463 lines
15 KiB
Python
463 lines
15 KiB
Python
# ##### BEGIN GPL LICENSE BLOCK #####
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#
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# This program is free software; you can redistribute it and/or
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# modify it under the terms of the GNU General Public License
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# as published by the Free Software Foundation; either version 2
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# of the License, or (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software Foundation,
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# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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#
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# ##### END GPL LICENSE BLOCK #####
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import bpy
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import threading
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import numpy as np
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import multiprocessing
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from multiprocessing import Process, Pool
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from mathutils import Vector
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try: from .numba_functions import numba_lerp2
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except: pass
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weight = []
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n_threads = multiprocessing.cpu_count()
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class ThreadVertexGroup(threading.Thread):
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def __init__ ( self, id, vertex_group, n_verts):
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self.id = id
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self.vertex_group = vertex_group
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self.n_verts = n_verts
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threading.Thread.__init__ ( self )
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def run (self):
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global weight
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global n_threads
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verts = np.arange(int(self.n_verts/8))*8 + self.id
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for v in verts:
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try:
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weight[v] = self.vertex_group.weight(v)
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except:
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pass
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def thread_read_weight(_weight, vertex_group):
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global weight
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global n_threads
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print(n_threads)
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weight = _weight
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n_verts = len(weight)
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threads = [ThreadVertexGroup(i, vertex_group, n_verts) for i in range(n_threads)]
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for t in threads: t.start()
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for t in threads: t.join()
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return weight
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def process_read_weight(id, vertex_group, n_verts):
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global weight
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global n_threads
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verts = np.arange(int(self.n_verts/8))*8 + self.id
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for v in verts:
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try:
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weight[v] = self.vertex_group.weight(v)
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except:
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pass
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def read_weight(_weight, vertex_group):
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global weight
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global n_threads
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print(n_threads)
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weight = _weight
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n_verts = len(weight)
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n_cores = multiprocessing.cpu_count()
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pool = Pool(processes=n_cores)
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multiple_results = [pool.apply_async(process_read_weight, (i, vertex_group, n_verts)) for i in range(n_cores)]
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#processes = [Process(target=process_read_weight, args=(i, vertex_group, n_verts)) for i in range(n_threads)]
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#for t in processes: t.start()
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#for t in processes: t.join()
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return weight
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#Recursivly transverse layer_collection for a particular name
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def recurLayerCollection(layerColl, collName):
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found = None
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if (layerColl.name == collName):
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return layerColl
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for layer in layerColl.children:
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found = recurLayerCollection(layer, collName)
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if found:
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return found
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def auto_layer_collection():
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# automatically change active layer collection
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layer = bpy.context.view_layer.active_layer_collection
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layer_collection = bpy.context.view_layer.layer_collection
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if layer.hide_viewport or layer.collection.hide_viewport:
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collections = bpy.context.object.users_collection
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for c in collections:
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lc = recurLayerCollection(layer_collection, c.name)
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if not c.hide_viewport and not lc.hide_viewport:
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bpy.context.view_layer.active_layer_collection = lc
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def lerp(a, b, t):
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return a + (b - a) * t
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def _lerp2(v1, v2, v3, v4, v):
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v12 = v1.lerp(v2,v.x) # + (v2 - v1) * v.x
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v34 = v3.lerp(v4,v.x) # + (v4 - v3) * v.x
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return v12.lerp(v34, v.y)# + (v34 - v12) * v.y
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def lerp2(v1, v2, v3, v4, v):
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v12 = v1 + (v2 - v1) * v.x
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v34 = v3 + (v4 - v3) * v.x
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return v12 + (v34 - v12) * v.y
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def lerp3(v1, v2, v3, v4, v):
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loc = lerp2(v1.co, v2.co, v3.co, v4.co, v)
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nor = lerp2(v1.normal, v2.normal, v3.normal, v4.normal, v)
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nor.normalize()
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return loc + nor * v.z
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def np_lerp2(v00, v10, v01, v11, vx, vy):
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#try:
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# co2 = numba_lerp2(v00, v10, v01, v11, vx, vy)
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#except:
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co0 = v00 + (v10 - v00) * vx
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co1 = v01 + (v11 - v01) * vx
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co2 = co0 + (co1 - co0) * vy
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return co2
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# Prevent Blender Crashes with handlers
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def set_animatable_fix_handler(self, context):
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old_handlers = []
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blender_handlers = bpy.app.handlers.render_init
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for h in blender_handlers:
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if "turn_off_animatable" in str(h):
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old_handlers.append(h)
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for h in old_handlers: blender_handlers.remove(h)
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################ blender_handlers.append(turn_off_animatable)
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return
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def turn_off_animatable(scene):
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for o in bpy.data.objects:
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o.tissue_tessellate.bool_run = False
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o.reaction_diffusion_settings.run = False
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#except: pass
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return
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### OBJECTS ###
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def convert_object_to_mesh(ob, apply_modifiers=True, preserve_status=True):
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try: ob.name
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except: return None
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if ob.type != 'MESH':
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if not apply_modifiers:
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mod_visibility = [m.show_viewport for m in ob.modifiers]
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for m in ob.modifiers: m.show_viewport = False
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#ob.modifiers.update()
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#dg = bpy.context.evaluated_depsgraph_get()
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#ob_eval = ob.evaluated_get(dg)
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#me = bpy.data.meshes.new_from_object(ob_eval, preserve_all_data_layers=True, depsgraph=dg)
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me = simple_to_mesh(ob)
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new_ob = bpy.data.objects.new(ob.data.name, me)
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new_ob.location, new_ob.matrix_world = ob.location, ob.matrix_world
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if not apply_modifiers:
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for m,vis in zip(ob.modifiers,mod_visibility): m.show_viewport = vis
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else:
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if apply_modifiers:
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new_ob = ob.copy()
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new_me = simple_to_mesh(ob)
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new_ob.modifiers.clear()
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new_ob.data = new_me
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else:
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new_ob = ob.copy()
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new_ob.data = ob.data.copy()
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new_ob.modifiers.clear()
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bpy.context.collection.objects.link(new_ob)
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if preserve_status:
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new_ob.select_set(False)
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else:
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for o in bpy.context.view_layer.objects: o.select_set(False)
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new_ob.select_set(True)
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bpy.context.view_layer.objects.active = new_ob
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return new_ob
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def simple_to_mesh(ob):
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dg = bpy.context.evaluated_depsgraph_get()
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ob_eval = ob.evaluated_get(dg)
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me = bpy.data.meshes.new_from_object(ob_eval, preserve_all_data_layers=True, depsgraph=dg)
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me.calc_normals()
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return me
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def join_objects(objects, link_to_scene=True, make_active=False):
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C = bpy.context
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bm = bmesh.new()
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materials = {}
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faces_materials = []
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dg = C.evaluated_depsgraph_get()
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for o in objects:
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bm.from_object(o, dg)
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# add object's material to the dictionary
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for m in o.data.materials:
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if m not in materials: materials[m] = len(materials)
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for f in o.data.polygons:
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index = f.material_index
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mat = o.material_slots[index].material
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new_index = materials[mat]
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faces_materials.append(new_index)
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bm.verts.ensure_lookup_table()
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bm.edges.ensure_lookup_table()
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bm.faces.ensure_lookup_table()
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# assign new indexes
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for index, f in zip(faces_materials, bm.faces): f.material_index = index
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# create object
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me = bpy.data.meshes.new('joined')
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bm.to_mesh(me)
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me.update()
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ob = bpy.data.objects.new('joined', me)
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if link_to_scene: C.collection.objects.link(ob)
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# make active
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if make_active:
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for o in C.view_layer.objects: o.select_set(False)
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ob.select_set(True)
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C.view_layer.objects.active = ob
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# add materials
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for m in materials.keys(): ob.data.materials.append(m)
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return ob
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### MESH FUNCTIONS
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def get_vertices_numpy(mesh):
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n_verts = len(mesh.vertices)
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verts = [0]*n_verts*3
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mesh.vertices.foreach_get('co', verts)
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verts = np.array(verts).reshape((n_verts,3))
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return verts
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def get_vertices_and_normals_numpy(mesh):
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n_verts = len(mesh.vertices)
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verts = [0]*n_verts*3
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normals = [0]*n_verts*3
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mesh.vertices.foreach_get('co', verts)
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mesh.vertices.foreach_get('normal', normals)
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verts = np.array(verts).reshape((n_verts,3))
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normals = np.array(normals).reshape((n_verts,3))
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return verts, normals
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def get_edges_numpy(mesh):
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n_edges = len(mesh.edges)
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edges = [0]*n_edges*2
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mesh.edges.foreach_get('vertices', edges)
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edges = np.array(edges).reshape((n_edges,2)).astype('int')
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return edges
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def get_edges_id_numpy(mesh):
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n_edges = len(mesh.edges)
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edges = [0]*n_edges*2
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mesh.edges.foreach_get('vertices', edges)
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edges = np.array(edges).reshape((n_edges,2))
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indexes = np.arange(n_edges).reshape((n_edges,1))
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edges = np.concatenate((edges,indexes), axis=1)
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return edges
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def get_vertices(mesh):
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n_verts = len(mesh.vertices)
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verts = [0]*n_verts*3
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mesh.vertices.foreach_get('co', verts)
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verts = np.array(verts).reshape((n_verts,3))
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verts = [Vector(v) for v in verts]
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return verts
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def get_faces(mesh):
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faces = [[v for v in f.vertices] for f in mesh.polygons]
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return faces
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def get_faces_numpy(mesh):
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faces = [[v for v in f.vertices] for f in mesh.polygons]
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return np.array(faces)
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def get_faces_edges_numpy(mesh):
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faces = [v.edge_keys for f in mesh.polygons]
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return np.array(faces)
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#try:
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#from numba import jit, njit
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#from numba.typed import List
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'''
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@jit
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def find_curves(edges, n_verts):
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#verts_dict = {key:[] for key in range(n_verts)}
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verts_dict = {}
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for key in range(n_verts): verts_dict[key] = []
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for e in edges:
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verts_dict[e[0]].append(e[1])
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verts_dict[e[1]].append(e[0])
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curves = []#List()
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loop1 = True
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while loop1:
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if len(verts_dict) == 0:
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loop1 = False
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continue
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# next starting point
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v = list(verts_dict.keys())[0]
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# neighbors
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v01 = verts_dict[v]
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if len(v01) == 0:
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verts_dict.pop(v)
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continue
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curve = []#List()
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curve.append(v) # add starting point
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curve.append(v01[0]) # add neighbors
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verts_dict.pop(v)
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loop2 = True
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while loop2:
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last_point = curve[-1]
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#if last_point not in verts_dict: break
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v01 = verts_dict[last_point]
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# curve end
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if len(v01) == 1:
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verts_dict.pop(last_point)
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loop2 = False
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continue
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if v01[0] == curve[-2]:
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curve.append(v01[1])
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verts_dict.pop(last_point)
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elif v01[1] == curve[-2]:
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curve.append(v01[0])
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verts_dict.pop(last_point)
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else:
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loop2 = False
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continue
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if curve[0] == curve[-1]:
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loop2 = False
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continue
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curves.append(curve)
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return curves
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'''
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def find_curves(edges, n_verts):
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verts_dict = {key:[] for key in range(n_verts)}
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for e in edges:
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verts_dict[e[0]].append(e[1])
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verts_dict[e[1]].append(e[0])
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curves = []
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while True:
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if len(verts_dict) == 0: break
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# next starting point
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v = list(verts_dict.keys())[0]
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# neighbors
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v01 = verts_dict[v]
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if len(v01) == 0:
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verts_dict.pop(v)
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continue
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curve = []
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if len(v01) > 1: curve.append(v01[1]) # add neighbors
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curve.append(v) # add starting point
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curve.append(v01[0]) # add neighbors
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verts_dict.pop(v)
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# start building curve
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while True:
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#last_point = curve[-1]
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#if last_point not in verts_dict: break
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# try to change direction if needed
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if curve[-1] in verts_dict: pass
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elif curve[0] in verts_dict: curve.reverse()
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else: break
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# neighbors points
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last_point = curve[-1]
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v01 = verts_dict[last_point]
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# curve end
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if len(v01) == 1:
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verts_dict.pop(last_point)
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if curve[0] in verts_dict: continue
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else: break
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# chose next point
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new_point = None
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if v01[0] == curve[-2]: new_point = v01[1]
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elif v01[1] == curve[-2]: new_point = v01[0]
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#else: break
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#if new_point != curve[1]:
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curve.append(new_point)
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verts_dict.pop(last_point)
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if curve[0] == curve[-1]:
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verts_dict.pop(new_point)
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break
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curves.append(curve)
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return curves
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def curve_from_points(points, name='Curve'):
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curve = bpy.data.curves.new(name,'CURVE')
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for c in points:
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s = curve.splines.new('POLY')
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s.points.add(len(c))
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for i,p in enumerate(c): s.points[i].co = p.xyz + [1]
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ob_curve = bpy.data.objects.new(name,curve)
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return ob_curve
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def curve_from_pydata(points, indexes, name='Curve', skip_open=False, merge_distance=1, set_active=True):
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curve = bpy.data.curves.new(name,'CURVE')
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curve.dimensions = '3D'
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for c in indexes:
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# cleanup
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pts = np.array([points[i] for i in c])
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if merge_distance > 0:
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pts1 = np.roll(pts,1,axis=0)
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dist = np.linalg.norm(pts1-pts, axis=1)
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count = 0
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n = len(dist)
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mask = np.ones(n).astype('bool')
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for i in range(n):
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count += dist[i]
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if count > merge_distance: count = 0
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else: mask[i] = False
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pts = pts[mask]
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bool_cyclic = c[0] == c[-1]
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if skip_open and not bool_cyclic: continue
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s = curve.splines.new('POLY')
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n_pts = len(pts)
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s.points.add(n_pts-1)
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w = np.ones(n_pts).reshape((n_pts,1))
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co = np.concatenate((pts,w),axis=1).reshape((n_pts*4))
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s.points.foreach_set('co',co)
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s.use_cyclic_u = bool_cyclic
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ob_curve = bpy.data.objects.new(name,curve)
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bpy.context.collection.objects.link(ob_curve)
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if set_active:
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bpy.context.view_layer.objects.active = ob_curve
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return ob_curve
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def curve_from_vertices(indexes, verts, name='Curve'):
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curve = bpy.data.curves.new(name,'CURVE')
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for c in indexes:
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s = curve.splines.new('POLY')
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s.points.add(len(c))
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for i,p in enumerate(c): s.points[i].co = verts[p].co.xyz + [1]
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ob_curve = bpy.data.objects.new(name,curve)
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return ob_curve
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### WEIGHT FUNCTIONS ###
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def get_weight(vertex_group, n_verts):
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weight = [0]*n_verts
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for i in range(n_verts):
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try: weight[i] = vertex_group.weight(i)
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except: pass
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return weight
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def get_weight_numpy(vertex_group, n_verts):
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weight = [0]*n_verts
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for i in range(n_verts):
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try: weight[i] = vertex_group.weight(i)
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except: pass
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return np.array(weight)
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