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2020-11-20 15:33:46 +00:00
# ##### BEGIN GPL LICENSE BLOCK #####
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
#
# ##### END GPL LICENSE BLOCK #####
import bpy
import threading
import numpy as np
import multiprocessing
from multiprocessing import Process, Pool
from mathutils import Vector
try: from .numba_functions import numba_lerp2
except: pass
weight = []
n_threads = multiprocessing.cpu_count()
class ThreadVertexGroup(threading.Thread):
def __init__ ( self, id, vertex_group, n_verts):
self.id = id
self.vertex_group = vertex_group
self.n_verts = n_verts
threading.Thread.__init__ ( self )
def run (self):
global weight
global n_threads
verts = np.arange(int(self.n_verts/8))*8 + self.id
for v in verts:
try:
weight[v] = self.vertex_group.weight(v)
except:
pass
def thread_read_weight(_weight, vertex_group):
global weight
global n_threads
print(n_threads)
weight = _weight
n_verts = len(weight)
threads = [ThreadVertexGroup(i, vertex_group, n_verts) for i in range(n_threads)]
for t in threads: t.start()
for t in threads: t.join()
return weight
def process_read_weight(id, vertex_group, n_verts):
global weight
global n_threads
verts = np.arange(int(self.n_verts/8))*8 + self.id
for v in verts:
try:
weight[v] = self.vertex_group.weight(v)
except:
pass
def read_weight(_weight, vertex_group):
global weight
global n_threads
print(n_threads)
weight = _weight
n_verts = len(weight)
n_cores = multiprocessing.cpu_count()
pool = Pool(processes=n_cores)
multiple_results = [pool.apply_async(process_read_weight, (i, vertex_group, n_verts)) for i in range(n_cores)]
#processes = [Process(target=process_read_weight, args=(i, vertex_group, n_verts)) for i in range(n_threads)]
#for t in processes: t.start()
#for t in processes: t.join()
return weight
#Recursivly transverse layer_collection for a particular name
def recurLayerCollection(layerColl, collName):
found = None
if (layerColl.name == collName):
return layerColl
for layer in layerColl.children:
found = recurLayerCollection(layer, collName)
if found:
return found
def auto_layer_collection():
# automatically change active layer collection
layer = bpy.context.view_layer.active_layer_collection
layer_collection = bpy.context.view_layer.layer_collection
if layer.hide_viewport or layer.collection.hide_viewport:
collections = bpy.context.object.users_collection
for c in collections:
lc = recurLayerCollection(layer_collection, c.name)
if not c.hide_viewport and not lc.hide_viewport:
bpy.context.view_layer.active_layer_collection = lc
def lerp(a, b, t):
return a + (b - a) * t
def _lerp2(v1, v2, v3, v4, v):
v12 = v1.lerp(v2,v.x) # + (v2 - v1) * v.x
v34 = v3.lerp(v4,v.x) # + (v4 - v3) * v.x
return v12.lerp(v34, v.y)# + (v34 - v12) * v.y
def lerp2(v1, v2, v3, v4, v):
v12 = v1 + (v2 - v1) * v.x
v34 = v3 + (v4 - v3) * v.x
return v12 + (v34 - v12) * v.y
def lerp3(v1, v2, v3, v4, v):
loc = lerp2(v1.co, v2.co, v3.co, v4.co, v)
nor = lerp2(v1.normal, v2.normal, v3.normal, v4.normal, v)
nor.normalize()
return loc + nor * v.z
def np_lerp2(v00, v10, v01, v11, vx, vy):
#try:
# co2 = numba_lerp2(v00, v10, v01, v11, vx, vy)
#except:
co0 = v00 + (v10 - v00) * vx
co1 = v01 + (v11 - v01) * vx
co2 = co0 + (co1 - co0) * vy
return co2
# Prevent Blender Crashes with handlers
def set_animatable_fix_handler(self, context):
old_handlers = []
blender_handlers = bpy.app.handlers.render_init
for h in blender_handlers:
if "turn_off_animatable" in str(h):
old_handlers.append(h)
for h in old_handlers: blender_handlers.remove(h)
################ blender_handlers.append(turn_off_animatable)
return
def turn_off_animatable(scene):
for o in bpy.data.objects:
o.tissue_tessellate.bool_run = False
o.reaction_diffusion_settings.run = False
#except: pass
return
### OBJECTS ###
def convert_object_to_mesh(ob, apply_modifiers=True, preserve_status=True):
try: ob.name
except: return None
if ob.type != 'MESH':
if not apply_modifiers:
mod_visibility = [m.show_viewport for m in ob.modifiers]
for m in ob.modifiers: m.show_viewport = False
#ob.modifiers.update()
#dg = bpy.context.evaluated_depsgraph_get()
#ob_eval = ob.evaluated_get(dg)
#me = bpy.data.meshes.new_from_object(ob_eval, preserve_all_data_layers=True, depsgraph=dg)
me = simple_to_mesh(ob)
new_ob = bpy.data.objects.new(ob.data.name, me)
new_ob.location, new_ob.matrix_world = ob.location, ob.matrix_world
if not apply_modifiers:
for m,vis in zip(ob.modifiers,mod_visibility): m.show_viewport = vis
else:
if apply_modifiers:
new_ob = ob.copy()
new_me = simple_to_mesh(ob)
new_ob.modifiers.clear()
new_ob.data = new_me
else:
new_ob = ob.copy()
new_ob.data = ob.data.copy()
new_ob.modifiers.clear()
bpy.context.collection.objects.link(new_ob)
if preserve_status:
new_ob.select_set(False)
else:
for o in bpy.context.view_layer.objects: o.select_set(False)
new_ob.select_set(True)
bpy.context.view_layer.objects.active = new_ob
return new_ob
def simple_to_mesh(ob):
dg = bpy.context.evaluated_depsgraph_get()
ob_eval = ob.evaluated_get(dg)
me = bpy.data.meshes.new_from_object(ob_eval, preserve_all_data_layers=True, depsgraph=dg)
me.calc_normals()
return me
def join_objects(objects, link_to_scene=True, make_active=False):
C = bpy.context
bm = bmesh.new()
materials = {}
faces_materials = []
dg = C.evaluated_depsgraph_get()
for o in objects:
bm.from_object(o, dg)
# add object's material to the dictionary
for m in o.data.materials:
if m not in materials: materials[m] = len(materials)
for f in o.data.polygons:
index = f.material_index
mat = o.material_slots[index].material
new_index = materials[mat]
faces_materials.append(new_index)
bm.verts.ensure_lookup_table()
bm.edges.ensure_lookup_table()
bm.faces.ensure_lookup_table()
# assign new indexes
for index, f in zip(faces_materials, bm.faces): f.material_index = index
# create object
me = bpy.data.meshes.new('joined')
bm.to_mesh(me)
me.update()
ob = bpy.data.objects.new('joined', me)
if link_to_scene: C.collection.objects.link(ob)
# make active
if make_active:
for o in C.view_layer.objects: o.select_set(False)
ob.select_set(True)
C.view_layer.objects.active = ob
# add materials
for m in materials.keys(): ob.data.materials.append(m)
return ob
### MESH FUNCTIONS
def get_vertices_numpy(mesh):
n_verts = len(mesh.vertices)
verts = [0]*n_verts*3
mesh.vertices.foreach_get('co', verts)
verts = np.array(verts).reshape((n_verts,3))
return verts
def get_vertices_and_normals_numpy(mesh):
n_verts = len(mesh.vertices)
verts = [0]*n_verts*3
normals = [0]*n_verts*3
mesh.vertices.foreach_get('co', verts)
mesh.vertices.foreach_get('normal', normals)
verts = np.array(verts).reshape((n_verts,3))
normals = np.array(normals).reshape((n_verts,3))
return verts, normals
def get_edges_numpy(mesh):
n_edges = len(mesh.edges)
edges = [0]*n_edges*2
mesh.edges.foreach_get('vertices', edges)
edges = np.array(edges).reshape((n_edges,2)).astype('int')
return edges
def get_edges_id_numpy(mesh):
n_edges = len(mesh.edges)
edges = [0]*n_edges*2
mesh.edges.foreach_get('vertices', edges)
edges = np.array(edges).reshape((n_edges,2))
indexes = np.arange(n_edges).reshape((n_edges,1))
edges = np.concatenate((edges,indexes), axis=1)
return edges
def get_vertices(mesh):
n_verts = len(mesh.vertices)
verts = [0]*n_verts*3
mesh.vertices.foreach_get('co', verts)
verts = np.array(verts).reshape((n_verts,3))
verts = [Vector(v) for v in verts]
return verts
def get_faces(mesh):
faces = [[v for v in f.vertices] for f in mesh.polygons]
return faces
def get_faces_numpy(mesh):
faces = [[v for v in f.vertices] for f in mesh.polygons]
return np.array(faces)
def get_faces_edges_numpy(mesh):
faces = [v.edge_keys for f in mesh.polygons]
return np.array(faces)
#try:
#from numba import jit, njit
#from numba.typed import List
'''
@jit
def find_curves(edges, n_verts):
#verts_dict = {key:[] for key in range(n_verts)}
verts_dict = {}
for key in range(n_verts): verts_dict[key] = []
for e in edges:
verts_dict[e[0]].append(e[1])
verts_dict[e[1]].append(e[0])
curves = []#List()
loop1 = True
while loop1:
if len(verts_dict) == 0:
loop1 = False
continue
# next starting point
v = list(verts_dict.keys())[0]
# neighbors
v01 = verts_dict[v]
if len(v01) == 0:
verts_dict.pop(v)
continue
curve = []#List()
curve.append(v) # add starting point
curve.append(v01[0]) # add neighbors
verts_dict.pop(v)
loop2 = True
while loop2:
last_point = curve[-1]
#if last_point not in verts_dict: break
v01 = verts_dict[last_point]
# curve end
if len(v01) == 1:
verts_dict.pop(last_point)
loop2 = False
continue
if v01[0] == curve[-2]:
curve.append(v01[1])
verts_dict.pop(last_point)
elif v01[1] == curve[-2]:
curve.append(v01[0])
verts_dict.pop(last_point)
else:
loop2 = False
continue
if curve[0] == curve[-1]:
loop2 = False
continue
curves.append(curve)
return curves
'''
def find_curves(edges, n_verts):
verts_dict = {key:[] for key in range(n_verts)}
for e in edges:
verts_dict[e[0]].append(e[1])
verts_dict[e[1]].append(e[0])
curves = []
while True:
if len(verts_dict) == 0: break
# next starting point
v = list(verts_dict.keys())[0]
# neighbors
v01 = verts_dict[v]
if len(v01) == 0:
verts_dict.pop(v)
continue
curve = []
if len(v01) > 1: curve.append(v01[1]) # add neighbors
curve.append(v) # add starting point
curve.append(v01[0]) # add neighbors
verts_dict.pop(v)
# start building curve
while True:
#last_point = curve[-1]
#if last_point not in verts_dict: break
# try to change direction if needed
if curve[-1] in verts_dict: pass
elif curve[0] in verts_dict: curve.reverse()
else: break
# neighbors points
last_point = curve[-1]
v01 = verts_dict[last_point]
# curve end
if len(v01) == 1:
verts_dict.pop(last_point)
if curve[0] in verts_dict: continue
else: break
# chose next point
new_point = None
if v01[0] == curve[-2]: new_point = v01[1]
elif v01[1] == curve[-2]: new_point = v01[0]
#else: break
#if new_point != curve[1]:
curve.append(new_point)
verts_dict.pop(last_point)
if curve[0] == curve[-1]:
verts_dict.pop(new_point)
break
curves.append(curve)
return curves
def curve_from_points(points, name='Curve'):
curve = bpy.data.curves.new(name,'CURVE')
for c in points:
s = curve.splines.new('POLY')
s.points.add(len(c))
for i,p in enumerate(c): s.points[i].co = p.xyz + [1]
ob_curve = bpy.data.objects.new(name,curve)
return ob_curve
def curve_from_pydata(points, indexes, name='Curve', skip_open=False, merge_distance=1, set_active=True):
curve = bpy.data.curves.new(name,'CURVE')
curve.dimensions = '3D'
for c in indexes:
# cleanup
pts = np.array([points[i] for i in c])
if merge_distance > 0:
pts1 = np.roll(pts,1,axis=0)
dist = np.linalg.norm(pts1-pts, axis=1)
count = 0
n = len(dist)
mask = np.ones(n).astype('bool')
for i in range(n):
count += dist[i]
if count > merge_distance: count = 0
else: mask[i] = False
pts = pts[mask]
bool_cyclic = c[0] == c[-1]
if skip_open and not bool_cyclic: continue
s = curve.splines.new('POLY')
n_pts = len(pts)
s.points.add(n_pts-1)
w = np.ones(n_pts).reshape((n_pts,1))
co = np.concatenate((pts,w),axis=1).reshape((n_pts*4))
s.points.foreach_set('co',co)
s.use_cyclic_u = bool_cyclic
ob_curve = bpy.data.objects.new(name,curve)
bpy.context.collection.objects.link(ob_curve)
if set_active:
bpy.context.view_layer.objects.active = ob_curve
return ob_curve
def curve_from_vertices(indexes, verts, name='Curve'):
curve = bpy.data.curves.new(name,'CURVE')
for c in indexes:
s = curve.splines.new('POLY')
s.points.add(len(c))
for i,p in enumerate(c): s.points[i].co = verts[p].co.xyz + [1]
ob_curve = bpy.data.objects.new(name,curve)
return ob_curve
### WEIGHT FUNCTIONS ###
def get_weight(vertex_group, n_verts):
weight = [0]*n_verts
for i in range(n_verts):
try: weight[i] = vertex_group.weight(i)
except: pass
return weight
def get_weight_numpy(vertex_group, n_verts):
weight = [0]*n_verts
for i in range(n_verts):
try: weight[i] = vertex_group.weight(i)
except: pass
return np.array(weight)