- Format
-
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130
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- Text format
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9228
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78
20
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9267
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- Formatting culture
- fdb39509-da56-4023-9d44-518751fa1aae
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- Culture
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-
9228
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78
20
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9267
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- Data to insert at {0} placeholders
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9228
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78
20
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- Formatted text
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9330
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24
60
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9342
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- Offset all items in a list.
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- Shift List
-
-
9264
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53
64
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9297
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- List to shift
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- List
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19
20
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9275.5
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- Shift offset
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-
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9266
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19
20
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- 12352323-c591-443d-bed8-08d75aae23ac
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-
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9266
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19
20
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-
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9309
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6
60
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9312
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- Group
- 1
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Explode
- Explode a curve into smaller segments.
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- true
- Explode
- Explode
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134
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9295
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- Curve to explode
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-
9226
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57
20
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9254.5
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- Recursive decomposition until all segments are atomic
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9226
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57
20
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9254.5
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- 1
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- 1
- Exploded segments that make up the base curve
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49
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- Vertices of the exploded segments
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9307
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49
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9331.5
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- true
- Evaluate Length
- Evaluate Length
-
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149
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9301
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- Curve to evaluate
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9218
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71
20
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9253.5
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- Length factor for curve evaluation
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- Length
- Length
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- 0
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9218
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71
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9253.5
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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9218
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71
20
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9253.5
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- Point at the specified length
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9313
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50
20
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9338
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- Tangent vector at the specified length
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9313
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50
20
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9338
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- Curve parameter at the specified length
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9313
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50
20
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9338
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- true
- Line SDL
- Line SDL
-
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110
64
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9310
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- Line start point
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9238
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60
20
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9276
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- Line tangent (direction)
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9238
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60
20
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9276
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0
0
1
- Line length
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- true
- Length
- Length
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- 1
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9238
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60
20
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9276
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- Line segment
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- 0
-
9322
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22
60
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9333
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- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
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- true
- Relative Differences
- Relative Differences
-
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116
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9280
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- 1
- List of data to operate on (numbers or points or vectors allowed)
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- Values
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33
24
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9251.5
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- Differences between consecutive items
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-
9292
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55
24
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9319.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- Replace Nulls
- Replace Nulls
-
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139
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9316
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- Items to test for null
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81
20
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9263.5
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- Items to replace nulls with
- 8d723b5a-3612-4eab-af73-2e9dda257360
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81
20
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9263.5
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- List without any nulls
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9328
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30
20
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9343
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- Number of items replaced
- 2ef8dbc1-9970-4aed-a294-6c634264040b
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- Count
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- 0
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30
20
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9343
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- A wire relay object
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40
16
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- Relay
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- A wire relay object
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40
16
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Curve Closest Point
- Find the closest point on a curve.
- true
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- true
- Curve Closest Point
- Curve Closest Point
-
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108
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- Point to project onto curve
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30
30
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- Curve to project onto
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9239
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30
30
-
9254
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- Point on the curve closest to the base point
- 1bb228a2-dc74-42f8-9286-2ea0a61f5541
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- 0
-
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20
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9318
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- Parameter on curve domain of closest point
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- 0
-
9293
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- Distance between base point and curve
- d8765e71-78cd-4bf9-b876-205587255b73
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- false
- 0
-
9293
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50
20
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9318
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- Line
- Create a line between two points.
- true
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- true
- Line
- Line
-
9240
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102
44
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- Line start point
- 58e4e377-468f-4afa-a3a3-179155c40ac4
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- Start Point
- false
- 1bb228a2-dc74-42f8-9286-2ea0a61f5541
- 1
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52
20
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- Line end point
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- false
- 3fc85d3c-c590-41ac-8b1b-785ce2f4dba5
- 1
-
9242
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52
20
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9268
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- Line segment
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- 0
-
9318
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22
40
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9329
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- Remap Numbers
- Remap numbers into a new numeric domain
- true
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- true
- Remap Numbers
- Remap Numbers
-
9214
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154
64
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9314
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- Value to remap
- 7f4d5879-b51d-44a5-bb9a-373af2a4d3e3
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- 3fb5b3a3-cc2e-46cb-b9b3-86a17ddf1e4d
- 1
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9216
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86
20
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- Data 0
- 0
- true
- db990e5a-7101-43fc-8c86-5d17627520de
- 1
-
9228
-46019
78
20
-
9267
-46009
- Formatted text
- 562d6de2-a470-4c87-851a-60f7d73c45ec
- true
- Text
- Text
- false
- 0
-
9330
-46059
24
60
-
9342
-46029
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- a74a9afa-f0e7-461e-8d02-835f7eb99731
- true
- Shift List
-
-
9264
-45777
53
64
-
9297
-45745
- 1
- List to shift
- b3c5bd37-19ee-4b56-9f84-99eeaf530316
- true
- List
-
- false
- e7ce9bba-c98c-4fa4-a826-13e1be5ec64f
- 1
-
9266
-45775
19
20
-
9275.5
-45765
- Shift offset
- 300e0933-a303-4121-98a7-8acbc90708a8
- true
- Shift
-
- false
- 0
-
9266
-45755
19
20
-
9275.5
-45745
- 1
- 1
- {0}
- 1
- Wrap values
- 1468092c-80ba-44ce-aa43-edc3111555c6
- true
- Wrap
-
- false
- 0
-
9266
-45735
19
20
-
9275.5
-45725
- 1
- 1
- {0}
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- 1
- Shifted list
- af081197-1368-48fe-8c47-3880d86c7e8a
- true
- List
-
- false
- 0
-
9309
-45775
6
60
-
9312
-45745
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fb655f23-53fb-4216-9244-493c145ef300
- 5ee7302e-0432-45a9-b320-4441d0df5f9d
- 13a26b56-0263-46e2-aa96-b8798a43d2c3
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- cd2a4e73-beef-4881-af60-1072c3d132d9
- 05e896ad-741a-401e-ae86-0f19c9494cec
- 33
- 0d3e5c8a-1561-4e11-9e1e-e2fca33efcdb
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- fb655f23-53fb-4216-9244-493c145ef300
- true
- Explode
- Explode
-
9224
-48076
134
44
-
9295
-48054
- Curve to explode
- 9767cfc5-25e4-4f8a-945a-f881a57c21aa
- true
- Curve
- Curve
- false
- 5dd2e2a9-34a6-4201-8cc9-620d4b4583f6
- 1
-
9226
-48074
57
20
-
9254.5
-48064
- Recursive decomposition until all segments are atomic
- 183a96dc-67cf-47eb-b503-33704d2de613
- true
- Recursive
- Recursive
- false
- 0
-
9226
-48054
57
20
-
9254.5
-48044
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 34e69f67-2c8a-4d6b-ab01-779325b2045d
- true
- Segments
- Segments
- false
- 0
-
9307
-48074
49
20
-
9331.5
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- 1
- Vertices of the exploded segments
- 0f682b44-c403-4726-bb64-4d33dc0bd13b
- true
- Vertices
- Vertices
- false
- 0
-
9307
-48054
49
20
-
9331.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 5ee7302e-0432-45a9-b320-4441d0df5f9d
- true
- Evaluate Length
- Evaluate Length
-
9216
-48159
149
64
-
9301
-48127
- Curve to evaluate
- 9a07bf97-34e2-444a-8e99-64a693f04333
- true
- Curve
- Curve
- false
- 34e69f67-2c8a-4d6b-ab01-779325b2045d
- 1
-
9218
-48157
71
20
-
9253.5
-48147
- Length factor for curve evaluation
- 1e21ec69-139a-4764-8822-04b4e11b8847
- true
- Length
- Length
- false
- 0
-
9218
-48137
71
20
-
9253.5
-48127
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
- Normalized
- Normalized
- false
- 0
-
9218
-48117
71
20
-
9253.5
-48107
- 1
- 1
- {0}
- true
- Point at the specified length
- c9713282-cead-492a-b99c-1e8de818a7e4
- true
- Point
- Point
- false
- 0
-
9313
-48157
50
20
-
9338
-48147
- Tangent vector at the specified length
- 6dc474d9-a129-4a18-904d-35c727af5e6f
- true
- Tangent
- Tangent
- false
- 0
-
9313
-48137
50
20
-
9338
-48127
- Curve parameter at the specified length
- d98fddae-6984-4a43-a07f-a359e67c1f4e
- true
- Parameter
- Parameter
- false
- 0
-
9313
-48117
50
20
-
9338
-48107
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 13a26b56-0263-46e2-aa96-b8798a43d2c3
- true
- Line SDL
- Line SDL
-
9236
-49939
110
64
-
9310
-49907
- Line start point
- 8ca90ede-8f05-48ff-96b8-962e60d968de
- true
- Start
- Start
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9238
-49937
60
20
-
9276
-49927
- Line tangent (direction)
- bd0c3312-24f2-4240-adc6-f68e9266b467
- true
- Direction
- Direction
- false
- 24cf92d8-0bb7-4e09-b78a-c442ecd7a305
- 1
-
9238
-49917
60
20
-
9276
-49907
- 1
- 1
- {0}
-
0
0
1
- Line length
- 5864852d-a783-4dfb-9d9b-aac5448bf4c7
- ABS(X)
- true
- Length
- Length
- false
- 387a9351-d494-47cf-851b-b4e757e2966e
- 1
-
9238
-49897
60
20
-
9276
-49887
- 1
- 1
- {0}
- 0.015625
- Line segment
- a60b1219-855c-4105-9d60-d49e4c21af43
- true
- Line
- Line
- false
- 0
-
9322
-49937
22
60
-
9333
-49907
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 5d6eced0-8de4-4481-a643-7bfe45510c30
- true
- Relative Differences
- Relative Differences
-
9233
-48502
116
28
-
9280
-48488
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 28b0ff60-628d-4633-8c52-3036259e9a32
- true
- Values
- Values
- false
- 15c4058c-d4ef-48f0-8cd6-a6e9d66cb373
- 1
-
9235
-48500
33
24
-
9251.5
-48488
- 1
- Differences between consecutive items
- b56f4c54-4961-4b83-92cb-a5fc08f6b38b
- true
- Differenced
- Differenced
- false
- 0
-
9292
-48500
55
24
-
9319.5
-48488
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- dd157dd8-02bf-451c-92e4-60a66dd76cd9
- true
- Replace Nulls
- Replace Nulls
-
9221
-48446
139
44
-
9316
-48424
- 1
- Items to test for null
- f6c4fa24-bc33-406c-b097-e39a132737fe
- true
- Items
- Items
- false
- 4b41e74f-ded6-4ba6-9d30-a92b8bd882f4
- 1
-
9223
-48444
81
20
-
9263.5
-48434
- 1
- Items to replace nulls with
- 8b3a37a0-c996-4736-88d7-5ab7c63a7236
- true
- Replacements
- Replacements
- false
- 0
-
9223
-48424
81
20
-
9263.5
-48414
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 15c4058c-d4ef-48f0-8cd6-a6e9d66cb373
- true
- Items
- Items
- false
- 0
-
9328
-48444
30
20
-
9343
-48434
- Number of items replaced
- a2be282f-7c76-48da-8645-5a7224e1ee72
- true
- Count
- Count
- false
- 0
-
9328
-48424
30
20
-
9343
-48414
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4b41e74f-ded6-4ba6-9d30-a92b8bd882f4
- true
- Relay
- false
- 666594ae-a74c-4919-83c2-fc42803f75a7
- 1
-
9271
-48383
40
16
-
9291
-48375
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 6793e99e-b90c-487a-b317-04ab2dc48de9
- true
- Relay
- false
- 75d25b48-e81a-46a3-9843-ac009cb61913
- 1
-
9271
-48747
40
16
-
9291
-48739
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 5d6eced0-8de4-4481-a643-7bfe45510c30
- dd157dd8-02bf-451c-92e4-60a66dd76cd9
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
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- 6793e99e-b90c-487a-b317-04ab2dc48de9
- f9c91711-b3d2-4453-a9eb-775517adcba2
- 8
- d8641b5a-18fd-47ec-99cf-7eb566173a48
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 3a93d28b-110b-43b0-b8c2-580efd293bb4
- true
- Curve Closest Point
- Curve Closest Point
-
9237
-48247
108
64
-
9281
-48215
- Point to project onto curve
- 86defb83-e045-45c7-ac87-bf491e14b959
- true
- Point
- Point
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9239
-48245
30
30
-
9254
-48230
- Curve to project onto
- 8a7848dd-9c5d-4065-88cd-d13e51ecd083
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9239
-48215
30
30
-
9254
-48200
- Point on the curve closest to the base point
- e097ffc2-4a02-4b14-a35a-099424ff6a9b
- true
- Point
- Point
- false
- 0
-
9293
-48245
50
20
-
9318
-48235
- Parameter on curve domain of closest point
- 58554dae-a515-4393-86fb-82d921c5d519
- true
- Parameter
- Parameter
- false
- 0
-
9293
-48225
50
20
-
9318
-48215
- Distance between base point and curve
- 799ed65d-4182-4ee6-bb81-1758bc6d3f32
- true
- Distance
- Distance
- false
- 0
-
9293
-48205
50
20
-
9318
-48195
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 293f4269-47f2-4643-ba3b-3e13a4fe7883
- true
- Line
- Line
-
9240
-48326
102
44
-
9306
-48304
- Line start point
- 4fb679bc-7f98-4a03-add5-497b6adf005f
- true
- Start Point
- Start Point
- false
- e097ffc2-4a02-4b14-a35a-099424ff6a9b
- 1
-
9242
-48324
52
20
-
9268
-48314
- Line end point
- 4c7dad60-41c8-4994-9282-109ef32dfa79
- true
- End Point
- End Point
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9242
-48304
52
20
-
9268
-48294
- Line segment
- 24cf92d8-0bb7-4e09-b78a-c442ecd7a305
- true
- Line
- Line
- false
- 0
-
9318
-48324
22
40
-
9329
-48304
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- a86281e6-4353-4d3f-9eb1-d7653305fca6
- true
- Remap Numbers
- Remap Numbers
-
9214
-49637
154
64
-
9314
-49605
- Value to remap
- 26f31415-96f7-4bd3-b74b-bd5d01d9d20f
- true
- Value
- Value
- false
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- 1
-
9216
-49635
86
20
-
9259
-49625
- Source domain
- ff3e2bfd-dae3-49c4-9eea-ec4da89835ef
- true
- Source
- Source
- false
- a6f1e98e-c654-4b65-9a18-c0d2a1b3b551
- 1
-
9216
-49615
86
20
-
9259
-49605
- 1
- 1
- {0}
-
0
1
- Target domain
- c324c9be-cf72-472a-bdac-be927c4f0854
- true
- Target
- Target
- false
- 0
-
9216
-49595
86
20
-
9259
-49585
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 4f4db73d-5173-4701-a0c5-73cdda611bc9
- true
- Mapped
- Mapped
- false
- 0
-
9326
-49635
40
30
-
9346
-49620
- Remapped and clipped number
- 07e65e72-7094-478b-8fa8-1dd7c589b1f2
- true
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- Clipped
- false
- 0
-
9326
-49605
40
30
-
9346
-49590
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- d727fe22-76d5-43e4-a2ad-e015518775ab
- true
- Bounds
- Bounds
-
9236
-49555
110
28
-
9294
-49541
- 1
- Numbers to include in Bounds
- 937f8b64-1f53-47a0-aace-e59d4558007d
- true
- Numbers
- Numbers
- false
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- 1
-
9238
-49553
44
24
-
9260
-49541
- Numeric Domain between the lowest and highest numbers in {N}
- a6f1e98e-c654-4b65-9a18-c0d2a1b3b551
- true
- Domain
- Domain
- false
- 0
-
9306
-49553
38
24
-
9325
-49541
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- true
- Relay
-
- false
- 6793e99e-b90c-487a-b317-04ab2dc48de9
- 1
-
9271
-49508
40
16
-
9291
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- a8912d4a-a935-4bad-872b-dc57f88db955
- true
- Multiplication
- Multiplication
-
9256
-49836
70
44
-
9281
-49814
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 126229b7-a3c9-48c2-907a-2efa6caee85a
- true
- A
- A
- true
- 40f47511-ffd1-477e-bc85-8e0aba14854a
- 1
-
9258
-49834
11
20
-
9263.5
-49824
- Second item for multiplication
- 63bd6145-31be-4e5b-be6f-5fdcbd3d404b
- true
- B
- B
- true
- 8f638ca0-ed19-449b-9dac-37d0d7994511
- 1
-
9258
-49814
11
20
-
9263.5
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- Result of multiplication
- 387a9351-d494-47cf-851b-b4e757e2966e
- true
- Result
- Result
- false
- 0
-
9293
-49834
31
40
-
9308.5
-49814
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 0af8b992-3a96-476d-9b99-13e9fc9f049e
- true
- Multiplication
- Multiplication
-
9256
-49729
70
44
-
9281
-49707
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- c4f9a2d0-ae90-4fbf-9466-3da40c26020b
- true
- A
- A
- true
- 677cfb40-4f5b-4b46-b8c2-bacf32c9f1f3
- 1
-
9258
-49727
11
20
-
9263.5
-49717
- Second item for multiplication
- 0a679f02-4d5e-4855-973a-578b79a2e366
- true
- B
- B
- true
- 4f4db73d-5173-4701-a0c5-73cdda611bc9
- 1
-
9258
-49707
11
20
-
9263.5
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Curve to evaluate
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- Length factor for curve evaluation
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Line start point
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- Compute relative differences for a list of data
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- Replace nulls or invalid data with other data
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- Find the closest point on a curve.
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- Point on the curve closest to the base point
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- Line
- Create a line between two points.
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- Line start point
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- Line end point
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- Line segment
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- Remap numbers into a new numeric domain
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- Value to remap
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- Source domain
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- Remapped number
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- Remapped and clipped number
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40
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- Create a numeric domain which encompasses a list of numbers.
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- Numbers to include in Bounds
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- Numeric Domain between the lowest and highest numbers in {N}
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- A wire relay object
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- Mathematical multiplication
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- First item for multiplication
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11
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- Second item for multiplication
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- Second item for multiplication
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- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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100
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- Allows for customized geometry previews
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- Custom Preview
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255;66;48;66
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255;255;255;255
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Create an OpenGL material.
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- Create Material
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- Emissive colour of the material
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9217
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- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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255;255;255;255
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- Display a set of y-values as a graph
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- Length
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- Replace nulls or invalid data with other data
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- Replace Nulls
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- Items to replace nulls with
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- List without any nulls
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- A group of Grasshopper objects
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- Find the closest point on a curve.
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- Curve Closest Point
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- Point on the curve closest to the base point
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- Create a line between two points.
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- Line
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- Line segment
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- Remap numbers into a new numeric domain
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- Remap Numbers
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- Value to remap
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- Source domain
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- Create a numeric domain which encompasses a list of numbers.
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- Bounds
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- Numbers to include in Bounds
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- Numeric Domain between the lowest and highest numbers in {N}
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- Relay
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- A wire relay object
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- Multiplication
- Mathematical multiplication
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- Second item for multiplication
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- Multiplication
- Mathematical multiplication
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255;255;255;255
- A group of Grasshopper objects
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255;255;255;255
- A group of Grasshopper objects
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- Panel
- A panel for custom notes and text values
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255;255;255;255
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255;255;255;255
- A group of Grasshopper objects
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255;0;255;255
- Emissive colour of the material
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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- Resulting material
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- Allows for customized geometry previews
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255;255;255;255
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- Curve to evaluate
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- Length factor for curve evaluation
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- Point at the specified length
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- Tangent vector at the specified length
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28
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9281
-4549
- Boolean value
- 4a19fc6e-2d7a-471b-bcce-d5a1412e0f43
- true
- A
- A
- false
- 80f66cc8-3f0d-4c83-97be-347c0623d535
- 1
-
9258
-4561
11
24
-
9263.5
-4549
- Inverse of {A}
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- true
- Result
- Result
- false
- 0
-
9293
-4561
31
24
-
9308.5
-4549
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 0fb387e0-8efc-430a-ad2a-08f863556546
- true
- Stream Filter
- Stream Filter
-
9258
-9145
77
64
-
9297
-9113
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 06399296-3657-4782-9f14-124355221b9f
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9260
-9143
25
20
-
9272.5
-9133
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 3ce03926-3ca1-4b34-9f25-cd3e173de9c7
- true
- false
- Stream 0
- 0
- true
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9260
-9123
25
20
-
9272.5
-9113
- 2
- Input stream at index 1
- 857fca33-c58b-41c7-8da9-c407944e98d0
- true
- false
- Stream 1
- 1
- true
- 6bd020fd-c652-4ed0-a741-6c88bd6ac075
- 1
-
9260
-9103
25
20
-
9272.5
-9093
- 2
- Filtered stream
- f05ffc93-07b8-46d2-ad82-99badcc3922f
- true
- false
- Stream
- S(0)
- false
- 0
-
9309
-9143
24
60
-
9321
-9113
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- 67c2acc7-61e8-4dc8-a403-e7221b033383
- true
- Pull Curve
- Pull Curve
-
9248
-8754
96
44
-
9300
-8732
- Curve to pull
- bf9a89d7-1a9d-482a-bf2a-6b0992a45c8e
- true
- Curve
- Curve
- false
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9250
-8752
38
20
-
9269
-8742
- Surface that pulls
- b5456d1f-1e8c-44b5-ab48-3f4ff8a70665
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9250
-8732
38
20
-
9269
-8722
- Curve pulled onto the surface
- f6a8a08e-b879-4b59-a042-87b09c2b6c2b
- true
- Curve
- Curve
- false
- 0
-
9312
-8752
30
40
-
9327
-8732
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 3aa22581-402f-4750-9268-ebe07eb256aa
- true
- Stream Filter
- Stream Filter
-
9252
-6015
77
64
-
9291
-5983
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0b765458-3919-4cd0-993f-6aa485fe7bf3
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9254
-6013
25
20
-
9266.5
-6003
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 90c1f92c-2d02-411c-9226-2b4827ecba0a
- true
- false
- Stream 0
- 0
- true
- 58715e09-1461-47aa-b311-c9878cbef364
- 1
-
9254
-5993
25
20
-
9266.5
-5983
- 2
- Input stream at index 1
- 37f8811e-d59a-4893-874f-2b9c4546f538
- true
- false
- Stream 1
- 1
- true
- 4a40ed77-eaa2-427a-b632-c4c14ac83a0b
- 1
-
9254
-5973
25
20
-
9266.5
-5963
- 2
- Filtered stream
- 043ef658-425b-4fc2-a0ed-57be30e7b117
- true
- false
- Stream
- S(0)
- false
- 0
-
9303
-6013
24
60
-
9315
-5983
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cffd2b57-8bcb-4248-b984-bdaff8648b5a
- true
- Pull Point
- Pull Point
-
9218
-5913
139
44
-
9280
-5891
- Point to search from
- fe439557-86d3-43a2-8342-9265ab7171de
- true
- Point
- Point
- false
- 58715e09-1461-47aa-b311-c9878cbef364
- 1
-
9220
-5911
48
20
-
9244
-5901
- 1
- Geometry that pulls
- 9eeef12b-bde5-45d2-bce9-93075540eb20
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9220
-5891
48
20
-
9244
-5881
- Point on [G] closest to [P]
- 4a40ed77-eaa2-427a-b632-c4c14ac83a0b
- true
- Closest Point
- Closest Point
- false
- 0
-
9292
-5911
63
20
-
9323.5
-5901
- Distance between [P] and its projection onto [G]
- c687cd8d-0db6-4027-9696-f010a1126597
- true
- Distance
- Distance
- false
- 0
-
9292
-5891
63
20
-
9323.5
-5881
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 345d893b-ae16-4ece-bd87-af320cd62598
- true
- Stream Filter
- Stream Filter
-
9253
-9703
77
64
-
9292
-9671
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 77af05a8-653a-45bd-830f-5a0030ac485c
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9255
-9701
25
20
-
9267.5
-9691
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- a3a17ee1-6a78-4b93-a151-c427f687d7e9
- true
- false
- Stream 0
- 0
- true
- a87341fb-0950-4665-a5d5-5556809dce9d
- 1
-
9255
-9681
25
20
-
9267.5
-9671
- 2
- Input stream at index 1
- d52d4520-ddac-4ef0-93e6-a0f531a518f5
- true
- false
- Stream 1
- 1
- true
- d93903ee-cfd9-4f91-a642-a9eaaec44230
- 1
-
9255
-9661
25
20
-
9267.5
-9651
- 2
- Filtered stream
- 2b484d46-7738-42ff-b212-eea1c16c05f0
- true
- false
- Stream
- S(0)
- false
- 0
-
9304
-9701
24
60
-
9316
-9671
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 1da4a747-337d-46d9-818d-512d2d11e43e
- true
- Pull Point
- Pull Point
-
9222
-9617
139
44
-
9284
-9595
- Point to search from
- 5e66e12e-afa5-4667-a021-d5ac897d3938
- true
- Point
- Point
- false
- a87341fb-0950-4665-a5d5-5556809dce9d
- 1
-
9224
-9615
48
20
-
9248
-9605
- 1
- Geometry that pulls
- 54065e6e-a92c-4ad6-99ee-f60600a2edea
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9224
-9595
48
20
-
9248
-9585
- Point on [G] closest to [P]
- d93903ee-cfd9-4f91-a642-a9eaaec44230
- true
- Closest Point
- Closest Point
- false
- 0
-
9296
-9615
63
20
-
9327.5
-9605
- Distance between [P] and its projection onto [G]
- 2e023752-5825-4542-b000-932bfa2ad17b
- true
- Distance
- Distance
- false
- 0
-
9296
-9595
63
20
-
9327.5
-9585
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a8f38f9e-b3b6-41bd-8db4-16fabd280f08
- true
- Stream Filter
- Stream Filter
-
9240
-12697
77
64
-
9279
-12665
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 765f81d8-ff1a-4ba1-a493-527c32710a12
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9242
-12695
25
20
-
9254.5
-12685
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- cf08a60a-85fc-4f3b-9da2-15233702dcb6
- true
- false
- Stream 0
- 0
- true
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9242
-12675
25
20
-
9254.5
-12665
- 2
- Input stream at index 1
- 48956a2f-d6d5-40df-a623-85bf867ad2c8
- true
- false
- Stream 1
- 1
- true
- 21adf162-6466-48ed-b0e4-8aa61cab45ec
- 1
-
9242
-12655
25
20
-
9254.5
-12645
- 2
- Filtered stream
- 1e2a7b7f-adc5-4de7-b89a-18f9809254ce
- true
- false
- Stream
- S(0)
- false
- 0
-
9291
-12695
24
60
-
9303
-12665
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- 99f6eb91-99d8-4603-b7d0-eca216200d71
- true
- Pull Curve
- Pull Curve
-
9243
-12281
96
44
-
9295
-12259
- Curve to pull
- 0fc24e2e-c021-40bb-b392-83f0246cbe7c
- true
- Curve
- Curve
- false
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9245
-12279
38
20
-
9264
-12269
- Surface that pulls
- d0cd04f6-9e03-4121-8fb3-ce8a508d7d13
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9245
-12259
38
20
-
9264
-12249
- Curve pulled onto the surface
- 2a1421bd-02db-438e-a5d2-207894cd0bdf
- true
- Curve
- Curve
- false
- 0
-
9307
-12279
30
40
-
9322
-12259
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 27beda7a-8035-4b7f-baa6-07b36b445f36
- true
- Stream Filter
- Stream Filter
-
9249
-13260
77
64
-
9288
-13228
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- eb605005-2673-4e61-ba1f-8c64b2ef9ade
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9251
-13258
25
20
-
9263.5
-13248
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- f7702fdb-1b65-460e-9e74-92dca8113c0c
- true
- false
- Stream 0
- 0
- true
- 042a386a-fcdb-4902-bf3e-1cca2eff73b7
- 1
-
9251
-13238
25
20
-
9263.5
-13228
- 2
- Input stream at index 1
- cfa06fd1-5b9b-4ca9-ad9f-5fb3d360486e
- true
- false
- Stream 1
- 1
- true
- ad599a39-f198-4941-8d4e-7089ae235a5c
- 1
-
9251
-13218
25
20
-
9263.5
-13208
- 2
- Filtered stream
- 33a6314b-e63e-4e80-b5e3-dcd21060daa4
- true
- false
- Stream
- S(0)
- false
- 0
-
9300
-13258
24
60
-
9312
-13228
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 344c01b0-b3be-4158-b3f3-3e875533be20
- true
- Pull Point
- Pull Point
-
9218
-13174
139
44
-
9280
-13152
- Point to search from
- d8d70767-e3b6-4210-87e4-db9f5422e6d5
- true
- Point
- Point
- false
- 042a386a-fcdb-4902-bf3e-1cca2eff73b7
- 1
-
9220
-13172
48
20
-
9244
-13162
- 1
- Geometry that pulls
- 3e9f1b53-15bb-4e99-8471-f8f99e6dd451
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9220
-13152
48
20
-
9244
-13142
- Point on [G] closest to [P]
- ad599a39-f198-4941-8d4e-7089ae235a5c
- true
- Closest Point
- Closest Point
- false
- 0
-
9292
-13172
63
20
-
9323.5
-13162
- Distance between [P] and its projection onto [G]
- 3619df5e-57e4-4d5b-94ee-4852c16b2c53
- true
- Distance
- Distance
- false
- 0
-
9292
-13152
63
20
-
9323.5
-13142
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- 50e1ac8e-1daf-4c52-bfc9-ae6c4c4b5d7f
- true
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- false
- e29ca557-b1ee-475d-8cd9-63721b3e955d
- 1
-
9161
-16336
260
24
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4337397e-3fc7-4255-8ed1-ffd880a2c289
- true
- Stream Filter
- Stream Filter
-
9253
-16279
77
64
-
9292
-16247
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 65692a58-3f42-4520-b6a7-f0151dcc0718
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9255
-16277
25
20
-
9267.5
-16267
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 2468b678-acbf-4073-b3ae-54742b7c16b3
- true
- false
- Stream 0
- 0
- true
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9255
-16257
25
20
-
9267.5
-16247
- 2
- Input stream at index 1
- f5e32804-3e4e-4b0b-a77b-6482c099a921
- true
- false
- Stream 1
- 1
- true
- fa5104ec-99e6-4c5c-94e7-3b82a0aab230
- 1
-
9255
-16237
25
20
-
9267.5
-16227
- 2
- Filtered stream
- e29ca557-b1ee-475d-8cd9-63721b3e955d
- true
- false
- Stream
- S(0)
- false
- 0
-
9304
-16277
24
60
-
9316
-16247
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- da88dd80-8efd-4e21-a39e-70ce76cc2119
- true
- Pull Curve
- Pull Curve
-
9248
-15858
96
44
-
9300
-15836
- Curve to pull
- 7d3eb441-b313-4123-b7c6-6acfea0e0451
- true
- Curve
- Curve
- false
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9250
-15856
38
20
-
9269
-15846
- Surface that pulls
- 35ff5b6f-8d0b-47ef-92d9-7c8f0c53416d
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9250
-15836
38
20
-
9269
-15826
- Curve pulled onto the surface
- 4ce8f03b-1734-4055-b3e3-dd585ded15d2
- true
- Curve
- Curve
- false
- 0
-
9312
-15856
30
40
-
9327
-15836
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e63d5bc1-5483-4565-b5c9-382b62dd7532
- true
- Stream Filter
- Stream Filter
-
9251
-16905
77
64
-
9290
-16873
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- ce043f9d-fe44-4b8a-9441-a4276d4b4af8
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9253
-16903
25
20
-
9265.5
-16893
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dc38c735-e61f-40d1-9269-c26f9f69c8ad
- true
- false
- Stream 0
- 0
- true
- 4c437000-729e-49e9-9151-342e882d2ecc
- 1
-
9253
-16883
25
20
-
9265.5
-16873
- 2
- Input stream at index 1
- 426541d6-3cf4-43c2-8d13-42c3fb62ef71
- true
- false
- Stream 1
- 1
- true
- cdf037a9-f123-4d5a-86f7-16caaac5483f
- 1
-
9253
-16863
25
20
-
9265.5
-16853
- 2
- Filtered stream
- bab303dd-61c9-49e9-a983-cbe9cf957b57
- true
- false
- Stream
- S(0)
- false
- 0
-
9302
-16903
24
60
-
9314
-16873
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 05d4fb4f-a50c-46d2-9aa5-be6d19680490
- true
- Pull Point
- Pull Point
-
9222
-16801
139
44
-
9284
-16779
- Point to search from
- 0e77c4aa-a22e-4306-beba-f9596e55ae3c
- true
- Point
- Point
- false
- 4c437000-729e-49e9-9151-342e882d2ecc
- 1
-
9224
-16799
48
20
-
9248
-16789
- 1
- Geometry that pulls
- 935e197b-5830-4f82-9942-4df625646cfd
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9224
-16779
48
20
-
9248
-16769
- Point on [G] closest to [P]
- cdf037a9-f123-4d5a-86f7-16caaac5483f
- true
- Closest Point
- Closest Point
- false
- 0
-
9296
-16799
63
20
-
9327.5
-16789
- Distance between [P] and its projection onto [G]
- 83b3f5e8-b221-404e-8d7c-8b3273cef8bd
- true
- Distance
- Distance
- false
- 0
-
9296
-16779
63
20
-
9327.5
-16769
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- 30482e7c-7286-4502-a14e-85a6c35b7c79
- true
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- false
- 1e2a7b7f-adc5-4de7-b89a-18f9809254ce
- 1
-
9155
-12746
272
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- cd5b889e-e4dd-448f-9673-4b231165ae21
- true
- CURWE INPUT
- CURWE INPUT
- false
- 0
-
9248
-599
101
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
- f26535d4-91e9-4d8f-8216-dab8258daddf
- true
- CURWE OUTPUT
- CURWE OUTPUT
- false
- 41be65b0-4832-475b-82e4-72e5cbea050c
- 1
-
9235
-738
112
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- 7821d745-ea35-4b5e-9bc1-0ed25432d936
- true
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- false
- 0
-
9210
-2092
178
24
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- true
- Number
- Number
- false
- 0
-
9267
-2126
52
24
-
9307.541
-2114.887
- 1
- 1
- {0}
- 256
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- 63995dad-5a38-4819-9bc6-c7368d2aa8c0
- true
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- false
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- 1
-
9204
-2195
189
24
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 811f77e7-8403-4ccc-a67a-e88eab309b40
- true
- 2
- Number
- Number
- false
- 0
-
9273
-4115
50
24
-
9306.541
-4103.887
- 1
- 2
- {0}
- 0
- 180
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- 8bb07237-8043-4bfc-9482-36c5f324e171
- true
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- false
- 0
-
9128
-4086
341
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- 99e87cc0-6a4b-442b-884b-8221f251b9bf
- true
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- false
- 811f77e7-8403-4ccc-a67a-e88eab309b40
- 1
-
9123
-4169
352
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- 1bf8b430-d382-4280-aaec-0188aafb741b
- true
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- false
- 0
-
9210
-4329
156
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- fd8be7fd-657d-4392-aabd-296e39ed305b
- true
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9220
-4422
167
24
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
- true
- d2b2d690-7218-44bb-aa7c-3040cab09077
- true
- Surface
- Surface
- false
- 1bf8b430-d382-4280-aaec-0188aafb741b
- 1
-
9271
-4359
50
24
-
9296.633
-4347
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- d992dcbb-ebd0-41d4-96b3-793a6c463864
- true
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- false
- 4a88ebb8-f367-4644-9b81-883895d1f5b5
- 1
-
9185
-5503
239
24
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4a88ebb8-f367-4644-9b81-883895d1f5b5
- true
- Relay
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9272
-5497
40
16
-
9292
-5489
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- 1bfd648a-9dbf-4c36-aaf1-6faf76bdedb5
- true
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- false
- 0
-
9136
-8490
318
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- 87c359c8-b31a-41d3-b2bd-e7427c264c27
- true
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- false
- f05ffc93-07b8-46d2-ad82-99badcc3922f
- 1
-
9138
-9208
325
24
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 4ce1f53e-bf61-44f8-95a4-3bf2d4d1053a
- true
- End Points
- End Points
-
9258
-5087
84
44
-
9302
-5065
- Curve to evaluate
- 8dae861f-afe2-42b0-9cb4-014ad80440a7
- true
- Curve
- Curve
- false
- 2158b91e-623b-4f9d-8297-f4edb0d6540d
- 1
-
9260
-5085
30
40
-
9275
-5065
- Curve start point
- 02964a7a-328e-4e32-b6c3-ac54c648bd49
- true
- Start
- Start
- false
- 0
-
9314
-5085
26
20
-
9327
-5075
- Curve end point
- 880ada06-8e88-49d0-a801-f5c9b0f2ca43
- true
- End
- End
- false
- 0
-
9314
-5065
26
20
-
9327
-5055
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 745e50c0-24f0-4225-8841-a5b5f1afa79a
- true
- Line
- Line
-
9252
-5317
102
44
-
9318
-5295
- Line start point
- a5d03a6d-660c-4a71-bd5e-77182badde8d
- true
- Start Point
- Start Point
- false
- b3380cd0-b123-474a-bec6-3ad36c042595
- 1
-
9254
-5315
52
20
-
9280
-5305
- Line end point
- 522b2fbe-2fde-49b8-8c7e-bd72f92ea85a
- true
- End Point
- End Point
- false
- 937ad2f4-5ea8-48a5-a340-e4353478cf5d
- 1
-
9254
-5295
52
20
-
9280
-5285
- Line segment
- 6eec554b-c75f-4491-ab5f-2ae78a628fbd
- true
- Line
- Line
- false
- 0
-
9330
-5315
22
40
-
9341
-5295
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- b0c7518a-4219-4602-839c-235029b1a34d
- true
- Pull Point
- Pull Point
-
9230
-5252
139
44
-
9292
-5230
- Point to search from
- 6420395e-ae10-439c-861f-5521d6b29247
- true
- Point
- Point
- false
- 02964a7a-328e-4e32-b6c3-ac54c648bd49
- 1
-
9232
-5250
48
20
-
9256
-5240
- 1
- Geometry that pulls
- d0a38b31-0118-4144-a9da-672b0ab438fe
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9232
-5230
48
20
-
9256
-5220
- Point on [G] closest to [P]
- b3380cd0-b123-474a-bec6-3ad36c042595
- true
- Closest Point
- Closest Point
- false
- 0
-
9304
-5250
63
20
-
9335.5
-5240
- Distance between [P] and its projection onto [G]
- e90fc0ab-3867-40e6-8233-7a7f6cfaf7ce
- true
- Distance
- Distance
- false
- 0
-
9304
-5230
63
20
-
9335.5
-5220
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 4a12da5d-898e-4144-8e8d-1b907f89642d
- true
- Pull Point
- Pull Point
-
9230
-5171
139
44
-
9292
-5149
- Point to search from
- 213f65d7-b440-4029-b830-2d5d796c2542
- true
- Point
- Point
- false
- 880ada06-8e88-49d0-a801-f5c9b0f2ca43
- 1
-
9232
-5169
48
20
-
9256
-5159
- 1
- Geometry that pulls
- a05f35ae-e2dc-4338-a49b-4407ac509c21
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9232
-5149
48
20
-
9256
-5139
- Point on [G] closest to [P]
- 937ad2f4-5ea8-48a5-a340-e4353478cf5d
- true
- Closest Point
- Closest Point
- false
- 0
-
9304
-5169
63
20
-
9335.5
-5159
- Distance between [P] and its projection onto [G]
- 933aaf31-a580-4971-99cd-3b6db6bd23a6
- true
- Distance
- Distance
- false
- 0
-
9304
-5149
63
20
-
9335.5
-5139
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 3697088f-7b9c-42f6-bd64-2174aa7f816c
- true
- End Points
- End Points
-
9244
-8813
84
44
-
9288
-8791
- Curve to evaluate
- 22caa755-7d7e-430f-9f50-e8a634162200
- true
- Curve
- Curve
- false
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9246
-8811
30
40
-
9261
-8791
- Curve start point
- 9657b5c7-9576-49ed-a6d7-ae032aeec3e9
- true
- Start
- Start
- false
- 0
-
9300
-8811
26
20
-
9313
-8801
- Curve end point
- 3d1c3c8e-ba45-4486-ad01-a0d1d102f456
- true
- End
- End
- false
- 0
-
9300
-8791
26
20
-
9313
-8781
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- ca04f8b3-a611-47df-b7e3-410b2099d099
- true
- Line
- Line
-
9235
-9036
102
44
-
9301
-9014
- Line start point
- b67fb9a3-7a4e-4873-9782-0b17a8a5c446
- true
- Start Point
- Start Point
- false
- 3eca4bac-2695-407c-9f4e-de9f268b685e
- 1
-
9237
-9034
52
20
-
9263
-9024
- Line end point
- d59b3a89-55ca-4698-a494-1201157d81dc
- true
- End Point
- End Point
- false
- 829d4ae8-b090-4cbd-84cb-f25ffc968842
- 1
-
9237
-9014
52
20
-
9263
-9004
- Line segment
- 6bd020fd-c652-4ed0-a741-6c88bd6ac075
- true
- Line
- Line
- false
- 0
-
9313
-9034
22
40
-
9324
-9014
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 8ab55463-0601-4907-8574-cbbcbe9cdf41
- true
- Pull Point
- Pull Point
-
9217
-8971
139
44
-
9279
-8949
- Point to search from
- 0e73b6dc-4f45-4736-bd0e-75ae29de8c32
- true
- Point
- Point
- false
- 9657b5c7-9576-49ed-a6d7-ae032aeec3e9
- 1
-
9219
-8969
48
20
-
9243
-8959
- 1
- Geometry that pulls
- b6589601-2a37-4656-b7c4-890bc1b15999
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9219
-8949
48
20
-
9243
-8939
- Point on [G] closest to [P]
- 3eca4bac-2695-407c-9f4e-de9f268b685e
- true
- Closest Point
- Closest Point
- false
- 0
-
9291
-8969
63
20
-
9322.5
-8959
- Distance between [P] and its projection onto [G]
- e7e57fe1-4371-40f7-8233-7868f5beca3c
- true
- Distance
- Distance
- false
- 0
-
9291
-8949
63
20
-
9322.5
-8939
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- b583d1cf-7a3f-4052-8904-153d81fdfdee
- true
- Pull Point
- Pull Point
-
9217
-8892
139
44
-
9279
-8870
- Point to search from
- 4fffb62b-fa07-4251-9e58-7a65bd99eb48
- true
- Point
- Point
- false
- 3d1c3c8e-ba45-4486-ad01-a0d1d102f456
- 1
-
9219
-8890
48
20
-
9243
-8880
- 1
- Geometry that pulls
- 15fcd9c7-22e4-4b03-bb4d-a4cb0e7ef473
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9219
-8870
48
20
-
9243
-8860
- Point on [G] closest to [P]
- 829d4ae8-b090-4cbd-84cb-f25ffc968842
- true
- Closest Point
- Closest Point
- false
- 0
-
9291
-8890
63
20
-
9322.5
-8880
- Distance between [P] and its projection onto [G]
- 590f8387-cbeb-4dcf-ab7c-2ee9a7c60ed0
- true
- Distance
- Distance
- false
- 0
-
9291
-8870
63
20
-
9322.5
-8860
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 4ce1f53e-bf61-44f8-95a4-3bf2d4d1053a
- 745e50c0-24f0-4225-8841-a5b5f1afa79a
- b0c7518a-4219-4602-839c-235029b1a34d
- 4a12da5d-898e-4144-8e8d-1b907f89642d
- 4
- d9196d88-f6ed-4b14-bb1c-1f183f4a7723
- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 3697088f-7b9c-42f6-bd64-2174aa7f816c
- ca04f8b3-a611-47df-b7e3-410b2099d099
- 8ab55463-0601-4907-8574-cbbcbe9cdf41
- b583d1cf-7a3f-4052-8904-153d81fdfdee
- 4
- 772ea870-567a-4c8e-ad36-cc1a3d7ca545
- Group
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- a4a57a95-519b-4236-a616-ec04d6438608
- true
- End Points
- End Points
-
9240
-12366
84
44
-
9284
-12344
- Curve to evaluate
- d142dd1e-e179-418f-b26a-0b0d1dae7ab5
- true
- Curve
- Curve
- false
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9242
-12364
30
40
-
9257
-12344
- Curve start point
- 126cde73-2db3-4894-9089-9c82ea8d9b3e
- true
- Start
- Start
- false
- 0
-
9296
-12364
26
20
-
9309
-12354
- Curve end point
- c886c9ca-e196-4a6e-86e8-e74a60881897
- true
- End
- End
- false
- 0
-
9296
-12344
26
20
-
9309
-12334
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 598915a3-e2fc-4bfb-b83f-aae6b06a75b4
- true
- Line
- Line
-
9231
-12589
102
44
-
9297
-12567
- Line start point
- 40d6e324-be45-4d56-b251-3dcff95ccada
- true
- Start Point
- Start Point
- false
- 608f6c3c-fd1f-4abb-ab11-9dbcb84297f7
- 1
-
9233
-12587
52
20
-
9259
-12577
- Line end point
- 1ba5e492-30bf-4985-b02c-c43e3b73f577
- true
- End Point
- End Point
- false
- e3ae76f8-04a9-4f7b-ba81-3036c248ecd0
- 1
-
9233
-12567
52
20
-
9259
-12557
- Line segment
- 21adf162-6466-48ed-b0e4-8aa61cab45ec
- true
- Line
- Line
- false
- 0
-
9309
-12587
22
40
-
9320
-12567
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 09211b76-ab65-4e72-8300-b36fcf6d33fe
- true
- Pull Point
- Pull Point
-
9213
-12524
139
44
-
9275
-12502
- Point to search from
- ac3a9740-ea3a-4365-ac94-3d1adb5db8c6
- true
- Point
- Point
- false
- 126cde73-2db3-4894-9089-9c82ea8d9b3e
- 1
-
9215
-12522
48
20
-
9239
-12512
- 1
- Geometry that pulls
- 3893bd59-caa5-4dc9-88bd-a5638da7ea20
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9215
-12502
48
20
-
9239
-12492
- Point on [G] closest to [P]
- 608f6c3c-fd1f-4abb-ab11-9dbcb84297f7
- true
- Closest Point
- Closest Point
- false
- 0
-
9287
-12522
63
20
-
9318.5
-12512
- Distance between [P] and its projection onto [G]
- 55874175-aeed-4069-9e8c-1eaaf48001a2
- true
- Distance
- Distance
- false
- 0
-
9287
-12502
63
20
-
9318.5
-12492
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- ef4b781e-70ad-4c5e-a3b3-3c742b04b013
- true
- Pull Point
- Pull Point
-
9213
-12445
139
44
-
9275
-12423
- Point to search from
- cfba421d-b82d-401a-b22a-40856c2c259e
- true
- Point
- Point
- false
- c886c9ca-e196-4a6e-86e8-e74a60881897
- 1
-
9215
-12443
48
20
-
9239
-12433
- 1
- Geometry that pulls
- 087a1959-4b4b-453c-b2bc-a946e32d298d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9215
-12423
48
20
-
9239
-12413
- Point on [G] closest to [P]
- e3ae76f8-04a9-4f7b-ba81-3036c248ecd0
- true
- Closest Point
- Closest Point
- false
- 0
-
9287
-12443
63
20
-
9318.5
-12433
- Distance between [P] and its projection onto [G]
- e47640d6-f942-4fb8-806e-736ae5daf030
- true
- Distance
- Distance
- false
- 0
-
9287
-12423
63
20
-
9318.5
-12413
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a4a57a95-519b-4236-a616-ec04d6438608
- 598915a3-e2fc-4bfb-b83f-aae6b06a75b4
- 09211b76-ab65-4e72-8300-b36fcf6d33fe
- ef4b781e-70ad-4c5e-a3b3-3c742b04b013
- 4
- 84271252-bd7b-4112-8561-43533ed4300d
- Group
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- fcdc1273-4010-457e-80e8-d6d2a5d24510
- true
- End Points
- End Points
-
9252
-15945
84
44
-
9296
-15923
- Curve to evaluate
- 596b6dfd-cafe-4d30-b26e-8cf2395a2f0f
- true
- Curve
- Curve
- false
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9254
-15943
30
40
-
9269
-15923
- Curve start point
- ad6e4059-cf08-4266-9c07-b1a6d3da3632
- true
- Start
- Start
- false
- 0
-
9308
-15943
26
20
-
9321
-15933
- Curve end point
- 47fbfce5-2649-4fe6-84d2-5ca940b91239
- true
- End
- End
- false
- 0
-
9308
-15923
26
20
-
9321
-15913
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- efcfa711-59f2-48c9-bcfb-c0892d3a75e4
- true
- Line
- Line
-
9243
-16168
102
44
-
9309
-16146
- Line start point
- d928da3a-7042-4685-be2a-1b49f40f181d
- true
- Start Point
- Start Point
- false
- 23d52e4e-bbda-4d7f-844c-64c4e07fdc3b
- 1
-
9245
-16166
52
20
-
9271
-16156
- Line end point
- 0699787b-b73a-496f-aeaa-4e621de61a86
- true
- End Point
- End Point
- false
- f476e52c-9f16-4cf9-9dc8-53464df41ada
- 1
-
9245
-16146
52
20
-
9271
-16136
- Line segment
- fa5104ec-99e6-4c5c-94e7-3b82a0aab230
- true
- Line
- Line
- false
- 0
-
9321
-16166
22
40
-
9332
-16146
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 9961c67c-7b6b-4764-bdd1-a1e48583f369
- true
- Pull Point
- Pull Point
-
9225
-16103
139
44
-
9287
-16081
- Point to search from
- 10023702-d29c-4ed1-a06b-2e077fc9a36e
- true
- Point
- Point
- false
- ad6e4059-cf08-4266-9c07-b1a6d3da3632
- 1
-
9227
-16101
48
20
-
9251
-16091
- 1
- Geometry that pulls
- a5a19b7e-cc7b-472d-af7e-50bd165f0291
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9227
-16081
48
20
-
9251
-16071
- Point on [G] closest to [P]
- 23d52e4e-bbda-4d7f-844c-64c4e07fdc3b
- true
- Closest Point
- Closest Point
- false
- 0
-
9299
-16101
63
20
-
9330.5
-16091
- Distance between [P] and its projection onto [G]
- 340b9418-c6dc-4b6b-b0ff-952302865f58
- true
- Distance
- Distance
- false
- 0
-
9299
-16081
63
20
-
9330.5
-16071
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 849936c1-69a8-4734-8c4b-cd2e6354bc19
- true
- Pull Point
- Pull Point
-
9225
-16024
139
44
-
9287
-16002
- Point to search from
- 7804dddf-f9e6-4021-aba2-4f4236e58c4d
- true
- Point
- Point
- false
- 47fbfce5-2649-4fe6-84d2-5ca940b91239
- 1
-
9227
-16022
48
20
-
9251
-16012
- 1
- Geometry that pulls
- 52da7787-182c-47ab-b503-dbddb37e317d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9227
-16002
48
20
-
9251
-15992
- Point on [G] closest to [P]
- f476e52c-9f16-4cf9-9dc8-53464df41ada
- true
- Closest Point
- Closest Point
- false
- 0
-
9299
-16022
63
20
-
9330.5
-16012
- Distance between [P] and its projection onto [G]
- 351ed84f-f1d6-4fc1-b0a9-9295c12aa741
- true
- Distance
- Distance
- false
- 0
-
9299
-16002
63
20
-
9330.5
-15992
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fcdc1273-4010-457e-80e8-d6d2a5d24510
- efcfa711-59f2-48c9-bcfb-c0892d3a75e4
- 9961c67c-7b6b-4764-bdd1-a1e48583f369
- 849936c1-69a8-4734-8c4b-cd2e6354bc19
- 4
- 20768bee-5b47-4218-ad74-075117bbc07d
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 22729d4a-b218-4fd7-989a-a31c84d0f10d
- true
- Stream Filter
- Stream Filter
-
9254
-19922
77
64
-
9293
-19890
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 8c435c18-1c44-4dc4-bfc6-2d79f98fdc94
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9256
-19920
25
20
-
9268.5
-19910
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 4b62bba8-d476-48b3-901d-1d8c18192635
- true
- false
- Stream 0
- 0
- true
- b222f383-0934-4242-940d-878ab3058ed4
- 1
-
9256
-19900
25
20
-
9268.5
-19890
- 2
- Input stream at index 1
- c04c446d-807e-48cc-b595-607445751779
- true
- false
- Stream 1
- 1
- true
- 70dbeb6f-403d-4459-9312-a0aa407b68fe
- 1
-
9256
-19880
25
20
-
9268.5
-19870
- 2
- Filtered stream
- e2196bca-51e1-4e30-9af9-41a11d87bd51
- true
- false
- Stream
- S(0)
- false
- 0
-
9305
-19920
24
60
-
9317
-19890
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- db7d019a-d6ff-498f-b514-5ea0e3912544
- true
- Stream Filter
- Stream Filter
-
9221
-20457
77
64
-
9260
-20425
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 613da226-e593-4484-90ed-b34623433f20
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9223
-20455
25
20
-
9235.5
-20445
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 24cf5d70-fc28-4a67-aa22-b6cd66137b41
- true
- false
- Stream 0
- 0
- true
- e4642eb7-9328-471f-b935-fefc6d0913b2
- 1
-
9223
-20435
25
20
-
9235.5
-20425
- 2
- Input stream at index 1
- 18e84f39-6a41-4c97-89b1-a57ebb0eea77
- true
- false
- Stream 1
- 1
- true
- c046a698-34b6-4f2a-8d95-ed65bd2086e5
- 1
-
9223
-20415
25
20
-
9235.5
-20405
- 2
- Filtered stream
- 37e45a94-23d7-420f-b036-38884c3e20f7
- true
- false
- Stream
- S(0)
- false
- 0
-
9272
-20455
24
60
-
9284
-20425
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 160e178b-42c7-40d2-a1ec-81249c9df8bf
- true
- Pull Point
- Pull Point
-
9215
-20366
139
44
-
9277
-20344
- Point to search from
- 3300ce3f-1a44-48bd-978a-9d57fd4e6e33
- true
- Point
- Point
- false
- e4642eb7-9328-471f-b935-fefc6d0913b2
- 1
-
9217
-20364
48
20
-
9241
-20354
- 1
- Geometry that pulls
- e24d1cb7-7a82-41f9-bb3f-f181c46c8f0c
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9217
-20344
48
20
-
9241
-20334
- Point on [G] closest to [P]
- c046a698-34b6-4f2a-8d95-ed65bd2086e5
- true
- Closest Point
- Closest Point
- false
- 0
-
9289
-20364
63
20
-
9320.5
-20354
- Distance between [P] and its projection onto [G]
- 1c849118-22dd-418b-947c-ff3ddb1925e1
- true
- Distance
- Distance
- false
- 0
-
9289
-20344
63
20
-
9320.5
-20334
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 24f73fbe-7c1b-4353-afad-1e194fccfe9e
- true
- End Points
- End Points
-
9245
-19553
84
44
-
9289
-19531
- Curve to evaluate
- 5b6be24b-2758-4b27-9dd3-1ef676245627
- true
- Curve
- Curve
- false
- b222f383-0934-4242-940d-878ab3058ed4
- 1
-
9247
-19551
30
40
-
9262
-19531
- Curve start point
- 12fc18e8-0eb3-49e0-a61c-f9a180f96129
- true
- Start
- Start
- false
- 0
-
9301
-19551
26
20
-
9314
-19541
- Curve end point
- 322a5174-be44-4720-834f-ce33a53f5317
- true
- End
- End
- false
- 0
-
9301
-19531
26
20
-
9314
-19521
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- e74a4531-a913-4207-a3ef-b18838106767
- true
- Line
- Line
-
9250
-19803
102
44
-
9316
-19781
- Line start point
- f951e113-ba16-4a17-a9f4-70cc3473f420
- true
- Start Point
- Start Point
- false
- 90645e4b-b95c-4f00-b0f8-9df3301174b9
- 1
-
9252
-19801
52
20
-
9278
-19791
- Line end point
- 657fa111-ec85-4e83-8d58-219a0f05d261
- true
- End Point
- End Point
- false
- adb6ba5c-3705-466e-a86f-e45769a74f16
- 1
-
9252
-19781
52
20
-
9278
-19771
- Line segment
- 70dbeb6f-403d-4459-9312-a0aa407b68fe
- true
- Line
- Line
- false
- 0
-
9328
-19801
22
40
-
9339
-19781
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 7d6aab00-a74d-4d7c-896c-db710a806431
- true
- Pull Point
- Pull Point
-
9226
-19733
139
44
-
9288
-19711
- Point to search from
- df282230-8696-4d69-9f31-e4c75d98c27d
- true
- Point
- Point
- false
- 12fc18e8-0eb3-49e0-a61c-f9a180f96129
- 1
-
9228
-19731
48
20
-
9252
-19721
- 1
- Geometry that pulls
- 1600942f-2c56-442e-bcdf-d19926b2931e
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9228
-19711
48
20
-
9252
-19701
- Point on [G] closest to [P]
- 90645e4b-b95c-4f00-b0f8-9df3301174b9
- true
- Closest Point
- Closest Point
- false
- 0
-
9300
-19731
63
20
-
9331.5
-19721
- Distance between [P] and its projection onto [G]
- 68d15499-e10c-4cd6-8720-45fa711f5ebe
- true
- Distance
- Distance
- false
- 0
-
9300
-19711
63
20
-
9331.5
-19701
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- fa53342d-6132-4ee6-ae1f-5b8810239bf4
- true
- Pull Point
- Pull Point
-
9228
-19642
139
44
-
9290
-19620
- Point to search from
- 19f00c4a-114d-449c-ab4b-c4f5fabf036c
- true
- Point
- Point
- false
- 322a5174-be44-4720-834f-ce33a53f5317
- 1
-
9230
-19640
48
20
-
9254
-19630
- 1
- Geometry that pulls
- f79da562-35aa-490d-bb37-da7addcb9b3f
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9230
-19620
48
20
-
9254
-19610
- Point on [G] closest to [P]
- adb6ba5c-3705-466e-a86f-e45769a74f16
- true
- Closest Point
- Closest Point
- false
- 0
-
9302
-19640
63
20
-
9333.5
-19630
- Distance between [P] and its projection onto [G]
- c031ba09-9341-4a49-ba56-fc10dba672f2
- true
- Distance
- Distance
- false
- 0
-
9302
-19620
63
20
-
9333.5
-19610
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 24f73fbe-7c1b-4353-afad-1e194fccfe9e
- e74a4531-a913-4207-a3ef-b18838106767
- 7d6aab00-a74d-4d7c-896c-db710a806431
- fa53342d-6132-4ee6-ae1f-5b8810239bf4
- 4
- ac64e75d-119f-4646-a091-52ab781d96c8
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a2a12fdc-a10c-49ea-a720-42d451fd7849
- true
- Stream Filter
- Stream Filter
-
9261
-23368
77
64
-
9300
-23336
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 16540671-f5c3-4dd1-ad0c-ac9d7b999f04
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9263
-23366
25
20
-
9275.5
-23356
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- d10d547d-7027-44d3-a3e8-e872073e8858
- true
- false
- Stream 0
- 0
- true
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- 1
-
9263
-23346
25
20
-
9275.5
-23336
- 2
- Input stream at index 1
- 1f1f4ca7-5552-43a4-8c5c-0e8f3195d14b
- true
- false
- Stream 1
- 1
- true
- 6b2d15eb-786a-4e29-b115-79c493b34b7e
- 1
-
9263
-23326
25
20
-
9275.5
-23316
- 2
- Filtered stream
- 8c57285f-88ad-4e27-b2fe-21dfb8d0c116
- true
- false
- Stream
- S(0)
- false
- 0
-
9312
-23366
24
60
-
9324
-23336
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 950bc8b3-379a-4e82-8f16-299c99da4440
- true
- Stream Filter
- Stream Filter
-
9228
-23957
77
64
-
9267
-23925
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 96968d9c-b897-4ae9-b053-bec42f9ffd50
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9230
-23955
25
20
-
9242.5
-23945
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 6909542d-0bfa-4ebf-a069-5edc7082b3c8
- true
- false
- Stream 0
- 0
- true
- b7c4cf28-434c-49cc-a026-b1e3b810d747
- 1
-
9230
-23935
25
20
-
9242.5
-23925
- 2
- Input stream at index 1
- 8bac3437-c56f-4736-ac60-457e51985cd9
- true
- false
- Stream 1
- 1
- true
- 7d2bec86-c155-449a-9b14-ae71252ef547
- 1
-
9230
-23915
25
20
-
9242.5
-23905
- 2
- Filtered stream
- bb1a355a-6f7f-4b8d-93f7-c629eab0cf46
- true
- false
- Stream
- S(0)
- false
- 0
-
9279
-23955
24
60
-
9291
-23925
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- c105f0d1-4e25-4771-9fbe-af4d0af47e02
- true
- Pull Point
- Pull Point
-
9222
-23866
139
44
-
9284
-23844
- Point to search from
- 4c3753c9-a621-4c2b-9e72-e8913618d3fd
- true
- Point
- Point
- false
- b7c4cf28-434c-49cc-a026-b1e3b810d747
- 1
-
9224
-23864
48
20
-
9248
-23854
- 1
- Geometry that pulls
- 099c64d2-359a-49be-877b-7d89ead7bb5f
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9224
-23844
48
20
-
9248
-23834
- Point on [G] closest to [P]
- 7d2bec86-c155-449a-9b14-ae71252ef547
- true
- Closest Point
- Closest Point
- false
- 0
-
9296
-23864
63
20
-
9327.5
-23854
- Distance between [P] and its projection onto [G]
- 591a4bc7-5055-48dc-83c8-500a6596d1a8
- true
- Distance
- Distance
- false
- 0
-
9296
-23844
63
20
-
9327.5
-23834
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 686e2d2d-d42a-4d0e-aed8-49dfb9e864a1
- true
- End Points
- End Points
-
9252
-22999
84
44
-
9296
-22977
- Curve to evaluate
- 5e51f792-f408-446f-907b-08f25ff1d208
- true
- Curve
- Curve
- false
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- 1
-
9254
-22997
30
40
-
9269
-22977
- Curve start point
- f478f996-c502-4760-9e7b-7376bb2984b5
- true
- Start
- Start
- false
- 0
-
9308
-22997
26
20
-
9321
-22987
- Curve end point
- 63430855-8e22-489b-b429-7ba46024fbf4
- true
- End
- End
- false
- 0
-
9308
-22977
26
20
-
9321
-22967
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 9f9c8983-e06f-45f2-b028-00b48a4df33f
- true
- Line
- Line
-
9257
-23249
102
44
-
9323
-23227
- Line start point
- 1909a56d-98b4-4f6e-ada0-239af8da5224
- true
- Start Point
- Start Point
- false
- cd8785b9-1101-4044-8df4-c8f682f35708
- 1
-
9259
-23247
52
20
-
9285
-23237
- Line end point
- 024bb59e-b534-41d8-8dac-da2ed1ed48d2
- true
- End Point
- End Point
- false
- 719f0cac-c2d9-4cc7-8323-fea1913404c2
- 1
-
9259
-23227
52
20
-
9285
-23217
- Line segment
- 6b2d15eb-786a-4e29-b115-79c493b34b7e
- true
- Line
- Line
- false
- 0
-
9335
-23247
22
40
-
9346
-23227
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cefafcd2-5a1f-4a1d-b499-f050365587e0
- true
- Pull Point
- Pull Point
-
9233
-23179
139
44
-
9295
-23157
- Point to search from
- b1b0f3d1-1f96-4a3e-b598-ad4c4ba6d677
- true
- Point
- Point
- false
- f478f996-c502-4760-9e7b-7376bb2984b5
- 1
-
9235
-23177
48
20
-
9259
-23167
- 1
- Geometry that pulls
- 3472d452-c5a8-4af9-9e57-842033d92c4a
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9235
-23157
48
20
-
9259
-23147
- Point on [G] closest to [P]
- cd8785b9-1101-4044-8df4-c8f682f35708
- true
- Closest Point
- Closest Point
- false
- 0
-
9307
-23177
63
20
-
9338.5
-23167
- Distance between [P] and its projection onto [G]
- d0418efe-9d2f-4140-b0a0-6665b510ad18
- true
- Distance
- Distance
- false
- 0
-
9307
-23157
63
20
-
9338.5
-23147
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- e2191903-1f01-4664-a19e-660b79cffb85
- true
- Pull Point
- Pull Point
-
9235
-23088
139
44
-
9297
-23066
- Point to search from
- c859b327-f96f-40b8-b105-2fc1bbe2eb9b
- true
- Point
- Point
- false
- 63430855-8e22-489b-b429-7ba46024fbf4
- 1
-
9237
-23086
48
20
-
9261
-23076
- 1
- Geometry that pulls
- 81e43296-a5f7-406a-b861-f77334fc2b9a
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9237
-23066
48
20
-
9261
-23056
- Point on [G] closest to [P]
- 719f0cac-c2d9-4cc7-8323-fea1913404c2
- true
- Closest Point
- Closest Point
- false
- 0
-
9309
-23086
63
20
-
9340.5
-23076
- Distance between [P] and its projection onto [G]
- 0a0205a7-4b56-4159-bf5d-5817ec1dfbb6
- true
- Distance
- Distance
- false
- 0
-
9309
-23066
63
20
-
9340.5
-23056
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 05b5844e-2d39-4d8c-8fc6-aba933fe2cdf
- true
- Stream Filter
- Stream Filter
-
9252
-26890
77
64
-
9291
-26858
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- a6ea476e-4929-43f8-bff2-318edbd3f6cf
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9254
-26888
25
20
-
9266.5
-26878
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 865683a0-1af5-4472-a1a5-3837f9e5259b
- true
- false
- Stream 0
- 0
- true
- 9a49f9f1-63b1-4713-8686-8e16f1aa6c2b
- 1
-
9254
-26868
25
20
-
9266.5
-26858
- 2
- Input stream at index 1
- 39830d77-e0b2-42c4-bba3-de726f5a643b
- true
- false
- Stream 1
- 1
- true
- 6ca20d94-d8d9-442f-acb2-5009044f939e
- 1
-
9254
-26848
25
20
-
9266.5
-26838
- 2
- Filtered stream
- 04846c6f-286e-480c-9c95-cf2ed46d9350
- true
- false
- Stream
- S(0)
- false
- 0
-
9303
-26888
24
60
-
9315
-26858
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 6f1c9af9-729a-48db-aa0a-03345ee8b37a
- true
- Stream Filter
- Stream Filter
-
9252
-27409
77
64
-
9291
-27377
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 11c13f00-254d-4f21-85ff-63095ff8a336
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9254
-27407
25
20
-
9266.5
-27397
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 1bf9cc42-2433-4a45-b426-0d5040be72e3
- true
- false
- Stream 0
- 0
- true
- b34dac8b-8d64-4e79-82bb-d85237582fc3
- 1
-
9254
-27387
25
20
-
9266.5
-27377
- 2
- Input stream at index 1
- 4b9ef8e6-736a-4b48-a1ce-e900ffef3f62
- true
- false
- Stream 1
- 1
- true
- 0170897e-17f0-4697-8902-62eec306f948
- 1
-
9254
-27367
25
20
-
9266.5
-27357
- 2
- Filtered stream
- 9e6fc360-1810-4da7-a170-2f0668ae3de2
- true
- false
- Stream
- S(0)
- false
- 0
-
9303
-27407
24
60
-
9315
-27377
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 0ec36096-bea3-4a12-9729-2f5990a754ac
- true
- Pull Point
- Pull Point
-
9221
-27318
139
44
-
9283
-27296
- Point to search from
- be30d659-fb5e-4f47-9d99-ce85f7cebf13
- true
- Point
- Point
- false
- b34dac8b-8d64-4e79-82bb-d85237582fc3
- 1
-
9223
-27316
48
20
-
9247
-27306
- 1
- Geometry that pulls
- 7996147a-6704-4c36-b2db-50e411c5b809
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9223
-27296
48
20
-
9247
-27286
- Point on [G] closest to [P]
- 0170897e-17f0-4697-8902-62eec306f948
- true
- Closest Point
- Closest Point
- false
- 0
-
9295
-27316
63
20
-
9326.5
-27306
- Distance between [P] and its projection onto [G]
- de8be8d3-73d8-425a-a946-31739fec03e9
- true
- Distance
- Distance
- false
- 0
-
9295
-27296
63
20
-
9326.5
-27286
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 39d9776d-f76c-4f82-bce1-ae05c71a08cd
- true
- End Points
- End Points
-
9249
-26521
84
44
-
9293
-26499
- Curve to evaluate
- 2b4700db-1406-42ff-aa0c-ce5673a87970
- true
- Curve
- Curve
- false
- 9a49f9f1-63b1-4713-8686-8e16f1aa6c2b
- 1
-
9251
-26519
30
40
-
9266
-26499
- Curve start point
- 94a350bc-140b-421c-bbc4-dbecf9d24995
- true
- Start
- Start
- false
- 0
-
9305
-26519
26
20
-
9318
-26509
- Curve end point
- 431f4190-46e7-4bae-a59d-f8b048d6e94e
- true
- End
- End
- false
- 0
-
9305
-26499
26
20
-
9318
-26489
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- ae24f77f-23d9-4cb6-84bd-e53fb80427de
- true
- Line
- Line
-
9240
-26771
102
44
-
9306
-26749
- Line start point
- 5b425db6-b031-410d-a08f-942dcefaa75e
- true
- Start Point
- Start Point
- false
- fd2b2675-0ad3-4ab8-9904-f69a6e4c20ca
- 1
-
9242
-26769
52
20
-
9268
-26759
- Line end point
- 6a96f43e-59c8-42ba-9a55-badc60c11f0e
- true
- End Point
- End Point
- false
- 168acd41-a9b7-4581-a4a4-fe7b47df39e5
- 1
-
9242
-26749
52
20
-
9268
-26739
- Line segment
- 6ca20d94-d8d9-442f-acb2-5009044f939e
- true
- Line
- Line
- false
- 0
-
9318
-26769
22
40
-
9329
-26749
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cf106e66-67a2-4127-844d-20791dc209f1
- true
- Pull Point
- Pull Point
-
9221
-26701
139
44
-
9283
-26679
- Point to search from
- b3780019-53f1-4c4d-9103-00d1b3599506
- true
- Point
- Point
- false
- 94a350bc-140b-421c-bbc4-dbecf9d24995
- 1
-
9223
-26699
48
20
-
9247
-26689
- 1
- Geometry that pulls
- 70485353-9b85-4e09-957d-2c142f55e863
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9223
-26679
48
20
-
9247
-26669
- Point on [G] closest to [P]
- fd2b2675-0ad3-4ab8-9904-f69a6e4c20ca
- true
- Closest Point
- Closest Point
- false
- 0
-
9295
-26699
63
20
-
9326.5
-26689
- Distance between [P] and its projection onto [G]
- c218ffee-f5fa-4436-a3a7-4119da79bce9
- true
- Distance
- Distance
- false
- 0
-
9295
-26679
63
20
-
9326.5
-26669
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- aabab78d-e59f-4a58-9fec-eb1130dd5718
- true
- Pull Point
- Pull Point
-
9221
-26610
139
44
-
9283
-26588
- Point to search from
- ebd90529-688d-44a2-a7d9-5e296817480e
- true
- Point
- Point
- false
- 431f4190-46e7-4bae-a59d-f8b048d6e94e
- 1
-
9223
-26608
48
20
-
9247
-26598
- 1
- Geometry that pulls
- 9911dff6-d919-4269-a928-c3fccf079da3
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9223
-26588
48
20
-
9247
-26578
- Point on [G] closest to [P]
- 168acd41-a9b7-4581-a4a4-fe7b47df39e5
- true
- Closest Point
- Closest Point
- false
- 0
-
9295
-26608
63
20
-
9326.5
-26598
- Distance between [P] and its projection onto [G]
- 775a7539-c249-4436-a3b1-89387fb4bef0
- true
- Distance
- Distance
- false
- 0
-
9295
-26588
63
20
-
9326.5
-26578
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 04872530-3f20-4b2f-bfcb-1e4ced53d625
- true
- Stream Filter
- Stream Filter
-
9253
-30149
77
64
-
9292
-30117
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c8c9d780-b51a-4ec1-8a6a-21663989f9e9
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9255
-30147
25
20
-
9267.5
-30137
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 4d7197ec-0f33-4d57-90e4-cafa0f59d5ae
- true
- false
- Stream 0
- 0
- true
- 1c102dcf-a427-4f9a-93eb-d8fa6673d9fa
- 1
-
9255
-30127
25
20
-
9267.5
-30117
- 2
- Input stream at index 1
- 39a3cf2e-702f-41da-9ff5-eed5fb11f062
- true
- false
- Stream 1
- 1
- true
- 0c2f603a-6b91-459a-8d58-dd4d022bde90
- 1
-
9255
-30107
25
20
-
9267.5
-30097
- 2
- Filtered stream
- f3d6514f-fd53-494b-8f2b-098b6dfb4a80
- true
- false
- Stream
- S(0)
- false
- 0
-
9304
-30147
24
60
-
9316
-30117
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4d5603f1-f731-4e75-a024-ce47a4061cb9
- true
- Stream Filter
- Stream Filter
-
9246
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77
64
-
9285
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- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- cc489051-35d3-4715-a85f-21a4eb5841da
- true
- Gate
- Gate
- false
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- 1
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9248
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25
20
-
9260.5
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- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- e0fbed4f-da0e-410a-b9ca-ed98673715f1
- true
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- Stream 0
- 0
- true
- f0dc78cf-7a27-4e9a-9ea4-ca79a5cff36e
- 1
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9248
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25
20
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9260.5
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- 2
- Input stream at index 1
- 15fd1cf3-6303-4107-b533-1f5d50e629e6
- true
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- Stream 1
- 1
- true
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- 1
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9248
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25
20
-
9260.5
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- 2
- Filtered stream
- 41cf09ce-b46e-4e22-a6db-894178c0dcee
- true
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- Stream
- S(0)
- false
- 0
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9297
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24
60
-
9309
-30627
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 001727be-06f5-426f-8507-40e7ecd342bc
- true
- Pull Point
- Pull Point
-
9215
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139
44
-
9277
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- Point to search from
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- true
- Point
- Point
- false
- f0dc78cf-7a27-4e9a-9ea4-ca79a5cff36e
- 1
-
9217
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48
20
-
9241
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- 1
- Geometry that pulls
- ed8fea6d-cbc9-40d0-8746-f450fb8ddda9
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9217
-30546
48
20
-
9241
-30536
- Point on [G] closest to [P]
- 5614e1a4-f43f-4919-8c28-c1402f0f9349
- true
- Closest Point
- Closest Point
- false
- 0
-
9289
-30566
63
20
-
9320.5
-30556
- Distance between [P] and its projection onto [G]
- 9277286a-67e0-4309-89e3-bf08dc9ff38b
- true
- Distance
- Distance
- false
- 0
-
9289
-30546
63
20
-
9320.5
-30536
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- bc56239c-7883-4555-ac8d-d09416fca409
- true
- End Points
- End Points
-
9255
-29815
84
44
-
9299
-29793
- Curve to evaluate
- f0cccf2e-a235-40bc-a9ea-c445d1403a70
- true
- Curve
- Curve
- false
- 1c102dcf-a427-4f9a-93eb-d8fa6673d9fa
- 1
-
9257
-29813
30
40
-
9272
-29793
- Curve start point
- 5340029a-6aea-4c69-a995-99563616299d
- true
- Start
- Start
- false
- 0
-
9311
-29813
26
20
-
9324
-29803
- Curve end point
- d13e35d7-8d6d-4f4b-8437-af04f2ffa2b6
- true
- End
- End
- false
- 0
-
9311
-29793
26
20
-
9324
-29783
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- f3fcbb9f-8a7e-4255-af44-a20f3b96ce10
- true
- Line
- Line
-
9246
-30055
102
44
-
9312
-30033
- Line start point
- 660a7b3a-3083-4c73-b850-e4e3fffb762f
- true
- Start Point
- Start Point
- false
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- 1
-
9248
-30053
52
20
-
9274
-30043
- Line end point
- 45133f96-9cb1-486f-91f3-908a569604bf
- true
- End Point
- End Point
- false
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- 1
-
9248
-30033
52
20
-
9274
-30023
- Line segment
- 0c2f603a-6b91-459a-8d58-dd4d022bde90
- true
- Line
- Line
- false
- 0
-
9324
-30053
22
40
-
9335
-30033
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 87eded33-ce93-4979-a534-f94d375e8e82
- true
- Pull Point
- Pull Point
-
9227
-29985
139
44
-
9289
-29963
- Point to search from
- 258e2c32-c148-4ede-ab5d-c348352d982b
- true
- Point
- Point
- false
- 5340029a-6aea-4c69-a995-99563616299d
- 1
-
9229
-29983
48
20
-
9253
-29973
- 1
- Geometry that pulls
- acf11bb4-950c-4168-81c8-722f4f1a154d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9229
-29963
48
20
-
9253
-29953
- Point on [G] closest to [P]
- 8ee83929-d92f-483a-9837-e03ee7b9f456
- true
- Closest Point
- Closest Point
- false
- 0
-
9301
-29983
63
20
-
9332.5
-29973
- Distance between [P] and its projection onto [G]
- 1f134c35-2893-42d4-ad8f-1a9c8f21e108
- true
- Distance
- Distance
- false
- 0
-
9301
-29963
63
20
-
9332.5
-29953
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- dac4915d-e17d-4c6d-b68a-449fa14067af
- true
- Pull Point
- Pull Point
-
9227
-29894
139
44
-
9289
-29872
- Point to search from
- 26f301ad-24a9-4f5e-a893-32f3de1d5c6d
- true
- Point
- Point
- false
- d13e35d7-8d6d-4f4b-8437-af04f2ffa2b6
- 1
-
9229
-29892
48
20
-
9253
-29882
- 1
- Geometry that pulls
- 8f7cf039-c2c4-4a45-af0d-e8f95889222b
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9229
-29872
48
20
-
9253
-29862
- Point on [G] closest to [P]
- 097de905-06d0-4aea-936b-314a41c047e9
- true
- Closest Point
- Closest Point
- false
- 0
-
9301
-29892
63
20
-
9332.5
-29882
- Distance between [P] and its projection onto [G]
- c28f4633-b7dd-479f-a71e-82a32547aea0
- true
- Distance
- Distance
- false
- 0
-
9301
-29872
63
20
-
9332.5
-29862
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- bfc5f4ab-3919-4abb-8151-d9a52a9477f3
- true
- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- false
- 0
-
9176
-4724
232
24
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 67705803-aa62-4c69-892f-e4ea4635854a
- Relay
- false
- 0b9f480b-88da-4856-9c83-6d1d5314a585
- 1
-
7635
-3971
40
16
-
7655
-3963
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 7e76fc74-ba9c-4acb-a67e-289d00443890
- true
- True Only Button
- false
- 0
- neutral,N
-
9494
-1742
66
22
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 27d5227d-aea4-40b9-9b52-ccdb41c7a034
- true
- Explode
- Explode
-
9954
-1792
134
44
-
10025
-1770
- Curve to explode
- 3ec42eaf-d4bb-48e0-bb83-62ef2d94e876
- true
- Curve
- Curve
- false
- 17eab43d-f378-464e-94b9-16c6b57b57c3
- 1
-
9956
-1790
57
20
-
9984.5
-1780
- Recursive decomposition until all segments are atomic
- 882fd16e-61d1-49b9-a981-48e435d8a579
- true
- Recursive
- Recursive
- false
- 0
-
9956
-1770
57
20
-
9984.5
-1760
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 6c67a789-2cb1-47dc-a134-7325a73e6d33
- true
- Segments
- Segments
- false
- 0
-
10037
-1790
49
20
-
10061.5
-1780
- 1
- Vertices of the exploded segments
- bd851341-95b6-403a-b02f-1a061b4e4b4f
- true
- Vertices
- Vertices
- false
- 0
-
10037
-1770
49
20
-
10061.5
-1760
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- d9dd41ea-65dd-49f2-9ef2-87054b73f6a6
- true
- Curve
- Curve
- false
- f1cb17b7-ee0e-49ec-95f6-e24ed89eb56e
- 1
-
9797
-1944
50
24
-
9822.633
-1932
- 1
- 4
- {0;0;1;0;0}
- -1
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
- 00000000-0000-0000-0000-000000000000
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ZNx5ONVbGzdwU0qUIUMyS8g8z6x7741UKho0aDAlITKkooSkQkVJcxEpkog0KJVCGTLP7I1GU6MQqve31+O1zvW+/XE6z6d9tr3Xb617fb/nOtfDwcnBwfGP+sX+nf1LgIv6y/rVXjv9/Bn+u3b5+2nIO20PDNrp72dprKWrr6Wnq29gQv2Njo6uhjxjj2/wnsDtln7b9wQHuvpqyDvscfPd6b58+/61/j7b/SwNDfX0THS3mxq7GxsaGurrzGD/FEn85lpLtvvv2h4cuF9r5Z5AtyDGnsCQ7TzUn84M+d9Pm+0a6O61M2S7vscuPv/d2/382K/i8XANdmW/aNasWVzsDyqkwsGhR/1+ZpJfgI+b+htB9l/4Ijk4uMYPcXH8ifjfl5r4x8UhOvUFJYXvbnXkbxR+9pdD6DCn4rdlC/ZLTFJ/Xjr1WiHuqReyPw03D8f/8+sb+n9lyp/9vzLj//tnya+DzmHxTmcz0P9+L0RXozf3cXx7PvW/y9BmvYva2WZVU16L5n4beHy7pAGF4z9vRl/KZm/l9GpDW/DrOlHVlcWc6+ewpl7fjZzMlFY7beyd+ufeobIb+Qs5NT5M/fMfkZEw49ftv5/QEH6fPnTjQH2ZU13/1M8dRKKfXc9zpg9Nve9XVJI5ZuBk/m3q/b+h0G3Pr9xO/z71c34gPbFjvJxzf079vJ+ov2KVv9Pe4amf+wtdj5Bovd39a+rnj6BNRizgXDY69TlGkchgRqZT/tjU9/qNKlL9RLKlx1EG/lzjKGq9URhnzATaij/fJDKb8/ed09dJJI4/5x/0o6TUPnvDX/QWf95/KGvfifucJf/QS/y5OUD3nNqp22c54Br+/BwwJ/Akw2kZJ4Th78EJffY/Rjn+ccJ6/H24oFTFKft2Phfo4+/FDalcj12cvLhBEH8/bjjYJSPGKcMDA/h78sDGh5FvbtfxQDn+vjPA8MyHg04xMyANf+8ZIOy3VI/TnBcO4e/PC0N2dz7e/soLzngdZsKbhcKXnNJngjFej5lw42/wKs6Ns2AeXpdZENnWyp09hw++4vXhgy0FFg+dSvigEq/TbDA9leLLuXc23MTrNRvEvHkUstX54TBeN374bu3V5NTND9vw+glAtVzVcc6zAmCO11EAMse1rbKXzgEJvJ5z4EjTmR9Of+fAT7yuc8E1dzSDM38u1OD1FQTLOGfn7B2CcBuvsyAI5LOOqs8Vgv+ttxCEpgj3RngJTa27EHw+wbBoLhGaWn8hcArbk6wuIzz1HIThldfNbxF7haeehzDoObUta64TnnouwpDC4L+hriEy9XxEYK6u5b+IGJGp5yQCB2T9NzZ3i0w9r3nQz5+ar24+b+q5zYMNv+vnRJ6dN/X85kHZRx6v5q/zpp6jKBg0GpWoLxOdep6icP2Fl3RkuujUcxUFobsXQ5r/ik49XzEIv1xVq75RbOo5i8Hg8b9qkfliU89bDDbt1TnSPEd86rmLw2sPN5a6l/jU8xcHo9VJppEl4lP7QBzSUdmZZmmJqf0gASKaY0PqeyWm9oUERCxQs4usk5jaHxLwZebm683q86f2yXzY/OvEpHrM/Kn9Mh8qep85RXbPn9o3kmBS+z232Uxyav9IQsbThfwaZyWn9pEkiN5etz3yq+TUfloAUeePPmteumBqXy2Ab0ceSWqkL5jaXwtga9BAUOTfBVP7TAqqXGTeNm+QmtpvUmC2cpWqRr7U1L6TglvmkVGRc6Sn9p80iC/O72zeIT21D6UhWvyDkUaJ9NR+lIYf3BKJkdIyU/tSBly+2w00h8hM7U8ZeMsMtdGok5napzJgUZV9LVJddmq/ykLWI+bv5iOyU/tWFubfFFqr0S07tX/lICaJnhNpJje1j+VgODJ4VkuS3NR+lgM3/ww3ja9yU/taHry0fJnPleSn9rc8yC06EjfgKA9heJ/LQ7PUVRPxQ/JT+10e4kUefIBsefiE97080PlqT/u0ycP/5qc8/P73GSXzKsA6fA4UIHeEc+i5vgII4POgAF5DCy4OuCjAS3wuFED2vf4S8ZMK8L+5qwDN7fbDUKQwdU4U4GTd9lSfzwpT50UBbF6Hr0wWU4RUfG4U4U/xuYnndEXYiM+PIhTcz7014K8IQvgcKYJv9pt14lcUoRyfJ0VQTOvlolUowkF8rhSh9cLEXZ9RRTDA52shnEoQ3ZKstHDqnC0E26Oas184Lpw6bwth8qDtg4HwhVPnbiEUBG/zEM9eOHX+FoK3zz5hWttCKMXncCHIuyUW+/AqQRg+j0rQvCHLJ1lfCXTxuVSC+FUv579wUYJP+HwqAd22s3TghBJcxedUCX5b/AoUL1KCdfi8KkGu/lx52mclEMDnVgl2qKlU+4gtgpf4/C4CWWopk+mLIBSf40XQJLFR5YX/ItDF53kRxM8NbBy4vAg+43O9CBgz4iLFKxbBNXy+F8H4RJoWbXQROOFzrgx5P550+Cgpwxx83pXBq6/pWLKjMrzC514Z5Lu/GL4IV4YwfP6VoaV55ruB28qgh+eAMpyslk8Qb1OGfjwPlMHmlakljVcFUvFcUIE/j1f3++irwAY8H1QgP8/nXLKLCszFc0IFvG9FW784oQJleF6ogOK1K98HHqtAOJ4bKtB2tvCq+GcVMMDzQwUS4muW08RUYRDPEVWwO/x5zIeuCml4nqjCv/2cGcn+qrAJzxVVuL97wZoXl1VBCM8XVfDdoc8x+EYVyvGcUQXFrfZ3xEdV4SCeN4uhbe32TTSlxWCI585iSFwePtPXcTEM4vmzGJbQzxUkhy+GNDyHFsM/k1zXF7cXwyY8jxbDfe03cwdbF4MQnkuLwUe5t0icVw3K8XxSg4UyE140fTUIx3NKDdrniYr7uqiBIZ5XapAwW/Nl8gk1GMBzSw2WcNrufvFYDa7j+aUGf0a3ygx+UoMNeI6pQcGXvRXiYuoghOeZOvh+SNhLo6vDazzX1EGpM1PJ118dIvB8U4fO+pK65MvqYILnnDqcedMR/uKNOnzB804dlj4fVh8cUYd0PPc0gOPBnDZxJQ34X77SgId3lGNojhogiuegBvinI33fcA2oxPNQA1QubehOvq0BUXguagAzMeDEi1YNMMXzUQPOHos1G5yhCd/wnNQE+0Npn8T1NeEWnpeawB3yJInmognb8NzUhCLfJprvCc2p+akJge5fviQ/1oRqPEc1QXXTzMsvPmnCYTxPNYHlIL90UFQLzPBc1YKzS0xHxOla8B3PVy2wt1qdRvPXglt4zmoBj6GPg+9lLXDB81YLitSj/yS/0QJxPHe1IFDxStaLES2oxvNXG1QlC9cPLtSGw3gOawNLsIZHwlEbzPE81oZk3s95tHBt+IHnsjas/MOxzfe2NmTi+awNM4YlBc61aoMLntPasHXPhc5uLp2pea0Dj78t0g+R1Jma2zog7nvvOL+ODrzC81sHAj9ZdafY6oA8nuM68Nat0shoiw4cwPNcB9SY609UBulAK57rOhCz8f07l1gdMMDzXQd6G3ebjaToQAKe8zpg5fAnIe6BDgziea8DFyuPf5J/qwN2eO7rwIituFXhex1Ix/NfB1aXXE9aPqEDHBx91D2gCzmW2gPdwrqwGd8HujD7UREtRFUXHuJ7QRc8DezO8yNdEMX3gy6U3G38krJOF3bje0IXZNVdbYx8daEK3xe6EJoxdKkyShdU8b2hC80KoT9cLuhCNL4/dEHvCu/Skbu60I3vEV04Of/MtbgyXbDA94ku9J+RG5Hv0oXz+F7RBVvBbPvCn7owjO8XXbgea5K2fLYeOOB7Rg/+zij93S2vB9n4vtGDTZGODiHGejDrGfve0YPCya4M/pV64IHvHz0Q2ef9J8VDD57je0gP/H6OrDEK0wNpfB/pQYXf4azKRD3Yh+8lPVDuF+R0vaUHjfh+0oOo7ZfXjxTrgQ6+p/SA2a2aE9ekB/H4vtIDs833eRQG9eAzvrf0ILmF5lzIpQ/W+P7Shx+r3+Ytl9SHFHyP6cPKt5tm9WjrwyS+z/Qha+mnrSG2+rAB32v6wFsadJ9/iz4U4PtNH9yAQyA1SB+Ewtn3nD4UF8W7GcXqgy++7/RhgbHko8oUfXiN7z19CLl3Q9D1gT4o4ftPH+o19TxHqvUhAt+D+qCVWfwk7r0+dOL7UB9ilZbPU5jQBxN8LxrAx2stOwuFDSAJ348GQJfyeL5c1QC+4XvSAK4mfxPvsTIAe3xfGsC48MFdIesM4Ba+Nw3A6QTfK35fA+CpZN+fBnBvVvKC1CgDcMH3qAHMjVYMMLpgAE/wfWoA3v9yyivvGsB8S/a9agBloeayrmUGEIzvVwNQHCkPHuk0gFp8zxpAeMDayrifBqCB71sDaB/sVlCYbQjH8L1rCEZeu/YVyhvCe3z/GsLpd7/fLjc2BMD3sCF82RqzqGeFIVzG97EhLGsXORDiYQhj+F42hIx11+r5wwxhLb6fDYGrTn1xaqIh5OJ72hC22j88ZHTLEARi2fe1ITwut26uLDYEL3xvG4I4o07DtckQXuH72xACi7ccHhkwBPlJ9j1uCG9N+9viuIzgAL7PjUDtfoiOgqQRtOJ73QhidLiPFmobgQG+342g9/apruW2RpCA73kjsFKRNujZbASD+L43govXb8WGBBmBHb73jWBExrCHP9YI0vH9bwSrL7wwTk0xAo4Wdg4wghzRlSeNHhjBZpwHjGB2Qvv7ymojeIhzgRF48u8wd31vBKJL2fnACEpifiaOjBvBbpwTjEGWK+JznLAxVOG8YAyhBwWQgqoxqBaxc4MxNI+dP1toZQzROD8Yg17wosHl64yhG+cIYzj5NY/e42MMFjhPGEO/t9WFkChjOI9zhTHYfqz4yn/BGIZxvjCG667rbVPvGoMDzhnG8Lfz3WWjMmPIxnnDGDZt2P2zstMYZiWzc4cxFDZMLnX9aQweOH8Yg8iq4ykjfCbwHOcQE/CrEBuNkzcB6VnsPGICFTbXVygYm8A+nEtMQPmFVnrhChNoxPnEBKIsisaXe5iATig7p5gA88ESx55QE4jHecUEzPQbb4YkmsBnnFtMIDnH5S//LROwxvnFBH4sHlqbWmwCKTjHmMDKG/tvGzWZwCTOMyaQJc/LVTVgAhtwrjEB3sunN7hymUIBzjem4CYhd3dkvikIrWPnHFMoPn17Rry2KfjivGMKC+aabFawNYXXOPeYQsjxV/cKN5uCUjk7/5hCPY8jn32QKUTgHGQKWhFd23qOm0InzkOmEDuxszAkxRRMTNm5yBQ+howICDwwhSScj0yB/iPKPbXaFL7hnGQKV3cJPjZ6bwr2OC+ZwvjnS0JV46ZwC+cmM3DyUN3hKmwGPNfZ+ckM7rEKno6omIELzlFmMNeZJhpvZQZPcJ4yA+/mam+FdWYwX5Sdq8ygzHHTi0IfMwjG+coMFKs/SthHmUEtzllmEG4X5Ndz3gw0Yth5ywzaX/57FXLXDI7h3GUGRiheSqDMDN7j/GUGpx/PD0ztNAMYY+cwM/hieOO10U8zuIzzmBksy9OVq+IzhzGcy8whQ6N4j6u8OazF+cwcuG4tqxoxModcnNPMYevCFsX4FeYg4MrOa+bw+Kr7fgUPc/DCuc0cxBd8qykMNYdXOL+ZQ+DZA8r2ieYg38DOcebwVojvYM9NcziA85w5qMWfbQgpNodWnOvMIWamoppAkzkY2LDznTn0RuVEpA6YQwLOeeZg9desxYjLAgZx3rOAi/vLNavmW4Adzn0WMDK8JtpV2wLScf6zgNW7u9tHbCyAI4edAy0gZ8BXN36zBWzGedACZu/4fVQhyAIe4lxoAZ69R5iFxy1AVJ6dDy2gZIuIoX2KBezGOdECZNuuxvUUWkAVzosWELpWvTek2gJUT7NzowU01zwwEXhvAdE4P1qA3nLrU6njFtCNc6QlnCyr/WAkbAkWPOw8aQn9tC0WVSqWcB7nSkuwfdp32tXKEoZxvrSE6yYhfSNrLcEB50xL+JvPBfE+lpCN86YlbNI+lawQZQmzdrFzpyUUZkkNFZ63BA+cPy1BRPkWw/6uJTzHOdQS/FINLvaUWoI0i51HLaFC+sW3kE5L2IdzqSUon1+xROCnJTTifGoJUfPar6TyWYGOIzunWgHzpOewkbwVxOO8agVms38uqzKygs84t1pB8pFDqa4rrMD6JTu/WsEPDoGxEXcrSME51gpWHji/Mj7UCiZxnrWCrFGlGwqJVrAB51or4A3Kmyi8aQUFON9agdsXy9X2xVYgpMHOuVZQvLPiVk+jFfjivGsFCz44/QsZsILXOPdaQYjLu3UCXAiUrrLzL4L6Dv/s1PkIInAORqC1fpLLWBtBJ87DCGLrj22sskFgIsTOxQg+rhDLdd2MIAnnYwT0N6m8o4EIvuGcjOCqtdaW+OMI7KPYeRnB+LPH+QopCG7h3IzAyXzJ7AeFCHj2s/MzgnuFDS721QhccI5GMFfP5UHPOwRPcJ5G4H1ncM7ecQTxOFcDuCdZ6MXMAjDD+RpAuD6qq3YewGecswGeCb45JiUHkIzzNsCuFYIGnmoA1jh3A0jFrWPlUtf9D5y/Ad68vhQ7AQApOIcD7OXtNbS1B1iJ8zjAImvVnoT1AJM4lwM0RPrFd7gBZOF8DhD5rMBY2Q9gA87pANp/xnt37wfglWbndYAuM9rJomiAApzbAeL2HTXlTQBww/kdwLSw+r3DJQChJnaOB/j0c17CpQyAYpznAc7qbjL/mAfgi3M9AMM/5aPOU4AFJ9n5HuB79sfEsNcAr3HOB7jWr2FZ1gAQgvM+wArVoM9CLAClJezcDzCx/dEZ536Aepz/ATLT/lll/AKIwD0AYH2PTf83Dhpo4T5Agxly8WfNBWjQiXsBDfI310OMBA1icT+ggevF+YO1ijQwwT2BBoKtW89JadHgI+4LNHgqdoPuaUqDJNwbaOCzZmAo15oGdNwfaCCZqHthYhUNvuEeQYPyt3utbZ1pcBX3CRrsESj+muBJA3vcK2iwcBnPpY4AGozjfkGDuqPLbJUP0uAW7hk0OFSa8H33MRo44b5BA03ulstFZ2jAo8juHTToABk73ms0uIf7Bw2Oh7v/dMiigQvuITQwfpJ59dJ9GsztYPcRGnz4/XXpx+c0eIJ7CQ3OGBv90qmigTfuJzSg7TmQEtZCg/lJ7J5Cg6/3SpaX9dKgDPcVGlz5NmtU6AsNgnFvocFyrVXXnX/TQHEFu7/Q4LfP2RUZPHSoxT2GDjczO8a+CdIhHPcZOqz7pJBuLkUHDV52r6ED9yKvVTHKdGjH/YYOeW4547W6dDiGew4dtqUM35CypIMR7jt0mMM0c/S0o8N73HvoUCQVOZm7hg6ncf+hw86N5TcnttIBcA+ig8S5OWtsvenwBfchOpQ2rvmbsIcOl3EvokOQyMXMjgg6LMP9iA4KDt1rlePpMIZ7Eh1qTihzBJyjQwbuS3Q4WOl7u+g6Hdbi3kQHdb58J94cOnCpsvsTHdpsf3M6PqJDLu5RdDgaje5cekWHrbhP0cGw5MiGjzV0EOhh9yo6vPtXya3bQYfHuF/RIdFS5G7YRzp44Z5FBxS2YVPZdzqIX2T3LToMPbw6Q/gPHV7h3sWASyPvc51nMSAQ9y8GLDVQ35wxjwHya9g9jAGjAQEzv8sy4C3uYwy4cffBPXM1BhzAvYwBa4b+bIkxZICaALufMYBT3ZqvDhjQinsaA+56xRZI2TMgBvc1BmzJqN3muZ4BBri3MYD/vTh/nhsDenF/Y8AjhS2FE7sYkIB7HAN2bEtztd3PACvc5xggdqVPIDGaAYO41zHgZbv2w45TDLiI+x0DAuaHuCtfYoAd7nkMkHN6MjcggwEjuO8xoPoM1+OiPAak497HgLA6u+28TxmwGvc/BiwWPCXk+JoBHFrsHsiAFvumoksNDMjBfZABR2KldnxkMmAz7oUM0H/tKqLbz4DZn9j9kAE9M249DfvFgIe4JzLgFOOLVxmHNXjivmgNlpEGosIC1iCawu6N1jBQHPrMWcIaSnB/tIYLk8+9MxStYTfukdawxGym+HdNa5DdyO6T1vBr74oX5qbWUIV7pTWk3T/jG2NtDaG4X1qD4882ibpV1qAqwu6Z1vBPR/6llLM1NOO+aQ13/Dz9PD2tIRr3Tmtwzs6WzAuwBj3cP62Br//Hq4kD1tCNe6g1PFAx3W17zBpO4j5qDdu3H5JKPGMNFriXWsO8tNKyjqvW0I/7qTW86OYPVM6yhvO4p1qDv+xqmYD71mCL+6o1yGw+/7rouTUM495qDZUXmEG8VdZwHfdXa9jfoiTn2GINDrjHWoOKmE/FpV5r+Iv7rDU0rc7b83HIGrJxr7WGwwmj8rq/rWET7rfWoPvWsiqMxwZmDbF7rg2w+KP3lgnaQCHuuzZwYmmForCUDXjg3msD5keF3jor24BIBrv/2kDfK6f9Gbo28Bz3YBs4x3VF6buFDfjhPmwDNvCuxtzOBqS3sXuxDfw8uDgsZo0NVOB+bAOpRf7KdVttYB/uyTaw6vf9OilvG1Cez+7LNvDHaPKA5x4baMS92QZuB9NV8yJsIAr3ZxvYeO9Yw0ScDejgHm0DM7+9Dbc9ZwNM3Kdt4L6mmFridRuIx73aBtx9nJs67tiAGe7XNiCcmRqh/MgGPuOebQPPPn5SD3hlA8m4b9vALiWtlqIaG7DGvdsGpNyCo3g7bOAH7t828ObaY03HjzaQgnu4Dezt4mi79N0GVuI+bgOLpJZEf5y0gUncy22hYcMJbd1ZtpCF+7ktRCY3tIfNs4UNuKfbgnajZEyZrC3w/mT3dVvoEnbRFVazhQLc220hblVGp7OhLbjh/m4LpicGj2aALQhls3u8LXyq0NP/vtwWinGft4Wzs/Yzzdfbgi/u9bbAsH12PMbNFhZsZ/d7W/h+eIZh3S5beI17vi1ce7G8W2q/LYTgvm8LK/4lxnlG24KSLLv328KERatR3ilbqMf9////nf3fGZzuXP3v3z/W//ffF/Bw+/5lu88O1xjzAL3pP6++XDvOdvlziUvbMpdPu6r336/YDU9S7jzterIvWWzfoKEy6vbMY9o/P5StwK+PPUy93mfa7c2E77J9OHGoWmVZwLRvvn7xJH6fEHHqfYKnXfz7Yy+2W/Sby1812DftnsqBlvj9PbdQ7x827WL05wJsj3YLDRSVOzTtsYwbzX/ZP1f9DfVzI6fdd7HCJbZnbFvtVspzeNr7v+lvYvv5Y60jbs+ipz07qWse2yvcnOM4QmOmXZ9f9vUfyp9ktctdNTg27cetf4Ww3U/aqcD86/Fpl1Fxl2e7fHC1XVtm3LQnx+14NUm5iB90hXicmPYIYy53tvOU5QSIyp2a9vhmvckJyqWkBbjbfBOm3e3H2Cm2G4AV9X0Tp/3+5zWybK/O3nUuROX0tO9j0W+OU16GLrqW8pwh6//glRrbUfNLddFe4uHjLbd+U75vRf8vt2dJ086sClVgu3DUnOd5l89O+0BjVtIY5d4OmrEcocnTXrhoOxfbGUlL165af27aW5UyvEcpv6zqJnvV4Py0c/vtrB6h/OynkM+DwhemvTs/U43tJ7OO3jP/StzmqkvUL8qPLk06EFt1cdrTb8Q0DrPX/9Jl27bMS9PeOSCiwPaNwSlCqkcvT7u1yMSOn5Tr37rWHuJxZdpnz9HP/EF5/MyL6aW0q9Pe/jP7/XfKS11O+YnKXZv2ppoNC9jODD9k4j5JvNpTadk3yidEDTnbfFOmvZl7Iugr5bPOqHhGdBBfaFl67gvlayUlKlWWpU677QOv+0OUux7h1ql5SLz6Q3nVIPu55w0mhahcn3avNy+6Bigf31P/WyaZ+Pnbup/7KR+5UbC1lCdt2kVbvwz0Ud4gfOalbxDxmWurPn+mfNuRXaqivcQtzpxnfmKvTznjRJFD+rSHqctUf6T89QWxH27PiBvFyBZ8YK/bg16n2Vo3pj01wfnMe8odm7OK8i4Tj/A+4f2Ocqu0XfIb+TOm/em8Haa9lM9+pXaEI5Q4l+TZf92Ur2/q6bv5mfhu9PQJi32+vE+vXLX+Jjnv2uG7mez5Odsif6SUuJe8/4IuylfoMiWuGtwi3ytC7nEH5W9W7jtgk0b8UYr4qnbKm0v4egaFM6f93JaG1lbKf3Ql2iRFEC94XenUQrkcSzDL/CvxVfW+r5soV/8RNffdlqxpL/4hqdnIXk/N/sDYKuItDRrR9ex5mGjdomt+e9pdxoerailP5U40b8skHun/gLeG8l0r316LmJ897VreOTrVlD+WmeBWPUr83NisZZWU806KedX8In4+s9/xDeULV8lUhXjcmXZlI58l5ZSz1grqyDYQL1ZLXlxKuYZc/5lSWg75/AneoyWUqybcHvXNJb75fPvd5+w5sM7RWVTu7rRr0yodi9nz831rcdEJ4i08op1F7HMXgBTdJ4kviwhf8YjyK2PP6UcMc6d9vmxZeiH78xxZOdzqS7z3+bnufMpXx5bd0EgnHuCX+C+X8s8zVdZHdBD3n6Bx5FD+t3rXrEaRvGkfe6Dak8Xe5/vOP1JZRtxc5n7KTfac8U33DoskbnXA1jKdPVdrTkrVPCTOk6N+P4U9H2LWVil+I65Zep33CuXiWj8OhKjcm/ZNL1q1L7DvKXEPzYqtxJ2t+7TOUp5lntElk0zcZymTM5FyBauCEwHVxM8y72bEU16+5bhlKU/+tHt3M6SOUb4oQH5ovgVx+Ye7thym/EBX0GXfIOKm0l+8w9nrefLg8udZxIsaAmn7KdcZNBqf10t8/oFkZhDlxg3nb+2QLCCvd+xGfpQ/PXbJqciBuPXESzcvyi/lGvEIHiN+Yn2qtRvl7TTXPLdn/3n9yle9zpRHhApvLRwhvj7Nw2wd5RINFrNna92fds7qG3YrKTf83nJ/y3biF6qSZy+h/MyFZpe8y8TnzNY7iCjXS1Xnn9FIXFxvyxVjyse6Xhds4C+cdjmJvh3alO8Vv7Ylm068ISmxTZnyrm9XZnCEEt8c8ueLDOX2PfnZa/KI624rThelfIHE29U3PxP3L3QYnc2eAztbR8flHkz76SSpdxyUX2M8vbRyPfGz+bs9Rv6yUPjJ7VbXTxJXdo3fO0D54KWHrF+lxAcDz87vptxc8PKhpX+IZ1lcYTRSvqz0p8wVg4fTLnjs2nA55W+KUh9/8yEucjJKpYjyU6NH1lmnEU/5Lt56h/KMneFfzrUTjymS4Eqh/E6D55EB4Udkn69XS01kf86s+QvQUuIokZkbRfntce/s0xHEHZJyNIIoX2CjZ/HxAfG7fX8F3Sl3dYc3pl+J9+yVdVpNeYKHx5oTyo+n/VCU7ThQvsrHu717C3H5rIujWuz1jJXaanCW+JpB1aXS7O+VYsk8WkX8cVpf3yzKxfTObOrgLiL75NizxuE/LCRD76jXMid+OWcvTzfl8Wp1tlGBxJ8dfxNUQfmBQI3Cpkzid/qcZAoot0hLkV/cQ9xh8vbEZcoPS3cdOTD/ybQfWYH4jlD+7mP8h5pVxJeWB4Av5aJHnNDCo8S/5J28tJryqpcdp0OKia8vqBQ1odzj2CPWm1/ENRrtMqQpb7pydJGM5lNyH4UILeOgfFdEq/tuD+JxWyXGeyep+0jV9OLLS8Rd8ixyX1H+qVbntXgDcd+fSz1vUN5TAkM7ZxeTXMf/U+wI5Zsk3s96SiOeSWt+6E755oOnFgjtJ15gc8CORnnIZK6Cey7xFZobimUoH7t/V6bwE/HW/eXzfk9Q8zZ9YA6f3DOS56VF6A2Ud216+t3ZibjtAW96NuU6z/a8zjlBvODA0Jxoyt3LtyRylhLnP3r9yibKZfUKl6+dJB6RFNavTbnjNeewBsnnZF6ZrRvipjxf9/XrA4bETz0audo8zkL7OQvmKDsS/yggMnaT8sun7iyt8SW+4S/j+17KHxyxOrDvGHFjc9HDtpRbnhxIV0gn7uH768Y8ysfUDV5WPCPe7GCzmvWbhR4mnG4O6iD+rt0+IpNy56AwpvQocW0HUA2kXP3DlvZSkRfT7ueL6KaU+yinvfHTIl4Zs67s7xgLeYXm3JZYRlzt8f7sEspzxzsPPd9OXFjo1GA05U93HrHZGUncK8cj3IZy3hljE8JXiA/MLNzIQ/lmp/Drjx8S3ymoHvJilIVKeJxN3BuJP9q1ofIA5bnpb57wfyMe+viZgxHlNUf/ahXwl5B9/qDmz9AINZfilU9uViFufOr9mzTKT/Z7tvEwiHOJ2WWvp9xvRpfgna3EJfj0LvNR/sXwqs66UOLqW18nPPpFzf8LD8z+nCX+KFIucgflFixNzRt5xI9lmHnMo9x23h/eFdXEkbCA7tNhFtL1nV8+/Jn4R889TA/KNcS9fS/zvCTP8c8S99mUZ/+t/8WQJ75Bw6bwzk9qv11TcxswJx50XfbtSsq3V1jlnl5PfPRBSOrQDxaKCmxgmgYR9yntVo6lnGPf9cHuk8TH9vesVaL8WYBz69Es4i/1vio8+U7tn71pKVplxD+vDox2pNx3QNS6qYd4/6XSwPffWCjSGr0I+0M8PsboXTDlO1oyxBUlX01736UZVVyUm6W8or82IP70refCk1+pfcLPa+3nQPxDYyRLnPKG51XzRX2Jf4kIHLn8hTrXO/2ePTpK/KXU0q3ylCeFGRhtSyMeXjx7TuoQNW+5N4fxPCOOsvPGZCm38RE7kdlO3ChbU+LiIJWjbKJ3rhwhfsfdY6sI5Yriz+b+FC4leTVX99XRAWp/StWEntMkLsPlZTXez0LzJXJvmy8lHlVYW7KTcv8FDtdYHsSlAzWWNPdReWbFqTWHI4jnhum/QJSnPkJlypeJ3xNPVs74zELpYot+vXlA/F3XpC8f5bonh7t8G4izZPhid35ioaLEteGCX4nv114XVPaRyhuXOhvyZpeR3FUXLCtPudg/0c41ysRnRP+KCPlA9a/8kKRfNOLGzK0Jb95T+VDBZzx5C3HOfj26JOVxA8v5TfYTZ+3/Erf9HQtteO72qjWJeNIhPvecXioPLOxT3J9L3MV19MnPHhZKtpylJFlF/NEKlVOGlP++2frq4Sfix07w1AR1s1CmhRvXBu5yMv8bRwJyWCzU+O5S24gsce0Et10fmCxU5+az5KwZ8ZP6mYXzKZ+lfsNO34n4qqjFDLsuFnJbLNBeG0B8VyuaFdzJQoVnHcd2nSA+4m87camDyicloimzM4kbp58Vft5O9Yih3uqMV8SD9aKhu4167nOMw+ndxPn37Tg42UrNpZv773RNEJ+dc+apKOW/z3Ns2CfxetpNFTePqLZQvebL3FARfeLHds2TMW1mIfm7jYLZK4lP3uRXsWlioZX3/MRsvP/jF5L5VjSy0LDvx5iuI8RFB2Y8dmhgIXil67InlbjuytuaDvUs5MLUuyLwlDi63bpxeR3VF34+ME1rJb7ctlufXkvNB7kwXdNh4gLvRfMMaqj9pqMY8VbwzbRzD74pU3zLQiMHrBTc1YlLHlvjLVBN/dwce6FRW+IDL3gTv1ey0IXkArtYN+I1V0x16iuoPPD3dal0OPFcfYZlzhvqvt5bHpVzgfhoadidI69ZiK7RGoruEw9vtgjZUM5CwTlzMmtqif8w7YlXLqPulwqPWdsGiZ9YXPrx6ysqJzi9OjM0s4LszzW2+wteUueO449N2ELiN/pfmgaXUOdL/o3kLES8Iv+qjPYLFqo/WsWXtIm4qKjpgg/PqH3rmCQkF0LcQmZUKbmYhYJyklUzE4mzLljp05+ykFSRnr3eHeKuknvN+oqovr80d8/j18TjJ/h04h6z0KH76BrtPXG5A258qo9YqOPu75Lyf8Qdi4eKnj1gIUkRVru9VCW511oXWK4uZKF12a3dtUbEr7I2RbEKqLkh9uDtmtXEL/2Uj9yRz0JhYXpXm3YR/76sV6s/j4XaAvvtnI4Tl0LikTtyqfuifPvrpnTikxuMdrFyWKh1uYj42ufEQ7YUf3a8w0J/sqzV6zqIW27S6Cu+zUKmxiacK0aJN9zj8FDOou7xormJ5SJV0/5Ys3jlsVss5Glf2wBaxOs5+6++z6DuWQmfkodLif96x7/M/AY1Dw3z12lvJ/5aNMcmPo3KV6FuMekRxMv9thxtSWUhuyXzV8y/TDw3OJNHJoWF7m7aeD32AXG6i1L+5qsstO36qfCJeuJRuu7Hki+zULHA7HbvL8TPFP/ZX3GRhSo2TWa38lVPu8OrkwfHzlM56nv4V+tFxItH84/Jn6P2Q87JC3eBePL8uYn0s9S5KxRIm7+Z+CQPLX7rGRZSWlHMHbGX+IW3P/2DE6nzfsM+/8Np4pZ1tbrRp6jz8sg6c2kOcavKI+UnTrCQwwKJrttviBeMvlROjGOh55UStgIfiD9QA5uTx1loQDy8w5vj7bS3fb03/8hRqve5eySVSxEfyWpN3nOEhdSEXu9QNCYeVhRwf9thaj3tj9uHrSZudZ3uzYik9udPb9P6XcSF1ERvyx9iIc2dIotUjhP/czp/1+gBKi/tnckbmk582/MfN8tDqXmiWVBf8Yz4i523ViXuo9bthUekZAfxsytzN60NoeZwwJJZniPEH/kOFAsFU3N7p++WXOGaaW83hcCyABbqzCoNGdMgfoF10XuPP9Wvvyovs7IjfjJ06IrMLipXn7OpjnQnzr9Zh+uZNwvNS374qyScePZKtxMbvai8tGXsIedF4o+6jhkObWehvrdbBazuEze7lvttvzsLxeiofNhbS7whYqjgnwsLLZbzM7k7QNxewnlf+FYWuvPy/J8A7tppf/ZNWnfEmcoJq1SF+YWJM/q2NnlupNb5u03ddVnislHrnGudWKj6ON3EVIO4trnVI721VN+5sg3emhJP+rLtwwlH6vOsq3nnuoT4Ei3+5p6VLHTzSIH08FriF9MuRmrZs9DOXMUP0W7EHXYHMYOWUvNZQNZYdDdx88QZ7/JsqV4Td0ng+kHii+lVRz4zqP3wKWKbVhxxltvKpxI0FhK8lb740XniMl2yEciKhbbqvvWgZxB35u96tc2c+l6192dX5P/n9fKGUftMWKiqnEfM4QXxlye6c44bstB693UHG98SP+OXQTujR91HM/Qt13cSnzHkrHtWm4WMzRasbO0jzp/9PviUBgtJVO/LXD9KfLO2PnfUYhba23HHromnjswxxtIGX2XqPhrkW+QoQrzW06Rz1UJqHXhrjCvliMdoK4qpy1NzplInlKFJ3Pm+yZ6/0lROS1j74ZEZcaWx4p9vJFmIf79joJYdcbclfMdOiLOQdLLOgtR1xLdlHly8dB6VW7iGmoTdiYvRk2omBVnoHnfw1YjdxJmPWgJuCVD7fPEN36GD//n8aR9m2vOx0LKg1aYb4oj3vfM7/mkGNU/84c/z88TrRE2+hHJRfcFDOU8lg/j6IUkt3n9MND8kZ0V8PvHdNzhpxyeYKKB6T+WX58TLNn2X5RljIvcSgYWr3hJPCuZ4HjLMRGm8o/Z3Oog38W6W7vnGRKV1t2l8fcRPGizRYAwxUcXc5N9uI8Q5EqU+X+5jopFY0V2PuevJvD201O7LByYqWhSaJChMXO3MBhvjXiaS5prr5SZL/E3fp5a9TCZqeMjffU+d+ObjOWN325noc1zaMIcp8eCHYSmsZiYSuTR+xd6WeMk649e8DdT6SKo3nl1D3FSz12tRDRPJR1mf6nQh/npZcph5JRM11S8vl/cjHrXs6G+7ciZSeG4e7BZGfG4GV+eKl0zU8ZXnZOox4hv/+Usve8ZEjbonBZhnia/1ciywLGKilEcFnyTSiD+5ybii+oBanw32EqtyibeF/q2dnc9Eho/kzhx+Styoce3S9zlM1HL+2+r7FcTNJQw57mcx0TaefSvftxDPd8j8eiCDeu5nPA8KfSBO920RtrjORObpHi2mP4i/9OR0/XGFifTPi6x1+Uf8yMEjLdcuMNGYIN/AYYGGaY/bxPS3PstEMqptZ9IliV+1TFPqTmCiF/cFbEuUibsqHvsWGM9E6LDy70594kvebXk7eZSJWuOvpw8D8cMbRR4dPMxELpYjiG8l8Yn9ubd/hTMRKyuhZIEzcZq/S6pHKBPNaWhfuNiLeEHujrMVe5gop8XY2WAP8Tfiiw+rBDDRsNkMF4so4qWDSp5hvkwUJXVpMe0U8bp/Y6ZlO5gocrf9Xfpl4mW3XcZnujNRvM2Oz5BJPOuDQRpsZSLfEYMq80Liata+Ors3MtGQ97ij/kviSrxSV5PXMpH/6rHdKrXE90kEfc5fxUR3t/nIz+8ibi36iv/1Muq5R8evn9FP/O6yMJ4GGybq00ic83WE+N6ihTWNwERGB26bNnE3kvkm6elVbc5EN47ObnggRPx6+azqJ0ZMJHimvTZZhvjplq+/r+sy0eIVNmqBasSDZ8gMHtKg9id/YPNSY+LFBXdT1qhQ78MXUyVjTTx34L2orCITPbuWzv3F4T/vs1LCliXNRDOPfw18vIX4TclnuuckmKhH8qjwYW/i+6QDm2xEmOhBRGzzkr3Eje690xoQoM4d9/xHs6KJexW9Nz86k4lOWq3ILU0g7p7sPi7JxUTfXJfkh18hvlXC1yttsgu5Byx8pJ9FnD9CJXrhaBeqjfr78H0h8Rshncsvfu9Cp/78ykx8STxq8svTmYNd6FubymGzWuKyHt2tPh+70Kvue+asTuKXbVddKuvuQnYDhRWH+ojf2zfKPb+jC/EvXKciPUJ84m+esEtTF1pAz7Ur4Goi+ZBzz8urNV1oUcPgIjtB4n+K18xvfNOFHgToFrZIEecODxfkeNWFImbf/OamSvxpOP2WYnEXspHaX9VnQHx7P1+v+cMu9OVHE/jSiLe/cH6y/F4Xkvz+xbp/BfHqig6j1dldyKN0rMZ9E3FG2DLHVRldCHLU21o9ie97F83PSOlCqg9erl8aRLzzbPR2zYtdyGSEg3H/EPG5J7Ztm5vUhSZfq5yWjif+QtDu94cTXWijUKTFofPEt56O1y842oV2+Gwy7Uonbpx8bu7+SOr1AbwRRnnEN8V8jTUI60IjfZ0z454Sf5RolPkxuAuN85i/bn9DvDJKzfuUXxf6dOrww0XNxAOT0t9qeXWhYDW5Wp9e4sj6Qssr1y7ksv8A750vxMcV5sc4Onehm+uF1vSNEz96eXlH49ouJMrrdEd+ZvO0z6/a17pyZRcS2VgjsGYe8UrTf+HPlnSha+95dkbIEb+avqFWmdaFkpRjHt1SJ/7+5fy30WZd6H1O369KY+KSM4f2t+lT62xTLdbPIL58zeUmJc0upC3cLMTtQPz7U953nspdiPt+LlN8M3EPm0Xp1+So87JHeO8iL+JDMXxSNfO7UNzagjqtYOIhgV1Lfwl3oSDNLR/1IojPnezVE+HvQo41Ldm68cQ1KoNaF/F0oQDRMWn188R5PnNY6vzpRP2jF7Tk0om3eYq46450oolbqW1zcolfF16yYvHXTmR/eUJstIj4TKG1fyU+dyLRS5c72suJj5/g2f+nuxMtrY1UfNTwn9e7mj5va+tEBQ25vYks4meyPzdn13cilG8sun2AuM4RmechlZ1o3bjGXb1R4lpnRsONX3WiwAd3b49ztUz7tYIs8a9POpFgxCfOp3OJf7waHnvlfidqDOTJ2r+A+NyIt130HOp7maDLOsrEeVNmibIyOtEMrrbaHl3idZw5OoHXOhHtmBScsCT+hWe18eS5TuTKu7FXbynxId6L6gcTOtFrw8G79WuJb5xhKfzrWCfKX2KS6utCfAJxD7pHdqKTXbdyOHyJH+0offZmfycy4rhXe3Iv8fvRfgnKgZ2oT6z2n/hh4rXzRl1Dval1aDlqcOEk8Wc6O01K3TpRJs1zh9hF4mGjXRIznTvRnTiOxLgbxOddOcgDazrRXNHhzIlc4gvFDnHtXt6Jbqz+mLX9CfH6Byri5xidqKwsOv5NOXHnzxWM++ad6Nn76CUqDcTFn7w5VaHPXuf0xnAmcYXrp/82q1PrCTc1avuIn+VPTWpf2Ily9jrbSf0iHih60KlJqhO9kD0r78LRSvKhZpFd+bxOxK+vk3OVn7hv6YR/Ln8nspUT6m8WJ9440l+bwN2JVqfKVc9SJP5PF3Z7TXSg7zkODgaaxEsHnq42/tmBxDdd9t1oQlzJXvfgn/4OtLOAS2ofg3gcM2D4cW8Hsr0XuzZhJfHHDNen/u0dyHMOXeT6RuK2H/o7peo7EE3FcsUdD+Kct7k3PHvTgVYOJP/N8ye+8l6m/qYXHUg/b7dcbijx2JnvgwcfUi7349bNI8RvuJbIh+R2oGcCS5POJxCf073ZYvRmB9q9PbM96hLx4YqGKv9rHShNYMUezwziEk6rWljJHejQi6AtjLz/fE7Pfy5LTnagOm73eMknxN+tl/LPONKBCn9vn/hcRvxXZQ/vnwMdaKFTdVpeHfF9gec1lwd3oKXwNTyok7hFR9znBJ8OJGuhEqP1ifiTJYKWb906UOO85nu93/+zzocO6HBv6kA7Slz/npok7nxL/7W2Ywfy2GboZjSzjZwXmUt8a+06UBn/i5YmYeI8q+TG/VEHmt29f4OfNPGHl/WuHTbqQEkdbV3/lInfN13x96RmB3Js2uYaq0vcZu6Q9GmlDvRo16nOORbEM66c5Tgh1YHkub7bxdoSrx2qyTkkQj2XVOGUfw7ENwWoaXrzdaBVXIc7djkTP/HTJNKeowPFhnYMN24nHhyTlKs82o4mR+9/MNhNvCSw4/nYUDs6O55380Qo8aTFeQ9K3rej5lNBBqxo4o+Niy9Gd7Sj5avSjiw+RTzeLNffqr4d0TZ8SfK9QFy82dTi2+t25O7Au/lWGnGvbBHei8/akZN7amPnHeJ/1o3Wmxe2I1VG6BjfQ+JCzpm3mrLbkc9ihxfaJcRvan6N35HWjma0fVRdWUV8tVLSke8X2lF4Cu/i7c3EPfZ4nQ9KaEdPNh8oCu4mflKPVjkU045kDki2H+gnXmk9ttDlYDuq5iwIPzhM/JCX762KIGodjiunhfwlnr04cqumdzviWOZA85rVPu123bL2x1za0UwpsTWrRYgnZuvt7XBqR/UhW+oNpIl7BuV8UF7RjgbCxR8JKhNPbz92xZvRjsr+6XK+0ya+x+ZpeoZpO1oVnJGeY0o8q3Y5Zwf1uud8/lcCGcRnrDJ9NJN6X4e0uA9aK4jH2Zyq16A+R1MXx953TsRrPjmvWUZ97oh5rcsTXIhri96juVDf89A2ua2G3sTVHDLT/Kh1uZzad7M+iPi5V1sO7aHWkTNq5UKvg8SHTL+1B1Pr/iTYu+JXDPFk0ZgnvtRzin269VxYAnEbx6VqW6jnGhfkGP37AvGwSC81W2of6B/ZFeefRlz1tfhLFWrfOD7pzejKJn6pOW6ck9pnsSUfahmFxEv6uFsaqX05sSiX+/oz4s3lz7amUPs4Y2uE6dhr4meLec57UPvetPGCr209cYXr0scVqHPy7r31ufiO/zz3qnUmLdS5aht8m1/xnvgmWe7sI9Q5/Lcy9gnHF+I3/4X1a1Dn9k3429tao8QL3aTHq6hz7sY/FraWOvf/1xnl1j3bqbngke2lEshHfDHalDFKzRFJh6O3jor85/XBZauiqLlzSP357yQp4hfujr6bQc0pz6posYtKxLt7XHZGUXNtkab9SLIm8R139n8cpebg+4rTyXFGxB0Dil09qbn5+Gn7t72I+Aqn3J5qas4aNdz+52xH/NjmJl8tai6b3D7z1NiRuJjPQ75j1Bznb1m0iH8T8RiXvuJ2au7PmpjQaXYj3qz057QydU/E/Ljfcd6H+NEnJ+J9qHvFfOS33Jpg4p83m93LpO4hrdLgMZ6DxCMjb87uoe6tBbVt23KOEI/nOnRZmLrnbHa8c1h18j+usdvPnLoX+QZWl31KJl7Tqn10K3WPlv/99njvNeKfYvYNhVL3bnLxicX/bhIX3Dv7VgJ1TzuMcswJzyW+svT202vUve7vquYy/JD42iOqhreoHKDJ/C7j9oI4L2u1WBaVG5Y8WEIrf0PcV517+w0qZ0j2KJUurCeuIDJf/SKVS8at4tL3thP/khHid4zKMT19R9pLeomfPjrbaDeVe0b2LXabMUA8+nfpMUcqJ622TzJCP4mfmXl9lwaVqza0fVm9e4I4unZ1gIPKYd1jPvfOU7ns/3runRK+Giq3cRkvdXjIT1zXQrommcp5c5VqVGrmEZ+Me07fQOVC3ZuOBl1SxJ11q3zmUTnyvaNOQO9C4m2a7o6vqdx5vaC5jalO/Bpf3ngIlVP3FDzZWa9P/PHAZz85Ktc693hKPzUnvibP5v4LKgdbVXsOXWUQf8M9u2kLlZvH3J1b9y4nnrMrouknlbN9GN9bl6whvsdv4ulhKpdnib7rn+tMXPRE09k5VI5f+eE3X7Ub8RU7AzwSqdwfGzlHL8qbeG+lqa4g1RMevOXZphX4n/e/n8p9lOoVoNwcX7efuJ2v0rsxnxZklnf0gU8k8bxjNi0eVG9Z80q7Y/IYcReOxE8VVM9ZZfHrZ3QCcR+dS1LqVC9qbxf8y32euNhHjrAjVI8aSXv9a/814u6eO+a0U70r1Ty05WMG8a3BB9pVqZ42yki8tiyHuLTTSF8A1esuFMUvu3Gf+LbWM4z7VA+02/y3ceQJ8fcO0l9/UL3x0e9Yc/SKuNm1bcNqVM9kdPeHhlcSl9Iwct5C9dIC/f5TBfXEVT9FqMdSPTZ+xc69PW3ExRmLd+VRvVddaovWjB7iPDoKqg1UT54XVpMn95m4iqi7x1eqV5dcYP3V+Uo8puT7Yl6qhy9dUSJiOkL8rX9rhATV2yV3l/Qb//nP57+hFrCQ6vlbzWjRmlTv/7++QZeHW4397wUuFnZK8hNvET9upR7RjOYcz/s+KUx84f4P6irBzWitW+vz5vnEu2NWNMh4Ua836FtyU464gdsfC8HNzeiJ0ONoP2Xiw7ymAROrmlH4FtM9GprEL2jZ7+tlNKMQWT+JHn3iQnqxm14ZN6Nc2Lcz3oz43r4V8qnqzSi/J2GnFo148fHfdfvkmtGNpNni5UuIL4kY2bt8XjNqTXfc5bSSeIz9/QWSM5uRoNPgrs61xG+vv1PSM96EBhXCxDc6Ez9UsXnfjS9NSOLnw+1VrsTXu9pZe/Q2oaNbwjYZeRFfajWhJdvchNwa7/1M9iN+9hEvreEN9T5d3jpfgokf1eE6fPhpE3qGKgQtwohH1sf+0cprQryG8xIjIoln+zIeNaU3IcHEtPyio8QFDBqL955vQjMHh0OGThA3PdkvLhbfhCrKL7eLJRGvbDWpuHOoCdHz7ZkGF4mf0g7poQU1oVk+9ZHLUogn627dXufZhD6NSpQ6ZRBfW5q7dfOmJtRUsfDWxmziNR26zb0rmpBMy3z1NfeIi+pnNnrQmpBBltFKxkPiQxK9br0GTWhuVJuwWjFxGZXbx51Vm9A219CQma+IC85tdqyVakLXFe8e6HhD3Hy58SsQbEL7jqstyqj5z/78cqMvm6sJta1+sntHE/GL6ycqREcakay1o4tcB/HOMZGAfX2NiMv053B1N/EZohXvWzobUbPOG+2gj8Rjw/5p6dc2ItYmCRHBQeJ6q89siH3ZiCYU0JXU78TFKj29uwobUZHxs3q10f+sW5/zLo2sRtR/Vb8ga5I4k77Oe++VRuRzfx1DgYs57RpPDL2LExpRieVk5MmZxJtWdO/hjG5EYzukAn8IEFd7aZwMexvRZNsrsRUixFlhso1h3o3o6gMV/6sSxKM1Q0zytzSir5kJER+liZvckKv66NCI1D/utF+kSPzC8fFz4taNSM3AvGmTCvG/0h/S6caNiDGcKXNUg/jgv6IJb7VGVKa0XzVLl3jnz403Tsk0omrP42MvjYjTr57LyhVqRI+42hIazYm/WL5c9C13I+odODzcAcRf59sNfBppQK9fvlRutyFu/MTF5G9fA3Lr/KpWs4z4BktXHuEu6vWmB3mKVhEfKBXdIF/bgK6d/lt4ZS3xLdvoFhovG9CdVUq2ezcSn7P6ziODwgbEGfvk/pKtxK/0ibaZZjagnJn5fILuxJeYGqSZX25APMbCttU7/rPO3S/kzU41IF7Vv35RvsRfVftvMoxqQN8OFx/TCiB+c8bABs09DSg/quBc3R7iYh4dSopeDUibuS3FJ5R4geu7snnODUj25Zabk+HEo1quLeFa2YA2PfPKiz5M/HjJzbtD0IBO3tnwkvsY8ZCZ8TOb9RuQ8lXF3v3xxBWMWtYXKTcg46etIp8S/vPc7edkXpFsQAWGWZuWnyUueeA290GBBrRe+F1xxgXicn0quzf+q0f1YoPWv68Q/xHwfUTvRz06fHXZD/p14p67/VP4PtSjW0EpVYcziGcf5NzT1VKP3l+53VaURZxp+O9ATkU9UjS2lRvIId468eD5gaf1SNvEM004n7jW00A7u9x6ZMWQ8dV+QDymcJe0cFo92u5z/pB10X++lwnTuuVsPRL4Lffe4RnxJ97f3lw8Vo8WqkukrH1JXEmsPN85rB7t+TXxaFU58aeuYbMX+NWj5iJPE3ol8e/p0s1NLvVo2+zZiho1xDmVcmVPralHVcvuHZzTQHxPp86gjW094t1rs/pjM/HV9qdsx03q0afXJRmF7cSHzPIMs9Xr0bUd9KhwJvHcqIAXzrL1KFrk14BlL/G8jmvfZwnXo4dvFg4MfyBufpPjbT53PcoK1j6a1kd8xxP7rZtH6tC7mITypUPEyw11s7j66lD59eb8T9/+s69g1aOMjjrEZ35rzcFh4gH95mfs3tahXL2SnNlj/9k/o4fQ5+d16H7YaNWpCeIHcs6VHsmvQ/0FOoUC/4gfvfdDQyGjDt0u8wmM5CL//wqqjT8PPD5fh0QPFfF9mUH8dt+3J45xdchdc0n0aj7iLzL0hj8erEOTFsv6cwSIv9wzvDh0dx36WzPPmluI+LHVHtv53euQy0bei6vmET+ecf3OxXV1qM/o3PAZceL+yiV8qnZ16OGylZtrJYmL55VH5JvVoStJpW08MsS7tbMkLTXrkEHlrT268sQD963ueCVXh6qGC0ycFhKv1r5UtUykDg3/e6AepEy8JMdh+C1PHZq9OWH9scXECz/pbHQcrUVuiRqlZzWIl68Y4Kzvq0W+bbEHL2kTN3gq/8uhsxadKnx4/IIecant7qZv39aisbj6H6cMicfeM2pa+qIWbTDkLgk3IV5nIVjzMr8WHbt6mMPTnLhm/mpNi4xaZOd88YGNFfF7letH7p2vRcbo0jcZGvGL+p46qnG1aPLXx4IvDOKVEYU9lw7WovFL/XMe2hJvUAoUmru7FkWsl5sRupS4pGt+SbhbLXr/gy/dwJ74fosjf4fWUuuw1+z/tHfn71Tt7QPHm5xEhDpKGUpSyhDqlFJ3OAgVdQwZooQKJZSx0CmhQsYSmQllyjxP27TZm0oiqUyHypipU3S+vnU5676e5z94rs/7t/2yrb32Xmt91vbLbaL/COWKLj31hqrNYF+v8U/QUcpdAwu31sk1Q45yD3O3NuV+j/tFZcWbQfdkhnWrLuXGIbtpEYLNoKJs3W2tj95XtRUrC3czZLu0y80YUu6ms/1vq8XNYOtZdeWGMeUDCw/tjvvUBFb+37NZTqHz4XDhkFVzEwRynRl0P005a2iqgExOEwi7dImPm1PuJL3sxWRYE7j16nuYnKX8AzNgTZ5bE9wrqxqlWVK+1WPoy+XTTSB+k89743nKxWrj3GQONsFteyMtVxt0viUIZA+KN8Fp+eA/Gm0p352eEBfP3QQr6Mxw3kuUp/Gf1TOYYsKrL0KyBg6Ux3XbtXN0MOHb8ZiN95woF6jPkS0rY4L7Z1tHhgvldz0XXbwQz4S37Lm7Z6+g66h1+f11Pkw4Mx5qK+pOeXK0ZU7NeSaENyiKq12jPIcz+JnNMSaoGgzamV+nfHtmzyTvLiZYvaZrunpSvjEmdFvxOiYsfMbHuOVF+aW4RleTBUw417tmMsiH8q+HvUcW9DHgTi7789DblF+VSPePrmdAZIXchSBfyoWHlpnvT2MA7Bp+4eNPeZ7b706vAxmwrtuRwyWA8iml4WeXHBngs0xsk1kQ5S27XVw4jBhgp6e36WAI5SqC4BJ/gAEtZYZrRO9Rzpbo2C63iQFyloGs3+9TXhepGM1YxoBbEQYLmh+gdWx9XKvJcCNYP+Jli4igPLHI48bo80YIerFtu2kk5YviHmW65zWCh9aiq8LRlB/urDPniGiE4o0s397EoONl65IU5tEIfHyx2QFx6PoK3XVNxLwRzmWpZR9IoDz43cnpVLVGyBKwWfIxEa3DF+R5fpNshHZ+73TfJMrlBafainnm9mchR/m2FHSe50UdU5xuAMUHTgdojynP5JO+WdPRADyiB/fqpVI+ZuPtolbeAH0q3wp70yj/08jyt4b4BnCaWEm3zqD8l61/lmv4NICWDa/9SCblJV9PCTWcb4BxWZ9y6yzKRb/8qa92rAFUhyeKe7Mp7/5T+XLNbw2w6XyvnV4u5damY06K6xpgQ2jvIC0PXUeTOZYl/9Dhkv6NnRIFlCucTNHa1UsHsURtvbuF6HiVM7Zn1NFBzXjAaLiI8r/0lnJvSaWDnUaLlmoJWs8rRacjA+iwemX6vvBSykeEewdWOcz5Nm7Jj2WUS/3x/pOPwZwzg8V3VFC+nzeB5ft+OjwceankXEl5lGrCXtuNdGBK2bkVVFFezL4vqGcpHRqYrP0TNMr5Fzzl1hmsh21Re7y31aDz00q2uLq5Ht5PJ1ufqEX3/Quv7+3MqQdm/NfIW3WUX5RJSY4Pqwe71mdiWfWUS669O8XjVg+cXK2rX9HR+jZ2+rqHaT0Yrkq3n2pA67zAgPaQSj14NbMc5GZQ/ge93kZ/Wz1oKt+I2sxEz+ePaaOtqAepCy9vyDVRfsBkLEhqog5URRMWqTZT3iQrlhjWVgfr2aM3aj1D77c8duXikjrgOGH/Wfs55Ubv495bxdQBS2ejs84LtM5oGXO3eNbBmiQD2tEWyu91jSTvtayD41wNb9ReovtvnGla7JE62G7fyNjXio7jmlThZbJ1sJWDI1biFTqOxk/ZbFbXwa6GPWZ8bZTnmylatnyrhcN8i4UWtlNu/utaZbn3tRCQxtPZi/yTV0/kQ1ottOj+mkx7ja5rqd9cFybXQmRBjm90B+W3l93rNPOtBU/BhyFObyjvb3Kqr7WtBQ4p+4ZDnej7g6i84lbdWliU2ykn8JbyQrqUxp09tSBv5PHpA3Kl2rv9Q4K18NZ05uPTd5SXRt9aq7m4Fq4ajio6vadcx3tXf3p/DdzunJ6V66Lc4E60FldjDczIPRb9gjy4vkT/YkYNRItH1T7tpjw9woGlObgGMm+bfTrXQ7l6S4yulHMNJEx6RQj0ouuxm0XL70QN6F8N6GMgb+PWnxhUqIF/tJc8c+mjPCRLQUVDtAaCHY3PifxFuYme7sFkthoIPbqmgI7cd0Zg9peRanA6G08/3095ggrXGbMX1ZC60CaJYwB978oM8a7Iq577e6fTKAV5H22pmWBENaxy0Pys9IHyLI3Mby4e1TBot87+NXK/m8yjr8yq4ZJHwIfzHykPM/U9K6tWDSeN/jb5jvxVGoeiv0Q1mFoEvr/9Cd0vjp16/5G7GrKUgy7zDlK+8todZZUpGlzxExOLRE6f8LSPeU0DtzPOLBuH0Pm5fpf1TCkNSqUerkpAfs7yirReHA0MRRJOigyj7+HGm6ozvWjg/su98WjknAMTW5Zb00C94vyrtSPoPuUTY2yhRQM2Lj7eQOS7/F+eKd9BAyuRqwW/jFL+q4aUylo+GmQfsmtwQl6iqvDNfrYKjj6g6QwgL/YI9GZ0VYGCt6ypzhjlR8MiR0RrqqAtxvZrGXJXnlZpj5QquC8msmXLZ8o/XovUavergqvl3RO+yF/UHjssYz/3uhy7LMeQOyorid3Wq4KPZhEBx8YpH+bJ7evZWwUZdu6XMpH37ui/Lr++Cn7t3sfPOYE+z+esLCFLqqCLVTTwLPLD55QshwYqITvQ4V05claW3GxlRiUkSxhzrJ6kPMPWoe9hZiW47f4mYoXcwDZgdjKkEjTtDKVKkHOMsn0/7FIJbE9cd3JMofvjrrf9CcaV0OmqesAQudPG70WzipVQ/vn+8UfIu4/puOpsroQt2ru9xpD7GNWIprJXgkBzR4vcNOXHF4iXLRmtgG7YrO6B/Ii+vrJRSwUI9z0eoSFv4FxbmJVfATnbBhhLv1Du4ikjyP6wAsQvqA4dRO624qSd6bUKkCrZoOuNXJNfP6/AvAIMk4u4apBXnmEMcalXgCCXyqZFf1NevcWC96xkBSh+6gyXR64ANdJlPHP7ufHOlcvI7U/dOsA7XQ7tp5WbniDPPKimdL6jHNomPoR3I7foDNpDKyuH1CDlj7xfKbcynRRdF18OgkdXVKohr44aZ7XzLocjth+2uiIPWb6iq866HCyOnBJ/jPzkl8p0oaNz29k/wmhH7pPledlh59zrOk/xLv2G3ldenQyDrxx8WKs5ZZE/vz/WpDpTBkapQcUnkAubzWydpJXBzZeem72Q0z2dHWN9yyDuVrJuOvJx2S25mrplcNBiWqsVefP5sv4ZwTLw9zomMIP8pcLw8pT+UtC/5V25fobyKR4jUb2MUvjV46jq78jzO5J2LHEuBe6Pmk8tkBtfPL87U6EUmNlcbN7IWcv2yhizlcLJHew6ScgtOKOE2f9/LoxwTFgtco69/Gz54SXQECb4tg/5oXHpD2ZmJeDCV7hl8Szl30ePl3NLlMAp92B3IeT1Mkvulk4WQ9WygoE9yEtkYo5blRaDrK6ApQ7yYP77a9d4FcO5UzHLbJC/WHiolaZZDA03VzC8kN9bvu6O7ZpiOOzBXxiFXD3TWF6wqwjELc605iJ3e2vVT08ugrI0580M5MPbgnwd7YpAVXLuNo48dukGKZG9RVDKm3Z1Gm+/+0Rj8+IiSJt28GX/TnmKvp/51cZC4C7V7hdE7m86/lUspBD4s83uSmO/SL/TeqIQpK+l+SohV314eN110ULIFBPp1UZ+gJmVKDVSANOcsffNke9o3y71Jq8AVEeG0y8jz3w0me3tUQBf+ookPZGr6W/fvVOtAGqt4vmCkfuZLS/o4i4AZT3Jy7HIT+c93eX3Oh8k39YrZyB3fKmWvScuH4JCn/mXIL8/NSnZb5UP+s639OjIx4TbHwXtyAfo2xjTilxXc6XQgdk8eBebd7Ebea1jZfBgdR7IfFSjDyFfXrBoWZhfHoycrc/8grd/bthVWS8Pvqqv2LYYzX8tlIkcGhPKA5Hf38lxINcQETOOHMiFnvD+Ll7k4sx4hnpmLmzYWyG6HvnlPzbJTzvngkTxCLsYchf3kuQ4xVzouNIVLI28o82NV4s9F0yyRmhyePvZzn/OvMiBQ57GUQrIx5RLhpIicsB9w4nNasiPZOkd1zHPAac3LCe1kIcL61YulMwBG03jQ3rInem0bWlT2aDkojdyAjl9QXqwQVk2NPYzNMyQpx8Umv3FOxv2vvQxs0TeYiJknqWVDYOGIH8R+SaN/EYTvmxYG+n38jJypuln2eXdWbByarGsK/KLJ14+yE/JgvNb1uh5ID9qeHahuX0WpNzf/rsncpnRzDPc8lmQ4BE144N8qUQ+o2RJFpRvjf/TDzlfsoesJeMpJEhatQXi436LK4w39CkEZnAuuIf8k5/190rjp6AWF/rtAd5P7rDTNpufgvbyvxsjkSeufFC3bjQTQtXXOsTi/VGyl6jLzwQ5E8aXBORcC7YEXrqWCbC7RTcZucLpoqn16pnwx+y7gCfI/1DabsjgyYRfjQMepyMfkPMpc+7IgKEup4SnyM2T6jaKxmeAvtzqaznIHYpHvZ5bZ4Di3U7IR77l0uJBt50ZYNYl0VOIXFGJJVp3Jh0S1Q2tS5A/6Xx3Jt03Hf4+lfKmDPmZijApVqF0eHvr6M5K5AXZO6dPZqTBgUPOjjTkVyC3tEAhDTIS5eNrkPtlCNzkeZEKjy2Ti+uQ1wtfOGxllgqC/uUVdOQi15JX0SafwKiXQ3Yjcs7bzzr4vZ7A1YisECbyv1/1x15e8wQO7de2aEbe8HroHDP5MdiZiG1+jty4r3f75r2PQaf+S9sLfBy3MafdG1OA0/7qlZfIb1ellLadSAGBtjM8r5BzpLp6So8kw8gR4/A2vJ0mhUO3PJLBymR29Wvk7DOzPD3cyeDP1+bdgXzneEb73rgkGLByGn6Dz09Tw+jgHUmw38VE7S1y4YFZi6HqR9A3zvLgHfKElWESKnqP4DfLN+/fI//njMRE5EAiJCVqCHYjZzMqKpx2ToSSBTnHepA/NFS6psWeCLZZdm69yDXrq1WTIxJAQaYtpg+56XdFzkWSCWByVabkL+SXDhW1GJTFw4bLdc39yJtmJcOztOLBRrzjzQDyhbqRp5Z3x8GoXGLXB+S9gcu2mNvP+dKT7z4inx68OFyyJA6yhPe0fsLr6r2WbN7QWBD2PFUziNfhqh2uNptj4WHP9/Qh5PsfBCjU5cdA/MRvQcPI5ZQ/Ld2gPud5Wy+OIJf9oMB07ogG9oJplVHkbkkhwc+to8FQO3/1GF73lBk5ujNRYDF+vRs77+A5RVahKBDWsHn0GV+PrgubChQioSbkjsU43o5YsKGV2UOQoX8SmkD+1ybhAX6vCKhsfvAC+97ox5eYyeGgmZNwbRJ5RvX2hR6ND+B6K++PedLzvrM801d6JAxu8Ew3Yk8pkFzbwx0G3aOHf8yrnveT7Y8Sg3fch/r6DT/mW8+7joqArIrePQj96BiMnb7Jv2zaORQC8rR/zM+ed6mHsxrJESGwtaEoCfvvzWfbDMqC4RhPxo/53PP+obvZbHl3EGj8JfsIu+aXnWMlS4JgdKPaj/nf8y4ie/+qzeZAOHZgzB87X+70sg3qAbDEUGIGu1ucduhz67vAe+S76Qzym/LGyqxC/tBUZEbDPubHaWxl5guBa0/9mHc+70XXCx2YybchvnTcAfsmY1N/6REfcOnmr8N+0fSXpOAd3nAp9c2P+evzXtiSWD7tfBOE5H7Oa5/3G9NK7QZlN+BiyPpw7Cu43s59DtdhoCG+FbvcqctsG9SvwbuusuV4Xv5N41UqrELuIPzadh/2da5yjsxkV+DO/Tmfft63RxnM7acTyDv8nGc/70u0neb25xL8tfbn/Pt/P2ehoLnXtQW++J/z8ufdkEtvbvtW8Ir753z9f9+X9I257ZjBVrOf8/j/ff6xE3PPNwS28J/z+/91OeM514B9Hfxzj97/64G3gzR32Mr8l//78//4vwG0slX7/nFf5DH/mP0/f4FEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBLpf6//Aw==
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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- Scale an object with non-uniform factors.
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- Deconstruct a numeric domain into its component parts.
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- Extract the end points of a curve.
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- Create a rectangle from a base plane and two points
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- Retrieve the base plane and side intervals of a rectangle.
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- Preview a Drawing in canvas.
Note: Right click on the component to save the image or svg
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- Solve oriented geometry bounding boxes.
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- Applies Stroke properties to a Shape
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- Stroke
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210
104
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11206
-659
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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11044
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11119
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11044
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11119
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0;212;212;212
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11044
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11119
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11044
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11119
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- The shape to be used at the end of open path
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11044
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11119
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11234
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- Deconstruct a box into its constituent parts.
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- Deconstruct Box
- Deconstruct Box
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10105
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10150
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10164
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- {x} dimension of box
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10150
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10164
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10150
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10150
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10164
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- Rotate an object in a plane.
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- Rotate
- Rotate
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9865
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9865
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9947
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9865
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9947
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0
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10037
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10062
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- Create an ellipse defined by base plane and two radii.
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10396.5
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0
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10396.5
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10484
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10484
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10504
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10484
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40
26
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10504
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- Deconstruct a numeric domain into its component parts.
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- Deconstruct Domain
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38
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10169
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10156
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42
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10169
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- Deconstruct a numeric domain into its component parts.
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108
44
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10142
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10092
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38
40
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10111
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- Start of domain
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10154
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10167
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- End of domain
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10154
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10167
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- Addition
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70
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10240
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10217
-239
11
20
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10222.5
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- Second item for addition
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10217
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11
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31
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70
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10242
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10219
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10254
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10269.5
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- Applies a Solid Fill color to a Shape
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- Solid Fill
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162
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10601
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10538
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10487
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102
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10538
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255;253;253;253
- A Graphic Plus Shape Object
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10613
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10629
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10546
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210
104
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10710
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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10548
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10623
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10548
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10623
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0;212;212;212
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10548
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10623
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10548
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10623
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10548
-300
150
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10623
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10722
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10738
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- Merge a bunch of data streams
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11025.5
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11025.5
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11025.5
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10994
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11025.5
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11065
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11080.5
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- Solve oriented geometry bounding boxes.
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10359
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10224
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10285.5
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0
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10381.5
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10371
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10381.5
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- Create a polar array of geometry.
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226
101
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9628
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39.5
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0
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58
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9694
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9784
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9809
73.75
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- Join as many curves as possible
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10015
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- true
- Shape
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10976
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32
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10992
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- Solid Fill
- Applies a Solid Fill color to a Shape
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- Solid Fill
- Solid Fill
-
10469
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162
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10585
-624
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 23bd9ad5-0ed7-4bd5-9ebf-540a6ef29898
- true
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- Shape / Geometry
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- 459c146e-b950-4487-9814-03c0b98d439f
- 1
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10471
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102
20
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10522
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- The solid fill Color
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- true
- Color
- Color
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- 0
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10471
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10522
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- {0}
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255;255;255;255
- A Graphic Plus Shape Object
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32
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10613
-624
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
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- Stroke
- Stroke
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9608
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104
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9772
202
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- true
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- Shape / Geometry
- false
- d5b4aeff-ff26-4ef9-b2e5-496815defd19
- 1
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9610
152
150
20
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9685
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- The stroke color
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- Color
- Color
- true
- 0
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9610
172
150
20
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9685
182
- 1
- 1
- {0}
-
0;212;212;212
- The stroke weight
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- Weight
- Weight
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- 0
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9610
192
150
20
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9685
202
- 1
- 1
- {0}
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- The stroke pattern
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- Pattern
- Pattern
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- 0
-
9610
212
150
20
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9685
222
- The shape to be used at the end of open path
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- true
- End Cap
- End Cap
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- 0
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9610
232
150
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9685
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- 1
- {0}
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- A Graphic Plus Shape Object
- true
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- true
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- Shape
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- 0
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9784
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32
100
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9800
202
- ae8329c9-147c-4440-b557-2977e71e7195
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- Blur
- Applies a Blur Effect to a Shape
- true
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- true
- Blur
- Blur
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10660
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183
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10797
-600
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- true
- Shape / Geometry
- Shape / Geometry
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- d91d7edd-1058-45d7-83bd-c03acddb095d
- 1
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10662
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123
20
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10723.5
-610
- The radius of the blur effect
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- Blur Radius
- Blur Radius
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- 0
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10662
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123
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10723.5
-590
- 1
- 1
- {0}
- 1873
- A Graphic Plus Shape Object
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- Shape
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10809
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32
40
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10825
-600
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- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- GraphMapper+
- External Graph mapper
You can Right click on the Heteromapper's icon and choose "AutoDomain" mode to define Output domain based on input domain interval; otherwise it'll be set to 0-1 in "Normalized" mode.
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- true
- GraphMapper+
- GraphMapper+
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200
155
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-161
- External curve as a graph
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- Curve
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- 1
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- Optional Rectangle boundary. If omitted the curve's would be landed
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- Boundary
- Boundary
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9762.5
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- 1
- List of input numbers
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- Numbers
- Numbers
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9696
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133
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9762.5
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- 9
- {0}
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- (Optional) Input Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
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- Input
- Input
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9696
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133
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9762.5
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- (Optional) Output Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
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- Output
- Output
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133
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9762.5
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- true
- Merge
- Merge
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- Data stream 1
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- Data 1
- D1
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31
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-278
- 2
- Data stream 2
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- Data 2
- D2
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31
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- 2
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- Data 3
- D3
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31
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9341.5
-238
- 2
- Result of merge
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- Result
- Result
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9381
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31
60
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9396.5
-258
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- cde9ae79-6dfc-4694-91e2-ee29e1d1dcd7
- true
- Join Curves
- Join Curves
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116
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9495
-183
- 1
- Curves to join
- 7e85ddef-afbe-4a51-8eb9-f1bf04d0e562
- true
- Curves
- Curves
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- dcf72494-3a24-4054-8e57-73ff14e59867
- 1
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9430
-203
53
20
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9456.5
-193
- Preserve direction of input curves
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- true
- Preserve
- Preserve
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- 0
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9430
-183
53
20
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9456.5
-173
- 1
- 1
- {0}
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- 1
- Joined curves and individual curves that could not be joined.
- f110d2a6-04ba-40d1-8ede-576629de1ee0
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- Curves
- Curves
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- 0
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9507
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35
40
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9524.5
-183
- 6da9f120-3ad0-4b6e-9fe0-f8cde3a649b7
- Gradient
- Represents a multiple colour gradient
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- 4ce826ff-60b9-473f-b4eb-19a5a0af2170
- true
- Gradient
- Gradient
- 2
- false
- false
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255;255;255;255
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255;255;255;255
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255;0;0;0
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255;0;0;0
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250
64
- Lower limit of gradient range
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- Lower limit
- Lower limit
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71
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9409.5
-98
- 1
- 1
- {0}
- 0
- Upper limit of gradient range
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- Upper limit
- Upper limit
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- 0
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9374
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71
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9409.5
-78
- 1
- 1
- {0}
- 1
- Parameter along gradient range
- c8a087a3-d6c3-4075-94f5-b6f03f5a18b8
- true
- Parameter
- Parameter
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9374
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71
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9409.5
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- 1
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- {0}
- 0.5
- Colour along gradient at parameter
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- true
- Colour
- Colour
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- 0
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9618
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0
64
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- 73688d20-ee53-456b-b585-492357d5b4d0
- true
- Bounds
- Bounds
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9431
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9489
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- 1
- Numbers to include in Bounds
- 53f4ce57-ff16-487d-8441-74fef124b562
- true
- Numbers
- Numbers
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- dc1f0f58-8adb-425c-a5a4-72b7549f074b
- 1
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9433
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44
24
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9455
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- Numeric Domain between the lowest and highest numbers in {N}
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- true
- Domain
- Domain
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- 0
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9501
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38
24
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9520
-23
- ae8329c9-147c-4440-b557-2977e71e7195
- a48ac930-c378-48dc-84da-26b2af9d8302
- Blur
- Applies a Blur Effect to a Shape
- true
- e1697a07-a9ef-47c4-be33-bd2577c238b3
- true
- Blur
- Blur
-
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167
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10793
-680
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 55536ade-da41-411e-869c-66f8f104949a
- true
- Shape / Geometry
- Shape / Geometry
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- 9b545ea8-d3f4-45eb-ab0f-79f46e4a2580
- 1
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10674
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107
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10727.5
-690
- The radius of the blur effect
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- true
- Blur Radius
- Blur Radius
- true
- 0
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10674
-680
107
20
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10727.5
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- 1
- 1
- {0}
- 4
- A Graphic Plus Shape Object
- true
- 8ea3d944-5234-46ce-8de0-309341193327
- true
- Shape
- Shape
- false
- 0
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10805
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32
40
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10821
-680
- e168ff6b-e5c0-48f1-b831-f6996bf3b459
- Interpolate data
- Interpolate a collection of data.
- true
- c38bf768-8e55-4765-a68e-79216a92a01f
- 1
- true
- Interpolate data
- Interp
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11601
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- 1
- Data to interpolate (simple data types only).
- ee7aa4b8-d343-4799-9e97-44326e8b51b2
- true
- Data
- D
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- 1
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11578
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11583.5
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- Normalised interpolation parameter.
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- Parameter
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- 1
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11578
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11583.5
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- Interpolated value.
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- V
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- 0
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11613
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10
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11618
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- Red
- Colour (palette) swatch
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 96f356b4-31d4-4a6c-a021-53224daa73cd
- Relay
- false
- 7fd0d788-1237-49d2-b610-14b9cdecf740
- 1
-
-14100
1403
40
16
-
-14080
1411
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1285/256))
- true
- 77885843-cab1-42df-89ef-8ef6f86566c5
- Expression
- Expression
-
-14842
1134
207
28
-
-14736
1148
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 1995246f-289e-4ca3-ba04-aced7cd0dd72
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1136
11
24
-
-14834.5
1148
- Result of expression
- 5293ab1a-72a3-466f-8acb-12d53fff800e
- Result
- false
- 0
-
-14643
1136
6
24
-
-14640
1148
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1423/256))
- true
- 62e50431-70a5-40a1-bbba-f39166ca5d3f
- Expression
- Expression
-
-14842
1083
207
28
-
-14736
1097
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- e995b869-e468-49a5-8a2d-d6a6c4ee65bb
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1085
11
24
-
-14834.5
1097
- Result of expression
- 0c05c4dc-a41d-4f25-8fa8-59904954782e
- Result
- false
- 0
-
-14643
1085
6
24
-
-14640
1097
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1488/256))
- true
- 6cddbed6-1dd7-44ed-a9e0-86fb89ef71a3
- Expression
- Expression
-
-14842
1032
207
28
-
-14736
1046
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 188ea3f9-3d71-488d-a663-f1aebd24f572
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1034
11
24
-
-14834.5
1046
- Result of expression
- b808466f-043c-43c9-872f-0833987d5625
- Result
- false
- 0
-
-14643
1034
6
24
-
-14640
1046
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1644/256))
- true
- e469ff08-a104-48ec-9f4e-573c7b3bfe16
- Expression
- Expression
-
-14842
985
207
28
-
-14736
999
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- e21cd616-c856-435f-b9bb-99df4f859c1a
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
987
11
24
-
-14834.5
999
- Result of expression
- 88231914-12a4-4ab2-8751-7897fa9c1043
- Result
- false
- 0
-
-14643
987
6
24
-
-14640
999
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1709.5/256))
- true
- 20d5d108-2056-41af-930a-8e90a1009dff
- Expression
- Expression
-
-14850
937
223
28
-
-14736
951
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- b43f180b-fc85-4b05-92b0-c3331dbc3dea
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
939
11
24
-
-14842.5
951
- Result of expression
- 59be1fbf-4cb3-42fe-8174-bf8b71739b0e
- Result
- false
- 0
-
-14635
939
6
24
-
-14632
951
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1794.5/256))
- true
- 87e01a5c-d135-4116-817d-da2496621529
- Expression
- Expression
-
-14850
882
223
28
-
-14736
896
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- dc9595aa-3dee-4da2-8d0c-c395029d8a6a
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
884
11
24
-
-14842.5
896
- Result of expression
- 34ff7268-139f-4f7c-918d-a790b243fd03
- Result
- false
- 0
-
-14635
884
6
24
-
-14632
896
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1874.5/256))
- true
- 03b98b72-99ad-4536-9e58-90622f9ef991
- Expression
- Expression
-
-14850
827
223
28
-
-14736
841
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 5853fbe8-0752-447a-bbce-fb563454ca9e
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
829
11
24
-
-14842.5
841
- Result of expression
- 47598a96-ccb9-4b95-ba69-e34e2d68ea96
- Result
- false
- 0
-
-14635
829
6
24
-
-14632
841
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1910.9609375/256))
- true
- 55a8e211-f823-44ad-b334-d360d90f528a
- Expression
- Expression
-
-14875
777
273
28
-
-14736
791
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 350f11e7-3838-41b6-a4ae-3223f4993da3
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14873
779
11
24
-
-14867.5
791
- Result of expression
- c8faf00d-35ab-4093-8e9d-f4865d3ec68f
- Result
- false
- 0
-
-14610
779
6
24
-
-14607
791
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- ⦿옷⦿ᑫᑭ⦿ᗩ⦿ᴥ⦿ᕤᕦ⦿◯⦿ᗝ⦿ᗱᗴ⦿ᑫᑭ⦿ᗩ⦿옷⦿ᔓᔕ⦿◯⦿ᔓᔕ⦿ᗱᗴ⦿ᑐᑕ⦿ИN⦿ᗱᗴ⦿ᴥ⦿ᗱᗴ⦿Θ⦿⊙⦿ᗝ⦿◯⦿ᗱᗴ⦿ᴥ⦿ᑎ⦿✤⦿ᗩ⦿ᗯ⦿ᴥ⦿ᑎ⦿ᑐᑕ⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿ᑐᑕ⦿ᑎ⦿ᴥ⦿ᗯ⦿ᗩ⦿✤⦿ᑎ⦿ᴥ⦿ᗱᗴ⦿◯⦿ᗝ⦿⊙⦿Θ⦿ᗱᗴ⦿ᴥ⦿ᗱᗴ⦿ИN⦿ᑐᑕ⦿ᗱᗴ⦿ᔓᔕ⦿◯⦿ᔓᔕ⦿옷⦿ᗩ⦿ᑫᑭ⦿ᗱᗴ⦿ᗝ⦿◯⦿ᕤᕦ⦿ᴥ⦿ᗩ⦿ᑫᑭ⦿옷⦿
-
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27409
55
20
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7620.5
27419
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7672
27369
38
20
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27389
38
20
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7691
27399
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7672
27409
38
20
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7691
27419
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- A wire relay object
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10418
28157
40
16
-
10438
28165
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28217
226
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28217.96
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255;255;255;255
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27373
78
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27395
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41
40
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8000
27375
9
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27395
9
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27083
90
104
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27135
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27085
31
20
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27105
31
20
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27125
31
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27145
31
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27155
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7822
27165
31
20
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27175
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7877
27085
31
100
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7892.5
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- Mathematical division
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8102
27360
70
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27382
- Item to divide (dividend)
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11
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- Item to divide with (divisor)
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8104
27382
11
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27362
31
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27041
78
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27063
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27043
41
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7501
27043
9
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27063
9
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26963
78
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26985
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26965
41
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26965
9
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26985
9
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111
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27039
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27009
61
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7629.5
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61
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7629.5
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0
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27049
61
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7629.5
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7684
27009
22
60
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7695
27039
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27128
197
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27130
122
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27140
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0
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7568
27150
122
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7629
27160
- Optional plane for 2D angle
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7568
27170
122
37
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7629
27188.5
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27130
47
38
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7729.5
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7714
27168
47
39
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7729.5
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226
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130
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27014
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26984
78
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7845
26994
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27004
78
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7845
27014
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27024
78
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7845
27034
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26984
24
60
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7920
27014
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26986
106
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27018
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47
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47
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47
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26988
31
60
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160
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46
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46
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11
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11
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11
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- Power of 2
- Raise 2 to the power of N.
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- Power of 2
- Raise 2 to the power of N.
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- 00000000-0000-0000-0000-000000000000
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 0b9f480b-88da-4856-9c83-6d1d5314a585
- 1
- 0208315a-ac5c-4218-a12b-42c843878280
- Group
- ⦿✺⦿✺⦿
- e9eb1dcf-92f6-4d4d-84ae-96222d60f56b
- Move
- Translate (move) an object along a vector.
- true
- a4283709-82ce-4012-a8b5-950c46998f27
- true
- Move
- Move
-
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201
44
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7587
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- Base geometry
- f417dbe0-4a39-4dcf-9737-e57f0d97ada0
- true
- Geometry
- Geometry
- true
- 97a5f791-e1a9-4f20-b7bf-bca497bdd92b
- 1
-
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123
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-
7513.5
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- Translation vector
- 0617d7e2-44db-444c-9bff-d35d80e4d831
- true
- Motion
- Motion
- false
- 0
-
7452
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123
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- 1
- 1
- {0}
-
0
0.5
0
- Translated geometry
- 121da76f-3b82-40b0-a2b6-62365e4ed90d
- true
- Geometry
- Geometry
- false
- 0
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20
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- Transformation data
- 1aa7ddc8-2b2d-47b6-b898-3fd430caa004
- true
- Transform
- Transform
- false
- 0
-
7599
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50
20
-
7624
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 6f1a16f5-76e8-400f-b6d6-b31f775ca595
- 32f809c0-d4e4-46b1-918c-88686e051997
- ecc4fafa-b694-4673-82b0-7ce4302cfe80
- 3
- 2dd6b27d-0ff2-44b8-9abd-26174c019846
- Group
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- ΘᗩΘ
-
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- Applies Stroke properties to a Shape
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- Color
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- The shape to be used at the end of open path
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- Removed all null and invalid items from a data tree.
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- Preview a Drawing in canvas.
Note: Right click on the component to save the image or svg
- true
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- Drawing Viewer
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- The PPI (Pixels Per Inch) resolution for the image which must be greater than or equal to 72.
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- Resolution
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- Applies Stroke properties to a Shape
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- Color
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- The stroke weight
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Length
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71
20
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71
20
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50
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- Close polyline
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- Closed
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40
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- Polyline
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38
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- Create a polyline connecting a number of points.
- true
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- PolyLine
- PolyLine
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106
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- Vertices
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40
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- Close polyline
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- Closed
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40
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- Resulting polyline
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38
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- Merge a bunch of data streams
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- Merge
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90
64
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- Data stream 2
- a994094a-2e0c-4d33-bd70-ab048da589ff
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- Data 2
- D2
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- a55f5b2b-59dd-4127-af45-fb2940b84e66
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- D3
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- Result
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Length factor for curve evaluation
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- Length
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71
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71
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- Tangent vector at the specified length
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- Curve parameter at the specified length
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- Create a polyline connecting a number of points.
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- Close polyline
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188
101
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- List of curves
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121
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- Optional points to define regions
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- Combine
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
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210
101
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132
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-
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0
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- Number of elements in array.
- e228660b-0381-4064-b83d-8ca570d2b8ed
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b2942652-4e75-4d30-be8c-77cf436e1982
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- Angle
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132
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-
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50
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50
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
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- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
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-
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- 1
- Points to operate on
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-
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113
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-
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- Proximity tolerance distance
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113
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39
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39
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- Number of input points represented by this output point
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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78
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- Data matrix to flip
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- Data
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25
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- Create a polar array of geometry.
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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132
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50
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- Cull Duplicates
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-
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180
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- Points to operate on
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-
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113
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- Proximity tolerance distance
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-
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113
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- 1
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- Culled points
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39
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39
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- Number of input points represented by this output point
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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78
28
-
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- Data matrix to flip
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- Data
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25
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25
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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149
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Tangent vector at the specified length
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210
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132
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132
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132
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50
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
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-
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180
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- Points to operate on
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113
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113
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- Number of input points represented by this output point
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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-
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78
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25
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- Number of elements in array.
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113
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35
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- The value will be false if the line was removed.
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35
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- Flip a matrix-like data tree by swapping rows and columns.
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94
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41
24
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- Create a polar array of geometry.
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-
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210
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132
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132
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- 1
- Polyline vertex points
- e59e4596-b562-49bf-8335-eefb53af9b9c
- true
- Vertices
- Vertices
- false
- 0
-
15691
-1103
50
20
-
15716
-1093
- 1
- 6
- {0}
-
0.253426732105701
-0.309892456276559
0
-
0.0334255287749989
-0.473981751578464
0
-
0.0516576726974328
0.289337340640768
0
-
0.594975561585963
0.271105196718334
0
-
0.577958893925024
-0.549341279791191
0
-
0.355526738071331
-0.302599598707586
0
- Close polyline
- f1f7d634-b5dd-4c51-9303-fe50639af409
- true
- Closed
- Closed
- false
- 0
-
15691
-1083
50
20
-
15716
-1073
- 1
- 1
- {0}
- false
- Resulting polyline
- 55e2b44c-7595-4da6-bdc2-27211f29bd8b
- true
- Polyline
- Polyline
- false
- 0
-
15765
-1103
38
40
-
15784
-1083
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 25a32639-1938-49fc-8728-8ad84876e376
- true
- Explode
- Explode
-
15869
-1067
134
44
-
15940
-1045
- Curve to explode
- c3ccf7ec-ba9f-499c-81a1-9d1dc74b42f4
- true
- Curve
- Curve
- false
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- 1
-
15871
-1065
57
20
-
15899.5
-1055
- Recursive decomposition until all segments are atomic
- 0f9cb2f4-802a-4cb2-82c8-2656e9252490
- true
- Recursive
- Recursive
- false
- 0
-
15871
-1045
57
20
-
15899.5
-1035
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 1b904cf9-6d07-4371-8794-c811f80ea402
- true
- Segments
- Segments
- false
- 0
-
15952
-1065
49
20
-
15976.5
-1055
- 1
- Vertices of the exploded segments
- 4452f4d1-91d8-4946-88d6-5888c9faa279
- true
- Vertices
- Vertices
- false
- 0
-
15952
-1045
49
20
-
15976.5
-1035
- ccc7b468-e743-4049-891f-299432545898
- Curve Middle
- Get the point in the middle of a curve
- true
- a98d7f24-e9a1-4711-acc6-2d87a7568bd0
- true
- Curve Middle
- Curve Middle
-
16022
-998
117
28
-
16066
-984
- Curve for mid-point.
- 9dad8727-e2b7-4175-a52c-cda81aebda87
- true
- Curve
- Curve
- false
- 1b904cf9-6d07-4371-8794-c811f80ea402
- 1
-
16024
-996
30
24
-
16039
-984
- Point in the middle of the curve
- 716c171e-2e0d-4bde-81a6-268ef5a60530
- true
- 1
- Midpoint
- Midpoint
- false
- 0
-
16078
-996
59
24
-
16099.5
-984
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- b7292e2d-a04b-41d3-a7b1-6e70cd4b600d
- true
- End Points
- End Points
-
16018
-1126
84
44
-
16062
-1104
- Curve to evaluate
- 07aaae07-05f0-46e9-9bb2-3521d8036832
- true
- Curve
- Curve
- false
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- 1
-
16020
-1124
30
40
-
16035
-1104
- Curve start point
- 179bff57-cd4a-493a-863d-25b9a179d84c
- true
- Start
- Start
- false
- 0
-
16074
-1124
26
20
-
16087
-1114
- Curve end point
- 4b7f86fb-520a-49f8-ab98-37b47b50d332
- true
- End
- End
- false
- 0
-
16074
-1104
26
20
-
16087
-1094
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- f598445f-c9bb-4632-ae5a-5ced170ec13e
- true
- Merge
- Merge
-
16173
-1112
106
84
-
16218
-1070
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 64df2663-8991-4145-9111-913541e81ca2
- true
- false
- Data 1
- D1
- true
- 179bff57-cd4a-493a-863d-25b9a179d84c
- 1
-
16175
-1110
31
20
-
16190.5
-1100
- 2
- Data stream 2
- 269a8b4a-e4c3-4863-bf1f-0deb0d87ac67
- true
- false
- Data 2
- D2
- true
- 716c171e-2e0d-4bde-81a6-268ef5a60530
- 1
-
16175
-1090
31
20
-
16190.5
-1080
- 2
- Data stream 3
- 16cd3125-c7cc-4272-b383-8acadd92fcfe
- true
- false
- Data 3
- D3
- true
- 4b7f86fb-520a-49f8-ab98-37b47b50d332
- 1
-
16175
-1070
31
20
-
16190.5
-1060
- 2
- Data stream 4
- 6e98d805-d129-410e-9208-7e959562de1b
- true
- false
- Data 4
- D4
- true
- 0
-
16175
-1050
31
20
-
16190.5
-1040
- 2
- Result of merge
- d41ee257-f83f-44a4-b288-3bff9e9da672
- true
- 1
- Result
- Result
- false
- 0
-
16230
-1110
47
80
-
16245.5
-1070
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a1cd0866-6775-4e14-9c95-510db4b8326d
- true
- PolyLine
- PolyLine
-
16310
-993
116
44
-
16374
-971
- 1
- Polyline vertex points
- ec7c6dab-9b0d-40fc-8bdc-62f65e696227
- true
- Vertices
- Vertices
- false
- d41ee257-f83f-44a4-b288-3bff9e9da672
- 1
-
16312
-991
50
20
-
16337
-981
- 1
- 6
- {0}
-
0.230849276451111
-0.197502004087453
0
-
0.0662562057590903
-0.223755241522163
0
-
0.0663636407279125
0.199099878871604
0
-
0.609184501908787
0.20516461549513
0
-
0.605827517736367
-0.203827499272069
0
-
0.401731366034673
-0.194413499441869
0
- Close polyline
- 05860923-c6b2-4151-b8ba-800a16aab90b
- true
- Closed
- Closed
- false
- 0
-
16312
-971
50
20
-
16337
-961
- 1
- 1
- {0}
- false
- Resulting polyline
- 99adb399-bb0d-42f7-995a-6b1d6ba6e352
- true
- Polyline
- Polyline
- false
- 0
-
16386
-991
38
40
-
16405
-971
- cc14daa5-911a-4fcc-8b3b-1149bf7f2eeb
- Point List
- Displays details about lists of points
- true
- 47957213-cdcf-4228-a22d-1459dac03b4a
- true
- Point List
- Point List
-
16324
-889
74
44
-
16384
-867
- 1
- Points to display
- true
- f53fe761-7495-41bb-984a-5d00113338bb
- true
- Points
- Points
- true
- 7dfed2fb-2c2d-43fe-80f7-67d25a4cb30d
- 1
-
16326
-887
46
20
-
16349
-877
- Optional text size (in Rhino units)
- 48a722bc-723e-4c9a-8aee-6d0321f04616
- true
- Size
- Size
- true
- 0
-
16326
-867
46
20
-
16349
-857
- 2576f657-2f0d-4e3e-9dfb-c79eb4cd13d7
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop Start
- Start the loop with this one. Double click to rerun.
- true
- dfbb98ef-98e2-40fb-9c5f-4322dc449848
- true
- Loop Start
- Loop Start
-
15824
-1312
118
64
-
15889
-1280
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 3
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Number of repeats
- dd387923-9b22-4629-bdb1-d0a610793581
- true
- Repeat
- Repeat
- true
- 0
-
15826
-1310
51
20
-
15851.5
-1300
- 1
- 1
- {0}
- 64
- 2
- If you want trigger loop to restart
- 85885200-e9ee-4621-a0fd-ea1c8eb9e686
- true
- Trigger
- Trigger
- true
- 8922d579-58bd-4f83-b1d2-2f7c1c847b74
- 1
-
15826
-1290
51
20
-
15851.5
-1280
- 2
- Data to loop
- f9b4de04-ed90-4a16-a896-ee43d05682a9
- true
- Data
- Data
- true
- 55e2b44c-7595-4da6-bdc2-27211f29bd8b
- 1
-
15826
-1270
51
20
-
15851.5
-1260
- Connect to Loop End
- 688aaa76-c5c0-437f-bb7b-d2fb2d647152
- true
- >
- >
- false
- 0
-
15901
-1310
39
20
-
15920.5
-1300
- Counter
- 150a773a-5aa8-4e0b-abca-14a9d8ff6e48
- true
- Counter
- Counter
- false
- 0
-
15901
-1290
39
20
-
15920.5
-1280
- 2
- Data to loop
- d5cadfaa-7751-4509-a208-173c2c13ffa1
- true
- Data
- Data
- false
- 0
-
15901
-1270
39
20
-
15920.5
-1260
- 15483310-2ce2-48c6-b803-9dee8cb7cc9b
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop End
- End the loop with this one. Double click to pause the loop.
- true
- 0088c44a-a145-4779-89de-19b000b39a60
- true
- Loop End
- Loop End
- 0
- false
- Constant & Record
-
16231
-1372
104
64
-
16280
-1340
- 3
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- 062f1d0d-2835-4808-a2e1-68ed71c83de0
- true
- <
- <
- false
- 688aaa76-c5c0-437f-bb7b-d2fb2d647152
- 1
-
16233
-1370
35
20
-
16250.5
-1360
- Set to true to exit the loop
- 446153a1-e5fe-4b51-9c06-03f3c8269142
- true
- Exit
- Exit
- true
- 0
-
16233
-1350
35
20
-
16250.5
-1340
- 1
- 1
- {0}
- false
- 2
- Data to loop
- 27320839-2dfa-4799-87b2-f5a27c549120
- true
- Data
- Data
- false
- 613432b1-7d77-4615-b262-15d13c6fc293
- 1
-
16233
-1330
35
20
-
16250.5
-1320
- 2
- Data after the loop
- 869cc8ba-3a74-4469-ae82-c452fd20180b
- true
- 1
- Data
- Data
- false
- 0
-
16292
-1370
41
60
-
16304.5
-1340
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 8922d579-58bd-4f83-b1d2-2f7c1c847b74
- true
- True Only Button
- True Only Button
- false
- 0
- neutral,N
-
15662
-953
148
22
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- true
- Relay
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
15965
-1186
40
16
-
15985
-1178
- 7a1e5fd7-b7da-4244-a261-f1da66614992
- Power of 2
- Raise 2 to the power of N.
- true
- a42b481f-1cac-406c-915c-78cd5dc17db5
- true
- Power of 2
- Power of 2
-
15840
-1443
103
28
-
15898
-1429
- Input value
- d2e297c3-b80c-4014-b980-9a8c29f5fcfe
- true
- Value
- Value
- false
- 0
-
15842
-1441
44
24
-
15864
-1429
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 16
- Output value
- 853f787d-d612-40ed-957d-502a109f80c4
- true
- Result
- Result
- false
- 0
-
15910
-1441
31
24
-
15925.5
-1429
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- dd01be7a-f004-4f2e-8f95-86bd6510ab44
- true
- Scale
- Scale
-
15798
-1535
201
64
-
15935
-1503
- Base geometry
- 7adec163-1f97-4ba6-9387-2030d32702d0
- true
- Geometry
- Geometry
- true
- d5cadfaa-7751-4509-a208-173c2c13ffa1
- 1
-
15800
-1533
123
20
-
15861.5
-1523
- Center of scaling
- 3b53ddef-ed80-4109-8689-e13f03a7db64
- true
- Center
- Center
- false
- 0
-
15800
-1513
123
20
-
15861.5
-1503
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- 4deef344-5568-4030-965e-c677619704f7
- true
- Factor
- Factor
- false
- 853f787d-d612-40ed-957d-502a109f80c4
- 1
-
15800
-1493
123
20
-
15861.5
-1483
- 1
- 1
- {0}
- 0.5
- Scaled geometry
- 6830d610-5ef3-4e8b-95f3-a34e4424f6f9
- true
- Geometry
- Geometry
- false
- 0
-
15947
-1533
50
30
-
15972
-1518
- Transformation data
- 937023b7-428d-448e-b8ce-626e522bf593
- true
- Transform
- Transform
- false
- 0
-
15947
-1503
50
30
-
15972
-1488
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- efd5b6f1-8a95-4da6-a382-798344be96a6
- true
- Scale
- Scale
-
16145
-1516
217
64
-
16298
-1484
- Base geometry
- d8eb3162-4f16-4420-bdb4-08565b3f2b85
- true
- Geometry
- Geometry
- true
- 99adb399-bb0d-42f7-995a-6b1d6ba6e352
- 1
-
16147
-1514
139
20
-
16224.5
-1504
- Center of scaling
- 83ecda89-b6c1-42f0-91b3-f8e168213f81
- true
- Center
- Center
- false
- 0
-
16147
-1494
139
20
-
16224.5
-1484
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- ce9b475d-ee91-4782-9281-c7430f998752
- 1/X
- true
- Factor
- Factor
- false
- 853f787d-d612-40ed-957d-502a109f80c4
- 1
-
16147
-1474
139
20
-
16224.5
-1464
- 1
- 1
- {0}
- 0.5
- Scaled geometry
- 613432b1-7d77-4615-b262-15d13c6fc293
- true
- Geometry
- Geometry
- false
- 0
-
16310
-1514
50
30
-
16335
-1499
- Transformation data
- 114d69b3-2bae-4eda-9527-28f1b502a88d
- true
- Transform
- Transform
- false
- 0
-
16310
-1484
50
30
-
16335
-1469
- 2162e72e-72fc-4bf8-9459-d4d82fa8aa14
- Divide Curve
- Divide a curve into equal length segments
- true
- 1cff164a-3135-4ae3-a5e4-0381ab2b137c
- true
- Divide Curve
- Divide Curve
-
16223
-808
139
64
-
16293
-776
- Curve to divide
- a7bc0aa0-0e3b-44c5-890d-3ecd63a3928b
- true
- Curve
- Curve
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
16225
-806
56
20
-
16261
-796
- Number of segments
- d491ebe7-c4d7-4c83-bec9-1f5b25370ad0
- X-1
- true
- Count
- Count
- false
- b62af334-f12b-4c33-a2b7-43592a10d8d0
- 1
-
16225
-786
56
20
-
16261
-776
- 1
- 1
- {0}
- 10
- Split segments at kinks
- 974ce49c-d65c-4c95-8ecb-7d37f65946f8
- true
- Kinks
- Kinks
- false
- 0
-
16225
-766
56
20
-
16261
-756
- 1
- 1
- {0}
- false
- 1
- Division points
- 7dfed2fb-2c2d-43fe-80f7-67d25a4cb30d
- true
- Points
- Points
- false
- 0
-
16305
-806
55
20
-
16332.5
-796
- 1
- Tangent vectors at division points
- fd7f89c6-9b02-4ce7-b568-7d86e954cf39
- true
- Tangents
- Tangents
- false
- 0
-
16305
-786
55
20
-
16332.5
-776
- 1
- Parameter values at division points
- b174f96b-e9d4-4e21-872d-c1ad6297b1eb
- true
- Parameters
- Parameters
- false
- 0
-
16305
-766
55
20
-
16332.5
-756
- ad013215-63f3-46da-8b16-ce3bf593a0c0
- 1c9de8a1-315f-4c56-af06-8f69fee80a7a
- Curve Edit Points
- Extract the edit points on a curve at knot averages, the points an interpolated curve interpolated through.
- true
- c1604d20-1e74-4275-a566-65b937656418
- true
- Curve Edit Points
- Curve Edit Points
-
15871
-807
123
64
-
15925
-775
- Curve to get the edit points of
- da149e96-5071-4803-bb0b-729c3e0c978d
- true
- Curve
- Curve
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
15873
-805
40
30
-
15893
-790
- If True, only the edit points at knots (span ends) are extracted (the points an interpolated curve interpolated through)
If False, all edit points are extracted which equals the same amount as the curve control points (like Rhino's EditPtOn command)
- d47fd754-782f-4f1f-ae61-b568debe71da
- true
- Knots
- Knots
- false
- 0
-
15873
-775
40
30
-
15893
-760
- 1
- 1
- {0}
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- 1
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136
20
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- 1
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- The stroke pattern
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-
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4365
136
20
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- The shape to be used at the end of open path
- 3b2d0b4e-7952-45d4-886b-05e5309579f4
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-
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136
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- 1
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- A Graphic Plus Shape Object
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-
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48
100
-
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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135
84
-
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- Remove null items from the tree.
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- Remove Nulls
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- 0
-
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4281
83
20
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- Remove invalid items from the tree.
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- Remove Invalid
- Remove Invalid
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-
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4301
83
20
-
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- 1
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- Remove empty branches from the tree.
- 05e7e3a4-06fe-4b37-a97a-5d5a480c4b29
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- Remove Empty
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-
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83
20
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- 1
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- Data tree to clean
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83
20
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- 2
- Spotless data tree
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24
80
-
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 177ebf54-672d-4201-9e7e-88a2174b5ff2
- Evaluate Length
- Evaluate Length
-
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149
64
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- Curve to evaluate
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- a24a49ab-358e-4f47-b080-236c1ea0aacb
- 1
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71
20
-
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- Length factor for curve evaluation
- 46bc8c22-474f-49f1-b450-e269dacf0b1b
- Length
- Length
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- 0
-
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4312
71
20
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- 1
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- eb593801-031c-40f0-8db8-091e757e5ec4
- Normalized
- Normalized
- false
- 0
-
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4332
71
20
-
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- 1
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- Point at the specified length
- 3ddda828-e9c1-4078-b462-64771241dc6d
- Point
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-
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50
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- Tangent vector at the specified length
- 922de02f-68ea-4be7-a5e4-fc94b0c23f34
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-
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50
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- Curve parameter at the specified length
- c4c88a0e-d01d-40be-963a-e7eaf6f06a16
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-
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4332
50
20
-
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
- true
- 1d9a43f1-7bac-4ed2-801e-a9c7a6aac879
- PolyLine
- PolyLine
-
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4291
106
44
-
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- Polyline vertex points
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- 1
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40
20
-
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- Close polyline
- 97326c2b-74f5-450c-86db-825b66614dec
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40
20
-
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- Resulting polyline
- a9b4cc96-5e89-49c4-875d-ca718cbdc917
- Polyline
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-
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38
40
-
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4313
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 3eade811-6687-448f-a858-7dabb735bb48
- PolyLine
- PolyLine
-
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4359
106
44
-
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- 1
- Polyline vertex points
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-
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40
20
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- Close polyline
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- 1
-
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40
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-
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- 1
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- Resulting polyline
- 5c2d1f27-5ef1-43ef-b347-99f836c288f6
- Polyline
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-
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4361
38
40
-
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- dc853760-8407-4c2d-9c2a-6157e33088bb
- Merge
- Merge
-
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4319
90
64
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- Data stream 1
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- Data 1
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31
20
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- Data stream 2
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- Data 2
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- 1
-
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31
20
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-
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31
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31
60
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 36b301bc-2889-448a-9d41-4f6d44c6af34
- Polar Array
- Polar Array
-
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210
101
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- Base geometry
- 2b4ac54a-5e7f-401d-a88f-4b659407a6db
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132
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- Polar array plane
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132
37
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-
0
0
0
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0
0
0
1
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- Number of elements in array.
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4330
132
20
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- false
-
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4350
132
20
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- 1
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- Arrayed geometry
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50
48
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50
49
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- 3bbe3d33-9dcf-4a79-bebf-9ef0a482100d
- Cull Duplicates
- Cull Duplicates
-
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4280
180
64
-
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- 1
- Points to operate on
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- 1
-
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4282
113
30
-
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- Proximity tolerance distance
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- 0
-
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113
30
-
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- 1
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- {0}
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- Culled points
- 866e7ffc-c040-4eed-bddf-8db76a85ee13
- Points
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-
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39
20
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- 1
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39
20
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- 1
- Number of input points represented by this output point
- 513924d2-15a9-4dc6-abd4-29e6692cdb90
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-
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39
20
-
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4332
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- c5a71207-a092-4929-bcd7-eed57b82b082
- Flip Matrix
- Flip Matrix
-
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4283
78
28
-
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- 2
- Data matrix to flip
- b63fec32-bf50-4ab0-a5fa-8e6912769524
- Data
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- 539162c7-ece1-4511-a6b4-f8ff9e54b0dd
- 1
-
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25
24
-
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- 2
- Flipped data matrix
- 2cc55d5c-3f1d-4267-bc1a-472a880b025d
- Data
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-
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4285
25
24
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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4399
149
64
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- Curve to evaluate
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- Curve
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-
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71
20
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- Length factor for curve evaluation
- dadde2e7-02b0-4b9a-a1ce-4765be8dd176
- Length
- Length
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- 0
-
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4421
71
20
-
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 5529414f-6d9a-4b0f-9552-0fdf3b5adacc
- Normalized
- Normalized
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- 0
-
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4441
71
20
-
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- 1
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- {0}
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- Point at the specified length
- 0360efd1-90c7-4136-9ae9-401adc7153a5
- Point
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- 0
-
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50
20
-
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- Tangent vector at the specified length
- bb833425-c617-498c-8bd5-3859afffa905
- Tangent
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- false
- 0
-
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50
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- Curve parameter at the specified length
- 5cb98dfa-3161-49a8-8c7c-eca161dc734b
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-
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50
20
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- 8560f4f8-e365-4844-a26a-f82cd9b05b89
- Polar Array
- Polar Array
-
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4399
210
101
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- Base geometry
- 85a3d78e-d56f-4116-91fd-86d3810607b6
- Geometry
- Geometry
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- 0360efd1-90c7-4136-9ae9-401adc7153a5
- 1
-
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4401
132
20
-
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- Polar array plane
- 676b7b59-00e0-40d2-af96-5dc6039143cb
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-
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132
37
-
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- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 989cffd7-42d4-4915-bcaf-19872b7e4d30
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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4458
132
20
-
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- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- e2e975e3-a06d-4af1-b298-ee9dbbb0c9ab
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- false
-
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132
20
-
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- 1
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- Arrayed geometry
- fd011762-3520-48d2-a6fd-14f37f6d119a
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-
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4401
50
48
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- Transform
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-
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4449
50
49
-
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4473.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- c021a3bf-0177-4b65-aa95-b18ca93e291f
- Cull Duplicates
- Cull Duplicates
-
-9262
4396
180
64
-
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4428
- 1
- Points to operate on
- a09bce55-f62d-4ecd-9500-4a2edf22ee4b
- Points
- Points
- false
- 1a9d7e15-c1be-43de-b0db-779afbd0a4dd
- 1
-
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4398
113
30
-
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- Proximity tolerance distance
- bb4706d5-e7cb-49e1-b0a1-3e09db22f4aa
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- 0
-
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4428
113
30
-
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- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 40e9a704-1897-40c9-a62f-c1ca756c1129
- Points
- Points
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- 0
-
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4398
39
20
-
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- 1
- Index map of culled points
- 3939c402-70d5-458a-ac4f-623402dd4f34
- Indices
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- false
- 0
-
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4418
39
20
-
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4428
- 1
- Number of input points represented by this output point
- 9ac7a65a-d317-4483-a0c1-a1a696a79822
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- 0
-
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4438
39
20
-
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 5723f52f-3856-490b-bb74-1bed6c50fdc9
- Flip Matrix
- Flip Matrix
-
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4411
78
28
-
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- 2
- Data matrix to flip
- c2ec5213-befc-4d81-8e58-70acd9a580bf
- Data
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- fd011762-3520-48d2-a6fd-14f37f6d119a
- 1
-
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4413
25
24
-
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- 2
- Flipped data matrix
- a2b0532f-503c-41b6-87ab-030285f5949d
- Data
- Data
- false
- 0
-
-9918
4413
25
24
-
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- 1017d33b-cbb5-459d-b84c-254beedb00ed
- Merge
- Merge
-
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5674
90
64
-
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- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
- b8844f2c-50e0-4aae-9c5a-3e610a7f5316
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- Data 1
- D1
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- 96f72f95-50c1-4167-a4ee-9dd0f5c4d8e3
- 1
-
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5676
31
20
-
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- 2
- Data stream 2
- fbdcee46-13e5-4211-b6da-e208fb91bbbd
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- Data 2
- D2
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- f8928777-412d-4924-99a2-19c3fa3f9f18
- 1
-
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31
20
-
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- 2
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- ee96b715-5b35-487d-914c-0c4cd6bbb536
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- Data 3
- D3
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- 0
-
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5716
31
20
-
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- 2
- Result of merge
- b0240898-22b6-4015-a2ad-5e69472840fa
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-
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5676
31
60
-
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- The shape to be used at the end of open path
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- Merge a bunch of data streams
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Cull Duplicates
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- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
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- Points to operate on
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113
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- Proximity tolerance distance
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- Number of input points represented by this output point
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39
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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5319
78
28
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- Data matrix to flip
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- Data
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25
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
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149
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71
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- Length factor for curve evaluation
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Tangent vector at the specified length
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- Create a polar array of geometry.
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- Polar Array
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210
101
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132
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- Count
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132
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50
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50
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- Cull Duplicates
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180
64
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- Points to operate on
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113
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113
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- Flip a matrix-like data tree by swapping rows and columns.
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25
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25
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255;255;255;255
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255;255;255;255
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166
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90
20
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500
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90
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188
84
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- The radius of the shadow effect
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112
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670
112
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- Create a polar array of geometry.
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- Removes duplicate lines in a list
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- Flip a matrix-like data tree by swapping rows and columns.
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255;80;233;0
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100
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- Removes duplicate lines in a list
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip a matrix-like data tree by swapping rows and columns.
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39
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- Number of input points represented by this output point
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39
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
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78
28
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- Data matrix to flip
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25
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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-
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210
101
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132
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- Cull points that are coincident within tolerance
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180
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78
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255;255;255;255
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136
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255;80;233;0
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48
100
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210
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- Removes duplicate lines in a list
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- Clean Duplicate Lines
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- Flip a matrix-like data tree by swapping rows and columns.
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- Create a polar array of geometry.
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- Removes duplicate lines in a list
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- Flip a matrix-like data tree by swapping rows and columns.
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- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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113
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- Indices
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35
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- The value will be false if the line was removed.
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35
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
-
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94
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- 2
- Data matrix to flip
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25
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41
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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210
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- Base geometry
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- Polar array plane
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 68fdcded-66fe-483d-b0e3-a958f1e182c7
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- Removes duplicate lines in a list
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- Clean Duplicate Lines
-
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- Lines to check for duplicates
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113
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- Distance check tolerance
- a00024cf-762e-4c59-b724-712c5638305b
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- bc879567-85d4-4dad-80d0-78d6e3a37c55
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- 1db72078-1077-497d-aa43-9eb502e38cfe
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- Indices
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- The value will be false if the line was removed.
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- Status
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35
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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94
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- 2
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- Data
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25
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- 030b487b-a566-476f-96a4-a0ae2ad283af
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- Applies Stroke properties to a Shape
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- Stroke
-
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- The stroke color
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- Color
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136
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- The stroke weight
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136
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- The shape to be used at the end of open path
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136
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48
100
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
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- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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135
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- cb95db89-6165-43b6-9c41-5702bc5bf137
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- Remove null items from the tree.
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83
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- Remove invalid items from the tree.
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- Remove Invalid
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83
20
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- Remove empty branches from the tree.
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- Remove Empty
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83
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- Data tree to clean
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83
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- Spotless data tree
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24
80
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- 835e1481-19b2-462a-92d8-b19bb04ba708
- Evaluate Length
- Evaluate Length
-
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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- Length
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71
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- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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71
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50
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- Tangent vector at the specified length
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- Curve parameter at the specified length
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50
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- Create a polyline connecting a number of points.
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40
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- Close polyline
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40
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38
40
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
- PolyLine
-
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106
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40
20
-
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- Close polyline
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- Closed
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40
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- 1
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38
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- 66cd0c34-b22e-4d50-81c8-586358999c73
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- Merge
-
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90
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31
60
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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210
101
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- Base geometry
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132
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132
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0
0
0
1
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- Number of elements in array.
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- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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132
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-
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50
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- Transformation data
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- Transform
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-
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50
49
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
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-
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- Points to operate on
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-
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113
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- Proximity tolerance distance
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-
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113
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- 1
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- 1.1641532182693481E-10
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- Culled points
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39
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- 1
- Index map of culled points
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-
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39
20
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9919
- 1
- Number of input points represented by this output point
- 82c5849d-ada1-40d6-bfb0-b619cee41fc6
- Valence
- Valence
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-
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39
20
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9939
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 9c55da62-3de4-48e9-be17-8e9539c901b9
- Flip Matrix
- Flip Matrix
-
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78
28
-
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- 2
- Data matrix to flip
- b2830708-1294-4943-ac9b-cbfaca80efa0
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- ac53c8e5-84ec-447a-a023-b73d81c9e8ec
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-
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25
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- 2
- Flipped data matrix
- 03e022f8-3fe1-4c18-aef5-bfd78f21620a
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-
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25
24
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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10006
149
64
-
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- Curve to evaluate
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- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 5f6f9b5d-58cd-42a6-8176-39b52af1d509
- Flip Matrix
- Flip Matrix
-
-9949
11348
94
28
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-9910
11362
- 2
- Data matrix to flip
- 2072431d-689c-433c-895b-3f63a8635214
- Data
- Data
- false
- a0aa3e0e-3c93-4e68-92ba-2fdd33a20280
- 1
-
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11350
25
24
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- Flipped data matrix
- 52a95820-c937-4b14-941f-6d7d7397fe14
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- Data
- Data
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- 0
-
-9898
11350
41
24
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11362
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 5244dd45-ad3f-4b7d-82f7-c054e23825ee
- Polar Array
- Polar Array
-
-10907
11465
210
101
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- Base geometry
- c1c266c3-9498-4d02-8020-f14f446f9792
- Geometry
- Geometry
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- b57febb9-de80-4050-97c9-798db961a75f
- 1
-
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11467
132
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- Polar array plane
- 7ba1e3a9-8000-4dd2-a7c0-4ab4e650b30b
- Plane
- Plane
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11487
132
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11505.5
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0
0
0
1
0
0
0
1
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- Number of elements in array.
- f55bf4a0-c974-4500-9dd0-66e4e33987d2
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10905
11524
132
20
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- 1
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- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 78468f3a-6bc6-4e7a-bcf6-c3f3e9b4ee98
- Angle
- Angle
- false
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- false
-
-10905
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132
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- 1
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- {0}
- 6.2831853071795862
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- Arrayed geometry
- 703b7a1e-9642-4134-bebf-f872ec7846bf
- Geometry
- Geometry
- false
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-
-10749
11467
50
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- Transformation data
- 2b97e4f9-7799-446e-8c13-702e2022cc42
- Transform
- Transform
- false
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-
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50
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- dc8aee5e-da26-45f0-b2c8-612fcf84157e
- 08b214d9-388c-4ad0-940b-716633b47e45
- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- 062a8dcf-22f4-4039-bcaa-62cf727c04e2
- Clean Duplicate Lines
- Clean Duplicate Lines
-
-9240
11474
176
64
-
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11506
- 1
- Lines to check for duplicates
- 24ca0b82-89f1-406a-a607-7d7ed0a788de
- Lines
- Lines
- false
- ba8c40b8-87c5-4333-a820-5c94a2f2195b
- 1
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11476
113
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- Distance check tolerance
- 20d50bdb-1853-4cb0-9ef5-d9d8708b40fa
- Tolerance
- Tolerance
- true
- 0
-
-9238
11506
113
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-
-9181.5
11521
- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Filtered lines
- 39b05f4f-af55-43a0-96fd-7cdc06605701
- Lines
- Lines
- false
- 0
-
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11476
35
20
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11486
- 1
- Mapped Indices
- 97cd3ef8-c9b5-41a1-8b02-d460a5cb8cc8
- Indices
- Indices
- false
- 0
-
-9101
11496
35
20
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-9083.5
11506
- 1
- The value will be false if the line was removed.
- 9a18b2de-b8b2-4b51-8c6e-af7cdaca2da6
- Status
- Status
- false
- 0
-
-9101
11516
35
20
-
-9083.5
11526
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 004ea8b7-3af1-469e-aa51-929e40b532b2
- Flip Matrix
- Flip Matrix
-
-9949
11477
94
28
-
-9910
11491
- 2
- Data matrix to flip
- d2c18788-502d-44a5-b5c0-25f37746cf81
- Data
- Data
- false
- 703b7a1e-9642-4134-bebf-f872ec7846bf
- 1
-
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11479
25
24
-
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- 2
- Flipped data matrix
- ba8c40b8-87c5-4333-a820-5c94a2f2195b
- 1
- Data
- Data
- false
- 0
-
-9898
11479
41
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- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- d3d0a1f7-3657-4151-8f18-270e63656301
- Stroke
- Stroke
-
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212
104
-
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- f813b03b-bc7a-4342-82b7-a2cc67934e4c
- Shape / Geometry
- Shape / Geometry
- false
- b6749caa-7b90-4824-bc78-e5c27b47f95d
- 1
-
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11098
136
20
-
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- The stroke color
- fee869e2-c091-4890-99fc-5d7cd153c7c4
- Color
- Color
- true
- 1597fcb6-8f36-4207-a151-eb0d7474c548
- 1
-
-5953
11118
136
20
-
-5885
11128
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 262e4331-5d26-4c86-86b5-2ec94cd2f9d9
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-5953
11138
136
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-
-5885
11148
- 1
- 1
- {0}
- 9
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- The stroke pattern
- 97f3ff38-05b7-453b-8742-56896709c933
- Pattern
- Pattern
- true
- 0
-
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11158
136
20
-
-5885
11168
- The shape to be used at the end of open path
- c8e8f20c-2a21-4040-b2c3-ee57c1228dd6
- End Cap
- End Cap
- true
- 0
-
-5953
11178
136
20
-
-5885
11188
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- fad97604-17fc-4325-bcf1-ff5188840485
- 1
- Shape
- Shape
- false
- 0
-
-5793
11098
48
100
-
-5777
11148
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- b0d97a8c-dbee-44dc-b42a-a8d7c228a649
- Clean Tree
- Clean Tree
-
-6789
11072
135
84
-
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11114
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- be405693-64bb-4cb2-8874-c7402d113b81
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6787
11074
83
20
-
-6745.5
11084
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 27769a15-df1d-44ae-b71d-ac0be3b5aeff
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6787
11094
83
20
-
-6745.5
11104
- 1
- 1
- {0}
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- Remove empty branches from the tree.
- fc226a65-355d-4e9d-b606-0392fc97b1dc
- Remove Empty
- Remove Empty
- false
- 0
-
-6787
11114
83
20
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11124
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 0110813f-61c4-4e77-a71c-eb9064f92961
- Tree
- Tree
- false
- de1d4127-3ebc-4e96-b709-c138964c9c4a
- 1
-
-6787
11134
83
20
-
-6745.5
11144
- 2
- Spotless data tree
- b6749caa-7b90-4824-bc78-e5c27b47f95d
- Tree
- Tree
- false
- 0
-
-6680
11074
24
80
-
-6668
11114
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 55db54fd-35cb-4494-b22e-8b00243041c5
- Evaluate Length
- Evaluate Length
-
-11800
11038
149
64
-
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11070
- Curve to evaluate
- b3f16c64-4a35-4549-b3b5-8360735caa91
- Curve
- Curve
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- 0375c488-e806-4ad1-a086-2da4152bef10
- 1
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-11798
11040
71
20
-
-11762.5
11050
- Length factor for curve evaluation
- f7529dff-5612-4a7e-bb35-2337f224168e
- Length
- Length
- false
- 0
-
-11798
11060
71
20
-
-11762.5
11070
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- a3cb0976-96a3-43b9-a506-a078bec8f622
- Normalized
- Normalized
- false
- 0
-
-11798
11080
71
20
-
-11762.5
11090
- 1
- 1
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- true
- Point at the specified length
- 58dffd57-f31f-4e4d-9f96-5943d0d979cf
- Point
- Point
- false
- 0
-
-11703
11040
50
20
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11050
- Tangent vector at the specified length
- 787996d9-49cb-4ed1-bee2-703c65ce4736
- Tangent
- Tangent
- false
- 0
-
-11703
11060
50
20
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- Curve parameter at the specified length
- fe4ad9cc-d5ce-49bc-bc4b-de7e64192269
- Parameter
- Parameter
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- 0
-
-11703
11080
50
20
-
-11678
11090
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 35e45fe2-f59e-4fb1-9ccc-0b96dc2155af
- PolyLine
- PolyLine
-
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11084
106
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11106
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- Polyline vertex points
- dcfb4d73-0517-4d12-85f1-d2c20ec185d0
- Vertices
- Vertices
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- aecdad6f-6666-49c9-836e-5e58c7364aad
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11086
40
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-
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11096
- Close polyline
- 7839dab4-f812-4eaf-bae1-4d712c51a039
- Closed
- Closed
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- 1
-
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11106
40
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- 1
- 1
- {0}
- true
- Resulting polyline
- 26090aad-f520-46d6-bc20-d3d0b5abca34
- Polyline
- Polyline
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- 0
-
-8108
11086
38
40
-
-8089
11106
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 8000371a-c674-4938-8be1-9853ca521f5f
- PolyLine
- PolyLine
-
-8174
11155
106
44
-
-8120
11177
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- Polyline vertex points
- a8039467-a655-453b-8e33-27e0c8e8d1d3
- Vertices
- Vertices
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- c12a69e6-399c-4909-80b1-7c0a64e86884
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-
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11157
40
20
-
-8152
11167
- Close polyline
- 12eb4781-ba9a-4c25-ad7b-89fed3038d82
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
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11177
40
20
-
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11187
- 1
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- Resulting polyline
- f8e5d2c3-f226-4087-89e8-926fdf5c4193
- Polyline
- Polyline
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-
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11157
38
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11177
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 82a572e1-d7b4-47c8-a014-d3d9bb56e2be
- Merge
- Merge
-
-7413
11112
90
64
-
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- Data stream 1
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- Data 1
- D1
- true
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31
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- Data stream 2
- 68c2cac2-9f21-4caa-8480-7c5cb57611ce
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- Data 2
- D2
- true
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31
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- Data stream 3
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- Data 3
- D3
- true
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31
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- Result of merge
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- Result
- Result
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-
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31
60
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11144
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- d29fff73-a495-4c71-bad6-d22e3561b93e
- Polar Array
- Polar Array
-
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11038
210
101
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- Base geometry
- b5a2fcf6-ae5d-4a25-a801-227f8a384175
- Geometry
- Geometry
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- 58dffd57-f31f-4e4d-9f96-5943d0d979cf
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-
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11040
132
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- Polar array plane
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- Plane
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11060
132
37
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11078.5
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
- deab8d0b-6f90-4cb3-92c5-173203a5031d
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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11097
132
20
-
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- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 3aacda92-a77b-45dd-9f44-f56a6b37a14b
- Angle
- Angle
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- 0
- false
-
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11117
132
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11127
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- Arrayed geometry
- 4841119b-6919-43e0-9f72-21da2df86cd2
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- Geometry
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- 0
-
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11040
50
48
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- Transformation data
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- Transform
- Transform
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- 0
-
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50
49
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 194f3671-9486-483d-9977-608dbabd14c8
- Cull Duplicates
- Cull Duplicates
-
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11047
180
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-
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11079
- 1
- Points to operate on
- c608489f-58cf-4ddd-9cd3-cd408626fed8
- Points
- Points
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-
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113
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- Proximity tolerance distance
- f65c7a2c-5351-46dc-8909-e28a5cc661b9
- Tolerance
- Tolerance
- false
- 0
-
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11079
113
30
-
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11094
- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Culled points
- aecdad6f-6666-49c9-836e-5e58c7364aad
- Points
- Points
- false
- 0
-
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11049
39
20
-
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11059
- 1
- Index map of culled points
- df89d8c0-9f72-452d-af60-a2c25f317a83
- Indices
- Indices
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- 0
-
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11069
39
20
-
-9083.5
11079
- 1
- Number of input points represented by this output point
- c1887c30-00f2-4924-a23b-b74b8656bf3c
- Valence
- Valence
- false
- 0
-
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11089
39
20
-
-9083.5
11099
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 455f0762-2713-4463-9220-4134b05d4f57
- Flip Matrix
- Flip Matrix
-
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11050
78
28
-
-9910
11064
- 2
- Data matrix to flip
- 2523c816-93d0-41ff-984f-d483c8d06d39
- Data
- Data
- false
- 4841119b-6919-43e0-9f72-21da2df86cd2
- 1
-
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11052
25
24
-
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- 2
- Flipped data matrix
- 627175b3-e269-4f62-be01-48fb72a7dc44
- Data
- Data
- false
- 0
-
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11052
25
24
-
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 59b7287b-dfe4-4f42-8db7-c8e67792c667
- Evaluate Length
- Evaluate Length
-
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11166
149
64
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- Curve to evaluate
- fe663895-26d1-4cfb-84ca-adc9481f8291
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- Curve
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-
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71
20
-
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- Length factor for curve evaluation
- 41621117-2021-49ba-b487-d4aedbf29fcc
- Length
- Length
- false
- 0
-
-11798
11188
71
20
-
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 6fde47c3-b049-48e7-8b58-c109b354b541
- Normalized
- Normalized
- false
- 0
-
-11798
11208
71
20
-
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11218
- 1
- 1
- {0}
- true
- Point at the specified length
- 6d5abb8c-34bb-4407-a45c-9ce18f00de6a
- Point
- Point
- false
- 0
-
-11703
11168
50
20
-
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- Tangent vector at the specified length
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101
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132
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180
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- Geometry
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132
20
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- Polar array plane
- a7e8c782-0fb1-4361-8dfb-d316b71ebeb4
- Plane
- Plane
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12621
132
37
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12639.5
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-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 7faec457-33ed-4073-ac50-10534e3e3c54
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
12658
132
20
-
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- 1
- 1
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- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 9f783047-67af-46e7-ae93-6ca2e6e77d8b
- Angle
- Angle
- false
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- false
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12678
132
20
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- Arrayed geometry
- 2f599679-2169-44a6-ad8d-2177463a5007
- Geometry
- Geometry
- false
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12601
50
48
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- Transformation data
- 40c04821-f11e-48c9-a448-1d17afb03091
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- Transform
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50
49
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12673.75
- dc8aee5e-da26-45f0-b2c8-612fcf84157e
- 08b214d9-388c-4ad0-940b-716633b47e45
- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- 37ea340c-c4b6-41c0-b9c3-0af409e1b462
- Clean Duplicate Lines
- Clean Duplicate Lines
-
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12608
176
64
-
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12640
- 1
- Lines to check for duplicates
- 2acd1072-3a2c-4004-a403-1ebeea0fc86d
- Lines
- Lines
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-
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12610
113
30
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- Distance check tolerance
- 79c4a1e0-1cff-49f2-b1fb-a3786cee7fab
- Tolerance
- Tolerance
- true
- 0
-
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12640
113
30
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12655
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Filtered lines
- 8b5e702e-fe66-451c-9d6f-7d420bedd33f
- Lines
- Lines
- false
- 0
-
-9141
12610
35
20
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12620
- 1
- Mapped Indices
- 9011f340-ae92-43f4-a4fb-968ae4580415
- Indices
- Indices
- false
- 0
-
-9141
12630
35
20
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-9123.5
12640
- 1
- The value will be false if the line was removed.
- da5155c9-1172-46c4-b4a9-07b1097720a4
- Status
- Status
- false
- 0
-
-9141
12650
35
20
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12660
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- cf17a6b1-9c69-4bea-8df9-aad3926d8a47
- Flip Matrix
- Flip Matrix
-
-9989
12611
94
28
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12625
- 2
- Data matrix to flip
- c9416a33-92e7-4e2a-80fe-f44883ffe9a1
- Data
- Data
- false
- 2f599679-2169-44a6-ad8d-2177463a5007
- 1
-
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25
24
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- 2
- Flipped data matrix
- 6f6badfc-3548-443d-9915-3e528056c5b5
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- Data
- false
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-
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12613
41
24
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12625
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- 5fe91bb1-4581-49ee-840e-15dde9daa1ec
- Stroke
- Stroke
-
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12230
212
104
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12282
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 34b44bad-c225-4b90-b038-e617f66ae7fc
- Shape / Geometry
- Shape / Geometry
- false
- d9b8d3cd-38bf-4578-839b-0a5ece250025
- 1
-
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12232
136
20
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12242
- The stroke color
- d912eabb-dfeb-4a6a-b312-3f8c3bf774ab
- Color
- Color
- true
- 6b1ee9b3-d527-4f0a-92bd-29a66feb6eb4
- 1
-
-5993
12252
136
20
-
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12262
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 4f659f4c-b3dc-4f09-8c77-586f57958c2d
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
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12272
136
20
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12282
- 1
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- {0}
- 9
- 1
- The stroke pattern
- ef45aa1c-d7c6-4913-b5e1-161fe8dcf0ef
- Pattern
- Pattern
- true
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-
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12292
136
20
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12302
- The shape to be used at the end of open path
- e2318e1e-0fc0-4106-b936-440f351dc506
- End Cap
- End Cap
- true
- 0
-
-5993
12312
136
20
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12322
- 1
- 1
- {0}
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- A Graphic Plus Shape Object
- true
- efce6428-f614-45c9-a29d-22fe028a15cc
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- Shape
- Shape
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-
-5833
12232
48
100
-
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12282
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 8d6e19cf-5301-40e0-9013-0f3c19973e8d
- Clean Tree
- Clean Tree
-
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12206
135
84
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12248
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 37690dac-ffe2-4835-91c1-6066f9d76ce6
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
12208
83
20
-
-6785.5
12218
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 5f89493f-76d6-4ac4-adc7-86ed0ddc2372
- Remove Invalid
- Remove Invalid
- false
- 0
-
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12228
83
20
-
-6785.5
12238
- 1
- 1
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- Remove empty branches from the tree.
- 23999a55-d9d8-4b4a-a9ee-dbc53c88822f
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
12248
83
20
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12258
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 5ed0643b-cc55-4597-aa6e-00dabf7f5245
- Tree
- Tree
- false
- 86daba70-2a3b-4a1c-a39a-106f8460fa2c
- 1
-
-6827
12268
83
20
-
-6785.5
12278
- 2
- Spotless data tree
- d9b8d3cd-38bf-4578-839b-0a5ece250025
- Tree
- Tree
- false
- 0
-
-6720
12208
24
80
-
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12248
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 1d88f662-fdb9-46e3-aba0-0600f05c556e
- Evaluate Length
- Evaluate Length
-
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12172
149
64
-
-11755
12204
- Curve to evaluate
- 71194947-2b03-49f9-ab5d-65d964bcd2b9
- Curve
- Curve
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- 360e3c71-f39a-4344-9b0b-f76f6040e9a5
- 1
-
-11838
12174
71
20
-
-11802.5
12184
- Length factor for curve evaluation
- d94423ca-039f-488d-9398-40cffcfd5922
- Length
- Length
- false
- 0
-
-11838
12194
71
20
-
-11802.5
12204
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 31c42d3d-1753-4b35-943e-43531dc22aa7
- Normalized
- Normalized
- false
- 0
-
-11838
12214
71
20
-
-11802.5
12224
- 1
- 1
- {0}
- true
- Point at the specified length
- 191da902-2fe2-4d59-8b2c-16c5826ea944
- Point
- Point
- false
- 0
-
-11743
12174
50
20
-
-11718
12184
- Tangent vector at the specified length
- 07a10d0e-6b2c-44ef-8a93-6203590c3610
- Tangent
- Tangent
- false
- 0
-
-11743
12194
50
20
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12204
- Curve parameter at the specified length
- 7e2d691f-777b-4ec3-aae8-d55f21baabc7
- Parameter
- Parameter
- false
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-
-11743
12214
50
20
-
-11718
12224
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a4cfa61c-6315-48e5-9748-41e6bff9dd13
- PolyLine
- PolyLine
-
-8214
12218
106
44
-
-8160
12240
- 1
- Polyline vertex points
- c12fcf9b-f7e1-4c33-8bed-749adaf240f8
- Vertices
- Vertices
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- 1
-
-8212
12220
40
20
-
-8192
12230
- Close polyline
- ab68209f-a1ff-4f85-b7ea-656a5a0329f4
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
12240
40
20
-
-8192
12250
- 1
- 1
- {0}
- true
- Resulting polyline
- cd6a97f5-0587-4a71-8611-22fa2aaa3840
- Polyline
- Polyline
- false
- 0
-
-8148
12220
38
40
-
-8129
12240
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a3b55592-fb58-4505-8d3e-ab1d2a9afc89
- PolyLine
- PolyLine
-
-8214
12289
106
44
-
-8160
12311
- 1
- Polyline vertex points
- 3874fd28-3057-4ffb-ba94-3127f375a64f
- Vertices
- Vertices
- false
- b85a0de9-2fc9-4d83-b473-65417e5818a7
- 1
-
-8212
12291
40
20
-
-8192
12301
- Close polyline
- b26490d5-64cf-465f-828d-9f73b4aaa9fd
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
12311
40
20
-
-8192
12321
- 1
- 1
- {0}
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- Resulting polyline
- 76e975c9-0859-4963-aa3d-d26213287614
- Polyline
- Polyline
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- 0
-
-8148
12291
38
40
-
-8129
12311
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 11da8026-3f02-41e4-9eb5-39a041af1bc2
- Merge
- Merge
-
-7453
12246
90
64
-
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12278
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- false
- Data 1
- D1
- true
- cd6a97f5-0587-4a71-8611-22fa2aaa3840
- 1
-
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12248
31
20
-
-7435.5
12258
- 2
- Data stream 2
- ba5eb681-4804-4efe-99dc-e0aba500cae3
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- Data 2
- D2
- true
- 76e975c9-0859-4963-aa3d-d26213287614
- 1
-
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12268
31
20
-
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12278
- 2
- Data stream 3
- 1462617e-c980-43e5-aaaf-c5eb62f9d386
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- Data 3
- D3
- true
- 0
-
-7451
12288
31
20
-
-7435.5
12298
- 2
- Result of merge
- 86daba70-2a3b-4a1c-a39a-106f8460fa2c
- Result
- Result
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- 0
-
-7396
12248
31
60
-
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12278
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 46c45a5b-1d60-4374-9874-2f46a8395bfd
- Polar Array
- Polar Array
-
-10947
12172
210
101
-
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12223
- Base geometry
- 79e27294-499c-48b8-b416-6eb8a231dc2d
- Geometry
- Geometry
- true
- 191da902-2fe2-4d59-8b2c-16c5826ea944
- 1
-
-10945
12174
132
20
-
-10879
12184
- Polar array plane
- bd66c505-b444-499f-9a5c-b744cf382212
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- Plane
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-10945
12194
132
37
-
-10879
12212.5
- 1
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- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- b0a02c9a-7404-49e4-aeb1-880997243f13
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
12231
132
20
-
-10879
12241
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 6b988194-31d4-4a16-bff3-69f35e94bfb3
- Angle
- Angle
- false
- 0
- false
-
-10945
12251
132
20
-
-10879
12261
- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
- 5f8c5ef7-ad16-42a2-9646-930141e9f464
- Geometry
- Geometry
- false
- 0
-
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12174
50
48
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-10764
12198.25
- 1
- Transformation data
- 07080f9d-e2dc-4146-85a8-d6b8d2c26ccc
- Transform
- Transform
- false
- 0
-
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12222
50
49
-
-10764
12246.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- f2a326c1-b3a7-4936-920d-cbeb331af976
- Cull Duplicates
- Cull Duplicates
-
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12181
180
64
-
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12213
- 1
- Points to operate on
- 7dd1da8a-1ac4-405f-ba33-3ffa8d49bced
- Points
- Points
- false
- 38ab9026-f5cf-4466-9caf-c97b7ae5e9fd
- 1
-
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12183
113
30
-
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12198
- Proximity tolerance distance
- 516ab31e-150a-4206-ac59-d027de7e7dc9
- Tolerance
- Tolerance
- false
- 0
-
-9280
12213
113
30
-
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12228
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 18c0a921-f72f-4e37-b0bb-7a27a6f1a621
- Points
- Points
- false
- 0
-
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12183
39
20
-
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12193
- 1
- Index map of culled points
- 03482fd5-7707-4c90-a892-c48c8986bf4d
- Indices
- Indices
- false
- 0
-
-9143
12203
39
20
-
-9123.5
12213
- 1
- Number of input points represented by this output point
- bb151dbc-c2c0-4200-900b-e7f3fda48e26
- Valence
- Valence
- false
- 0
-
-9143
12223
39
20
-
-9123.5
12233
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- a8d83d35-138a-41e7-93a1-22679fbc2439
- Flip Matrix
- Flip Matrix
-
-9989
12184
78
28
-
-9950
12198
- 2
- Data matrix to flip
- 6a2d23e5-4524-4315-aa03-8d7a304f84df
- Data
- Data
- false
- 5f8c5ef7-ad16-42a2-9646-930141e9f464
- 1
-
-9987
12186
25
24
-
-9974.5
12198
- 2
- Flipped data matrix
- 260ef8d4-4714-4379-8975-e217a4b3e16f
- Data
- Data
- false
- 0
-
-9938
12186
25
24
-
-9925.5
12198
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 33d80a7b-276c-4f76-bef1-be6388f7eb34
- Evaluate Length
- Evaluate Length
-
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12300
149
64
-
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12332
- Curve to evaluate
- f32669f8-7f9d-44f8-acec-3061277735c3
- Curve
- Curve
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- 0f7d41df-0b88-413c-bf09-4b93aebfd26f
- 1
-
-11838
12302
71
20
-
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12312
- Length factor for curve evaluation
- d8d5579c-f745-42c3-a9d0-85590e33ca5d
- Length
- Length
- false
- 0
-
-11838
12322
71
20
-
-11802.5
12332
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 27bdb2b4-cd9c-4657-bef0-d7aca6df4452
- Normalized
- Normalized
- false
- 0
-
-11838
12342
71
20
-
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12352
- 1
- 1
- {0}
- true
- Point at the specified length
- e4bc4020-8141-4a7d-b4cb-85d0f43fc123
- Point
- Point
- false
- 0
-
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12302
50
20
-
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12312
- Tangent vector at the specified length
- c6d2c933-7f36-46d4-89e5-f4c6e5ecc676
- Tangent
- Tangent
- false
- 0
-
-11743
12322
50
20
-
-11718
12332
- Curve parameter at the specified length
- 5d82cdc3-80d2-4fed-911b-2b37c1ba5ff5
- Parameter
- Parameter
- false
- 0
-
-11743
12342
50
20
-
-11718
12352
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 656f3f38-f138-4399-bd8e-f76e210d93db
- Polar Array
- Polar Array
-
-10947
12300
210
101
-
-10801
12351
- Base geometry
- 74d9afb7-f715-4f56-9e7c-4befd1ec6bec
- Geometry
- Geometry
- true
- e4bc4020-8141-4a7d-b4cb-85d0f43fc123
- 1
-
-10945
12302
132
20
-
-10879
12312
- Polar array plane
- 13e96852-2bc7-42aa-bea0-f7014624b7ad
- Plane
- Plane
- false
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- Arrayed geometry
- 3fc82d5e-7989-4464-a1f2-e35bc71b39be
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- Geometry
- false
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- Transformation data
- c2cf4656-f293-4432-a8a2-c5908d06faae
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- Transform
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- dc8aee5e-da26-45f0-b2c8-612fcf84157e
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- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- a91d1b7d-9d8e-48be-ae93-1739dd0f5998
- Clean Duplicate Lines
- Clean Duplicate Lines
-
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13778
176
64
-
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- 1
- Lines to check for duplicates
- 7ca0d81f-f0f4-4b9d-8ff1-b3f72e7b9687
- Lines
- Lines
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-
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113
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- Distance check tolerance
- e66ee9e6-9c8a-4a42-84ab-c3d0c0b61d34
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- Tolerance
- true
- 0
-
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113
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13825
- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Filtered lines
- b878599a-93df-47ad-8ccb-3fb6666ef98a
- Lines
- Lines
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- 0
-
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35
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- Mapped Indices
- 2b1d52f6-8468-482f-93ae-9a4fb9d1dfc6
- Indices
- Indices
- false
- 0
-
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13800
35
20
-
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13810
- 1
- The value will be false if the line was removed.
- 5ad77074-97fc-4dbb-b9e4-b3d9597dd378
- Status
- Status
- false
- 0
-
-9141
13820
35
20
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13830
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ca92eeb5-0c1f-4fdb-8882-fcb7e9eed882
- Flip Matrix
- Flip Matrix
-
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94
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- Data matrix to flip
- 6fe0510d-52f1-4682-b8e2-55283346ca39
- Data
- Data
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- 3fc82d5e-7989-4464-a1f2-e35bc71b39be
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-
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25
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- Flipped data matrix
- 476dc671-a77d-48fd-b913-946bc603a6d2
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- Data
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-
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- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
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- d9bae896-445c-4f81-909c-3e75cff0dee7
- Stroke
- Stroke
-
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212
104
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 5227eb0b-46ca-49c2-aa4a-62b85816bf74
- Shape / Geometry
- Shape / Geometry
- false
- 986a4ea2-6d71-45b5-9958-cb0ff67dcc00
- 1
-
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13402
136
20
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- The stroke color
- 4cab67c0-dd40-4838-90b1-7d135e74022f
- Color
- Color
- true
- bb795819-a6c6-4e55-a863-d50b1c8f2040
- 1
-
-5993
13422
136
20
-
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13432
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 1692da24-7c26-4ac1-b9d4-5a848ee2e055
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
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136
20
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- {0}
- 9
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- The stroke pattern
- ee818197-99d6-4bff-9b99-ad9871e7514a
- Pattern
- Pattern
- true
- 0
-
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13462
136
20
-
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- The shape to be used at the end of open path
- 36c8692e-b4aa-40d8-80ef-840011193383
- End Cap
- End Cap
- true
- 0
-
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13482
136
20
-
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13492
- 1
- 1
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- A Graphic Plus Shape Object
- true
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- 1
- Shape
- Shape
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-
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13402
48
100
-
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13452
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 1699dbef-9b40-4a59-89b2-d575c6368831
- Clean Tree
- Clean Tree
-
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13376
135
84
-
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13418
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- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 82022d82-52cb-4ae7-a2a4-6cb10355572a
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
13378
83
20
-
-6785.5
13388
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 425eefb3-38bd-43a4-b684-54e7df9d61c7
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
13398
83
20
-
-6785.5
13408
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 087a5d61-135f-4c98-8922-7c44e9c1852b
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
13418
83
20
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13428
- 1
- 1
- {0}
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- 2
- Data tree to clean
- 95c1bf20-b4f3-4e52-a270-b8458219a044
- Tree
- Tree
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- 89600b18-6607-4de2-a6a1-41f9e72185f2
- 1
-
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13438
83
20
-
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13448
- 2
- Spotless data tree
- 986a4ea2-6d71-45b5-9958-cb0ff67dcc00
- Tree
- Tree
- false
- 0
-
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13378
24
80
-
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13418
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 2a568e96-3e71-4a50-9fd1-3e4ce13e70f5
- Evaluate Length
- Evaluate Length
-
-11840
13342
149
64
-
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13374
- Curve to evaluate
- 4c239629-3b78-433c-9285-5438917e626c
- Curve
- Curve
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- 609b5d6e-7b75-4e1a-8a12-faf652c3c682
- 1
-
-11838
13344
71
20
-
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13354
- Length factor for curve evaluation
- 6feaf1a9-b8e6-4c02-b75f-cc8982d91726
- Length
- Length
- false
- 0
-
-11838
13364
71
20
-
-11802.5
13374
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 573b8081-cb2c-4cd2-b6be-ed5a8fbd352b
- Normalized
- Normalized
- false
- 0
-
-11838
13384
71
20
-
-11802.5
13394
- 1
- 1
- {0}
- true
- Point at the specified length
- f9679928-c7a3-4d10-94a2-003b0737b7c6
- Point
- Point
- false
- 0
-
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13344
50
20
-
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13354
- Tangent vector at the specified length
- 2efa796c-48c3-4be3-92b6-4fe5af425c3b
- Tangent
- Tangent
- false
- 0
-
-11743
13364
50
20
-
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13374
- Curve parameter at the specified length
- 95fd76a4-439d-4d69-852d-8097fac143e9
- Parameter
- Parameter
- false
- 0
-
-11743
13384
50
20
-
-11718
13394
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 962f300e-d13a-4cfb-8775-3332be224a3b
- PolyLine
- PolyLine
-
-8214
13388
106
44
-
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13410
- 1
- Polyline vertex points
- eb63dc90-64a2-4093-83ed-e8aeacb0a275
- Vertices
- Vertices
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- d88c6a85-1583-416c-834b-da43cc4b6ff9
- 1
-
-8212
13390
40
20
-
-8192
13400
- Close polyline
- df21ddec-7724-4a3d-a7a2-7cc64268a33c
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
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13410
40
20
-
-8192
13420
- 1
- 1
- {0}
- true
- Resulting polyline
- 22e94c20-c8b5-422f-ad04-0b643f130e29
- Polyline
- Polyline
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- 0
-
-8148
13390
38
40
-
-8129
13410
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 543bb0df-8039-457a-aa73-cedeb032ee5c
- PolyLine
- PolyLine
-
-8214
13459
106
44
-
-8160
13481
- 1
- Polyline vertex points
- a4af2146-6a13-4cc3-9bcc-8866e2bf66c1
- Vertices
- Vertices
- false
- 302ea92b-a67e-4cda-af4d-800b4f829f22
- 1
-
-8212
13461
40
20
-
-8192
13471
- Close polyline
- be2b82c1-1411-4f86-9681-02d93a113ff2
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
13481
40
20
-
-8192
13491
- 1
- 1
- {0}
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- Resulting polyline
- 660bf03b-9848-4309-bb76-41f35d76729e
- Polyline
- Polyline
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- 0
-
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13461
38
40
-
-8129
13481
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 18c4dff3-a6c4-4b00-a9d7-b6caf73180f0
- Merge
- Merge
-
-7453
13416
90
64
-
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13448
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 2
- Data stream 1
- a1d0bbe6-b200-40ce-bbea-0fac78383987
- false
- Data 1
- D1
- true
- 22e94c20-c8b5-422f-ad04-0b643f130e29
- 1
-
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13418
31
20
-
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13428
- 2
- Data stream 2
- d6695219-64fc-4e9d-9bd2-d27ff3ece270
- false
- Data 2
- D2
- true
- 660bf03b-9848-4309-bb76-41f35d76729e
- 1
-
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13438
31
20
-
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- 2
- Data stream 3
- 1852818a-0863-4c53-838f-65738bb00e53
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- Data 3
- D3
- true
- 0
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13458
31
20
-
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13468
- 2
- Result of merge
- 89600b18-6607-4de2-a6a1-41f9e72185f2
- Result
- Result
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- 0
-
-7396
13418
31
60
-
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13448
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- eded538d-9e14-4b3b-8511-012d710a4202
- Polar Array
- Polar Array
-
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13342
210
101
-
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- Base geometry
- 25ef12c1-95e7-4f96-82d7-df17d6607e32
- Geometry
- Geometry
- true
- f9679928-c7a3-4d10-94a2-003b0737b7c6
- 1
-
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13344
132
20
-
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- Polar array plane
- 2b96e6d5-9614-40b1-acf2-34b19ce4ca4f
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-
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13364
132
37
-
-10879
13382.5
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- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 58eccda3-d61f-4806-9e7b-4cac97b391c3
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
13401
132
20
-
-10879
13411
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b9d8fa57-8017-48c7-b39b-951608e6d413
- Angle
- Angle
- false
- 0
- false
-
-10945
13421
132
20
-
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13431
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 99daf0cc-a43f-450a-b90f-272d1153ba8a
- Geometry
- Geometry
- false
- 0
-
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13344
50
48
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-10764
13368.25
- 1
- Transformation data
- 7768115b-1c42-4ff7-b6fe-8ba943768f3e
- Transform
- Transform
- false
- 0
-
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13392
50
49
-
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13416.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 53dadc15-5b5d-4d86-a82b-9c99c687e599
- Cull Duplicates
- Cull Duplicates
-
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13351
180
64
-
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- 1
- Points to operate on
- d5a21377-8e13-40ca-87b6-c3ce316d4284
- Points
- Points
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- 7a082c6f-007d-4f4d-88ae-98d6d5d1f17a
- 1
-
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13353
113
30
-
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13368
- Proximity tolerance distance
- ea47d601-9b7a-485a-aafe-60fe26ddaae6
- Tolerance
- Tolerance
- false
- 0
-
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13383
113
30
-
-9223.5
13398
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
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- Points
- Points
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- 0
-
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13353
39
20
-
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13363
- 1
- Index map of culled points
- cd46575f-a154-4a06-a33b-9c164ea46ccc
- Indices
- Indices
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- 0
-
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13373
39
20
-
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13383
- 1
- Number of input points represented by this output point
- 52a6aaa7-6e75-4b91-9c70-46767f1da2b5
- Valence
- Valence
- false
- 0
-
-9143
13393
39
20
-
-9123.5
13403
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 39875cab-f112-4d5e-8493-bea84926f5e6
- Flip Matrix
- Flip Matrix
-
-9989
13358
78
28
-
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- 2
- Data matrix to flip
- 3d6273bb-a233-47ac-b046-6c1b482618bd
- Data
- Data
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- 99daf0cc-a43f-450a-b90f-272d1153ba8a
- 1
-
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13360
25
24
-
-9974.5
13372
- 2
- Flipped data matrix
- b8290ff5-cc18-4aed-b419-0380c7314516
- Data
- Data
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- 0
-
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13360
25
24
-
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13372
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 9646f763-5f33-4816-a637-889100b707fe
- Evaluate Length
- Evaluate Length
-
-11840
13470
149
64
-
-11755
13502
- Curve to evaluate
- 7d56b35b-39f2-4ff4-9691-a2043e2af748
- Curve
- Curve
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- 68ed2259-a880-4020-a4fa-5102d6548b24
- 1
-
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13472
71
20
-
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- Length factor for curve evaluation
- ace16953-c438-4ca0-ba26-fc3f7c426e21
- Length
- Length
- false
- 0
-
-11838
13492
71
20
-
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13502
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- d0d762db-efb7-4e56-a6cc-c8251bf47a0a
- Normalized
- Normalized
- false
- 0
-
-11838
13512
71
20
-
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13522
- 1
- 1
- {0}
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- Point at the specified length
- 3224f531-fcc0-4069-98d6-72111ade37c7
- Point
- Point
- false
- 0
-
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50
20
-
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- Tangent vector at the specified length
- ebb51016-99ab-421c-be6c-e0ccc7108e15
- Tangent
- Tangent
- false
- 0
-
-11743
13492
50
20
-
-11718
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- Curve parameter at the specified length
- e3ea3454-734c-453f-8949-03fc9323b976
- Parameter
- Parameter
- false
- 0
-
-11743
13512
50
20
-
-11718
13522
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 6477d210-711d-4699-93a8-6bde781c3f7a
- Polar Array
- Polar Array
-
-10947
13470
210
101
-
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- Base geometry
- 5494aaf9-a934-4696-bab5-ff2557ead832
- Geometry
- Geometry
- true
- 3224f531-fcc0-4069-98d6-72111ade37c7
- 1
-
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13472
132
20
-
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- Polar array plane
- 2e21f5f8-44c0-43a3-ab9f-91911709aba1
- Plane
- Plane
- false
- 0
-
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13492
132
37
-
-10879
13510.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f3bae605-ca2c-4b34-9ab3-182d03df58f9
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
13529
132
20
-
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13539
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- e4f278f6-967a-45ed-8b63-cbdd1fa95005
- Angle
- Angle
- false
- 0
- false
-
-10945
13549
132
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-
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13559
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- a2b0bb3c-0097-402a-a4da-133df59b5297
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- Geometry
- false
- 0
-
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13472
50
48
-
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- 1
- Transformation data
- 9bd95ff5-7cf4-41aa-bb33-086c3c6f832c
- Transform
- Transform
- false
- 0
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113
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- Lines
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35
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- Indices
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35
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- The value will be false if the line was removed.
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- Status
- Status
- false
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-
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35
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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94
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- 030b487b-a566-476f-96a4-a0ae2ad283af
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- Applies Stroke properties to a Shape
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- Stroke
- Stroke
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212
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- f96b899f-6d17-4937-8f63-a809a943d375
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- Shape / Geometry
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136
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- The stroke color
- 37088d6f-cb86-472e-b59c-298e8c3b88e8
- Color
- Color
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-
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14501
136
20
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- {0}
-
255;21;0;255
- The stroke weight
- 5d3df0ae-99af-4eb3-8f55-5439e25d08bb
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
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136
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- The stroke pattern
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- Pattern
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136
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- The shape to be used at the end of open path
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- End Cap
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136
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- A Graphic Plus Shape Object
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48
100
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
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- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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14455
135
84
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- cb95db89-6165-43b6-9c41-5702bc5bf137
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- Remove null items from the tree.
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- Remove Nulls
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-
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83
20
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- Remove invalid items from the tree.
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- Remove Invalid
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14477
83
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- Remove empty branches from the tree.
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83
20
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- Data tree to clean
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14517
83
20
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- Spotless data tree
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14457
24
80
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 4ece2bad-44ab-4c65-9d83-11d636649fbe
- Evaluate Length
- Evaluate Length
-
-11840
14421
149
64
-
-11755
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- Curve to evaluate
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14423
71
20
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- Length factor for curve evaluation
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- Length
- Length
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-
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14443
71
20
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14453
- 1
- 1
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- false
- 0
-
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14463
71
20
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- 1
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- Point at the specified length
- 8b3658f2-d9eb-4ff3-b6d5-fb133de62fd5
- Point
- Point
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-
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14423
50
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- Tangent vector at the specified length
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- Tangent
- Tangent
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- Curve parameter at the specified length
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50
20
-
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
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- 44683d76-8a35-44ed-949b-30141fdf9139
- PolyLine
- PolyLine
-
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106
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- Polyline vertex points
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-
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40
20
-
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- Close polyline
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40
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- Resulting polyline
- 9fc4e560-6e7f-46af-bebe-161db37b149c
- Polyline
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-
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14469
38
40
-
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e13f38a0-10b9-4295-9d8b-bf9e69299e2c
- PolyLine
- PolyLine
-
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14538
106
44
-
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- Polyline vertex points
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-
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14540
40
20
-
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- Close polyline
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40
20
-
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- Resulting polyline
- 5a89161b-d07b-4559-aad8-0c85fd87afc4
- Polyline
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38
40
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
- Merge
-
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90
64
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- Data stream 1
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- Data 1
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- Data stream 2
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- Data 2
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31
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31
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31
60
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
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-
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210
101
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- Base geometry
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132
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- Polar array plane
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132
37
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0
0
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0
0
0
1
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- Number of elements in array.
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- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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-
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132
20
-
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- false
-
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132
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- 1
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- Arrayed geometry
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- Geometry
- Geometry
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-
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50
48
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- Transformation data
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- Transform
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-
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50
49
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
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- Points to operate on
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- Points
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-
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113
30
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- Proximity tolerance distance
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- Tolerance
- Tolerance
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- 0
-
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113
30
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14477
- 1
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- 1.1641532182693481E-10
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- Culled points
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- Points
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-
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39
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- Index map of culled points
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-
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39
20
-
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- Number of input points represented by this output point
- 31775788-8e35-466b-9c61-4bd7db70d4d2
- Valence
- Valence
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-
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39
20
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 887c7df8-f58a-477f-a647-9f7f4df65452
- Flip Matrix
- Flip Matrix
-
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78
28
-
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- 2
- Data matrix to flip
- e161da66-411b-49e5-a5c4-241e250daa13
- Data
- Data
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- c945af59-6bd4-4bbb-a72f-3179c172e355
- 1
-
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25
24
-
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- 2
- Flipped data matrix
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- Data
- Data
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-
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25
24
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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149
64
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- Curve to evaluate
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-
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71
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-
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- Length factor for curve evaluation
- 35207d3d-0e24-4aa4-94dc-55c0c7dce157
- Length
- Length
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-
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71
20
-
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- 1
- 1
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 451b4f84-441d-437f-bbc9-09be16c9b9e2
- Normalized
- Normalized
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- 0
-
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71
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-
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- 1
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- Point at the specified length
- 8a32f9b6-c5ff-4b22-a7ce-4daf530718c6
- Point
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-
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50
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- Tangent vector at the specified length
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- Tangent
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-
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50
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- Curve parameter at the specified length
- b3381614-7d25-460c-9f4a-5a095ffe7c5b
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-
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50
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- f812766a-18a1-4288-8d6e-7dcd02316302
- Polar Array
- Polar Array
-
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210
101
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- Base geometry
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- 1
-
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132
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- Polar array plane
- f6b5b82e-1c7b-45b4-b48e-eaba2f79ef21
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-
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132
37
-
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-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 9dc6bcca-bb46-4c8c-acec-2d144c59a035
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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14608
132
20
-
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- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 8145af6d-c7ef-42bc-9049-9e286624e582
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- false
-
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14628
132
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- 1
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- 6.2831853071795862
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- Arrayed geometry
- 0cf31f4b-5998-48de-89ee-310044622439
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-
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50
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- 1
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- Transform
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-
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50
49
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- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 438847c3-266b-464a-b75f-f7f717333f9f
- Cull Duplicates
- Cull Duplicates
-
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14546
180
64
-
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- 1
- Points to operate on
- 84319d3c-f942-4ab8-800d-a053b27f4f8f
- Points
- Points
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- 2c9cd1a3-de48-4ce5-be20-36b483914987
- 1
-
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113
30
-
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- Proximity tolerance distance
- aecc6dd9-a2ff-4422-843d-1ea3dba089c9
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- 0
-
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113
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- 1
- 1
- {0}
- 1.1641532182693481E-10
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- false
- 0
-
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15942
35
20
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-9123.5
15952
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ae556089-e277-4e01-aeed-a4880d8dc2ad
- Flip Matrix
- Flip Matrix
-
-9989
15903
94
28
-
-9950
15917
- 2
- Data matrix to flip
- 8ffea371-ed13-48e7-880f-74b30789f15e
- Data
- Data
- false
- d51b821f-a8b8-48bf-8607-af0de2b157a6
- 1
-
-9987
15905
25
24
-
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15917
- 2
- Flipped data matrix
- ee9b6e00-5fdf-479b-85f8-490a96da5593
- 1
- Data
- Data
- false
- 0
-
-9938
15905
41
24
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-9925.5
15917
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- 97ad3468-8c1b-4978-8267-6befe3fc5c22
- Stroke
- Stroke
-
-5995
15522
212
104
-
-5845
15574
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- d173172d-7b48-480e-b296-8adbbcad4256
- Shape / Geometry
- Shape / Geometry
- false
- 30e8295c-3a26-49df-aef1-101d48a13c2b
- 1
-
-5993
15524
136
20
-
-5925
15534
- The stroke color
- 592109e0-df36-4b5c-94a0-cbd7baf26a6b
- Color
- Color
- true
- 6c6fb177-f0ba-4860-8ebe-5a36c08f4a14
- 1
-
-5993
15544
136
20
-
-5925
15554
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- fd4f3b5f-203a-4333-b50e-b9209eee2034
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-5993
15564
136
20
-
-5925
15574
- 1
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- {0}
- 9
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- The stroke pattern
- 5ae57219-d11a-4fc8-b9fd-b79e756353f0
- Pattern
- Pattern
- true
- 0
-
-5993
15584
136
20
-
-5925
15594
- The shape to be used at the end of open path
- 35002325-80cb-42cd-ab96-b47be73fd80b
- End Cap
- End Cap
- true
- 0
-
-5993
15604
136
20
-
-5925
15614
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 9e12c21c-2e26-4f4c-9f08-61fe6812af57
- 1
- Shape
- Shape
- false
- 0
-
-5833
15524
48
100
-
-5817
15574
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 34879ece-4417-40d3-aeed-ab5ce1ef32db
- Clean Tree
- Clean Tree
-
-6829
15498
135
84
-
-6732
15540
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 09ff579e-ffeb-4ffc-aa55-759e5e193f50
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
15500
83
20
-
-6785.5
15510
- 1
- 1
- {0}
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- Remove invalid items from the tree.
- d0961bf5-04f9-4781-a961-e55a0a67b97d
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
15520
83
20
-
-6785.5
15530
- 1
- 1
- {0}
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- Remove empty branches from the tree.
- 0a9d932d-83ff-428b-86a5-943c1d0e8dd5
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
15540
83
20
-
-6785.5
15550
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 9950c6f4-47d2-4cdc-b0d7-7d1f51ee7e3c
- Tree
- Tree
- false
- 5f0869c0-9bc2-45ba-b9bc-7bd6ce42b320
- 1
-
-6827
15560
83
20
-
-6785.5
15570
- 2
- Spotless data tree
- 30e8295c-3a26-49df-aef1-101d48a13c2b
- Tree
- Tree
- false
- 0
-
-6720
15500
24
80
-
-6708
15540
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a1ee8a14-8a22-497a-8572-ee31d0c10743
- Evaluate Length
- Evaluate Length
-
-11840
15464
149
64
-
-11755
15496
- Curve to evaluate
- 7ff01179-ea77-4869-ad68-0c9536995559
- Curve
- Curve
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- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- 1
-
-11838
15466
71
20
-
-11802.5
15476
- Length factor for curve evaluation
- b3590d82-b7a8-40b8-adec-cee0fef3d24e
- Length
- Length
- false
- 0
-
-11838
15486
71
20
-
-11802.5
15496
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 80ea4189-9088-46a2-9b7e-85ab6608bc9b
- Normalized
- Normalized
- false
- 0
-
-11838
15506
71
20
-
-11802.5
15516
- 1
- 1
- {0}
- true
- Point at the specified length
- 8139e3a6-7ad0-46d9-9244-0ef47834cdd8
- Point
- Point
- false
- 0
-
-11743
15466
50
20
-
-11718
15476
- Tangent vector at the specified length
- fabfec87-a549-4543-a177-dfd67fb18d4d
- Tangent
- Tangent
- false
- 0
-
-11743
15486
50
20
-
-11718
15496
- Curve parameter at the specified length
- aa5bc4ba-a857-4868-b36d-46b8926f3f6d
- Parameter
- Parameter
- false
- 0
-
-11743
15506
50
20
-
-11718
15516
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 34133586-fdfd-447f-8e4c-9fc9bdf5f0e4
- PolyLine
- PolyLine
-
-8214
15510
106
44
-
-8160
15532
- 1
- Polyline vertex points
- 96f12eda-fc94-4baf-bb18-9e67bc34d3d0
- Vertices
- Vertices
- false
- 3fe4e5ef-c18f-4e75-b445-569590545a8e
- 1
-
-8212
15512
40
20
-
-8192
15522
- Close polyline
- 13e0205c-351a-499d-b36c-dd55a61bf7c2
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
15532
40
20
-
-8192
15542
- 1
- 1
- {0}
- true
- Resulting polyline
- 8db4425b-83e2-40c4-87be-14b2cc962742
- Polyline
- Polyline
- false
- 0
-
-8148
15512
38
40
-
-8129
15532
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 54552803-fcb7-47e3-85b6-f8522ddca3a7
- PolyLine
- PolyLine
-
-8214
15581
106
44
-
-8160
15603
- 1
- Polyline vertex points
- a7f94eda-da8a-4121-a5d9-4d6fec2c6da4
- Vertices
- Vertices
- false
- 374bcae9-a010-466e-9d02-a93c7753a60d
- 1
-
-8212
15583
40
20
-
-8192
15593
- Close polyline
- 39f77415-45d3-4a69-b629-5b6a3423aeff
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
15603
40
20
-
-8192
15613
- 1
- 1
- {0}
- false
- Resulting polyline
- 1292e96a-373f-4615-878b-73b06199438a
- Polyline
- Polyline
- false
- 0
-
-8148
15583
38
40
-
-8129
15603
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 55428555-7510-47e7-b34a-f9e35f2c711d
- Merge
- Merge
-
-7453
15538
90
64
-
-7408
15570
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
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- 1
-
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15540
31
20
-
-7435.5
15550
- 2
- Data stream 2
- 330680e9-fb57-4a38-8d98-f9a023615dc6
- false
- Data 2
- D2
- true
- 1292e96a-373f-4615-878b-73b06199438a
- 1
-
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15560
31
20
-
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15570
- 2
- Data stream 3
- b6c59f4a-7a29-43c4-9880-663646ed73c7
- false
- Data 3
- D3
- true
- 0
-
-7451
15580
31
20
-
-7435.5
15590
- 2
- Result of merge
- 5f0869c0-9bc2-45ba-b9bc-7bd6ce42b320
- Result
- Result
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- 0
-
-7396
15540
31
60
-
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15570
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 16f260a6-3bfa-4177-9700-dbd2b19bd644
- Polar Array
- Polar Array
-
-10947
15464
210
101
-
-10801
15515
- Base geometry
- 8ca529ad-ddb5-459f-b521-fa1dfb48965c
- Geometry
- Geometry
- true
- 8139e3a6-7ad0-46d9-9244-0ef47834cdd8
- 1
-
-10945
15466
132
20
-
-10879
15476
- Polar array plane
- 82ce54f1-9164-4aad-accc-a41175a73316
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- Plane
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- 0
-
-10945
15486
132
37
-
-10879
15504.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 3a48ed06-c501-413e-8978-b8dc1375db5e
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
15523
132
20
-
-10879
15533
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- fcc69342-30ed-45ed-8833-c6aba74d4db8
- Angle
- Angle
- false
- 0
- false
-
-10945
15543
132
20
-
-10879
15553
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 1ff37f60-11fa-4998-b09a-100ed37fa4b5
- Geometry
- Geometry
- false
- 0
-
-10789
15466
50
48
-
-10764
15490.25
- 1
- Transformation data
- a6adc338-b316-4e18-a5aa-0992c712727d
- Transform
- Transform
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- 0
-
-10789
15514
50
49
-
-10764
15538.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- f9de9d1c-9d35-4a4f-981b-2fa481c0d868
- Cull Duplicates
- Cull Duplicates
-
-9282
15473
180
64
-
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15505
- 1
- Points to operate on
- f2f14759-281c-41b9-82df-a03f03285868
- Points
- Points
- false
- e87642af-d7f4-4c8a-badf-e9466bf0b858
- 1
-
-9280
15475
113
30
-
-9223.5
15490
- Proximity tolerance distance
- 0353c331-b4a5-43b1-a20e-7a0b43bfd2e5
- Tolerance
- Tolerance
- false
- 0
-
-9280
15505
113
30
-
-9223.5
15520
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 3fe4e5ef-c18f-4e75-b445-569590545a8e
- Points
- Points
- false
- 0
-
-9143
15475
39
20
-
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15485
- 1
- Index map of culled points
- 9fde27e7-a677-4304-a18f-c2676737d8b0
- Indices
- Indices
- false
- 0
-
-9143
15495
39
20
-
-9123.5
15505
- 1
- Number of input points represented by this output point
- 6f6bcb5e-d048-436c-aa76-f32f093b621e
- Valence
- Valence
- false
- 0
-
-9143
15515
39
20
-
-9123.5
15525
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- af6b5adb-149b-4459-9dbf-137428ec716c
- Flip Matrix
- Flip Matrix
-
-9989
15476
78
28
-
-9950
15490
- 2
- Data matrix to flip
- 4728b728-dde9-45ad-a962-6b8d3dc26dd4
- Data
- Data
- false
- 1ff37f60-11fa-4998-b09a-100ed37fa4b5
- 1
-
-9987
15478
25
24
-
-9974.5
15490
- 2
- Flipped data matrix
- 82f35a99-14e7-47ff-900d-a54c896b2c78
- Data
- Data
- false
- 0
-
-9938
15478
25
24
-
-9925.5
15490
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e5d41782-59e3-422f-8dc1-39d1a4c31f64
- Evaluate Length
- Evaluate Length
-
-11840
15592
149
64
-
-11755
15624
- Curve to evaluate
- fdab1e59-e8a6-4ca8-a6fb-ffc5e907e94c
- Curve
- Curve
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- 11ceca9b-30b2-4213-b35d-85e5be45643a
- 1
-
-11838
15594
71
20
-
-11802.5
15604
- Length factor for curve evaluation
- 5e598139-29f5-4d32-9b67-673c1e882f4e
- Length
- Length
- false
- 0
-
-11838
15614
71
20
-
-11802.5
15624
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 2e3a9590-1657-41a4-b518-a093017be771
- Normalized
- Normalized
- false
- 0
-
-11838
15634
71
20
-
-11802.5
15644
- 1
- 1
- {0}
- true
- Point at the specified length
- 473b46fc-6cd7-4a94-8ca5-b05277cc1d8b
- Point
- Point
- false
- 0
-
-11743
15594
50
20
-
-11718
15604
- Tangent vector at the specified length
- 52a87992-e8a0-4f0f-8c05-55153f97d863
- Tangent
- Tangent
- false
- 0
-
-11743
15614
50
20
-
-11718
15624
- Curve parameter at the specified length
- b130efa6-1671-4814-8eb7-15fed1ab4d7d
- Parameter
- Parameter
- false
- 0
-
-11743
15634
50
20
-
-11718
15644
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- e09ba9cc-f215-4476-a87b-f3262cdad00d
- Polar Array
- Polar Array
-
-10947
15592
210
101
-
-10801
15643
- Base geometry
- 08a3a0e5-ab76-4f85-9791-6ef4be0b9757
- Geometry
- Geometry
- true
- 473b46fc-6cd7-4a94-8ca5-b05277cc1d8b
- 1
-
-10945
15594
132
20
-
-10879
15604
- Polar array plane
- 4437a4ce-48b8-4487-86a8-909e6464789d
- Plane
- Plane
- false
- 0
-
-10945
15614
132
37
-
-10879
15632.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- cecf5e04-5877-483f-b076-ffa1ae57d765
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
15651
132
20
-
-10879
15661
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 7ec85d43-0d12-4cf3-9654-7e21d2143d62
- Angle
- Angle
- false
- 0
- false
-
-10945
15671
132
20
-
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15681
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 81827009-40cb-4a9d-81cd-2bdaedb2032c
- Geometry
- Geometry
- false
- 0
-
-10789
15594
50
48
-
-10764
15618.25
- 1
- Transformation data
- 1dfc6ef3-24e3-4422-8c65-70641f970550
- Transform
- Transform
- false
- 0
-
-10789
15642
50
49
-
-10764
15666.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- fe0fc6e9-e5f7-4110-a364-f3890ca938b3
- Cull Duplicates
- Cull Duplicates
-
-9282
15589
180
64
-
-9155
15621
- 1
- Points to operate on
- a3e211f7-c4ad-4867-8204-98cdbb3340d2
- Points
- Points
- false
- 0156a723-76fc-4a7c-8320-97d012f1e76e
- 1
-
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15591
113
30
-
-9223.5
15606
- Proximity tolerance distance
- f068b07d-0de1-42d7-8d2f-b5669a2a9a29
- Tolerance
- Tolerance
- false
- 0
-
-9280
15621
113
30
-
-9223.5
15636
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 374bcae9-a010-466e-9d02-a93c7753a60d
- Points
- Points
- false
- 0
-
-9143
15591
39
20
-
-9123.5
15601
- 1
- Index map of culled points
- a878cb80-e1bb-449d-8caf-1900890ade4e
- Indices
- Indices
- false
- 0
-
-9143
15611
39
20
-
-9123.5
15621
- 1
- Number of input points represented by this output point
- 7f3f23e9-8b29-441d-86b2-02da645e2b58
- Valence
- Valence
- false
- 0
-
-9143
15631
39
20
-
-9123.5
15641
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- e35cce34-d103-45dc-93d5-42459738908e
- Flip Matrix
- Flip Matrix
-
-9989
15604
78
28
-
-9950
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- Stroke
- Applies Stroke properties to a Shape
- true
- f6e61e3a-a382-4f5c-9492-122915e38592
- Stroke
- Stroke
-
-5995
16693
212
104
-
-5845
16745
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 0b430a89-5c68-4b7e-9f4c-5b801713e699
- Shape / Geometry
- Shape / Geometry
- false
- bc172503-953b-42d6-9f6c-01e9cdbf6da9
- 1
-
-5993
16695
136
20
-
-5925
16705
- The stroke color
- 41e2b278-73d3-4577-b3ff-d52999f2df92
- Color
- Color
- true
- 5d585ae3-4a99-4be5-a4d5-4354c3267ffe
- 1
-
-5993
16715
136
20
-
-5925
16725
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- b3028dec-57fe-46a7-8d26-9b740b41f34c
- Weight
- Weight
- true
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-5993
16735
136
20
-
-5925
16745
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- e06b7cea-813c-493a-b99d-44255dc7076b
- Pattern
- Pattern
- true
- 0
-
-5993
16755
136
20
-
-5925
16765
- The shape to be used at the end of open path
- ac47fdcd-c4a0-47fe-934c-7abccec6e33a
- End Cap
- End Cap
- true
- 0
-
-5993
16775
136
20
-
-5925
16785
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- e8350921-bce9-4dab-befe-7c6e8c133aeb
- 1
- Shape
- Shape
- false
- 0
-
-5833
16695
48
100
-
-5817
16745
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- d995efc2-7519-4417-ae0a-d36bf296b9f7
- Clean Tree
- Clean Tree
-
-6829
16669
135
84
-
-6732
16711
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 6782aa1f-a2bf-49dd-b7f4-cc4138a697d5
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
16671
83
20
-
-6785.5
16681
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- ee053123-99d9-4c17-9a85-9dd25085669a
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
16691
83
20
-
-6785.5
16701
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 6c263a19-fcf7-42c1-a05f-6297b0615acd
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
16711
83
20
-
-6785.5
16721
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 0786fe94-2693-4e2f-a530-ba3f25454d65
- Tree
- Tree
- false
- 91b737a8-c046-47f6-8f04-9f251cd03527
- 1
-
-6827
16731
83
20
-
-6785.5
16741
- 2
- Spotless data tree
- bc172503-953b-42d6-9f6c-01e9cdbf6da9
- Tree
- Tree
- false
- 0
-
-6720
16671
24
80
-
-6708
16711
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 02737097-b8b1-41db-98c1-fc50380663f5
- Evaluate Length
- Evaluate Length
-
-11840
16635
149
64
-
-11755
16667
- Curve to evaluate
- 2a5446b7-932d-41bb-aad7-99f4765a1b0c
- Curve
- Curve
- false
- 2f545125-747a-4904-9cb7-05bc0727e11d
- 1
-
-11838
16637
71
20
-
-11802.5
16647
- Length factor for curve evaluation
- 97db9dfb-d83f-43bc-aa6c-74315e99c866
- Length
- Length
- false
- 0
-
-11838
16657
71
20
-
-11802.5
16667
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- b97a0607-d9c4-424b-bf06-962419323acb
- Normalized
- Normalized
- false
- 0
-
-11838
16677
71
20
-
-11802.5
16687
- 1
- 1
- {0}
- true
- Point at the specified length
- f264c5ca-1559-4c36-92b0-2d97232c46ad
- Point
- Point
- false
- 0
-
-11743
16637
50
20
-
-11718
16647
- Tangent vector at the specified length
- 8a1eee52-af70-4242-b077-63631f092dd9
- Tangent
- Tangent
- false
- 0
-
-11743
16657
50
20
-
-11718
16667
- Curve parameter at the specified length
- 2f54eb4c-185e-4cf1-a1fd-9e1135d4fa77
- Parameter
- Parameter
- false
- 0
-
-11743
16677
50
20
-
-11718
16687
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e0561d63-9b13-44a4-b9ea-99a9cb1c13e2
- PolyLine
- PolyLine
-
-8214
16681
106
44
-
-8160
16703
- 1
- Polyline vertex points
- 528e6586-6ecf-40b3-a743-0d6f9fe0bfbb
- Vertices
- Vertices
- false
- 1c9cf092-7009-4949-8f7f-f9236794e9fe
- 1
-
-8212
16683
40
20
-
-8192
16693
- Close polyline
- d00b5e18-77f2-45e7-9369-4182df4cb587
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
16703
40
20
-
-8192
16713
- 1
- 1
- {0}
- true
- Resulting polyline
- ced6c00c-4ac4-4fb8-8f0e-7f436ffdab13
- Polyline
- Polyline
- false
- 0
-
-8148
16683
38
40
-
-8129
16703
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- dbe88505-9526-40fb-9e1b-1d78e902c27b
- PolyLine
- PolyLine
-
-8214
16752
106
44
-
-8160
16774
- 1
- Polyline vertex points
- 1c49aba5-694f-462f-a831-11170af53bec
- Vertices
- Vertices
- false
- 9349eef4-58b8-408a-a0c5-e579ddf40767
- 1
-
-8212
16754
40
20
-
-8192
16764
- Close polyline
- 8233a329-2e4f-44bd-96f8-223124a1bc74
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
16774
40
20
-
-8192
16784
- 1
- 1
- {0}
- false
- Resulting polyline
- 1207f491-dbbb-4093-b3ad-3c374a18a952
- Polyline
- Polyline
- false
- 0
-
-8148
16754
38
40
-
-8129
16774
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- b45fdf0c-87e6-4bba-86a6-8fed07429172
- Merge
- Merge
-
-7453
16709
90
64
-
-7408
16741
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 485cb551-bbd8-419d-8466-46125ba0477f
- false
- Data 1
- D1
- true
- ced6c00c-4ac4-4fb8-8f0e-7f436ffdab13
- 1
-
-7451
16711
31
20
-
-7435.5
16721
- 2
- Data stream 2
- 25ff9633-f2c4-4e2e-9a91-bc534e46c8cc
- false
- Data 2
- D2
- true
- 1207f491-dbbb-4093-b3ad-3c374a18a952
- 1
-
-7451
16731
31
20
-
-7435.5
16741
- 2
- Data stream 3
- 038257c2-b3a0-4434-aaa7-dda6c93c1836
- false
- Data 3
- D3
- true
- 0
-
-7451
16751
31
20
-
-7435.5
16761
- 2
- Result of merge
- 91b737a8-c046-47f6-8f04-9f251cd03527
- Result
- Result
- false
- 0
-
-7396
16711
31
60
-
-7380.5
16741
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 7c40bd65-f93b-4501-8448-a9384bf4ddce
- Polar Array
- Polar Array
-
-10947
16635
210
101
-
-10801
16686
- Base geometry
- 09e1489a-38c3-4586-a46e-83107b7f002a
- Geometry
- Geometry
- true
- f264c5ca-1559-4c36-92b0-2d97232c46ad
- 1
-
-10945
16637
132
20
-
-10879
16647
- Polar array plane
- 764fb3a2-368f-4b97-93ef-08ec580daf72
- Plane
- Plane
- false
- 0
-
-10945
16657
132
37
-
-10879
16675.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f82733ea-5617-4886-bc83-2fe7b3095cdc
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
16694
132
20
-
-10879
16704
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 6800c134-8e8f-44a1-9722-8a746870d50a
- Angle
- Angle
- false
- 0
- false
-
-10945
16714
132
20
-
-10879
16724
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 23d7f84a-bc05-46db-b2ea-0f7b23826746
- Geometry
- Geometry
- false
- 0
-
-10789
16637
50
48
-
-10764
16661.25
- 1
- Transformation data
- 7722b4a9-f344-48f8-b43d-c047dcd621a7
- Transform
- Transform
- false
- 0
-
-10789
16685
50
49
-
-10764
16709.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 9887bd44-97bb-4024-9f89-c1252834018a
- Cull Duplicates
- Cull Duplicates
-
-9282
16644
180
64
-
-9155
16676
- 1
- Points to operate on
- e79e43c6-1e2b-46be-8454-f2a5d0a9e7a3
- Points
- Points
- false
- d3503a0a-25d4-40f9-b392-12c89e516f16
- 1
-
-9280
16646
113
30
-
-9223.5
16661
- Proximity tolerance distance
- 26c15905-27a6-4859-83f1-faa8fec300f6
- Tolerance
- Tolerance
- false
- 0
-
-9280
16676
113
30
-
-9223.5
16691
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 1c9cf092-7009-4949-8f7f-f9236794e9fe
- Points
- Points
- false
- 0
-
-9143
16646
39
20
-
-9123.5
16656
- 1
- Index map of culled points
- 7359f5b0-78b4-4f91-80f2-ac08726f8f96
- Indices
- Indices
- false
- 0
-
-9143
16666
39
20
-
-9123.5
16676
- 1
- Number of input points represented by this output point
- a8c0bb0c-fdc4-47b0-b658-845db3b475f1
- Valence
- Valence
- false
- 0
-
-9143
16686
39
20
-
-9123.5
16696
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- b5d93ecd-2ef1-4b68-b74f-be0a5cca1d2b
- Flip Matrix
- Flip Matrix
-
-9989
16647
78
28
-
-9950
16661
- 2
- Data matrix to flip
- 32e8694b-97fc-455a-9d25-12c6106e2bec
- Data
- Data
- false
- 23d7f84a-bc05-46db-b2ea-0f7b23826746
- 1
-
-9987
16649
25
24
-
-9974.5
16661
- 2
- Flipped data matrix
- 6de70eee-64cc-4d17-ad90-5e27d252e6e5
- Data
- Data
- false
- 0
-
-9938
16649
25
24
-
-9925.5
16661
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e44419a3-3e7b-451b-ad2b-befe815a1642
- Evaluate Length
- Evaluate Length
-
-11840
16763
149
64
-
-11755
16795
- Curve to evaluate
- f21d970a-0a31-4084-abcd-1f722bb29097
- Curve
- Curve
- false
- 29946d34-0db3-4cc0-bbb0-27c79f7c8eb9
- 1
-
-11838
16765
71
20
-
-11802.5
16775
- Length factor for curve evaluation
- 7d649dc5-fa68-41b5-aa84-d93b3189a6d1
- Length
- Length
- false
- 0
-
-11838
16785
71
20
-
-11802.5
16795
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 39b0d8c4-19df-4207-ad20-b62f10657d75
- Normalized
- Normalized
- false
- 0
-
-11838
16805
71
20
-
-11802.5
16815
- 1
- 1
- {0}
- true
- Point at the specified length
- e2dea9a1-a097-4340-b25a-e37176bd7740
- Point
- Point
- false
- 0
-
-11743
16765
50
20
-
-11718
16775
- Tangent vector at the specified length
- c761ff1f-1345-4339-b98a-8f8a9a16ae44
- Tangent
- Tangent
- false
- 0
-
-11743
16785
50
20
-
-11718
16795
- Curve parameter at the specified length
- 81533d08-e4df-4b3d-b9b6-a85448cf8ead
- Parameter
- Parameter
- false
- 0
-
-11743
16805
50
20
-
-11718
16815
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- af57175f-b87d-4d4b-865c-8de67eb6f48c
- Polar Array
- Polar Array
-
-10947
16763
210
101
-
-10801
16814
- Base geometry
- f22d30c8-4b4b-4cea-9ec0-0edbc8672688
- Geometry
- Geometry
- true
- e2dea9a1-a097-4340-b25a-e37176bd7740
- 1
-
-10945
16765
132
20
-
-10879
16775
- Polar array plane
- 99756a04-f589-4b3d-9f05-522affd1de67
- Plane
- Plane
- false
- 0
-
-10945
16785
132
37
-
-10879
16803.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 840959dc-1048-4e82-9559-88d1802886bb
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
16822
132
20
-
-10879
16832
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 31487356-e2ba-44a1-a310-e5120d4ff151
- Angle
- Angle
- false
- 0
- false
-
-10945
16842
132
20
-
-10879
16852
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 90282863-2ca2-4350-a4f0-8ba50b257398
- Geometry
- Geometry
- false
- 0
-
-10789
16765
50
48
-
-10764
16789.25
- 1
- Transformation data
- b7364e57-5ffd-4559-9ef0-07aedc662109
- Transform
- Transform
- false
- 0
-
-10789
16813
50
49
-
-10764
16837.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- a2446556-35a4-42a2-992b-4c5465def5ca
- Cull Duplicates
- Cull Duplicates
-
-9282
16760
180
64
-
-9155
16792
- 1
- Points to operate on
- 176aa800-b998-4c0a-9503-57c602bcda9e
- Points
- Points
- false
- 4dfda7fb-90ae-4f9e-9305-08baf23c2d50
- 1
-
-9280
16762
113
30
-
-9223.5
16777
- Proximity tolerance distance
- cb095ab5-a871-4ea2-ae23-443a1fbeee58
- Tolerance
- Tolerance
- false
- 0
-
-9280
16792
113
30
-
-9223.5
16807
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 9349eef4-58b8-408a-a0c5-e579ddf40767
- Points
- Points
- false
- 0
-
-9143
16762
39
20
-
-9123.5
16772
- 1
- Index map of culled points
- 26dd8312-d3ae-477c-9e0c-1009f60f5c95
- Indices
- Indices
- false
- 0
-
-9143
16782
39
20
-
-9123.5
16792
- 1
- Number of input points represented by this output point
- c419d320-3140-47d8-8d0d-fc6df26eece9
- Valence
- Valence
- false
- 0
-
-9143
16802
39
20
-
-9123.5
16812
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 14074e3a-0c4f-43d3-8ef6-6d6fa0d55c7b
- Flip Matrix
- Flip Matrix
-
-9989
16775
78
28
-
-9950
16789
- 2
- Data matrix to flip
- 4bf40f1b-5da2-40d3-a958-12d3c3d9ad5e
- Data
- Data
- false
- 90282863-2ca2-4350-a4f0-8ba50b257398
- 1
-
-9987
16777
25
24
-
-9974.5
16789
- 2
- Flipped data matrix
- 87fdae07-bcf5-489b-89b1-aec57ffa9c17
- Data
- Data
- false
- 0
-
-9938
16777
25
24
-
-9925.5
16789
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 2f545125-747a-4904-9cb7-05bc0727e11d
- Relay
- false
- 598eec7f-8923-45a9-bb06-9d39462f5b42
- 1
-
-12721
16653
40
16
-
-12701
16661
- b6236720-8d88-4289-93c3-ac4c99f9b97b
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17836
136
20
-
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17846
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- 1c98149e-e677-40ca-aaec-c82501e35e88
- Pattern
- Pattern
- true
- 0
-
-5993
17856
136
20
-
-5925
17866
- The shape to be used at the end of open path
- 82225c16-8dba-42a0-9a33-7130e468373b
- End Cap
- End Cap
- true
- 0
-
-5993
17876
136
20
-
-5925
17886
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 0e15a768-0ee5-4b2c-8524-5d790cc8917d
- 1
- Shape
- Shape
- false
- 0
-
-5833
17796
48
100
-
-5817
17846
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- b78ab8de-5b2e-4309-9c68-2222a272421b
- Clean Tree
- Clean Tree
-
-6829
17770
135
84
-
-6732
17812
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- e4c683fe-95ce-4292-867b-df623aa4a2b6
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
17772
83
20
-
-6785.5
17782
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- bfa076b6-fb4b-40d6-be9f-67fb884e8d6c
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
17792
83
20
-
-6785.5
17802
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 329824a3-1ac9-4d57-9735-a29b88f515c5
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
17812
83
20
-
-6785.5
17822
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- a38d6fc8-c43a-4b4a-9553-733995115f34
- Tree
- Tree
- false
- 625c9542-af93-4f62-aed4-573bb02b38ee
- 1
-
-6827
17832
83
20
-
-6785.5
17842
- 2
- Spotless data tree
- 60a0df0e-bd21-4cdf-a3f4-16fb4176c3ae
- Tree
- Tree
- false
- 0
-
-6720
17772
24
80
-
-6708
17812
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- fd943d99-68a3-4898-b506-68be67cd4cf2
- Evaluate Length
- Evaluate Length
-
-11840
17736
149
64
-
-11755
17768
- Curve to evaluate
- 21446a6b-2f2d-4abc-a8c3-b71cb39432c9
- Curve
- Curve
- false
- 1504e2b4-e091-439c-ace1-a3e70d52839d
- 1
-
-11838
17738
71
20
-
-11802.5
17748
- Length factor for curve evaluation
- 80653072-e8be-483c-a4a2-f30d6bd332e8
- Length
- Length
- false
- 0
-
-11838
17758
71
20
-
-11802.5
17768
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- ced79bb1-e361-42a4-89f7-a85a93ea6d28
- Normalized
- Normalized
- false
- 0
-
-11838
17778
71
20
-
-11802.5
17788
- 1
- 1
- {0}
- true
- Point at the specified length
- 7b21e7c4-e20e-484d-818d-a663768d8508
- Point
- Point
- false
- 0
-
-11743
17738
50
20
-
-11718
17748
- Tangent vector at the specified length
- c4a0d5f8-e9f9-4097-afb7-0f148a2fc879
- Tangent
- Tangent
- false
- 0
-
-11743
17758
50
20
-
-11718
17768
- Curve parameter at the specified length
- 74969c75-1dd5-4e4d-ad34-4225f6ae85e0
- Parameter
- Parameter
- false
- 0
-
-11743
17778
50
20
-
-11718
17788
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a2436e8a-9975-43b5-8abc-89e175cb9bcd
- PolyLine
- PolyLine
-
-8214
17782
106
44
-
-8160
17804
- 1
- Polyline vertex points
- 5062ab4b-7936-4329-a512-9a867699e9d8
- Vertices
- Vertices
- false
- efa1592b-bbf9-4d3b-9415-7562319eaad4
- 1
-
-8212
17784
40
20
-
-8192
17794
- Close polyline
- e11365c4-bde5-47cf-845b-e1c75c83629b
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
17804
40
20
-
-8192
17814
- 1
- 1
- {0}
- true
- Resulting polyline
- 4713e6bd-a9c4-4e05-984f-ea9377a0e684
- Polyline
- Polyline
- false
- 0
-
-8148
17784
38
40
-
-8129
17804
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- fb1f3eff-3a65-4bda-9df9-54842bb38cd9
- PolyLine
- PolyLine
-
-8214
17853
106
44
-
-8160
17875
- 1
- Polyline vertex points
- 4bd91e38-4208-49d6-bc7c-3b81596309b1
- Vertices
- Vertices
- false
- ffd681a6-6a65-4c1f-9085-7033988b0b32
- 1
-
-8212
17855
40
20
-
-8192
17865
- Close polyline
- 02d0af90-446c-49a4-af64-6a50853b6df9
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
17875
40
20
-
-8192
17885
- 1
- 1
- {0}
- false
- Resulting polyline
- d0ac4694-9cbb-408e-a7c4-fe13ed702009
- Polyline
- Polyline
- false
- 0
-
-8148
17855
38
40
-
-8129
17875
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- a8f9a73d-06ad-4ff7-a9f6-5af2990ec6f6
- Merge
- Merge
-
-7453
17810
90
64
-
-7408
17842
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 9acadea0-bd13-47ca-b3be-42b06838ca1e
- false
- Data 1
- D1
- true
- 4713e6bd-a9c4-4e05-984f-ea9377a0e684
- 1
-
-7451
17812
31
20
-
-7435.5
17822
- 2
- Data stream 2
- 8a35825f-12c6-4369-b4a8-095ea5853786
- false
- Data 2
- D2
- true
- d0ac4694-9cbb-408e-a7c4-fe13ed702009
- 1
-
-7451
17832
31
20
-
-7435.5
17842
- 2
- Data stream 3
- 2ace1d5c-cb95-4db9-8c22-afa659881bf5
- false
- Data 3
- D3
- true
- 0
-
-7451
17852
31
20
-
-7435.5
17862
- 2
- Result of merge
- 625c9542-af93-4f62-aed4-573bb02b38ee
- Result
- Result
- false
- 0
-
-7396
17812
31
60
-
-7380.5
17842
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- c605e62b-d6b6-4e76-91bb-368d21f313f5
- Polar Array
- Polar Array
-
-10947
17736
210
101
-
-10801
17787
- Base geometry
- 9e87d25c-f926-4f0e-9456-35e638186c1d
- Geometry
- Geometry
- true
- 7b21e7c4-e20e-484d-818d-a663768d8508
- 1
-
-10945
17738
132
20
-
-10879
17748
- Polar array plane
- 697e3b87-e310-46b2-807a-5dab2983da65
- Plane
- Plane
- false
- 0
-
-10945
17758
132
37
-
-10879
17776.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 50e55b22-9ec1-4670-b88a-e1f7bcdf83c0
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
17795
132
20
-
-10879
17805
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 574e6b39-ce22-4257-b82d-a817ecf2b838
- Angle
- Angle
- false
- 0
- false
-
-10945
17815
132
20
-
-10879
17825
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 2b5ab43a-bf29-46b7-97f8-b9a1e5f5505d
- Geometry
- Geometry
- false
- 0
-
-10789
17738
50
48
-
-10764
17762.25
- 1
- Transformation data
- 9d851bcf-7c36-4420-a968-df9aea2eeabe
- Transform
- Transform
- false
- 0
-
-10789
17786
50
49
-
-10764
17810.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 22c8303a-ab41-4056-b0f0-d75617008c03
- Cull Duplicates
- Cull Duplicates
-
-9282
17745
180
64
-
-9155
17777
- 1
- Points to operate on
- db3726a7-ccba-464a-9d6c-4365a485eaa6
- Points
- Points
- false
- 3b0f4ca8-63aa-4144-82ce-e47ac4bbb7e5
- 1
-
-9280
17747
113
30
-
-9223.5
17762
- Proximity tolerance distance
- 10e85b55-fe13-40a0-b8a2-043f1dddde10
- Tolerance
- Tolerance
- false
- 0
-
-9280
17777
113
30
-
-9223.5
17792
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- efa1592b-bbf9-4d3b-9415-7562319eaad4
- Points
- Points
- false
- 0
-
-9143
17747
39
20
-
-9123.5
17757
- 1
- Index map of culled points
- 3aca07e1-b1b8-44f0-81b1-8d23b1d0bb0f
- Indices
- Indices
- false
- 0
-
-9143
17767
39
20
-
-9123.5
17777
- 1
- Number of input points represented by this output point
- 50ed2f1f-0e8b-46b5-b32e-bdbe742f4fc2
- Valence
- Valence
- false
- 0
-
-9143
17787
39
20
-
-9123.5
17797
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ddafa6fc-5d20-4aaa-86d7-657fc631898f
- Flip Matrix
- Flip Matrix
-
-9989
17748
78
28
-
-9950
17762
- 2
- Data matrix to flip
- 4a24e956-c5f1-4b2a-9f10-68d207dcd243
- Data
- Data
- false
- 2b5ab43a-bf29-46b7-97f8-b9a1e5f5505d
- 1
-
-9987
17750
25
24
-
-9974.5
17762
- 2
- Flipped data matrix
- 7e35038d-d7b3-4169-a2e1-ee147c9aa897
- Data
- Data
- false
- 0
-
-9938
17750
25
24
-
-9925.5
17762
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- b06ef032-a6e7-4452-9651-12a4aa2e7cec
- Evaluate Length
- Evaluate Length
-
-11840
17864
149
64
-
-11755
17896
- Curve to evaluate
- 2c14f2cf-46ba-4918-8f1c-b3272ba74995
- Curve
- Curve
- false
- 587de0b9-9f06-4d87-bf93-b93668a84499
- 1
-
-11838
17866
71
20
-
-11802.5
17876
- Length factor for curve evaluation
- de6d2a10-b91a-4a82-a095-c0c9229e0510
- Length
- Length
- false
- 0
-
-11838
17886
71
20
-
-11802.5
17896
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 32924ee0-ca83-49e6-845a-57621ca8781b
- Normalized
- Normalized
- false
- 0
-
-11838
17906
71
20
-
-11802.5
17916
- 1
- 1
- {0}
- true
- Point at the specified length
- ab1cebea-9440-45d3-b22a-729e57d3f393
- Point
- Point
- false
- 0
-
-11743
17866
50
20
-
-11718
17876
- Tangent vector at the specified length
- c4f283c6-130d-4973-b31d-0b4e1e300c93
- Tangent
- Tangent
- false
- 0
-
-11743
17886
50
20
-
-11718
17896
- Curve parameter at the specified length
- f8e517ea-def4-4d7a-b176-d494f464103b
- Parameter
- Parameter
- false
- 0
-
-11743
17906
50
20
-
-11718
17916
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 613d5bca-f997-48a6-99da-2794f7a3babf
- Polar Array
- Polar Array
-
-10947
17864
210
101
-
-10801
17915
- Base geometry
- 863bdee8-d814-4028-a927-080f2ae9d329
- Geometry
- Geometry
- true
- ab1cebea-9440-45d3-b22a-729e57d3f393
- 1
-
-10945
17866
132
20
-
-10879
17876
- Polar array plane
- af140e57-5203-44d4-b935-2c282782fc2f
- Plane
- Plane
- false
- 0
-
-10945
17886
132
37
-
-10879
17904.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f07b7b89-6eed-4d38-bbd7-03d43ae2b722
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
17923
132
20
-
-10879
17933
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 4334bf6d-2032-41a4-94b1-ab89a78e6cb8
- Angle
- Angle
- false
- 0
- false
-
-10945
17943
132
20
-
-10879
17953
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 5b1d4834-80d0-4db9-ac90-af4511687158
- Geometry
- Geometry
- false
- 0
-
-10789
17866
50
48
-
-10764
17890.25
- 1
- Transformation data
- e5d1d1bc-46cb-4015-8dfd-098bb74775d3
- Transform
- Transform
- false
- 0
-
-10789
17914
50
49
-
-10764
17938.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 7da63af0-39d5-4057-9777-ed62661c16b2
- Cull Duplicates
- Cull Duplicates
-
-9282
17861
180
64
-
-9155
17893
- 1
- Points to operate on
- 38f185c5-7c31-409b-abb8-cca7ff4ae1ac
- Points
- Points
- false
- 7415449f-d53b-4906-8899-d2695a78b338
- 1
-
-9280
17863
113
30
-
-9223.5
17878
- Proximity tolerance distance
- a1c113c7-5886-4257-a65f-cc641c5d5e71
- Tolerance
- Tolerance
- false
- 0
-
-9280
17893
113
30
-
-9223.5
17908
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- ffd681a6-6a65-4c1f-9085-7033988b0b32
- Points
- Points
- false
- 0
-
-9143
17863
39
20
-
-9123.5
17873
- 1
- Index map of culled points
- b9843477-48d7-4054-b06a-b93861e7f600
- Indices
- Indices
- false
- 0
-
-9143
17883
39
20
-
-9123.5
17893
- 1
- Number of input points represented by this output point
- 37d80b0c-37cc-4b41-8b86-0405fac43c2d
- Valence
- Valence
- false
- 0
-
-9143
17903
39
20
-
-9123.5
17913
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- d3afd561-a88c-4672-82f5-740dd875dd98
- Flip Matrix
- Flip Matrix
-
-9989
17876
78
28
-
-9950
17890
- 2
- Data matrix to flip
- f0fd6251-e51b-4d26-a996-a53e51e57a84
- Data
- Data
- false
- 5b1d4834-80d0-4db9-ac90-af4511687158
- 1
-
-9987
17878
25
24
-
-9974.5
17890
- 2
- Flipped data matrix
- eb27fc67-93d3-4155-93e7-01f56e95a084
- Data
- Data
- false
- 0
-
-9938
17878
25
24
-
-9925.5
17890
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 1504e2b4-e091-439c-ace1-a3e70d52839d
- Relay
- false
- 56e8bb2d-4b74-4665-8007-49becf882746
- 1
-
-12721
17757
40
16
-
-12701
17765
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 587de0b9-9f06-4d87-bf93-b93668a84499
- Relay
- false
- 4106a4b6-ae1e-4c1a-aa13-89f01b1f0d6e
- 1
-
-12721
17905
40
16
-
-12701
17913
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 1504e2b4-e091-439c-ace1-a3e70d52839d
- 587de0b9-9f06-4d87-bf93-b93668a84499
- 2
- 653f1ce8-71ff-4bd6-8b5b-9fd09ed2f5ac
- Group
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 876934e9-655e-4c18-8ecc-1f5a9916c57f
- Merge
- Merge
-
-5154
17941
106
84
-
-5109
17983
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Clean Tree
- Clean Tree
-
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18912
135
84
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18954
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- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
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- Remove Nulls
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- 0
-
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18914
83
20
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18924
- 1
- 1
- {0}
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- Remove invalid items from the tree.
- 0c3fecef-2554-4bfa-adc7-e0de3a33ea8a
- Remove Invalid
- Remove Invalid
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- 0
-
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18934
83
20
-
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18944
- 1
- 1
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- Remove empty branches from the tree.
- 7371a2b2-d381-459e-affc-3d53ad85deb8
- Remove Empty
- Remove Empty
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- 0
-
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18954
83
20
-
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18964
- 1
- 1
- {0}
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- Data tree to clean
- b9a404d9-8458-4fe8-abe1-ed12c7d32048
- Tree
- Tree
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- 160c7d88-f5b0-4294-bfa1-649a8ee28944
- 1
-
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18974
83
20
-
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18984
- 2
- Spotless data tree
- 44d4ba80-f520-479f-8909-f0d56df54de0
- Tree
- Tree
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-
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18914
24
80
-
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18954
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- fa291861-d949-4bce-b86b-6a37fa2376ef
- Evaluate Length
- Evaluate Length
-
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18878
149
64
-
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- Curve to evaluate
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- 49eeb6cb-33ad-4c36-b3da-903f4f48a3dc
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-
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18880
71
20
-
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- Length factor for curve evaluation
- 606142ac-ca1e-4256-abb7-6816d1878fce
- Length
- Length
- false
- 0
-
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18900
71
20
-
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18910
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 14d537d2-cda1-49e1-b5f6-1c4b41224094
- Normalized
- Normalized
- false
- 0
-
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18920
71
20
-
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18930
- 1
- 1
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- Point at the specified length
- f10c4e95-dbce-468a-9c4e-100f931a3443
- Point
- Point
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- 0
-
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18880
50
20
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18890
- Tangent vector at the specified length
- 315b4d59-1f34-4249-9641-c9da074f79ed
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-
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18900
50
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- Curve parameter at the specified length
- 514bac3d-628b-44d0-98f0-6f1bef253852
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-
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18920
50
20
-
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18930
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
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- da18f131-7a27-40bc-b68d-7f901b717384
- PolyLine
- PolyLine
-
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18924
106
44
-
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- Polyline vertex points
- 6f49cf12-1468-4634-813e-de6e70e9612f
- Vertices
- Vertices
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- 3606ae1a-a45f-48d1-a992-4ac71a0775e4
- 1
-
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18926
40
20
-
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18936
- Close polyline
- 694a68d4-97a8-4a7d-84cd-0664b93e4c50
- Closed
- Closed
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- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
18946
40
20
-
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18956
- 1
- 1
- {0}
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- Resulting polyline
- 52b4596b-5174-4b48-af16-45f55b685c27
- Polyline
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-
-8148
18926
38
40
-
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18946
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- c34fa604-6cdc-4331-84e4-5f9370955b30
- PolyLine
- PolyLine
-
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18995
106
44
-
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19017
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- Polyline vertex points
- d5d9eae5-8d8d-460d-a0b3-58cf1135a14f
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- 1
-
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18997
40
20
-
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19007
- Close polyline
- c8ed8166-34f1-462d-8911-718cfdb56a67
- Closed
- Closed
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- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
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19017
40
20
-
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19027
- 1
- 1
- {0}
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- Resulting polyline
- 5d541f70-e0c5-4828-8290-1655d1ce11b3
- Polyline
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-
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18997
38
40
-
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19017
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- 4c517ba1-39e4-45fa-9c9c-a8787379bb0a
- Merge
- Merge
-
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18952
90
64
-
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18984
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
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- 1
-
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18954
31
20
-
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- 2
- Data stream 2
- 9398cba2-7a4e-4fc2-91d8-b33acb298ec7
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- Data 2
- D2
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- 1
-
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18974
31
20
-
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- 2
- Data stream 3
- 0ce5fac0-dced-4a1a-96da-0f97013002f3
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- Data 3
- D3
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- 0
-
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18994
31
20
-
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- Result of merge
- 160c7d88-f5b0-4294-bfa1-649a8ee28944
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-
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18954
31
60
-
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18984
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 020d7e9b-2333-4de8-bef4-92bdc9ea1505
- Polar Array
- Polar Array
-
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18878
210
101
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- Base geometry
- b1b2e24f-e9ab-4202-b7fa-96d1c47258be
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-
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18880
132
20
-
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- Polar array plane
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-
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18900
132
37
-
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-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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18937
132
20
-
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- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- fcb77176-dad3-411b-877d-8fa9e333a25c
- Angle
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- false
-
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18957
132
20
-
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18967
- 1
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- Arrayed geometry
- e71be443-1b77-45d9-ae18-84613f8b4029
- Geometry
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-
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18880
50
48
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- Transformation data
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- Transform
- Transform
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-
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18928
50
49
-
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18952.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- e47c18b0-9fa8-4d6c-a3c0-d9ca99a4865e
- Cull Duplicates
- Cull Duplicates
-
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18887
180
64
-
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18919
- 1
- Points to operate on
- c862758d-3903-4936-81fe-d6730676a207
- Points
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- 08b1439d-5ab5-4767-9432-dd21bf667ba5
- 1
-
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18889
113
30
-
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- Proximity tolerance distance
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- Tolerance
- Tolerance
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- 0
-
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18919
113
30
-
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18934
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 3606ae1a-a45f-48d1-a992-4ac71a0775e4
- Points
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-
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18889
39
20
-
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- 1
- Index map of culled points
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18909
39
20
-
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18919
- 1
- Number of input points represented by this output point
- ae042c2a-c410-49ce-bd53-aa52fe251b49
- Valence
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-
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18929
39
20
-
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18939
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 5e48da67-4f4c-4f6b-899a-232a45af31c8
- Flip Matrix
- Flip Matrix
-
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18890
78
28
-
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18904
- 2
- Data matrix to flip
- 6fa3c829-5595-410c-885e-e4ec87bba766
- Data
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- e71be443-1b77-45d9-ae18-84613f8b4029
- 1
-
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18892
25
24
-
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- 2
- Flipped data matrix
- 182d589b-76e3-4b99-9fab-733f3b63b534
- Data
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-
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18892
25
24
-
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18904
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 14c26d48-70db-4b8d-a885-c903820dbcbd
- Evaluate Length
- Evaluate Length
-
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19006
149
64
-
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- Curve to evaluate
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- Curve
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- 85657344-165d-4b95-8882-7df5de611f5a
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-
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71
20
-
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- Length factor for curve evaluation
- e2d71b00-17d4-4805-ad48-2c5d2349e590
- Length
- Length
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- 0
-
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19028
71
20
-
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- 1
- 1
- {0}
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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- 0
-
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19048
71
20
-
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- 1
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- {0}
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- Point at the specified length
- 764527b5-a4ab-4375-84e1-78fdfca5bc18
- Point
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- 0
-
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19008
50
20
-
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19018
- Tangent vector at the specified length
- dac01bff-d24b-4b5d-81b8-6390f46353fc
- Tangent
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- 0
-
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19028
50
20
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- Curve parameter at the specified length
- 86533b7f-b99b-417c-89c5-7db154976f73
- Parameter
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-
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19048
50
20
-
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19058
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 455db4d3-55f1-4a45-a6c6-14452ce61cd6
- Polar Array
- Polar Array
-
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19006
210
101
-
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19057
- Base geometry
- aba03caf-73d4-462b-87a7-77fcae1169e4
- Geometry
- Geometry
- true
- 764527b5-a4ab-4375-84e1-78fdfca5bc18
- 1
-
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19008
132
20
-
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19018
- Polar array plane
- d7b9fc96-aa90-4327-bf29-df24962e56fb
- Plane
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- 0
-
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19028
132
37
-
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19046.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 06b2eedb-e668-4526-bca3-de09f0cf93e4
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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19065
132
20
-
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- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 4e358a14-df07-4921-a06d-e6243d39310b
- Angle
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- false
-
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19085
132
20
-
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19095
- 1
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- {0}
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- Arrayed geometry
- b5b94566-1972-4613-ab99-a41b4fd22467
- Geometry
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-
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19008
50
48
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19032.25
- 1
- Transformation data
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- Transform
- Transform
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-
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19056
50
49
-
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19080.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- baed7f70-ba6d-49b2-a182-9e1f41050dbb
- Cull Duplicates
- Cull Duplicates
-
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19003
180
64
-
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19035
- 1
- Points to operate on
- 773057f2-6fb9-4926-b702-2375bf405cb2
- Points
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- 4fef4eb8-0fc3-486e-9c41-26f4afe1b295
- 1
-
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19005
113
30
-
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- Proximity tolerance distance
- 5ed74f67-042e-48f6-8a09-afb04b819fde
- Tolerance
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- 0
-
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19035
113
30
-
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19050
- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Culled points
- 24b409ff-5abd-4ba7-9d16-73e6c5e16e28
- Points
- Points
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- 0
-
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19005
39
20
-
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19015
- 1
- Index map of culled points
- 290ddc15-14b9-47aa-a4ae-b3d4225cf59e
- Indices
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- 0
-
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19025
39
20
-
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19035
- 1
- Number of input points represented by this output point
- 3c5fc8b1-ebf1-47b4-9142-659c4acdc232
- Valence
- Valence
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- 0
-
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19045
39
20
-
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19055
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ee15d0c7-57af-49f4-8399-91ebb54d3fbd
- Flip Matrix
- Flip Matrix
-
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19018
78
28
-
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19032
- 2
- Data matrix to flip
- 9e6fff63-efc4-46b4-bd2f-e80500468b8b
- Data
- Data
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- b5b94566-1972-4613-ab99-a41b4fd22467
- 1
-
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19020
25
24
-
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19032
- 2
- Flipped data matrix
- 62d6ed83-3071-4687-a5e0-09c3b2be03ec
- Data
- Data
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- 0
-
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19020
25
24
-
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19032
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- Relay
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- 0aa97910-040a-4b31-a691-e832adf11984
- 1
-
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18896
40
16
-
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18904
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
- 85657344-165d-4b95-8882-7df5de611f5a
- Relay
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- 09bd24b2-9b17-46e1-bb2c-fbfcd0cef0c7
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-
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19044
40
16
-
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19052
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
- 49eeb6cb-33ad-4c36-b3da-903f4f48a3dc
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- 2
- 82e45e7a-9d1d-412d-ab28-00d4da49847b
- Group
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- Merge
- Merge a bunch of data streams
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- 5e63a198-8193-43a2-9211-a843baa5ebae
- Merge
- Merge
-
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19083
106
84
-
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19125
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
- 536bf0e9-9cc6-4b01-bc21-84aaf9ac43f0
- false
- Data 1
- D1
- true
- b355f109-25fc-4ac1-95af-11e2b44904eb
- 1
-
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19085
31
20
-
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19095
- 2
- Data stream 2
- f588e906-9559-4e3b-afce-057921253f2e
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- Data 2
- D2
- true
- 7d7e65fd-a768-498d-9278-b4230ff815a3
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-
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31
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- Data stream 3
- 3e89e829-ae01-4af2-a652-0fc8d1a41536
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- Data 3
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19125
31
20
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19135
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20032
83
20
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20042
- 1
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- Data tree to clean
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20052
83
20
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20062
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- Spotless data tree
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19992
24
80
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20032
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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19956
149
64
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19988
- Curve to evaluate
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19958
71
20
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19968
- Length factor for curve evaluation
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- Length
- Length
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-
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19978
71
20
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19988
- 1
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
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-
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19998
71
20
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20008
- 1
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- Point at the specified length
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- Point
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19958
50
20
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19968
- Tangent vector at the specified length
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19978
50
20
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19988
- Curve parameter at the specified length
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19998
50
20
-
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20008
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
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- PolyLine
- PolyLine
-
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20002
106
44
-
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20024
- 1
- Polyline vertex points
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20004
40
20
-
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20014
- Close polyline
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-
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20024
40
20
-
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20034
- 1
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- Resulting polyline
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- Polyline
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-
-8128
20004
38
40
-
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20024
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
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- f560aaac-123d-465c-8191-c1047fd222d3
- PolyLine
- PolyLine
-
-8194
20073
106
44
-
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20095
- 1
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- 1
-
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20075
40
20
-
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20085
- Close polyline
- b9854ef1-54b9-4e60-844b-4397346b7628
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- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
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20095
40
20
-
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20105
- 1
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- Resulting polyline
- 94c19071-e38a-4b13-9af9-048665b18ff3
- Polyline
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-
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20075
38
40
-
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20095
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
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-
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20030
90
64
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20062
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- Data 1
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20032
31
20
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20042
- 2
- Data stream 2
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20052
31
20
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20062
- 2
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20072
31
20
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20082
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20032
31
60
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20062
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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19956
210
101
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20007
- Base geometry
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19958
132
20
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19968
- Polar array plane
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19978
132
37
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19996.5
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0
0
0
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0
0
0
1
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- Number of elements in array.
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- Count
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20015
132
20
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20025
- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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20035
132
20
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20045
- 1
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- Arrayed geometry
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- Geometry
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19958
50
48
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19982.25
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- Transformation data
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- Transform
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20006
50
49
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20030.75
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- Cull Duplicates
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- Cull points that are coincident within tolerance
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- 93442037-38d0-4883-a028-e3db395ca18a
- Cull Duplicates
- Cull Duplicates
-
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19965
180
64
-
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19997
- 1
- Points to operate on
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- Points
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- 5bc2b19d-ee68-47a6-82eb-a318b39d70ea
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-
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19967
113
30
-
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19982
- Proximity tolerance distance
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19997
113
30
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20012
- 1
- 1
- {0}
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- Culled points
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- Points
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19967
39
20
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19977
- 1
- Index map of culled points
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19987
39
20
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19997
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- Number of input points represented by this output point
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-
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20007
39
20
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20017
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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19968
78
28
-
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19982
- 2
- Data matrix to flip
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- Data
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19970
25
24
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19982
- 2
- Flipped data matrix
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19970
25
24
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19982
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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20084
149
64
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20116
- Curve to evaluate
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20086
71
20
-
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20096
- Length factor for curve evaluation
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- Length
- Length
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- 0
-
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20106
71
20
-
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20116
- 1
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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- 0
-
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20126
71
20
-
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20136
- 1
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- Point at the specified length
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- Point
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-
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20086
50
20
-
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20096
- Tangent vector at the specified length
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- Tangent
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-
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20106
50
20
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20116
- Curve parameter at the specified length
- 26e0ff5f-501e-4993-941d-95ca9955229c
- Parameter
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-
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20126
50
20
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20136
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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20084
210
101
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20135
- Base geometry
- 2ff31a93-ec8c-468a-a25a-292730cb10fb
- Geometry
- Geometry
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- 59ed0548-dad9-4044-87cf-7f6e19440ac6
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-
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20086
132
20
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20096
- Polar array plane
- a656c790-d5b5-4f87-a651-7e130d661606
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20106
132
37
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20124.5
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-
0
0
0
1
0
0
0
1
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- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
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20143
132
20
-
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20153
- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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- false
-
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20163
132
20
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20173
- 1
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20086
50
48
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20110.25
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- Transformation data
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-
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20134
50
49
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20158.75
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
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-
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20081
180
64
-
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20113
- 1
- Points to operate on
- ecfd6858-0615-46ed-8488-18102c5e6e15
- Points
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-
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20083
113
30
-
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20098
- Proximity tolerance distance
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-
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20113
113
30
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20128
- 1
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- {0}
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- Culled points
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- Points
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-
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20083
39
20
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20093
- 1
- Index map of culled points
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-
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20103
39
20
-
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20113
- 1
- Number of input points represented by this output point
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-
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20123
39
20
-
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20133
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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-
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20096
78
28
-
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20110
- 2
- Data matrix to flip
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- Data
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-
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20098
25
24
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20110
- 2
- Flipped data matrix
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- Data
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-
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20098
25
24
-
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20110
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- Relay
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-
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19978
40
16
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19986
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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-
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20126
40
16
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20134
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
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-
255;255;255;255
- A group of Grasshopper objects
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- 2dc18481-206c-487a-8196-ae80e51e7dfb
- Group
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- Merge
- Merge a bunch of data streams
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-
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20161
106
84
-
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20203
- 4
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- Data stream 1
- 96e04837-099b-4b7a-a0dd-8ee341de2fc7
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20163
31
20
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20173
- 2
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20183
31
20
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20193
- 2
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20203
31
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20213
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20223
31
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20233
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20163
47
80
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20203
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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665
112
344
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837
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- Curve to evaluate
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Sort a list of numeric keys.
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- Sort List
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- Compute Euclidean distance between two point coordinates.
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- Distance
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- WL Code
- Evaluate Wolfram Language code
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- true
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- The Wolfram Language expression to execute
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- The link to the Wolfram Engine
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31
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5623
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31
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- Split some text into fragments using separators
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- Text Split
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49
44
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- Text to split.
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15
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6
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- A panel for custom notes and text values
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- FabiusF::usage="FabiusF[x] gives the value of the Fabius function F(x) for a non-negative real argument x.";
Macros`SetArgumentCount[FabiusF,1];
SyntaxInformation[FabiusF]={"ArgumentsPattern"->{_}};
SetAttributes[FabiusF,{NumericFunction,Listable}];
Derivative[n_Integer][FabiusF]:=2^(n (n+1)/2) FabiusF[2^n #]&
(*https://mathematica.stackexchange.com/a/13245*)
powerOfTwoQ[n_]:=IntegerQ[n]&&BitAnd[n,n-1]==0
FabiusF[Infinity]=Interval[{-1,1}];
FabiusF[x_?NumberQ]/;If[0<=Re[x]&&Im[x]==0,powerOfTwoQ[Denominator[x]],Message[FabiusF::realnn,x];False]:=iFabiusF[x]
ariasD[0]=1;
ariasD[n_Integer?Positive]:=ariasD[n]=Sum[2^((k (k-1)-n (n-1))/2) ariasD[k]/(n-k+1)!,{k,0,n-1}]/(2^n-1);
tri[x_]:=Piecewise[{{2-x,x>1}},x]
iFabiusF[x_]:=Module[{prec=Precision[x],s=1,y=0,z=SetPrecision[x,Infinity],n,p,q,tol,w},z=If[0<=z<=2,tri[z],q=Quotient[z,2];
(*can replace ThueMorse[] with the implementation in https://mathematica.stackexchange.com/a/89351*)If[ThueMorse[q]==1,s=-1];tri[z-2 q]];
tol=10^(-prec);
While[z>0,n=-Floor[RealExponent[z,2]];p=2^n;z-=1/p;w=1;
Do[w=ariasD[m]+p z w/(n-m+1);p/=2,{m,n}];
y=w-y;
If[Abs[w]<Abs[y] tol,Break[]]];
SetPrecision[s Abs[y],prec]];
ᐱ=1;
ƧS=16;
ᔓᔕ={ImageSize-> Full,AspectRatio-> 1/16,MaxRecursion->0,PlotPoints-> 1+2^(Log[ƧS]/Log[2]) };
ꗳ={Abs[FabiusF[x*2*ᐱ]]};
Plot[ꗳ,{x,0,1},Evaluate[ᔓᔕ]];
N[(Log[ƧS]/Log[2])];
StringReplace[
ToString[
Table[
N[
Evaluate[SetPrecision[SetAccuracy[ꗳ,Infinity],Infinity]]
]
,{x,Flatten[Range[0,ƧS]/ƧS]}]
,InputForm]
,{"{"-> "","}"-> ""," "-> "","*^"-> "*10^"}]
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255;255;255;255
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- 4df8df00-3635-45bd-95e6-f9206296c110
- Replace Text
- Replace all occurences of a specific text fragment with another
- true
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- true
- Replace Text
- Replace Text
- false
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5548
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- Text to operate on.
- 597504ac-2032-4b8f-a571-c44c46b116aa
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- Text
- Text
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- Fragment to replace.
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- true
- Find
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64
-
5622
-3743
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0e3d5ec1-8fa7-4002-9434-37c9a26ef80d
- true
- Gate
- Gate
- false
- 0
-
5570
-3773
40
20
-
5590
-3763
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dddb3d20-af6d-4e00-8270-25008d01bdcc
- true
- false
- Stream 0
- 0
- true
- 67a89d9d-9c53-46e9-9e3f-3e39885aabe6
- 1
-
5570
-3753
40
20
-
5590
-3743
- 2
- Input stream at index 1
- 11f89342-c3fd-4efd-8cd9-023be367ae59
- true
- false
- Stream 1
- 1
- true
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5570
-3733
40
20
-
5590
-3723
- 2
- Filtered stream
- 2e80dba7-8ea9-4746-89bb-af50ebc1a23f
- true
- false
- Stream
- S(0)
- false
- 0
-
5634
-3773
24
60
-
5646
-3743
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- daf2bda9-7f56-4f78-8ca0-4010ff8841e3
- true
- Stream Filter
- Stream Filter
-
5568
-2304
92
64
-
5622
-2272
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 3a46a533-d39a-4446-b923-8921005cb645
- true
- Gate
- Gate
- false
- 0
-
5570
-2302
40
20
-
5590
-2292
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- cdbdb7cf-4d36-4f5c-afa1-21cd4773d7e5
- true
- false
- Stream 0
- 0
- true
- 0
-
5570
-2282
40
20
-
5590
-2272
- 2
- Input stream at index 1
- 0d26362b-b98e-4fd1-9f2e-069c5b52ef3a
- true
- false
- Stream 1
- 1
- true
- 20eec82c-3638-4068-b8ec-f7754f44d1d0
- 1
-
5570
-2262
40
20
-
5590
-2252
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Filtered stream
- aa6e20b3-ed69-4615-8194-b0e2c46ede90
- true
- false
- Stream
- S(1)
- false
- 0
-
5634
-2302
24
60
-
5646
-2272
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2d1fa5b0-bc84-4c71-a356-02c3ae09bc4c
- true
- Stream Filter
- Stream Filter
-
5568
-3204
92
64
-
5622
-3172
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4263c740-37b0-49a0-abf2-6d797694626c
- true
- Gate
- Gate
- false
- 25de4f3d-bbbe-4d69-a2f8-eafb39ed11c3
- 1
-
5570
-3202
40
20
-
5590
-3192
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 403a03e8-2056-460d-811a-7288a41cfbaa
- true
- false
- Stream 0
- 0
- true
- 0
-
5570
-3182
40
20
-
5590
-3172
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Input stream at index 1
- b0bfffc4-ceeb-44e9-b31c-fb638dd0a66c
- true
- false
- Stream 1
- 1
- true
- 8e2c479f-1986-4a29-ac9c-d76908386441
- 1
-
5570
-3162
40
20
-
5590
-3152
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Filtered stream
- 7ec9447f-503b-4550-a46d-b2f1773da413
- true
- false
- Stream
- S(1)
- false
- 0
-
5634
-3202
24
60
-
5646
-3172
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- de03810f-58b7-4c2c-89d6-49cb00614695
- true
- Gate Not
- Gate Not
-
5574
-3099
80
28
-
5609
-3085
- Boolean value
- a0efc076-2674-4a8e-966a-cd6ff8b2cfb5
- true
- A
- A
- false
- 0
-
5576
-3097
21
24
-
5586.5
-3085
- 1
- 1
- {0}
- false
- Inverse of {A}
- 25de4f3d-bbbe-4d69-a2f8-eafb39ed11c3
- true
- Result
- Result
- false
- 0
-
5621
-3097
31
24
-
5636.5
-3085
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 88726205-2a30-44c4-8e25-19521cf91261
- true
- Stream Filter
- Stream Filter
-
5568
-2219
92
64
-
5622
-2187
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0b8d4ebb-ff0a-438f-873f-ac724eb994b3
- true
- Gate
- Gate
- false
- 0
-
5570
-2217
40
20
-
5590
-2207
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- e1375ca2-bad5-46e1-83e4-8bcf1f144b8e
- true
- false
- Stream 0
- 0
- true
- 0
-
5570
-2197
40
20
-
5590
-2187
- 2
- Input stream at index 1
- d7733ad1-9026-423d-8042-4e6431d6e982
- true
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- Stream 1
- 1
- true
- 051df130-9b07-4484-aee6-c11038f9920f
- 1
-
5570
-2177
40
20
-
5590
-2167
- 2
- Filtered stream
- 20eec82c-3638-4068-b8ec-f7754f44d1d0
- true
- false
- Stream
- S(1)
- false
- 0
-
5634
-2217
24
60
-
5646
-2187
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e84dba12-64d4-4086-bd66-0d891880a38b
- true
- Stream Filter
- Stream Filter
-
5568
-3038
92
64
-
5622
-3006
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- cde52939-d91f-48c0-852f-d1d931c679d1
- true
- Gate
- Gate
- false
- 0
-
5570
-3036
40
20
-
5590
-3026
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- 30fb0819-1aec-45bd-86ad-db3341956079
- true
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- Stream 0
- 0
- true
- 0
-
5570
-3016
40
20
-
5590
-3006
- 2
- Input stream at index 1
- fb00641f-71e1-43db-ad33-197aac2070b3
- true
- false
- Stream 1
- 1
- true
- 26b600f6-cf65-413e-ae98-aa04c9baea3f
- 1
-
5570
-2996
40
20
-
5590
-2986
- 2
- Filtered stream
- 8e2c479f-1986-4a29-ac9c-d76908386441
- true
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- Stream
- S(1)
- false
- 0
-
5634
-3036
24
60
-
5646
-3006
- 7a1e5fd7-b7da-4244-a261-f1da66614992
- Power of 2
- Raise 2 to the power of N.
- true
- 722c82cf-9886-4262-9816-99e5cd56678c
- true
- Power of 2
- Power of 2
-
5599
-592
49
28
-
5628
-578
- Input value
- ee9c09b1-533c-4d4a-be2d-82b761176c38
- true
- Value
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- 0
-
5601
-590
15
24
-
5608.5
-578
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 4
- Output value
- c24a11ca-4b56-465e-a295-4d23379c5a82
- true
- Result
- false
- 0
-
5640
-590
6
24
-
5643
-578
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 6dde463b-8ec4-4fed-8469-a81cead81ceb
- true
- Quick Graph
- Quick Graph
- false
- 0
- 67a89d9d-9c53-46e9-9e3f-3e39885aabe6
- 1
-
5545
-3668
150
150
-
5545.936
-3667.635
- -1
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- a13feeb8-9203-4a56-91d0-bffa77e0adec
- true
- Quick Graph
- Quick Graph
- false
- 0
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5544
-2734
150
150
-
5544.146
-2733.611
- -1
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 13394695-7838-4186-a49f-10abd5475f71
- true
- Curve
- Curve
- false
- 7fd0d788-1237-49d2-b610-14b9cdecf740
- 1
-
5856
-861
50
24
-
5881.943
-849.5875
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 293ffb2b-17b1-499c-ab83-ca4b6b12d7cc
- true
- Evaluate Length
- Evaluate Length
-
5992
-1067
158
64
-
6086
-1035
- Curve to evaluate
- cae78a03-2530-469e-8072-6dc15a29e5de
- true
- Curve
- Curve
- false
- 13394695-7838-4186-a49f-10abd5475f71
- 1
-
5994
-1065
80
20
-
6042
-1055
- Length factor for curve evaluation
- c6389f43-3849-4238-a5f7-cd2e422f9150
- (((1-X)+.25)%1)*0+X
- true
- Length
- Length
- false
- ef28f44c-dbc6-4685-a989-6732ef0bb7c2
- 1
-
5994
-1045
80
20
-
6042
-1035
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 92dc2b87-a073-4931-ae5c-34b2de2739af
- true
- Normalized
- Normalized
- false
- 0
-
5994
-1025
80
20
-
6042
-1015
- 1
- 1
- {0}
- true
- Point at the specified length
- 7591450a-f055-4d21-a585-f8ae56edcd48
- true
- Point
- Point
- false
- 0
-
6098
-1065
50
20
-
6123
-1055
- Tangent vector at the specified length
- 17858ac8-32f7-44d6-b6f8-2d508ecaa5fd
- true
- Tangent
- Tangent
- false
- 0
-
6098
-1045
50
20
-
6123
-1035
- Curve parameter at the specified length
- 49590bed-a20e-4773-8468-19bcd687b41d
- true
- Parameter
- Parameter
- false
- 0
-
6098
-1025
50
20
-
6123
-1015
- d27b55c6-9d5f-4d05-be7b-b91009aad383
- c2ea695e-1a09-6f42-266d-113498879f60
- DotDisplay
- Show points as round dots
- true
- 7eb88e78-1c37-4abe-86a2-1d9a5462c467
- true
- DotDisplay
- DotDisplay
-
6260
-1030
55
28
-
6301
-1016
- Points to display
- 1269a20e-0305-403a-89e4-6ce870afc658
- true
- Point
- Point
- false
- 7591450a-f055-4d21-a585-f8ae56edcd48
- 1
-
6262
-1028
27
24
-
6275.5
-1016
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 2b49245c-cda0-4c54-82f2-915c2c2d3104
- true
- Relay
- false
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5856
-1105
40
16
-
5876
-1097
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- a032b96c-6401-439f-b3f3-904dda76193d
- true
- Shift List
- Shift List
-
5971
-796
85
64
-
6023
-764
- 1
- List to shift
- 59903599-7e96-4aa6-bbc0-1dd19bc6b732
- true
- List
- List
- false
- 7685ddf3-078a-480f-99b7-862e703168f0
- 1
-
5973
-794
38
20
-
5992
-784
- Shift offset
- fa55991b-de79-429a-9f60-49f921ce5b6c
- true
- Shift
- Shift
- false
- 8b406b6e-1939-4eca-b757-fee45c7bdd1a
- 1
-
5973
-774
38
20
-
5992
-764
- 1
- 1
- {0}
- 1
- Wrap values
- 87a68ae4-9a06-4490-a950-0b2e160b1389
- true
- Wrap
- Wrap
- false
- 0
-
5973
-754
38
20
-
5992
-744
- 1
- 1
- {0}
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- 1
- Shifted list
- 23a6c8c0-0b37-4d13-a7e3-8809dcbe6e24
- true
- List
- List
- false
- 0
-
6035
-794
19
60
-
6044.5
-764
- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- 7763af33-af48-446f-a61a-b14eef73d6b4
- true
- Division
- Division
-
5903
-1211
85
44
-
5943
-1189
- Item to divide (dividend)
- e8d7559e-d7e9-47c0-a40f-d442f2b00caf
- true
- A
- A
- false
- 2b49245c-cda0-4c54-82f2-915c2c2d3104
- 1
-
5905
-1209
26
20
-
5918
-1199
- Item to divide with (divisor)
- 4d7f72d4-79ff-494e-9a40-70f92811487e
- true
- B
- B
- false
- 0
-
5905
-1189
26
20
-
5918
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- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- The result of the Division
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- Result
- Result
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- 0
-
5955
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31
40
-
5970.5
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- Subtraction
- Mathematical subtraction
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- true
- Subtraction
- Subtraction
-
6107
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85
44
-
6147
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- 0b42fc02-1e42-476d-82b8-58fa966fb336
- true
- A
- A
- true
- 0
-
6109
-762
26
20
-
6122
-752
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
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- 1
- Second operand for subtraction
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- true
- B
- B
- true
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- 1
-
6109
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26
20
-
6122
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- Result of subtraction
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- 0
-
6159
-762
31
40
-
6174.5
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 9ae96cdd-eee0-4568-afce-7d59699d1545
- true
- Merge
- Merge
-
6271
-905
106
64
-
6316
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- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- true
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- Data 1
- D1
- true
- 8ac10f4f-35e5-4926-b1ad-69680a469255
- 1
-
6273
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31
20
-
6288.5
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- 2
- Data stream 2
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- Data 2
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- c1a886a6-a389-4bef-92a8-675272355ed7
- 1
-
6273
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31
20
-
6288.5
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- 2
- Data stream 3
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- Data 3
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-
6273
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31
20
-
6288.5
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- Result of merge
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-
6328
-903
47
60
-
6343.5
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- 059b72b0-9bb3-4542-a805-2dcd27493164
- Cloud Display
- Draw a collection of points as a fuzzy cloud
- true
- 824f4431-dcb9-474b-a2f2-5c55348e3898
- true
- Cloud Display
- Cloud Display
- 1
-
6352
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119
64
-
6457
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- 1
- Location for each blob
- true
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- true
- 2
- Points
- Points
- true
- 7591450a-f055-4d21-a585-f8ae56edcd48
- 1
-
6354
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91
20
-
6417.5
-1055
- 1
- Colour for each blob
- ca51359a-3873-47c3-bcac-fb0729baa349
- true
- Colours
- Colours
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- 0
-
6354
-1045
91
20
-
6417.5
-1035
- 1
- 1
- {0}
-
255;0;244;124
- Size for each blob
- a73e21b3-0789-4f1e-be52-243347a3b340
- X/64
- true
- 2
- Size
- Size
- true
- 0
-
6354
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91
20
-
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101
64
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100
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237
84
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170
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92
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40
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40
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40
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92
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24
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92
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40
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92
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40
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40
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40
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92
64
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40
20
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40
20
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40
20
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24
60
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255;255;255;255
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- Filters a collection of input streams
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- Stream Filter
- Stream Filter
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92
64
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6806
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40
20
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40
20
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40
20
-
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24
60
-
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- Filters a collection of input streams
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- Stream Filter
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92
64
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40
20
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40
20
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40
20
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- Filtered stream
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24
60
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255;255;255;255
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- Stream Filter
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92
64
-
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8082
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8052
40
20
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40
20
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8092
40
20
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8052
24
60
-
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8082
- eeafc956-268e-461d-8e73-ee05c6f72c01
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92
64
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40
20
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40
20
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7955
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40
20
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24
60
-
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7955
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-
255;255;255;255
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9151
92
64
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9183
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9153
40
20
-
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9163
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40
20
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9193
40
20
-
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9153
24
60
-
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9183
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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9024
92
64
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-
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9026
40
20
-
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9036
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9046
40
20
-
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9056
- 2
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-
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9066
40
20
-
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9076
- 2
- Filtered stream
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9026
24
60
-
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9056
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Stream Filter
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-
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10310
92
64
-
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- Index of Gate stream
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-
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10312
40
20
-
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40
20
-
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- 2
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-
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10352
40
20
-
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10312
24
60
-
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10342
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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-
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10183
92
64
-
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10215
- 3
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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-
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10185
40
20
-
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10195
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-
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10205
40
20
-
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10215
- 2
- Input stream at index 1
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- true
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-
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40
20
-
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24
60
-
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10215
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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88
271
155
-
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166
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-
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90
196
20
-
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100
- An optional frame for the drawing. If blank, the shapes bounding box will be used
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-
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110
196
71
-
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145.5
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-
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181
196
20
-
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191
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- {0}
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-
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201
196
20
-
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211
- 1
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- {0}
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- An optional background color
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-
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221
196
20
-
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231
- 1
- 1
- {0}
-
0;255;255;255
- A Graphic Plus Drawing Object
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-
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90
47
75
-
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127.75
- The bounding rectangle
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-
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165
47
76
-
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203.25
- eeafc956-268e-461d-8e73-ee05c6f72c01
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92
64
-
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- 1
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- Index of Gate stream
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- Gate
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-
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40
20
-
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40
20
-
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- 2
- Input stream at index 1
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- true
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40
20
-
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- 2
- Filtered stream
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24
60
-
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11521
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 6aca94d8-afdf-4e43-9aec-6c6b8d8bd741
- Stream Filter
- Stream Filter
-
-11187
11362
92
64
-
-11133
11394
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 98509d08-f026-438c-b89f-2eb6ec90cb1a
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11185
11364
40
20
-
-11165
11374
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- bf002089-c5b9-4416-9f6c-5fe17fd01f1e
- false
- Stream 0
- 0
- true
- 0
-
-11185
11384
40
20
-
-11165
11394
- 2
- Input stream at index 1
- a56bdc29-a764-4fb7-a967-e87314bc4dd0
- false
- Stream 1
- 1
- true
- 0375c488-e806-4ad1-a086-2da4152bef10
- 1
-
-11185
11404
40
20
-
-11165
11414
- 2
- Filtered stream
- 6a68f77b-051c-4818-852a-84702d6a3fcb
- false
- Stream
- S(0)
- false
- 0
-
-11121
11364
24
60
-
-11109
11394
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fa81a8b4-cf5f-45a2-87c3-3995dfc08e89
- 6aca94d8-afdf-4e43-9aec-6c6b8d8bd741
- 2
- 14b30f5b-f7e1-48df-a27f-19c0ea0559a6
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2afd3edb-d771-40ba-9e12-ae84a3d2c52b
- Stream Filter
- Stream Filter
-
-11227
12608
92
64
-
-11173
12640
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- ce0052fb-c8b6-402a-bccf-0ecc6ebf441c
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
12610
40
20
-
-11205
12620
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dc35d3b8-24b9-4476-aa26-4045c6111021
- false
- Stream 0
- 0
- true
- 0
-
-11225
12630
40
20
-
-11205
12640
- 2
- Input stream at index 1
- 42c2fd41-52b1-46a2-b9eb-39d5d4b30ba9
- false
- Stream 1
- 1
- true
- 0f7d41df-0b88-413c-bf09-4b93aebfd26f
- 1
-
-11225
12650
40
20
-
-11205
12660
- 2
- Filtered stream
- c275b6a1-118d-4ab6-9708-51c158efd69c
- false
- Stream
- S(0)
- false
- 0
-
-11161
12610
24
60
-
-11149
12640
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 97dc2833-b406-498f-8847-89d4d247ff99
- Stream Filter
- Stream Filter
-
-11227
12481
92
64
-
-11173
12513
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f67731f9-a091-40ee-aac8-252fde956cc9
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
12483
40
20
-
-11205
12493
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 664f2c9c-c93a-4673-b7c2-0db2519483c4
- false
- Stream 0
- 0
- true
- 0
-
-11225
12503
40
20
-
-11205
12513
- 2
- Input stream at index 1
- 2a419803-185f-4277-895c-31b5e3a9ab90
- false
- Stream 1
- 1
- true
- 360e3c71-f39a-4344-9b0b-f76f6040e9a5
- 1
-
-11225
12523
40
20
-
-11205
12533
- 2
- Filtered stream
- f71f118e-dff3-449b-8eb8-77a6b5272af6
- false
- Stream
- S(0)
- false
- 0
-
-11161
12483
24
60
-
-11149
12513
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 2afd3edb-d771-40ba-9e12-ae84a3d2c52b
- 97dc2833-b406-498f-8847-89d4d247ff99
- 2
- 7fe95677-b648-4e7c-af60-2ac98b6280e5
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- c319f1fd-9a2f-4e3e-b41a-462b6183ff1f
- Stream Filter
- Stream Filter
-
-11227
13778
92
64
-
-11173
13810
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c744c5fd-cb6e-4fef-8386-ddde37a92a96
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
13780
40
20
-
-11205
13790
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- bc4c971e-516e-458d-9bd8-d9e361610a32
- false
- Stream 0
- 0
- true
- 0
-
-11225
13800
40
20
-
-11205
13810
- 2
- Input stream at index 1
- 49be4b2e-7253-4819-a896-eca1a5b70d13
- false
- Stream 1
- 1
- true
- 68ed2259-a880-4020-a4fa-5102d6548b24
- 1
-
-11225
13820
40
20
-
-11205
13830
- 2
- Filtered stream
- 27bc95ad-0ae8-4000-9aff-03a94c23bb45
- false
- Stream
- S(0)
- false
- 0
-
-11161
13780
24
60
-
-11149
13810
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b23a953e-f5fe-490d-b4e1-4836f77bf220
- Stream Filter
- Stream Filter
-
-11227
13651
92
64
-
-11173
13683
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 2b1b6ad2-d1bc-4881-bdc4-6b4113ab2662
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
13653
40
20
-
-11205
13663
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 6f575b6a-e190-4cac-aaeb-3ba7716f3380
- false
- Stream 0
- 0
- true
- 0
-
-11225
13673
40
20
-
-11205
13683
- 2
- Input stream at index 1
- dccef9cf-5d4b-443b-be87-4160cd59f0f9
- false
- Stream 1
- 1
- true
- 609b5d6e-7b75-4e1a-8a12-faf652c3c682
- 1
-
-11225
13693
40
20
-
-11205
13703
- 2
- Filtered stream
- d3e6f2a9-2986-4d0e-9d6d-14be9dfd713f
- false
- Stream
- S(0)
- false
- 0
-
-11161
13653
24
60
-
-11149
13683
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- c319f1fd-9a2f-4e3e-b41a-462b6183ff1f
- b23a953e-f5fe-490d-b4e1-4836f77bf220
- 2
- f2403d64-acca-4fec-8df9-48668cb8aada
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 21885950-be69-465c-9d96-960f153c1764
- Stream Filter
- Stream Filter
-
-11227
14883
92
64
-
-11173
14915
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- e55bda3b-8bbe-4404-9461-64492dce29bb
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
14885
40
20
-
-11205
14895
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 5aa6f597-e792-4a71-975e-df7a2cd6a126
- false
- Stream 0
- 0
- true
- 0
-
-11225
14905
40
20
-
-11205
14915
- 2
- Input stream at index 1
- bceaa58d-d972-4d19-8468-d1e80f9fb6ef
- false
- Stream 1
- 1
- true
- 0ba93922-a608-4ac3-8ad6-de58e4e01a8f
- 1
-
-11225
14925
40
20
-
-11205
14935
- 2
- Filtered stream
- 367d9c37-ecf5-4adb-a85a-2bdcd57e2092
- false
- Stream
- S(0)
- false
- 0
-
-11161
14885
24
60
-
-11149
14915
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 269cc0bb-67ab-43ed-a590-db3e7b6ab08f
- Stream Filter
- Stream Filter
-
-11227
14756
92
64
-
-11173
14788
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4dc57c65-7ba5-4cd5-a06e-202a19c48e94
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
14758
40
20
-
-11205
14768
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- ee9327d4-ebf1-4450-8c01-edff53e474b5
- false
- Stream 0
- 0
- true
- 0
-
-11225
14778
40
20
-
-11205
14788
- 2
- Input stream at index 1
- 2c4e6896-5d80-416c-a893-d11cea4c865d
- false
- Stream 1
- 1
- true
- 589e948c-d0d2-4b05-9c56-6855d5c435b4
- 1
-
-11225
14798
40
20
-
-11205
14808
- 2
- Filtered stream
- a6314d11-f0d5-419c-bc82-24c2862d0c35
- false
- Stream
- S(0)
- false
- 0
-
-11161
14758
24
60
-
-11149
14788
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 21885950-be69-465c-9d96-960f153c1764
- 269cc0bb-67ab-43ed-a590-db3e7b6ab08f
- 2
- b718a122-9098-4399-a42f-a974dc783cd7
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a740a9fc-8b55-4c5c-a871-f76e1efb3a41
- Stream Filter
- Stream Filter
-
-11227
15907
92
64
-
-11173
15939
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 1bac5d72-7374-401e-bbea-792f52769d0f
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
15909
40
20
-
-11205
15919
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 7fdefbf2-2487-451b-99fe-444e9f9a1b96
- false
- Stream 0
- 0
- true
- 0
-
-11225
15929
40
20
-
-11205
15939
- 2
- Input stream at index 1
- ecac3ee8-866c-4c84-adc9-06193c3e68a8
- false
- Stream 1
- 1
- true
- 11ceca9b-30b2-4213-b35d-85e5be45643a
- 1
-
-11225
15949
40
20
-
-11205
15959
- 2
- Filtered stream
- c0cb4ede-8eab-4fd5-9c53-b62df174b453
- false
- Stream
- S(0)
- false
- 0
-
-11161
15909
24
60
-
-11149
15939
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 074a7f4a-bb6e-4134-9cbd-8a3674cd6458
- Stream Filter
- Stream Filter
-
-11227
15780
92
64
-
-11173
15812
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 21e3aca0-77dd-499a-99b5-265b7782e734
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
15782
40
20
-
-11205
15792
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 1c62efb8-aa5e-432e-a3ce-d919a2e82c28
- false
- Stream 0
- 0
- true
- 0
-
-11225
15802
40
20
-
-11205
15812
- 2
- Input stream at index 1
- 84fe6fe7-3c54-4b99-a392-fae62be28538
- false
- Stream 1
- 1
- true
- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- 1
-
-11225
15822
40
20
-
-11205
15832
- 2
- Filtered stream
- bec1d112-916e-46f3-aec4-8d3439e35c7f
- false
- Stream
- S(0)
- false
- 0
-
-11161
15782
24
60
-
-11149
15812
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a740a9fc-8b55-4c5c-a871-f76e1efb3a41
- 074a7f4a-bb6e-4134-9cbd-8a3674cd6458
- 2
- d0cbf364-bbd3-443f-baf9-ddf9faa06c95
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ca8ca783-f945-428f-a2f3-e0f01c9d6b16
- Stream Filter
- Stream Filter
-
-11227
17087
92
64
-
-11173
17119
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 90ecef0b-9236-441c-a23f-6a5ab3009534
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
17089
40
20
-
-11205
17099
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- f0caa3d9-32b1-4924-902e-592380384fda
- false
- Stream 0
- 0
- true
- 0
-
-11225
17109
40
20
-
-11205
17119
- 2
- Input stream at index 1
- e2dae74c-9f51-441d-a4fb-3cd6933b04c7
- false
- Stream 1
- 1
- true
- 29946d34-0db3-4cc0-bbb0-27c79f7c8eb9
- 1
-
-11225
17129
40
20
-
-11205
17139
- 2
- Filtered stream
- c1a066d8-bd60-41c5-aa56-6f9a6e46db6f
- false
- Stream
- S(0)
- false
- 0
-
-11161
17089
24
60
-
-11149
17119
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 5a1f7027-0875-4c99-9a72-e52c18b199e4
- Stream Filter
- Stream Filter
-
-11227
16960
92
64
-
-11173
16992
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- b6110d43-b2e8-4417-b027-d4c7f9597bc7
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
16962
40
20
-
-11205
16972
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 9560843a-4de3-4059-a942-481ddeac3fbb
- false
- Stream 0
- 0
- true
- 0
-
-11225
16982
40
20
-
-11205
16992
- 2
- Input stream at index 1
- 800847d4-b720-4cb9-97f6-f12f98eb114e
- false
- Stream 1
- 1
- true
- 2f545125-747a-4904-9cb7-05bc0727e11d
- 1
-
-11225
17002
40
20
-
-11205
17012
- 2
- Filtered stream
- 5f27d6a1-8003-43a4-bbbb-1f5ca0d473f0
- false
- Stream
- S(0)
- false
- 0
-
-11161
16962
24
60
-
-11149
16992
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- ca8ca783-f945-428f-a2f3-e0f01c9d6b16
- 5a1f7027-0875-4c99-9a72-e52c18b199e4
- 2
- 1c15b9f5-09dc-4725-ac96-59ef9df1e148
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 677fd46b-d68b-4325-99d3-40ba2c3fc641
- Stream Filter
- Stream Filter
-
-11227
18184
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35
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35
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26
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116
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116
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- Preserve direction of input curves
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53
20
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- Joined curves and individual curves that could not be joined.
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35
40
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- Extract the end points of a curve.
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- Curve to evaluate
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- Curve start point
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26
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- Curve end point
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26
20
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- Create a polyline connecting a number of points.
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- PolyLine
- PolyLine
-
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10674
116
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50
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- Close polyline
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50
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- Resulting polyline
- a88ea8e4-8dc1-49ff-88c5-bfcffa9ffd98
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38
40
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10696
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- Create a polyline connecting a number of points.
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- PolyLine
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-
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10742
116
44
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50
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- Close polyline
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50
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- Resulting polyline
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10744
38
40
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
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-
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10663
90
64
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- Data 1
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31
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31
60
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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90
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- Data stream 1
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- Data 1
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31
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- Data stream 2
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31
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31
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- Result of merge
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31
60
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- Relay
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40
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- Stroke
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196
104
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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136
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- The stroke color
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10670
136
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- The stroke weight
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136
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136
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- The shape to be used at the end of open path
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136
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32
100
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135
84
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- Remove null items from the tree.
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10606
83
20
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- Remove invalid items from the tree.
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10626
83
20
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10636
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- Remove empty branches from the tree.
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-
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10646
83
20
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10656
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- Data tree to clean
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83
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- Spotless data tree
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24
80
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- A group of Grasshopper objects
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- Group
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223
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6
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610
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- Merge
- Merge a bunch of data streams
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126
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67
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67
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67
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31
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166
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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90
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- The solid fill Color
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90
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255;255;0;255
- A Graphic Plus Shape Object
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48
40
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11771
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116
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53
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- Preserve direction of input curves
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11710
53
20
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11720
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- Joined curves and individual curves that could not be joined.
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11690
35
40
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11710
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- Extract the end points of a curve.
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11779
84
44
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- Curve to evaluate
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30
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- Curve start point
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26
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- Curve end point
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11801
26
20
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11811
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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116
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- Polyline vertex points
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11737
50
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- Close polyline
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11757
50
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- Resulting polyline
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11737
38
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-
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11757
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
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11803
116
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11805
50
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- Close polyline
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11825
50
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11835
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- Resulting polyline
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11805
38
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11825
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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90
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136
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136
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83
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- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6999
10609
40
20
-
-6979
10619
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- d877597c-2f26-4a27-b4fc-6235f9374e04
- false
- Stream 0
- 0
- true
- 0
-
-6999
10629
40
20
-
-6979
10639
- 2
- Input stream at index 1
- 04ea4ce4-b469-43fb-974a-e3deda460b53
- false
- Stream 1
- 1
- true
- 83090ea2-cf17-4a67-8116-52ffd5b88d8f
- 1
-
-6999
10649
40
20
-
-6979
10659
- 2
- Filtered stream
- e0d9dc3c-a861-43f9-91f6-3db048f151b6
- false
- Stream
- S(0)
- false
- 0
-
-6935
10609
24
60
-
-6923
10639
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 5bd7e8d1-8354-4393-a409-e505ccf86e90
- Stream Filter
- Stream Filter
-
-7077
11677
92
64
-
-7023
11709
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 99af0755-0d84-453a-a8f0-15a402ce3130
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7075
11679
40
20
-
-7055
11689
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 381db23c-40f2-4021-afd3-85010a193c00
- false
- Stream 0
- 0
- true
- 0
-
-7075
11699
40
20
-
-7055
11709
- 2
- Input stream at index 1
- f24880ec-3c8b-4ef8-8553-fadec6b85d96
- false
- Stream 1
- 1
- true
- c6e722f2-92b0-4558-beb1-fba620419e63
- 1
-
-7075
11719
40
20
-
-7055
11729
- 2
- Filtered stream
- aeb61ff0-bd0a-4098-9475-efec72c7673e
- false
- Stream
- S(0)
- false
- 0
-
-7011
11679
24
60
-
-6999
11709
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- f0e96c3f-e779-44a4-9862-315edd179c43
- Stream Filter
- Stream Filter
-
-7017
12915
92
64
-
-6963
12947
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 1e78bad0-2df3-443c-b14f-9b6f48e3a96d
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7015
12917
40
20
-
-6995
12927
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 29b9ee40-fa7c-434a-8169-183398e57a15
- false
- Stream 0
- 0
- true
- 0
-
-7015
12937
40
20
-
-6995
12947
- 2
- Input stream at index 1
- 47b12ec4-d344-4d33-b2d9-05e633a6fdca
- false
- Stream 1
- 1
- true
- 27e7c501-931a-4323-ba95-c1dcd8638c1d
- 1
-
-7015
12957
40
20
-
-6995
12967
- 2
- Filtered stream
- 4b0cab58-d257-4fb7-b9a9-1b04f696e2d2
- false
- Stream
- S(0)
- false
- 0
-
-6951
12917
24
60
-
-6939
12947
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b017d256-9aa7-4060-98d9-5e784a0a7cd9
- Stream Filter
- Stream Filter
-
-6997
14088
92
64
-
-6943
14120
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 451ee843-75ac-4d73-998b-164ece4342a3
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6995
14090
40
20
-
-6975
14100
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- cfcf9154-9cae-495b-a03b-6698625fad23
- false
- Stream 0
- 0
- true
- 0
-
-6995
14110
40
20
-
-6975
14120
- 2
- Input stream at index 1
- ceb29de5-b1a3-4559-8146-d37078b28f88
- false
- Stream 1
- 1
- true
- 87166262-f90e-4df6-bfdc-8d5ff0afe20e
- 1
-
-6995
14130
40
20
-
-6975
14140
- 2
- Filtered stream
- 5c35a26d-0d9c-4676-a3af-c45b854148ca
- false
- Stream
- S(0)
- false
- 0
-
-6931
14090
24
60
-
-6919
14120
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b664df6a-5160-42e7-87b8-af9f0ea1ee2b
- Stream Filter
- Stream Filter
-
-7012
15164
92
64
-
-6958
15196
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 9213edc5-888d-469e-aee2-74bad8a0a83d
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7010
15166
40
20
-
-6990
15176
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 0b82203c-37e3-4e34-a3b8-904d9d892742
- false
- Stream 0
- 0
- true
- 0
-
-7010
15186
40
20
-
-6990
15196
- 2
- Input stream at index 1
- f8052ad8-4ad0-41de-a504-d9e881240d73
- false
- Stream 1
- 1
- true
- 55a9b8da-f51b-46f7-9956-1cfce98363c7
- 1
-
-7010
15206
40
20
-
-6990
15216
- 2
- Filtered stream
- d9c00061-44f3-4e23-ba0c-cc1b7e5671df
- false
- Stream
- S(0)
- false
- 0
-
-6946
15166
24
60
-
-6934
15196
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4704d271-59ce-4af9-94e5-1a62eceb5448
- Stream Filter
- Stream Filter
-
-6953
16167
92
64
-
-6899
16199
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 97f7d4c6-2d9f-497c-bfe7-9b442195f935
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6951
16169
40
20
-
-6931
16179
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 8014dc77-ab2a-45db-86b8-56d8e2730d32
- false
- Stream 0
- 0
- true
- 0
-
-6951
16189
40
20
-
-6931
16199
- 2
- Input stream at index 1
- 0e3e51de-66ab-4127-b872-4ef8c2ef2b67
- false
- Stream 1
- 1
- true
- 1149d574-8501-435b-a0b2-df2ba22f96e8
- 1
-
-6951
16209
40
20
-
-6931
16219
- 2
- Filtered stream
- 45c7a574-b387-4fe3-ae3e-00a14add492e
- false
- Stream
- S(0)
- false
- 0
-
-6887
16169
24
60
-
-6875
16199
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 94d38037-9a7a-4ac3-a117-fac9adb58793
- Stream Filter
- Stream Filter
-
-6962
17296
92
64
-
-6908
17328
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0ad6ae3a-a3a2-4866-b3e0-f27eac6c76a3
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6960
17298
40
20
-
-6940
17308
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 40d0ebce-b00e-4be8-aaf8-1eb5645b63d0
- false
- Stream 0
- 0
- true
- 0
-
-6960
17318
40
20
-
-6940
17328
- 2
- Input stream at index 1
- 98d5a932-b282-41b4-8424-cc6528fc2c5c
- false
- Stream 1
- 1
- true
- be615a1b-b5ca-456f-9216-7ca55cad191c
- 1
-
-6960
17338
40
20
-
-6940
17348
- 2
- Filtered stream
- e232eef0-15de-49e4-b844-a2a662441091
- false
- Stream
- S(0)
- false
- 0
-
-6896
17298
24
60
-
-6884
17328
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ae977cc2-007b-4819-aab1-607bc574da3d
- Stream Filter
- Stream Filter
-
-6908
18452
92
64
-
-6854
18484
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4ee2ac55-a2ce-4aa3-a2c4-3ae4de5c9a12
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6906
18454
40
20
-
-6886
18464
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 2f671999-2df2-49bd-a78a-0968fb4e4704
- false
- Stream 0
- 0
- true
- 0
-
-6906
18474
40
20
-
-6886
18484
- 2
- Input stream at index 1
- 43ec97a6-501d-4840-b451-153ff951bf39
- false
- Stream 1
- 1
- true
- 424c8d2f-e0fa-482b-81a1-f7c2a6375ff5
- 1
-
-6906
18494
40
20
-
-6886
18504
- 2
- Filtered stream
- 6cf5bfc7-cc33-45ca-add3-e4f38a61d380
- false
- Stream
- S(0)
- false
- 0
-
-6842
18454
24
60
-
-6830
18484
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 40d0d220-c1df-41fe-a4ac-5d725e326324
- Stream Filter
- Stream Filter
-
-6871
19591
92
64
-
-6817
19623
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 915699c1-b62b-42ae-90b0-0885d42ed97d
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6869
19593
40
20
-
-6849
19603
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 64c59ebc-ffa2-49d1-8621-423b5b4f03a6
- false
- Stream 0
- 0
- true
- 0
-
-6869
19613
40
20
-
-6849
19623
- 2
- Input stream at index 1
- 286cdb93-f769-441f-a32f-c56ca6656fde
- false
- Stream 1
- 1
- true
- df097d69-a4f5-4ef7-ab1f-1a0727ff6f06
- 1
-
-6869
19633
40
20
-
-6849
19643
- 2
- Filtered stream
- 7c3b70d3-ffab-4356-a42b-31da084be03a
- false
- Stream
- S(0)
- false
- 0
-
-6805
19593
24
60
-
-6793
19623
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 38e33091-5805-4830-b960-f7b95e820fd2
- 1
- a1ac0900-3dd8-44d2-860f-83352b920fda
- Group
- ᗱᗴ
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 87daaa5c-75e3-464f-ac08-f6f513799ccb
- Panel
- #
- false
- 0
- 0
- 1024
-
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156
160
100
- 0
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- 0
-
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156.4436
-
255;255;255;255
- true
- true
- true
- false
- false
- true
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- e2d5421d-793a-4786-9e3b-7530f182e59f
- Number
- Number
- false
- 0
-
-4530
86
49
24
-
-4498.137
98.35362
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 1e42e4ee-225b-427d-95a0-827d03bae077
- Panel
- ⊚
- false
- 0
- e7c315e7-6046-4360-a3b1-dc1f18620e40
- 1
-
-3906
779
147
55
- 0
- 0
- 0
-
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779.59
- 2
-
255;255;255;255
- false
- false
- true
- false
- false
- true
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 35cc33c8-2ec6-4de4-82f7-cbdc643d1827
- Null Item
- Null Item
-
-7093
11580
128
64
-
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11612
- Item to test
- a17212d0-4c05-4c33-8e3d-389e5333f6de
- Item
- Item
- true
- c6e722f2-92b0-4558-beb1-fba620419e63
- 1
-
-7091
11582
24
60
-
-7079
11612
- True if item is Null
- 24b97ec9-2c74-4757-aca7-87fb8d388365
- 1
- Null Flags
- Null Flags
- false
- 0
-
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11582
76
20
-
-7013
11592
- True if item is Invalid
- bf5046cf-2155-4f6e-aa97-c7c55ce87f98
- Invalid Flags
- Invalid Flags
- false
- 0
-
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11602
76
20
-
-7013
11612
- A textual description of the object state
- a10398c8-44c9-4840-97e2-4a47e8b317c9
- Description
- Description
- false
- 0
-
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11622
76
20
-
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11632
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 72339650-e0db-4bb9-9c0e-29a807d12cb2
- Min / Max
- Min / Max
-
-6929
11580
115
44
-
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11602
- 1
- Set of Numbers
- c79128a8-a368-42d7-bc90-4b4dc2419210
- Number
- Number
- false
- 24b97ec9-2c74-4757-aca7-87fb8d388365
- 1
-
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11582
39
40
-
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11602
- Minimum
- 3043b375-5d68-4163-b9ad-80de0cb16839
- Minimum
- Minimum
- false
- 0
-
-6864
11582
48
20
-
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11592
- Maximum
- 907cc860-6b5a-4cb7-95ec-26a204048c14
- Maximum
- Maximum
- false
- 0
-
-6864
11602
48
20
-
-6840
11612
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- bf0f2a74-6bf4-4cf8-a0a2-02cb0de8c4fe
- Gate Not
- Gate Not
-
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11584
70
28
-
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11598
- Boolean value
- 0ab56caa-5df1-45c9-88c6-79cf55870520
- A
- A
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- 1
-
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11586
11
24
-
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11598
- Inverse of {A}
- 25111c3d-21ca-4ffb-afd0-0f0c756e1d39
- Result
- Result
- false
- 0
-
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11586
31
24
-
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11598
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- f1109cf8-3e0b-4391-afe5-5fcd61c8a0de
- Stream Filter
- Stream Filter
-
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11719
92
64
-
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11751
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 91ab83a0-f6c5-46ec-b2e7-1d708acac6ab
- Gate
- Gate
- false
- 25111c3d-21ca-4ffb-afd0-0f0c756e1d39
- 1
-
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11721
40
20
-
-5555
11731
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 4ef35a03-9705-4eb0-9f68-1816dc541ae1
- false
- Stream 0
- 0
- true
- 0
-
-5575
11741
40
20
-
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11751
- 2
- Input stream at index 1
- 2bba781c-6a7b-4152-a92f-e9f1714f5686
- false
- Stream 1
- 1
- true
- 0f119f9f-261b-4425-b9ac-cb6a8fa58f56
- 1
-
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11761
40
20
-
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11771
- 2
- Filtered stream
- fa4bc97d-3c82-4a5a-8b8b-dd5445560a7c
- false
- Stream
- S(0)
- false
- 0
-
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11721
24
60
-
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11751
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 3f2325cf-9510-4d9c-b4b7-a3f70c723cd9
- Null Item
- Null Item
-
-7747
2953
128
64
-
-7709
2985
- Item to test
- e61d4284-20de-4b87-9616-b0ae87afc3d0
- Item
- Item
- true
- d040adbf-b17a-4020-beba-bdab4bcf43d5
- 1
-
-7745
2955
24
60
-
-7733
2985
- True if item is Null
- a70c3c9f-2f96-442b-beec-394a2663079b
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7697
2955
76
20
-
-7667
2965
- True if item is Invalid
- 4513738e-8338-47f0-8028-43fc37ad03ba
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7697
2975
76
20
-
-7667
2985
- A textual description of the object state
- 9127bce0-f88e-4b9b-8325-b682b0d2be9a
- Description
- Description
- false
- 0
-
-7697
2995
76
20
-
-7667
3005
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 4013bb1a-8a06-4b2a-a77a-11ec68c8c8bb
- Min / Max
- Min / Max
-
-7597
2943
115
44
-
-7544
2965
- 1
- Set of Numbers
- d09b6ab3-e05e-43ef-beb3-af650ad843fa
- Number
- Number
- false
- a70c3c9f-2f96-442b-beec-394a2663079b
- 1
-
-7595
2945
39
40
-
-7575.5
2965
- Minimum
- 330c5023-18e8-4911-af46-8bb9d7a1fdf4
- Minimum
- Minimum
- false
- 0
-
-7532
2945
48
20
-
-7508
2955
- Maximum
- 0b1b7c6e-4ca1-4bcd-b0f9-21d2409f20bd
- Maximum
- Maximum
- false
- 0
-
-7532
2965
48
20
-
-7508
2975
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 189dd2a9-82f7-49c4-878c-0e52bb36583f
- Gate Not
- Gate Not
-
-7459
2961
70
28
-
-7434
2975
- Boolean value
- 901f909c-7bb2-417a-97ff-4963637a9801
- A
- A
- false
- 0b1b7c6e-4ca1-4bcd-b0f9-21d2409f20bd
- 1
-
-7457
2963
11
24
-
-7451.5
2975
- Inverse of {A}
- 538bcd17-2e47-46da-b7c8-d30390ab8c9c
- Result
- Result
- false
- 0
-
-7422
2963
31
24
-
-7406.5
2975
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ac4eb0e1-0629-423d-86d3-698fe1fbe3be
- Stream Filter
- Stream Filter
-
-5795
2997
92
64
-
-5741
3029
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 33978c7b-0a2d-46eb-b2d9-63c16f7a391c
- Gate
- Gate
- false
- 538bcd17-2e47-46da-b7c8-d30390ab8c9c
- 1
-
-5793
2999
40
20
-
-5773
3009
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- e146e615-c617-4312-a7d2-08ee2a1b3ab3
- false
- Stream 0
- 0
- true
- 0
-
-5793
3019
40
20
-
-5773
3029
- 2
- Input stream at index 1
- 64d60379-b575-4112-bc03-90d913bcd4c1
- false
- Stream 1
- 1
- true
- cc39f9f6-c9c7-4df2-b57d-b44bce6c64c0
- 1
-
-5793
3039
40
20
-
-5773
3049
- 2
- Filtered stream
- 75fc82ae-e535-43d8-8cea-21b2a580a62e
- false
- Stream
- S(1)
- false
- 0
-
-5729
2999
24
60
-
-5717
3029
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- a8094a18-bafe-447f-a1e5-d50f443f6c8d
- Null Item
- Null Item
-
-7219
3929
128
64
-
-7181
3961
- Item to test
- 82a62292-6bc5-47d6-b336-1369d94ba43a
- Item
- Item
- true
- bf02b6a7-2c32-4838-9324-0fa547efef5e
- 1
-
-7217
3931
24
60
-
-7205
3961
- True if item is Null
- c3a4ae0a-d5e9-483b-a4dc-2ea16ff547d4
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7169
3931
76
20
-
-7139
3941
- True if item is Invalid
- 86d204a4-ec45-4555-ad20-960e96e72291
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7169
3951
76
20
-
-7139
3961
- A textual description of the object state
- 1a0611c8-0f02-4920-bb42-ecae33d37518
- Description
- Description
- false
- 0
-
-7169
3971
76
20
-
-7139
3981
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- be452c49-8669-4366-becd-7b6bb0edf3ce
- Min / Max
- Min / Max
-
-7055
3929
115
44
-
-7002
3951
- 1
- Set of Numbers
- fe9cc553-c348-415d-a674-35ca07f8cb3f
- Number
- Number
- false
- c3a4ae0a-d5e9-483b-a4dc-2ea16ff547d4
- 1
-
-7053
3931
39
40
-
-7033.5
3951
- Minimum
- 8208d769-9be0-477f-8940-4b5859bf4c22
- Minimum
- Minimum
- false
- 0
-
-6990
3931
48
20
-
-6966
3941
- Maximum
- d598ed14-f257-4d9b-a5f3-99946b1fbb4d
- Maximum
- Maximum
- false
- 0
-
-6990
3951
48
20
-
-6966
3961
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- d646942a-7636-44c6-98e1-f72444dfd831
- Gate Not
- Gate Not
-
-6904
3933
70
28
-
-6879
3947
- Boolean value
- 8ab5f103-6967-4002-8173-15d9a6fe2d8e
- A
- A
- false
- d598ed14-f257-4d9b-a5f3-99946b1fbb4d
- 1
-
-6902
3935
11
24
-
-6896.5
3947
- Inverse of {A}
- 5fa81d7b-ae98-4e4a-bfdb-9ada698cf631
- Result
- Result
- false
- 0
-
-6867
3935
31
24
-
-6851.5
3947
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2df6c65e-08c7-4660-9cc8-f4a18301d889
- Stream Filter
- Stream Filter
-
-5777
3985
92
64
-
-5723
4017
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 16406ef3-d8bd-4150-be29-dead03773ad7
- Gate
- Gate
- false
- 5fa81d7b-ae98-4e4a-bfdb-9ada698cf631
- 1
-
-5775
3987
40
20
-
-5755
3997
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 93e1a8fc-06ec-42ce-b0ab-e189211ba4d3
- false
- Stream 0
- 0
- true
- 0
-
-5775
4007
40
20
-
-5755
4017
- 2
- Input stream at index 1
- 120144d8-961e-4ffc-87b7-f4de9a43fe62
- false
- Stream 1
- 1
- true
- b67db8b0-4ac4-430d-be27-39be205c7d61
- 1
-
-5775
4027
40
20
-
-5755
4037
- 2
- Filtered stream
- 9fcffae3-3a3f-4651-a205-1f89243e9353
- false
- Stream
- S(1)
- false
- 0
-
-5711
3987
24
60
-
-5699
4017
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- d7f3135f-1177-4b0f-8b05-6ce46940feb4
- Null Item
- Null Item
-
-7147
4863
128
64
-
-7109
4895
- Item to test
- 7a5e3346-84c6-4356-96e0-47a3a51f957e
- Item
- Item
- true
- 9aa9fdf5-c248-4bf6-afe3-b324ca007251
- 1
-
-7145
4865
24
60
-
-7133
4895
- True if item is Null
- 53617fcd-cb0c-43ea-a0e9-9a35a5ee4099
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7097
4865
76
20
-
-7067
4875
- True if item is Invalid
- b78284f8-37d3-4341-ad05-89a04047fe05
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7097
4885
76
20
-
-7067
4895
- A textual description of the object state
- 058b65a1-c2e5-4625-8df7-3570ebf8e99f
- Description
- Description
- false
- 0
-
-7097
4905
76
20
-
-7067
4915
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 00ceb525-9e87-4db3-9802-667580ba1078
- Min / Max
- Min / Max
-
-6983
4863
115
44
-
-6930
4885
- 1
- Set of Numbers
- c3315609-f58f-4506-b8ef-5b499ee91f26
- Number
- Number
- false
- 53617fcd-cb0c-43ea-a0e9-9a35a5ee4099
- 1
-
-6981
4865
39
40
-
-6961.5
4885
- Minimum
- 6eecbe0a-786e-4500-9023-e0036260ce84
- Minimum
- Minimum
- false
- 0
-
-6918
4865
48
20
-
-6894
4875
- Maximum
- 93be164d-631d-4706-aaa0-61f1c643d2e6
- Maximum
- Maximum
- false
- 0
-
-6918
4885
48
20
-
-6894
4895
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- f3c88c5d-9ab5-4a48-8e2b-b86ef9537f38
- Gate Not
- Gate Not
-
-6832
4867
70
28
-
-6807
4881
- Boolean value
- 9af6d155-d97a-4a53-a1e5-d55dcbf2dca3
- A
- A
- false
- 93be164d-631d-4706-aaa0-61f1c643d2e6
- 1
-
-6830
4869
11
24
-
-6824.5
4881
- Inverse of {A}
- fbb890a1-5183-4102-944f-95013c6261bd
- Result
- Result
- false
- 0
-
-6795
4869
31
24
-
-6779.5
4881
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 17755101-7062-42de-ba3b-de5fe2af1944
- Stream Filter
- Stream Filter
-
-5677
4913
92
64
-
-5623
4945
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f49fe484-3cfc-47b0-aadd-80e2434a514a
- Gate
- Gate
- false
- fbb890a1-5183-4102-944f-95013c6261bd
- 1
-
-5675
4915
40
20
-
-5655
4925
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- b0223655-9b78-4e47-ace1-2cc5ed775f3a
- false
- Stream 0
- 0
- true
- 0
-
-5675
4935
40
20
-
-5655
4945
- 2
- Input stream at index 1
- e1e8c4b5-f1e0-4114-a673-f363d5af642c
- false
- Stream 1
- 1
- true
- 25d8da2c-a18b-475a-87f0-e332861fb3b3
- 1
-
-5675
4955
40
20
-
-5655
4965
- 2
- Filtered stream
- e49badfa-457c-44b7-a041-d1654e42fc37
- false
- Stream
- S(1)
- false
- 0
-
-5611
4915
24
60
-
-5599
4945
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 6cb3cdab-825d-4a25-b6d7-c8ce93e6b860
- Null Item
- Null Item
-
-7063
5875
128
64
-
-7025
5907
- Item to test
- 05d22590-dfa4-487b-b9fc-40746c5187e9
- Item
- Item
- true
- 14273b4c-e52e-48ca-b8ab-682e73fe2600
- 1
-
-7061
5877
24
60
-
-7049
5907
- True if item is Null
- 9f954724-61fd-4f30-bf3b-5be741d2ad38
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7013
5877
76
20
-
-6983
5887
- True if item is Invalid
- e5ac74b2-2304-49c2-ab3b-e514ffb5d702
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7013
5897
76
20
-
-6983
5907
- A textual description of the object state
- 3f775720-99c8-4d87-8082-1a114e50fb73
- Description
- Description
- false
- 0
-
-7013
5917
76
20
-
-6983
5927
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 072e65b2-2f5a-4a67-ba98-de57ff321e0a
- Min / Max
- Min / Max
-
-6899
5875
115
44
-
-6846
5897
- 1
- Set of Numbers
- 3ee8b196-b2a7-43bd-87fa-c9d70c55996f
- Number
- Number
- false
- 9f954724-61fd-4f30-bf3b-5be741d2ad38
- 1
-
-6897
5877
39
40
-
-6877.5
5897
- Minimum
- f4b55248-208f-4228-ab11-054e59d08b2a
- Minimum
- Minimum
- false
- 0
-
-6834
5877
48
20
-
-6810
5887
- Maximum
- e4b0b066-26b0-448e-a5c8-f4e5c3b4bcc8
- Maximum
- Maximum
- false
- 0
-
-6834
5897
48
20
-
-6810
5907
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 01823b6f-3915-46e2-bb6c-45ee2f0b1d75
- Gate Not
- Gate Not
-
-6748
5879
70
28
-
-6723
5893
- Boolean value
- 0927c3b9-4aa8-43e1-9078-1096f8ec3895
- A
- A
- false
- e4b0b066-26b0-448e-a5c8-f4e5c3b4bcc8
- 1
-
-6746
5881
11
24
-
-6740.5
5893
- Inverse of {A}
- d3d8423d-b76c-460e-8176-3ebcb3be397d
- Result
- Result
- false
- 0
-
-6711
5881
31
24
-
-6695.5
5893
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 87135cf1-b079-4cb3-bf64-3722c5ca823e
- Stream Filter
- Stream Filter
-
-5593
5925
92
64
-
-5539
5957
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 204e91b7-8b54-469d-8ad1-fb4ff58123c3
- Gate
- Gate
- false
- d3d8423d-b76c-460e-8176-3ebcb3be397d
- 1
-
-5591
5927
40
20
-
-5571
5937
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 453b8df4-ff60-46ce-88f0-6efb394b4562
- false
- Stream 0
- 0
- true
- 0
-
-5591
5947
40
20
-
-5571
5957
- 2
- Input stream at index 1
- 3b3e7dd0-c139-49fb-a308-7abf58d2d736
- false
- Stream 1
- 1
- true
- 51de33f0-e511-4a37-8537-cce5e8deb152
- 1
-
-5591
5967
40
20
-
-5571
5977
- 2
- Filtered stream
- e9c7e654-d046-48b6-9a42-23807c78b8a8
- false
- Stream
- S(1)
- false
- 0
-
-5527
5927
24
60
-
-5515
5957
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 4f25cec0-7e3f-43b9-a363-1b7cd2747a9f
- Null Item
- Null Item
-
-7060
7022
128
64
-
-7022
7054
- Item to test
- f993cfcd-d680-46b8-a928-2bfb242ea0d7
- Item
- Item
- true
- 43c898bd-1523-42e9-9485-b3cd42382016
- 1
-
-7058
7024
24
60
-
-7046
7054
- True if item is Null
- 71caca59-5a1d-4b88-9d15-ba7633f6f69a
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7010
7024
76
20
-
-6980
7034
- True if item is Invalid
- dfc56233-4395-44f5-be6e-afcaff8f8714
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7010
7044
76
20
-
-6980
7054
- A textual description of the object state
- 3b681b16-66d2-4e3b-b309-b5b35b58583d
- Description
- Description
- false
- 0
-
-7010
7064
76
20
-
-6980
7074
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 4bec467c-e348-430f-a67d-ad4288ebf902
- Min / Max
- Min / Max
-
-6896
7022
115
44
-
-6843
7044
- 1
- Set of Numbers
- 3bb95461-355d-431f-b4d5-6a0dcee3139d
- Number
- Number
- false
- 71caca59-5a1d-4b88-9d15-ba7633f6f69a
- 1
-
-6894
7024
39
40
-
-6874.5
7044
- Minimum
- 1fd4fb0a-fd07-4924-a15e-e0cb43abe349
- Minimum
- Minimum
- false
- 0
-
-6831
7024
48
20
-
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7034
- Maximum
- 1a36e77a-f207-41a8-8a48-ef7fb3367cdd
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-
-6831
7044
48
20
-
-6807
7054
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- a97852d9-a598-4352-8c86-7221c33fc96a
- Gate Not
- Gate Not
-
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7026
70
28
-
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7040
- Boolean value
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- A
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- 1a36e77a-f207-41a8-8a48-ef7fb3367cdd
- 1
-
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7028
11
24
-
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7040
- Inverse of {A}
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- Result
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- 0
-
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7028
31
24
-
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7040
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2c24899b-2b57-4192-8893-96e535b58ccd
- Stream Filter
- Stream Filter
-
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7082
92
64
-
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7114
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Index of Gate stream
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- Gate
- Gate
- false
- d7a5e523-7978-46d0-9ffe-8254a2b71250
- 1
-
-5535
7084
40
20
-
-5515
7094
- 1
- 1
- {0}
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- Input stream at index 0
- a2af7d81-1e5d-4c0c-931d-b7e2fbf931c8
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- Stream 0
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-
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7104
40
20
-
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7114
- 2
- Input stream at index 1
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- false
- Stream 1
- 1
- true
- 6c97f623-62c8-4828-a8bf-06f573b3a0c5
- 1
-
-5535
7124
40
20
-
-5515
7134
- 2
- Filtered stream
- 2188b720-4c97-42ae-9fcb-7e1a982bad49
- false
- Stream
- S(1)
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- 0
-
-5471
7084
24
60
-
-5459
7114
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 37488903-bcf2-4b36-a4bf-5cc30a0b9a3c
- Null Item
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-
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8147
128
64
-
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8179
- Item to test
- 525d82a8-491f-434d-a0a1-6246a0a543db
- Item
- Item
- true
- 5bc7a3d5-b08a-4185-93b3-ed22b830d52b
- 1
-
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8149
24
60
-
-7068
8179
- True if item is Null
- ddaf865a-6a4f-4207-8f3b-9c3d651c3962
- 1
- Null Flags
- Null Flags
- false
- 0
-
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8149
76
20
-
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8159
- True if item is Invalid
- 7665f0dc-1418-4dc5-8995-e4ea104a0578
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7032
8169
76
20
-
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8179
- A textual description of the object state
- 0f3fb516-7a33-40f7-8a9d-b275f97d5e0a
- Description
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-
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8189
76
20
-
-7002
8199
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 85ad36ee-61e0-44af-961f-930419003d84
- Min / Max
- Min / Max
-
-6918
8147
115
44
-
-6865
8169
- 1
- Set of Numbers
- 77ad5e58-68af-4019-a7c0-ede669fa6eb4
- Number
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- false
- ddaf865a-6a4f-4207-8f3b-9c3d651c3962
- 1
-
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8149
39
40
-
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8169
- Minimum
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- Minimum
- Minimum
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- 0
-
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8149
48
20
-
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8159
- Maximum
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- Maximum
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- 0
-
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8169
48
20
-
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8179
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- ab5ce525-5bd9-49a2-a408-5d8a2814337b
- Gate Not
- Gate Not
-
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8151
70
28
-
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8165
- Boolean value
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- A
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- a6df61a9-5d42-4b23-8a4f-5b3b2a19750d
- 1
-
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8153
11
24
-
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8165
- Inverse of {A}
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- Result
- Result
- false
- 0
-
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8153
31
24
-
-6714.5
8165
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 204e7fe9-7a7e-479a-b489-4892b355619f
- Stream Filter
- Stream Filter
-
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8207
92
64
-
-5505
8239
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
- b16f4576-fb27-4f10-9fe6-0e4da0596c1a
- 1
-
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8209
40
20
-
-5537
8219
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 83bd125d-6fc5-42ce-9201-07e195f5a9a0
- false
- Stream 0
- 0
- true
- 0
-
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8229
40
20
-
-5537
8239
- 2
- Input stream at index 1
- 8789779f-0f56-4994-8d3a-befb8c2533dc
- false
- Stream 1
- 1
- true
- 04d3379a-0378-4c82-ae41-61eb01f18331
- 1
-
-5557
8249
40
20
-
-5537
8259
- 2
- Filtered stream
- 7d5a3f05-11af-425b-82e5-419e541ce9a6
- false
- Stream
- S(1)
- false
- 0
-
-5493
8209
24
60
-
-5481
8239
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 2c8bcb43-7b73-46d0-96e4-219adbe7c087
- Null Item
- Null Item
-
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9353
128
64
-
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9385
- Item to test
- 6eeec69a-a1d4-4858-898f-e498b382e12b
- Item
- Item
- true
- 183384e9-0dcf-4b35-adf3-b86f942908d0
- 1
-
-7063
9355
24
60
-
-7051
9385
- True if item is Null
- 2b4a67fb-ae7c-4ba1-bc65-027125293f34
- 1
- Null Flags
- Null Flags
- false
- 0
-
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9355
76
20
-
-6985
9365
- True if item is Invalid
- 0d2c0dc8-f3ea-431e-9788-c6837d202db8
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7015
9375
76
20
-
-6985
9385
- A textual description of the object state
- bdb6013c-1541-4765-a267-1cf5d8d4a3ad
- Description
- Description
- false
- 0
-
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9395
76
20
-
-6985
9405
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- d7f23d19-54d1-4799-831a-57a3a7ec8ba4
- Min / Max
- Min / Max
-
-6901
9353
115
44
-
-6848
9375
- 1
- Set of Numbers
- 7dbcddeb-55b6-416d-a06e-76e11fb3c1cd
- Number
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- false
- 2b4a67fb-ae7c-4ba1-bc65-027125293f34
- 1
-
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9355
39
40
-
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9375
- Minimum
- fbdd786e-1ab7-417e-a127-b398583e8ed3
- Minimum
- Minimum
- false
- 0
-
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9355
48
20
-
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9365
- Maximum
- 8eea0321-eced-40bb-ab55-6bed6726c9ba
- Maximum
- Maximum
- false
- 0
-
-6836
9375
48
20
-
-6812
9385
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 8cd4a1d2-ace0-4a5e-b868-df7b83f2402a
- Gate Not
- Gate Not
-
-6750
9357
70
28
-
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9371
- Boolean value
- d753f1c2-cfd4-47e6-96c0-0234fa1a2988
- A
- A
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- 8eea0321-eced-40bb-ab55-6bed6726c9ba
- 1
-
-6748
9359
11
24
-
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9371
- Inverse of {A}
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- Result
- Result
- false
- 0
-
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9359
31
24
-
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9371
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ccbe8cdf-717b-4b38-a4b0-d2265f7b5b4d
- Stream Filter
- Stream Filter
-
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9413
92
64
-
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9445
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- cf8f1d40-481a-4a0f-b880-52074d3f28d5
- Gate
- Gate
- false
- f95d28f9-5c1b-4737-880d-d56ef8853fd9
- 1
-
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9415
40
20
-
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9425
- 1
- 1
- {0}
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- Input stream at index 0
- 893def05-ac6b-49ca-9d84-5f626fe4fcf6
- false
- Stream 0
- 0
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- 0
-
-5540
9435
40
20
-
-5520
9445
- 2
- Input stream at index 1
- 4ae4fde1-8026-4227-ba5d-04b145dbda87
- false
- Stream 1
- 1
- true
- ad549466-4ec2-4830-aced-c029153ed38a
- 1
-
-5540
9455
40
20
-
-5520
9465
- 2
- Filtered stream
- ce57a692-0419-4a89-a644-041b170de089
- false
- Stream
- S(1)
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- 0
-
-5476
9415
24
60
-
-5464
9445
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- ef845926-e270-4238-9c31-7826bcd7dc35
- Null Item
- Null Item
-
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10521
128
64
-
-6985
10553
- Item to test
- 26cdc6fc-da24-482d-9fc1-0a8bde92164c
- Item
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- true
- 83090ea2-cf17-4a67-8116-52ffd5b88d8f
- 1
-
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10523
24
60
-
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10553
- True if item is Null
- f24a96ec-f551-424d-b26a-072846e268de
- 1
- Null Flags
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- 0
-
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10523
76
20
-
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10533
- True if item is Invalid
- 0663b653-456a-4146-93ca-64ca58e64262
- Invalid Flags
- Invalid Flags
- false
- 0
-
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10543
76
20
-
-6943
10553
- A textual description of the object state
- f8cb1f09-78c3-4b9f-94af-5b7bb63e1fb9
- Description
- Description
- false
- 0
-
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10563
76
20
-
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10573
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- bfeb3fd9-9103-4fd0-95ac-022b5a5f48c1
- Min / Max
- Min / Max
-
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10521
115
44
-
-6806
10543
- 1
- Set of Numbers
- e6f63a9c-2422-4f1b-ab10-3931a44cbea1
- Number
- Number
- false
- f24a96ec-f551-424d-b26a-072846e268de
- 1
-
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10523
39
40
-
-6837.5
10543
- Minimum
- ea7d8250-db50-42c3-b883-81505d9a4d09
- Minimum
- Minimum
- false
- 0
-
-6794
10523
48
20
-
-6770
10533
- Maximum
- 5a85cc1f-6412-43ab-9da8-073b8bf971a4
- Maximum
- Maximum
- false
- 0
-
-6794
10543
48
20
-
-6770
10553
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 192df5d3-f93a-4aef-a40e-cbad90f6d75b
- Gate Not
- Gate Not
-
-6708
10525
70
28
-
-6683
10539
- Boolean value
- 1505cf56-234b-45ad-bc75-ef43fab88efb
- A
- A
- false
- 5a85cc1f-6412-43ab-9da8-073b8bf971a4
- 1
-
-6706
10527
11
24
-
-6700.5
10539
- Inverse of {A}
- 6aa859da-faad-431e-8679-ca71bf8af6fe
- Result
- Result
- false
- 0
-
-6671
10527
31
24
-
-6655.5
10539
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 25c75de0-e074-469e-af87-ed42c1e4189a
- Stream Filter
- Stream Filter
-
-5500
10581
92
64
-
-5446
10613
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c9427943-f9a8-4d48-8a43-7797e98aa96a
- Gate
- Gate
- false
- 6aa859da-faad-431e-8679-ca71bf8af6fe
- 1
-
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10583
40
20
-
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10593
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 7a2c1e3d-a216-4034-9974-967db57e4d3f
- false
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- 0
- true
- 0
-
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10603
40
20
-
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10613
- 2
- Input stream at index 1
- 9979f7c5-ee42-4ff1-91fe-d3b6929249b4
- false
- Stream 1
- 1
- true
- 0de2eaa7-c2bc-4cbc-b548-271df3bcf16a
- 1
-
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10623
40
20
-
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10633
- 2
- Filtered stream
- ba724b87-59f4-42c1-b032-80d0e7a043b6
- false
- Stream
- S(1)
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- 0
-
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10583
24
60
-
-5422
10613
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 6fe9ab0f-7fbf-4f24-b49d-8304568d8891
- Null Item
- Null Item
-
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12802
128
64
-
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12834
- Item to test
- 0657d3b2-41e9-4609-9ab0-562af0750fc2
- Item
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- 27e7c501-931a-4323-ba95-c1dcd8638c1d
- 1
-
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12804
24
60
-
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12834
- True if item is Null
- 82ba3565-15cc-43a6-bdb7-bb0c8ae0ea70
- 1
- Null Flags
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- false
- 0
-
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12804
76
20
-
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12814
- True if item is Invalid
- c11ab35c-f6a2-455a-a926-c8fae612bbfd
- Invalid Flags
- Invalid Flags
- false
- 0
-
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12824
76
20
-
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12834
- A textual description of the object state
- e42c47ed-b240-43f9-8c39-4fc406defff3
- Description
- Description
- false
- 0
-
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12844
76
20
-
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12854
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- a5b1c0c0-ed53-4928-9e19-8b13e166f8f5
- Min / Max
- Min / Max
-
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12802
115
44
-
-6836
12824
- 1
- Set of Numbers
- 23cdb5f2-8684-4c36-8b48-513a3f5fe399
- Number
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- false
- 82ba3565-15cc-43a6-bdb7-bb0c8ae0ea70
- 1
-
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12804
39
40
-
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12824
- Minimum
- a6a165b8-0196-4899-85c2-2530b99211c8
- Minimum
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- false
- 0
-
-6824
12804
48
20
-
-6800
12814
- Maximum
- 95d42b9f-4d49-4210-81a8-27c77c8defdb
- Maximum
- Maximum
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- 0
-
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12824
48
20
-
-6800
12834
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- f7ba651d-d70d-496b-a389-a5b02e0b590b
- Gate Not
- Gate Not
-
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12806
70
28
-
-6713
12820
- Boolean value
- 84082a0b-436f-4eff-9826-68e040df03b5
- A
- A
- false
- 95d42b9f-4d49-4210-81a8-27c77c8defdb
- 1
-
-6736
12808
11
24
-
-6730.5
12820
- Inverse of {A}
- 7e03e96a-60c3-44b8-8508-4a0249f6e5a0
- Result
- Result
- false
- 0
-
-6701
12808
31
24
-
-6685.5
12820
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- d7bbe7be-7e27-4e12-8d82-e69c3c3513bb
- Stream Filter
- Stream Filter
-
-5530
12862
92
64
-
-5476
12894
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 406127bb-7c1f-41d0-8cb8-dcbdb5d6ffe8
- Gate
- Gate
- false
- 7e03e96a-60c3-44b8-8508-4a0249f6e5a0
- 1
-
-5528
12864
40
20
-
-5508
12874
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 606a32c4-23ff-47c3-9b3e-eed9a14b7088
- false
- Stream 0
- 0
- true
- 0
-
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12884
40
20
-
-5508
12894
- 2
- Input stream at index 1
- 74a2c323-ef25-41bc-8530-9c13e7708302
- false
- Stream 1
- 1
- true
- 1bebc86d-5784-4955-910d-2d5169d1baac
- 1
-
-5528
12904
40
20
-
-5508
12914
- 2
- Filtered stream
- e53053d4-d564-44a6-beee-0050818b6f00
- false
- Stream
- S(0)
- false
- 0
-
-5464
12864
24
60
-
-5452
12894
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- ee7da382-815b-415a-9861-1675753f8b17
- Null Item
- Null Item
-
-7016
13991
128
64
-
-6978
14023
- Item to test
- c4b9f8a6-2632-4dff-9be8-b7e2d47fa350
- Item
- Item
- true
- 87166262-f90e-4df6-bfdc-8d5ff0afe20e
- 1
-
-7014
13993
24
60
-
-7002
14023
- True if item is Null
- 1648d712-ddcb-484f-86a6-3bf455dc71bf
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6966
13993
76
20
-
-6936
14003
- True if item is Invalid
- 46a8e847-c729-4b2b-a671-abcb1f8f1882
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6966
14013
76
20
-
-6936
14023
- A textual description of the object state
- 58a3745f-6e95-4031-9372-871e1a3230e4
- Description
- Description
- false
- 0
-
-6966
14033
76
20
-
-6936
14043
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 2c4de2de-7fd1-4247-920b-e4e4d985f902
- Min / Max
- Min / Max
-
-6852
13991
115
44
-
-6799
14013
- 1
- Set of Numbers
- a3dbc77a-bf20-4311-b2ed-f205798a4147
- Number
- Number
- false
- 1648d712-ddcb-484f-86a6-3bf455dc71bf
- 1
-
-6850
13993
39
40
-
-6830.5
14013
- Minimum
- 644f30e6-cd45-4fa5-bcb1-d2f3ec0088c0
- Minimum
- Minimum
- false
- 0
-
-6787
13993
48
20
-
-6763
14003
- Maximum
- f554aac2-085e-4c30-b33b-9feebb9269ae
- Maximum
- Maximum
- false
- 0
-
-6787
14013
48
20
-
-6763
14023
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 869a7ab1-6d37-4602-997f-d7610372f50e
- Gate Not
- Gate Not
-
-6701
13995
70
28
-
-6676
14009
- Boolean value
- 32e3041b-5ee5-409a-b83f-7f221bf3158f
- A
- A
- false
- f554aac2-085e-4c30-b33b-9feebb9269ae
- 1
-
-6699
13997
11
24
-
-6693.5
14009
- Inverse of {A}
- f5241e2f-e3b9-4b92-a0a2-bb5535a30bc5
- Result
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- false
- 0
-
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13997
31
24
-
-6648.5
14009
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2dc62a4f-fa9a-4d00-9304-565cbbb21053
- Stream Filter
- Stream Filter
-
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14054
92
64
-
-5383
14086
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f9a060e6-874f-4dc4-a2a6-f1c341a55364
- Gate
- Gate
- false
- f5241e2f-e3b9-4b92-a0a2-bb5535a30bc5
- 1
-
-5435
14056
40
20
-
-5415
14066
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- a3bbb5c5-ecca-4e4a-88e8-6a12ec936b83
- false
- Stream 0
- 0
- true
- 0
-
-5435
14076
40
20
-
-5415
14086
- 2
- Input stream at index 1
- 62df6a11-051f-4b24-9ace-aa4802a9bda6
- false
- Stream 1
- 1
- true
- 429f2160-9c55-4489-9f07-6fc421633a0f
- 1
-
-5435
14096
40
20
-
-5415
14106
- 2
- Filtered stream
- 371e8722-687f-4b56-97c4-03bfd4ba7a21
- false
- Stream
- S(0)
- false
- 0
-
-5371
14056
24
60
-
-5359
14086
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- bc8a43f9-69f8-416a-97c3-5e6fb9733f5e
- Null Item
- Null Item
-
-7036
15064
128
64
-
-6998
15096
- Item to test
- 0ea97718-8927-4b3b-b427-e9da7cd6e334
- Item
- Item
- true
- 55a9b8da-f51b-46f7-9956-1cfce98363c7
- 1
-
-7034
15066
24
60
-
-7022
15096
- True if item is Null
- c72b0ed7-9c5d-47da-a98f-4953bbef1271
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6986
15066
76
20
-
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15076
- True if item is Invalid
- a1cf6f25-d078-429b-9e50-5d148274fe7b
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6986
15086
76
20
-
-6956
15096
- A textual description of the object state
- 7accc688-6afc-4a9b-8d14-e2ce628d350e
- Description
- Description
- false
- 0
-
-6986
15106
76
20
-
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15116
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- acfba1bb-b50c-4af6-a793-334e02358a94
- Min / Max
- Min / Max
-
-6872
15064
115
44
-
-6819
15086
- 1
- Set of Numbers
- 7304bb6d-12d4-4be8-9f55-d2a0ee349bc6
- Number
- Number
- false
- c72b0ed7-9c5d-47da-a98f-4953bbef1271
- 1
-
-6870
15066
39
40
-
-6850.5
15086
- Minimum
- e705aece-6cd6-4c26-9f72-1b586d5c7a5e
- Minimum
- Minimum
- false
- 0
-
-6807
15066
48
20
-
-6783
15076
- Maximum
- 0b7e60b9-9058-4d68-80e5-3d388446894a
- Maximum
- Maximum
- false
- 0
-
-6807
15086
48
20
-
-6783
15096
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 1b86b70a-3104-4e2b-9ea8-e7b621f91e72
- Gate Not
- Gate Not
-
-6721
15068
70
28
-
-6696
15082
- Boolean value
- 143deb72-368b-4a20-bf86-6ab0afed5bcb
- A
- A
- false
- 0b7e60b9-9058-4d68-80e5-3d388446894a
- 1
-
-6719
15070
11
24
-
-6713.5
15082
- Inverse of {A}
- 1cc96b60-6c9d-4b5a-952b-d87e0f026373
- Result
- Result
- false
- 0
-
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15070
31
24
-
-6668.5
15082
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 7a50b3ba-d956-42c7-85ae-020294238131
- Stream Filter
- Stream Filter
-
-5377
15051
92
64
-
-5323
15083
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 6c3c0a55-54ee-48bc-933d-5f10e406781f
- Gate
- Gate
- false
- 1cc96b60-6c9d-4b5a-952b-d87e0f026373
- 1
-
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15053
40
20
-
-5355
15063
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- afb7c341-6a0d-49ee-9fe7-8bfe8897afe5
- false
- Stream 0
- 0
- true
- 0
-
-5375
15073
40
20
-
-5355
15083
- 2
- Input stream at index 1
- eab2eb72-06e3-4ad5-b3a5-80d0b1552cfd
- false
- Stream 1
- 1
- true
- 498b7dc4-3bbe-40d4-94f3-8a7fd2ddd8cb
- 1
-
-5375
15093
40
20
-
-5355
15103
- 2
- Filtered stream
- 7be70df7-f6d7-45a4-acba-b061356bcd53
- false
- Stream
- S(0)
- false
- 0
-
-5311
15053
24
60
-
-5299
15083
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 69a6a8b7-8a4c-461d-a8e3-38b25f1090de
- Null Item
- Null Item
-
-6974
16069
128
64
-
-6936
16101
- Item to test
- 8e171002-c9c5-40fa-94a1-1001311e625d
- Item
- Item
- true
- 1149d574-8501-435b-a0b2-df2ba22f96e8
- 1
-
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16071
24
60
-
-6960
16101
- True if item is Null
- d86c8275-c6b6-49f3-8e58-8b6a74aacae9
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6924
16071
76
20
-
-6894
16081
- True if item is Invalid
- f3ff0523-ef2a-4496-9a34-d44373395db9
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6924
16091
76
20
-
-6894
16101
- A textual description of the object state
- b75efb85-ddd2-4c87-9141-e5f4c1331f1e
- Description
- Description
- false
- 0
-
-6924
16111
76
20
-
-6894
16121
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- df4df02e-61f8-4247-b4ae-e627c2119ddb
- Min / Max
- Min / Max
-
-6810
16069
115
44
-
-6757
16091
- 1
- Set of Numbers
- 180b7c54-6a7e-486f-9082-88a8b1879e13
- Number
- Number
- false
- d86c8275-c6b6-49f3-8e58-8b6a74aacae9
- 1
-
-6808
16071
39
40
-
-6788.5
16091
- Minimum
- dc5521b1-348f-45e2-815d-692347349b5c
- Minimum
- Minimum
- false
- 0
-
-6745
16071
48
20
-
-6721
16081
- Maximum
- 51b0ebbf-b611-45ce-9ca3-e7db982d471a
- Maximum
- Maximum
- false
- 0
-
-6745
16091
48
20
-
-6721
16101
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 4d572279-4b57-4ccb-9b17-4cf6a61cddfb
- Gate Not
- Gate Not
-
-6659
16073
70
28
-
-6634
16087
- Boolean value
- db135412-13b1-494a-9e44-f2a298e2a893
- A
- A
- false
- 51b0ebbf-b611-45ce-9ca3-e7db982d471a
- 1
-
-6657
16075
11
24
-
-6651.5
16087
- Inverse of {A}
- e5221d87-c7c5-441c-b2a0-f5d656b5e19f
- Result
- Result
- false
- 0
-
-6622
16075
31
24
-
-6606.5
16087
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 8c75690a-9909-4a23-b4bd-03ea933c5c1b
- Stream Filter
- Stream Filter
-
-5315
16056
92
64
-
-5261
16088
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4b34dd7b-a876-46ea-bcee-2d2e42db6605
- Gate
- Gate
- false
- e5221d87-c7c5-441c-b2a0-f5d656b5e19f
- 1
-
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16058
40
20
-
-5293
16068
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 8e44a545-9b16-42f4-a5bf-929298a5975b
- false
- Stream 0
- 0
- true
- 0
-
-5313
16078
40
20
-
-5293
16088
- 2
- Input stream at index 1
- a8e94b10-1280-48b2-8c43-a75c4c94a665
- false
- Stream 1
- 1
- true
- 17cd7088-f1b9-4fd0-a76a-67c8e527f68b
- 1
-
-5313
16098
40
20
-
-5293
16108
- 2
- Filtered stream
- ff5ee03c-6fb6-4999-ba11-3c9add44a863
- false
- Stream
- S(0)
- false
- 0
-
-5249
16058
24
60
-
-5237
16088
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- a3813988-9a7d-44cb-bb48-1e51bfd8122c
- Null Item
- Null Item
-
-6991
17200
128
64
-
-6953
17232
- Item to test
- 02fb06c2-1fc1-4719-a1c0-19e6f6320810
- Item
- Item
- true
- be615a1b-b5ca-456f-9216-7ca55cad191c
- 1
-
-6989
17202
24
60
-
-6977
17232
- True if item is Null
- 54d595a2-8560-4ac7-b251-1c1614234d33
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6941
17202
76
20
-
-6911
17212
- True if item is Invalid
- 3ca9f52a-60ea-41dd-8091-248edad96e5b
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6941
17222
76
20
-
-6911
17232
- A textual description of the object state
- 248cb7c4-9def-47e7-a8b6-793822c6f00d
- Description
- Description
- false
- 0
-
-6941
17242
76
20
-
-6911
17252
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 595f90c7-3ca3-4d10-8958-7f8fa2e74a29
- Min / Max
- Min / Max
-
-6827
17200
115
44
-
-6774
17222
- 1
- Set of Numbers
- 32637777-e83c-4c23-b669-258135f86f6d
- Number
- Number
- false
- 54d595a2-8560-4ac7-b251-1c1614234d33
- 1
-
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17202
39
40
-
-6805.5
17222
- Minimum
- 00364658-7a30-463d-9002-9917505e5b1a
- Minimum
- Minimum
- false
- 0
-
-6762
17202
48
20
-
-6738
17212
- Maximum
- 26c41fcb-0fcc-4ec1-9bd4-79abb98e013c
- Maximum
- Maximum
- false
- 0
-
-6762
17222
48
20
-
-6738
17232
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 3b77b2f4-e654-4020-829d-ef86cca75bcf
- Gate Not
- Gate Not
-
-6676
17204
70
28
-
-6651
17218
- Boolean value
- e6521ab1-bd41-4cfc-81e4-9e57473d1419
- A
- A
- false
- 26c41fcb-0fcc-4ec1-9bd4-79abb98e013c
- 1
-
-6674
17206
11
24
-
-6668.5
17218
- Inverse of {A}
- 56f940ac-dac3-4e7c-ae76-4c5d06f6a203
- Result
- Result
- false
- 0
-
-6639
17206
31
24
-
-6623.5
17218
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4ed3b515-31a0-4a8a-ac08-7a94b811e048
- Stream Filter
- Stream Filter
-
-5332
17187
92
64
-
-5278
17219
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- b677065e-0f8e-4e53-838f-96e373aa2f38
- Gate
- Gate
- false
- 56f940ac-dac3-4e7c-ae76-4c5d06f6a203
- 1
-
-5330
17189
40
20
-
-5310
17199
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 0463558b-f3ba-4e8e-9375-4a54ed58ee17
- false
- Stream 0
- 0
- true
- 0
-
-5330
17209
40
20
-
-5310
17219
- 2
- Input stream at index 1
- fbebdd51-24e2-4e04-8bad-2a46a7d9649c
- false
- Stream 1
- 1
- true
- a9429e5a-d32c-4087-b07f-09998c87b547
- 1
-
-5330
17229
40
20
-
-5310
17239
- 2
- Filtered stream
- 659efc47-65df-4ea8-8eae-843b8943b7ff
- false
- Stream
- S(0)
- false
- 0
-
-5266
17189
24
60
-
-5254
17219
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- b579c9d7-271d-457f-bd33-499bb0a04854
- Null Item
- Null Item
-
-6952
18329
128
64
-
-6914
18361
- Item to test
- bcb8b65d-4922-46cf-956d-7c4a16ea0146
- Item
- Item
- true
- 424c8d2f-e0fa-482b-81a1-f7c2a6375ff5
- 1
-
-6950
18331
24
60
-
-6938
18361
- True if item is Null
- 06fb23ec-2d77-4414-bf96-2c966bd4481f
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6902
18331
76
20
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6423
24
40
-
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6443
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77
64
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6373
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6343
25
20
-
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6353
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25
20
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25
20
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6343
24
60
-
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6373
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- Group
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
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6582
94
44
-
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6604
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- Data tree to flatten
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- Tree
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6584
42
20
-
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6594
- Path of flattened tree
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6604
42
20
-
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6614
- 1
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- Flattened data tree
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-
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6584
24
40
-
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6604
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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6502
77
64
-
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6534
- 3
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- Gate
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6504
25
20
-
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6514
- 1
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6524
25
20
-
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- 2
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6544
25
20
-
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- 2
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6504
24
60
-
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6534
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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7682
94
44
-
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7704
- 2
- Data tree to flatten
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- Tree
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7684
42
20
-
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7694
- Path of flattened tree
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- Path
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-
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7704
42
20
-
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7714
- 1
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- Flattened data tree
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- Tree
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-
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7684
24
40
-
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7704
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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7602
77
64
-
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7634
- 3
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- Gate
- Gate
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-
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7604
25
20
-
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7614
- 1
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- Input stream at index 0
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- true
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- 1
-
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7624
25
20
-
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- 2
- Input stream at index 1
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-
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7644
25
20
-
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- 2
- Filtered stream
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- Stream
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-
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7604
24
60
-
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7634
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten Tree
- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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7849
94
44
-
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7871
- 2
- Data tree to flatten
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- Tree
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-
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7851
42
20
-
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7861
- Path of flattened tree
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- Path
- Path
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-
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7871
42
20
-
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7881
- 1
- 1
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- Flattened data tree
- 5f78256b-d668-4c53-9536-b4be29f63afc
- Tree
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-
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7851
24
40
-
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7871
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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7769
77
64
-
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7801
- 3
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- Index of Gate stream
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- Gate
- Gate
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-
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7771
25
20
-
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7781
- 1
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- Input stream at index 0
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- true
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-
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7791
25
20
-
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7801
- 2
- Input stream at index 1
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- true
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- 1
-
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7811
25
20
-
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7821
- 2
- Filtered stream
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- false
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- 0
-
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7771
24
60
-
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7801
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten Tree
- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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8821
94
44
-
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8843
- 2
- Data tree to flatten
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-
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8823
42
20
-
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8833
- Path of flattened tree
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- Path
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-
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8843
42
20
-
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8853
- 1
- 1
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- Flattened data tree
- e80b7bae-86c9-4814-bb58-3252f354450f
- Tree
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-
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8823
24
40
-
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8843
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- a733ee46-1c61-4182-881c-58059fd0c75e
- Stream Filter
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-
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8741
77
64
-
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8773
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
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- 1
-
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8743
25
20
-
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8753
- 1
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- Input stream at index 0
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- false
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- 0
- true
- 5401c540-5198-42b3-87b3-f345cc7cd369
- 1
-
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8763
25
20
-
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8773
- 2
- Input stream at index 1
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- false
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- 1
- true
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- 1
-
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8783
25
20
-
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8793
- 2
- Filtered stream
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- false
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- 0
-
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8743
24
60
-
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8773
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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8977
94
44
-
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8999
- 2
- Data tree to flatten
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- Tree
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-
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8979
42
20
-
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8989
- Path of flattened tree
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- Path
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-
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8999
42
20
-
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9009
- 1
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- Flattened data tree
- 5ac9adbb-2bda-4c4a-af9e-b8b446b4e17f
- Tree
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-
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8979
24
40
-
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8999
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2deabdcb-ef3e-4d3e-b160-684ca6c912fd
- Stream Filter
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-
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8897
77
64
-
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8929
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
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- Index of Gate stream
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- Gate
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- 1
-
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8899
25
20
-
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8909
- 1
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- Input stream at index 0
- 04a1bc39-9c62-42d8-9a7a-ef2f4f2f814d
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- true
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- 1
-
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25
20
-
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- 2
- Input stream at index 1
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- 1
- true
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-
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25
20
-
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- 2
- Filtered stream
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-
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8899
24
60
-
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8929
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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94
44
-
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- 2
- Data tree to flatten
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-
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9969
42
20
-
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- Path of flattened tree
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-
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9989
42
20
-
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9999
- 1
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- Flattened data tree
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- Tree
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-
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24
40
-
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9989
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
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- Stream Filter
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-
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9887
77
64
-
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9919
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
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- Index of Gate stream
- a5d96677-68d1-469b-8275-b2c99f0a086e
- Gate
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- d4a3053e-492d-459f-b24d-a486603f6732
- 1
-
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9889
25
20
-
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9899
- 1
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- Input stream at index 0
- 08efcd40-1cc3-474b-9b99-18eafd5f19c3
- false
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- true
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25
20
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- 2
- Input stream at index 1
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- false
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- true
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25
20
-
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25
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25
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42
20
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24
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11138
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77
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25
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25
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25
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94
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42
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25
20
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11220
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25
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25
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42
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42
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24
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25
20
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25
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25
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24
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42
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42
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24
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42
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13614
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- Filters a collection of input streams
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- Stream Filter
- Stream Filter
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13512
77
64
-
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13544
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- Index of Gate stream
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- Gate
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13514
25
20
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13524
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- true
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13534
25
20
-
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13544
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13554
25
20
-
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13564
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- Stream
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- 0
-
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13514
24
60
-
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13544
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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14515
94
44
-
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14537
- 2
- Data tree to flatten
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- Tree
- Tree
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-
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14517
42
20
-
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14527
- Path of flattened tree
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-
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14537
42
20
-
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14547
- 1
- 1
- {0}
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- Flattened data tree
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- Tree
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-
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14517
24
40
-
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14537
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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14435
77
64
-
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14467
- 3
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- Index of Gate stream
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- Gate
- Gate
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-
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14437
25
20
-
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14447
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- true
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14457
25
20
-
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14467
- 2
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-
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14477
25
20
-
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14487
- 2
- Filtered stream
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- Stream
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- 0
-
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14437
24
60
-
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14467
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten Tree
- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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14667
94
44
-
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14689
- 2
- Data tree to flatten
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- Tree
- Tree
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-
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14669
42
20
-
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14679
- Path of flattened tree
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- Path
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-
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14689
42
20
-
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14699
- 1
- 1
- {0}
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- Flattened data tree
- 17c2fa1d-80d9-4ba6-a5e5-7271d56f0aa2
- Tree
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- 0
-
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14669
24
40
-
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14689
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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14587
77
64
-
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14619
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- Index of Gate stream
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- Gate
- Gate
- false
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- 1
-
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14589
25
20
-
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14599
- 1
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- {0}
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- true
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- 1
-
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14609
25
20
-
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14619
- 2
- Input stream at index 1
- b89664d2-d57e-4cec-b3d8-bcbee474db65
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- 1
- true
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- 1
-
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14629
25
20
-
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14639
- 2
- Filtered stream
- 2c9cd1a3-de48-4ce5-be20-36b483914987
- false
- Stream
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- 0
-
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14589
24
60
-
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14619
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten Tree
- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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15545
94
44
-
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15567
- 2
- Data tree to flatten
- c2596fcd-b45d-4447-a8cc-62a9fa0d6542
- Tree
- Tree
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- 1
-
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15547
42
20
-
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15557
- Path of flattened tree
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- Path
- Path
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- 0
-
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15567
42
20
-
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15577
- 1
- 1
- {0}
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- Flattened data tree
- 1c0f4ea3-98e7-4928-bbe9-4b1f42d8c904
- Tree
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-
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15547
24
40
-
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15567
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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15465
77
64
-
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15497
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
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- Index of Gate stream
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- Gate
- Gate
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- 1
-
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15467
25
20
-
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15477
- 1
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- {0}
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- Input stream at index 0
- b1d14263-646f-42ec-99ce-735724dc0e82
- false
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- true
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- 1
-
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15487
25
20
-
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15497
- 2
- Input stream at index 1
- 4f444ff3-ff4e-4b5b-a8a3-9f1110b9bff4
- false
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- 1
- true
- 1c0f4ea3-98e7-4928-bbe9-4b1f42d8c904
- 1
-
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15507
25
20
-
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15517
- 2
- Filtered stream
- e87642af-d7f4-4c8a-badf-e9466bf0b858
- false
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- S(1)
- false
- 0
-
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15467
24
60
-
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15497
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- 2
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- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
- true
- eafcf1eb-de31-48ae-96e9-a31a5648a08a
- Flatten Tree
- Flatten Tree
-
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15716
94
44
-
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15738
- 2
- Data tree to flatten
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- Tree
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- 1
-
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15718
42
20
-
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15728
- Path of flattened tree
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- Path
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- 0
-
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15738
42
20
-
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15748
- 1
- 1
- {0}
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- Flattened data tree
- 66f2a9d6-153a-446e-bcda-ef81bac878c3
- Tree
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-
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15718
24
40
-
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15738
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- 40d05bdf-aa00-4b00-a946-8411fa96e9a9
- Stream Filter
- Stream Filter
-
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15636
77
64
-
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15668
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
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- Index of Gate stream
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- Gate
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- 1
-
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15638
25
20
-
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15648
- 1
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- {0}
- 1
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- Input stream at index 0
- 3b1611a6-7144-46ad-9be5-c24368f34f9e
- false
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- 0
- true
- 535c49a7-eac1-4cc0-b695-b51aef04808e
- 1
-
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15658
25
20
-
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15668
- 2
- Input stream at index 1
- 3a38a898-df07-4fb0-89f1-77c597e8a5df
- false
- Stream 1
- 1
- true
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- 1
-
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15678
25
20
-
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15688
- 2
- Filtered stream
- 0156a723-76fc-4a7c-8320-97d012f1e76e
- false
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- S(1)
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- 0
-
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15638
24
60
-
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15668
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- 2
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- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
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- d33f5346-f62e-4d82-87ac-174c836d814e
- Flatten Tree
- Flatten Tree
-
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16723
94
44
-
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16745
- 2
- Data tree to flatten
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- Tree
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- 1
-
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16725
42
20
-
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16735
- Path of flattened tree
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- Path
- Path
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- 0
-
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16745
42
20
-
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16755
- 1
- 1
- {0}
- {0}
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- Flattened data tree
- 679d2e91-fa27-4ccb-b44d-365f3bbea2eb
- Tree
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-
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16725
24
40
-
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16745
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 28fc51b3-790c-4602-8eb8-8f320335323d
- Stream Filter
- Stream Filter
-
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16643
77
64
-
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16675
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
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- 1
-
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16645
25
20
-
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16655
- 1
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- {0}
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- Input stream at index 0
- 2adf4b98-d7aa-4f67-ab63-d8621af51ed8
- false
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- true
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- 1
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16665
25
20
-
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16675
- 2
- Input stream at index 1
- ea998311-e0ed-4639-ac92-79e2f0b6aadb
- false
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- 1
- true
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- 1
-
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16685
25
20
-
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16695
- 2
- Filtered stream
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- false
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- 0
-
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16645
24
60
-
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16675
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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16889
94
44
-
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16911
- 2
- Data tree to flatten
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- Tree
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- 1
-
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16891
42
20
-
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16901
- Path of flattened tree
- 441d093b-88ee-44ed-a10a-0fc1ea6d1fc6
- Path
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- false
- 0
-
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16911
42
20
-
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16921
- 1
- 1
- {0}
- {0}
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- Flattened data tree
- 57fa38b0-5e0c-4990-ad3a-70ab8fd6f13a
- Tree
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- 0
-
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16891
24
40
-
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16911
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e884606f-0e12-4361-b99c-de945016ca3e
- Stream Filter
- Stream Filter
-
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16809
77
64
-
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16841
- 3
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 3059c6ca-30de-4165-96cd-b69abb9182e3
- Gate
- Gate
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- 1
-
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16811
25
20
-
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16821
- 1
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- {0}
- 1
- 2
- Input stream at index 0
- ea58797c-a1d6-4dec-9635-c92180f62f31
- false
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- 0
- true
- 87fdae07-bcf5-489b-89b1-aec57ffa9c17
- 1
-
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16831
25
20
-
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16841
- 2
- Input stream at index 1
- ec901e21-d674-4c43-97bf-5c75be692802
- false
- Stream 1
- 1
- true
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- 1
-
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16851
25
20
-
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16861
- 2
- Filtered stream
- 4dfda7fb-90ae-4f9e-9305-08baf23c2d50
- false
- Stream
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- false
- 0
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