def to_point(self, centers, falloff):
n = len(centers)
if n == 1:
sfield = SvScalarFieldPointDistance(centers[0], falloff=falloff)
vfield = SvVectorFieldPointDistance(centers[0], falloff=falloff)
elif self.point_mode == 'AVG':
sfields = [SvScalarFieldPointDistance(center, falloff=falloff) for center in centers]
sfield = SvMergedScalarField('AVG', sfields)
vfields = [SvVectorFieldPointDistance(center, falloff=falloff) for center in centers]
vfield = SvAverageVectorField(vfields)
elif self.point_mode == 'MIN':
kdt = kdtree.KDTree(len(centers))
for i, v in enumerate(centers):
kdt.insert(v, i)
kdt.balance()
vfield = SvKdtVectorField(kdt=kdt, falloff=falloff)
sfield = SvKdtScalarField(kdt=kdt, falloff=falloff)
else: # SEP
sfield = [SvScalarFieldPointDistance(center, falloff=falloff) for center in centers]
vfield = [SvVectorFieldPointDistance(center, falloff=falloff) for center in centers]
return vfield, sfield
def match_raycast_vertex(self):
self.bm = bmesh.new()
self.bm.from_mesh(self.obj_t.data)
self.bm.verts.ensure_lookup_table()
self.bm.edges.ensure_lookup_table()
self.bm.faces.ensure_lookup_table()
bmesh.ops.remove_doubles(self.bm, verts=list(self.bm.verts), dist=3)
size = len(self.bm.verts)
kd = kdtree.KDTree(size)
for i, vtx in enumerate(self.bm.verts):
v = Vector((vtx.co.x, vtx.co.y, 0.0))
kd.insert(v, i)
kd.balance()
plane = bpy.data.objects['Plane.001']
self.bm.verts.ensure_lookup_table()
self.bm.edges.ensure_lookup_table()
self.bm.faces.ensure_lookup_table()
for p in plane.data.vertices:
wp = plane.matrix_world @ p.co
lp = self.obj_t.matrix_world.inverted() @ wp
#BL_DEBUG.set_mark(self.obj_t.matrix_world @ location)
#BL_DEBUG.set_mark(plane.matrix_world @ p.co)
location = Vector((lp.x, lp.y, 0.0))
co, index, dist = kd.find(location) # dist is the distance
#print("Found", co, index, dist)
#BL_DEBUG.set_mark(self.obj_t.matrix_world @ co)
self.bm.verts[index].co[2] = lp.z ## translated coords
# tune this. There are more space (2-4m)
if dist > 0.4:
self.bm.verts[index].co[0] = lp.x ## translated coords
self.bm.verts[index].co[1] = lp.y ## translated coords
self.update_bm(freeit=True)
def object_list2(objects, active=0):
"""
Return an approximate shortest path through objects starting at the
active index using the nearest neighbor heuristic.
"""
s = time()
# calculate a kd tree to quickly answer nearest neighbor queries
kd = kdtree.KDTree(len(objects))
for i, ob in enumerate(objects):
kd.insert(ob.location, i)
kd.balance()
current = objects[active]
chain = [current] # we start at the chosen object
added = {active}
for i in range(1, len(objects)): # we know how many objects to add
# when looking for the nearest neighbor we start with two neigbors
# (because we include the object itself in the search) and if
# the other neigbors is not yet in the chain we add it, otherwise
# we expand our search to a maximum of the total number of objects
for n in range(2, len(objects)):
neighbors = {
index
for _, index, _ in kd.find_n(current.location, n)
}
neighbors -= added
if neighbors: # strictly speaking we shoudl assert that len(neighbors) == 1
chain.extend(objects[i] for i in neighbors)
added |= neighbors
break
current = chain[-1]
print("{n:d} objects {t:.1f}s".format(t=time() - s, n=len(objects)))
return chain
def mirror_l_to_r_back():
bpy.ops.object.mode_set(mode = 'OBJECT')
obj = bpy.context.active_object
mesh = obj.data
size = len(mesh.vertices)
kd = kdtree.KDTree(size)
rside_indices = [i for i,v in enumerate(mesh.vertices) if v.co.x < 0]
lside_pos = [[i,(-v.co.x , v.co.y , v.co.z )] for i,v in enumerate(mesh.vertices) if v.co.x < 0]
# selectedVtxIndex = set([v.index for v in obj.data.vertices if v.select])
# print(selectedVtxIndex)
print(lside_pos)
for i, v in enumerate(mesh.vertices):
kd.insert(v.co, i)
kd.balance()
#co_find = (0.0, 0.0, 0.0)
bpy.ops.object.mode_set(mode = 'EDIT')
bpy.ops.mesh.select_mode(type="VERT")
bpy.ops.mesh.select_all(action = 'DESELECT')
bpy.ops.object.mode_set(mode = 'OBJECT')
for p in lside_pos:
co, index, dist = kd.find( p[1] )
print("Close to center:",p[0],':', co, index, dist)
obj.data.vertices[p[0]].co = (-co.x,co.y,co.z)
# for i in rside_indices:
# mesh.vertices[i].select = True
#obj.data.vertices[i].co.x = 2.0
bpy.ops.object.mode_set(mode = 'EDIT')
def sv_main(v=[[]], mdist=0.4):
in_sockets = [
['v', 'verts', v],
['s', 'mdist', mdist]
]
e = []
if v and v[0]:
v = v[0]
# make kd tree
# documentation mathutils.kdtree.html
size = len(v)
kd = kdtree.KDTree(size)
for i, vtx in enumerate(v):
kd.insert(Vector(vtx), i)
kd.balance()
# makes edges
for i, vtx in enumerate(v):
num_edges = 0
for (co, index, dist) in kd.find_range(vtx, mdist):
if i == index or (num_edges > 2):
continue
e.append([i, index])
num_edges += 1
# out boilerplate
out_sockets = [
['s', 'Edges', [e]]
]
return in_sockets, out_sockets
def by_sphere(self, vertices, edges, faces):
radius = self.inputs['Radius'].sv_get(default=[1.0])[0][0]
centers = self.inputs['Center'].sv_get()[0]
if len(centers) == 1:
center = centers[0]
out_verts_mask = [((Vector(v) - Vector(center)).length <= radius) for v in vertices]
else:
# build KDTree
tree = kdtree.KDTree(len(centers))
for i, v in enumerate(centers):
tree.insert(v, i)
tree.balance()
out_verts_mask = []
for vertex in vertices:
_, _, rho = tree.find(vertex)
mask = rho <= radius
out_verts_mask.append(mask)
out_edges_mask = self.select_edges_by_verts(out_verts_mask, edges)
out_faces_mask = self.select_faces_by_verts(out_verts_mask, faces)
return out_verts_mask, out_edges_mask, out_faces_mask
def init_guess():
us = np.linspace(u_min, u_max, num=init_samples)
vs = np.linspace(v_min, v_max, num=init_samples)
us, vs = np.meshgrid(us, vs)
us = us.flatten()
vs = vs.flatten()
points = surface.evaluate_array(us, vs).tolist()
kdt = kdtree.KDTree(len(us))
for i, v in enumerate(points):
kdt.insert(v, i)
kdt.balance()
us_out = []
vs_out = []
nearest_out = []
for point_from in points_from:
nearest, i, distance = kdt.find(point_from)
us_out.append(us[i])
vs_out.append(vs[i])
nearest_out.append(tuple(nearest))
return us_out, vs_out, nearest_out
def process(self):
if not any(output.is_linked for output in self.outputs):
return
vertices_s = self.inputs['Vertices'].sv_get(default=[[]])
masks_s = self.inputs['Mask'].sv_get()
radius_s = self.inputs['Radius'].sv_get()
out_coeffs = []
meshes = match_long_repeat([vertices_s, masks_s, radius_s])
for vertices, masks, radius in zip(*meshes):
fullList(masks, len(vertices))
if isinstance(radius, list) and isinstance(radius[0],
(int, float)):
radius = radius[0]
# build KDTree
base = [v for v, mask in zip(vertices, masks) if mask]
tree = kdtree.KDTree(len(base))
for i, v in enumerate(base):
tree.insert(v, i)
tree.balance()
coeffs = []
for vertex, mask in zip(vertices, masks):
if mask:
coef = 1.0
else:
_, _, rho = tree.find(vertex)
coef = self.falloff(radius, rho)
coeffs.append(coef)
out_coeffs.append(coeffs)
self.outputs['Coeffs'].sv_set(out_coeffs)
def creat_tree(line):
# Create KDTree for line
tree = kdtree.KDTree(len(line))
[tree.insert(p, i) for i, p in enumerate(line)]
tree.balance()
return tree
def Terraform(index, startY, startX, distY, distX, endY, endX, level, radius,
lenY, lenX, falloff, vertY, vertX, realY, realX, m, terraKey,
exclude):
index = eval(index)
dy = index[0] - startY
dx = index[1] - startX
localPos = (200 * dy, 200 * dx)
worldPos = Vector([realX + localPos[1], realY + localPos[0], 0])
cellDict = core.world["cellDict"]
worldKey = (dx + realX, dy + realY)
if worldKey not in cellDict:
cellDict[worldKey] = {"heightMap": [], "objects": [], "init": False}
file = gamepath + "\\dsm\\cache\\landmass\\%s\\exclude.txt" % (terraKey)
exclude = eval(exclude)
if str(index) in exclude:
return False
cvi = core.grid["verts"][vertY, vertX][0]
origin = Vector(m.getVertex(0, cvi).getXYZ()[0:2]) + Vector([realX, realY])
try:
f = np.load(gamepath + "\\dsm\\cache\\landmass\\%s\\%s.npy" %
(terraKey, str(index)))
except:
kd = kdtree.KDTree(41 * 41)
f = np.full((41, 41), abs(radius * level))
terraLoop1_ufunc(kd, terra_i, worldPos.x, worldPos.y)
kd.balance()
near = kd.find_range(Vector([realX, realY, 0]), radius**2)
doLenAdjust = lenX != lenY
for n in near:
co, kd_index, dist = n
point = ps[kd_index]
if doLenAdjust:
if min(lenX, lenY) == lenX:
distX = np.linalg.norm(
Vector([co.x, 0, 0]) - Vector([origin.x, 0, 0]))
dist += distX * (16 * falloff)
elif min(lenX, lenY) == lenY:
distY = np.linalg.norm(
Vector([0, co.y, 0]) - Vector([0, origin.y, 0]))
dist += distY * (16 * falloff)
e = max(0, dist)
new_f = getHeightFactor(level, radius, falloff, e)
if abs(new_f) > 0: f[i_list[kd_index]] = e
if len(f[f != abs(radius * level)].tolist()) > 0:
np.save(
gamepath + "\\dsm\\cache\\landmass\\%s\\%s.npy" %
(terraKey, str(index)), f)
else:
exclude = open(file, "a")
exclude.write(str(index) + "\n")
if len(f[f != abs(radius * level)].tolist()) > 0:
cellDict[worldKey]["heightMap"].append(
[vertY, vertX, radius, level, falloff, f, (lenX, lenY)])
return True
def execute(self, context):
depsgraph = bpy.context.depsgraph
ob = bpy.context.active_object
obj_eval = depsgraph.objects.get(ob.name, None)
# particleObj = context.active_object
particleObj = obj_eval
if bpy.context.active_object.particle_systems is None: # create new one
self.report({'INFO'}, 'No active Particle Hair System found!')
return {"CANCELLED"}
index = particleObj.particle_systems.active_index
psys_active = particleObj.particle_systems[index]
if psys_active.settings.type != 'HAIR': # create new one
self.report({'INFO'},
'Active Particle System is not Hair type! Cancelling')
return {"CANCELLED"}
pointsList_hair = []
context.scene.update()
if len(psys_active.particles) == 0: # require more that three strands
self.report({'INFO'},
'Active Particle System has zero strands! Cancelling')
return {"CANCELLED"}
diagonal = sqrt(
pow(particleObj.dimensions[0], 2) +
pow(particleObj.dimensions[1], 2) +
pow(particleObj.dimensions[2], 2)) # to normalize some values
for particle in psys_active.particles: # for strand point
pointsList_hair.append([
hair_key.co for hair_key in particle.hair_keys
]) # DONE: exclude duplicates if first strand[0] in list already
if len(psys_active.particles
) == 1: #create two fake strands so that barycentric works
pointsList_hair.append([
x.xyz + Vector((0.01 * diagonal, 0, 0))
for x in pointsList_hair[0]
])
pointsList_hair.append([
x.xyz + Vector((0, 0.01 * diagonal, 0))
for x in pointsList_hair[0]
])
elif len(psys_active.particles
) == 2: #create one fake strands so that barycentric works
pointsList_hair.append([
x.xyz + Vector((0.01 * diagonal, 0, 0))
for x in pointsList_hair[0]
])
pointsList_uniq = []
[
pointsList_uniq.append(x) for x in pointsList_hair
if x not in pointsList_uniq
] #removing doubles (can cause zero size tris)
#same_point_count cos barycentric transform requires it
pointsList = interpol_Catmull_Rom(
pointsList_uniq,
self.t_in_y,
uniform_spacing=True,
same_point_count=True) # just gives smoother result on borders
searchDistance = 100 * diagonal
parentRoots = [strand[0]
for strand in pointsList] # first point of roots
#create nnew Part Sytem with uniform points
pointsChildRoots = self.createUniformParticleSystem(
context, self.childCount, self.PlacementJittering,
self.Seed) # return child part roots positions
kd = kdtree.KDTree(len(parentRoots))
for i, root in enumerate(parentRoots):
kd.insert(root, i)
kd.balance()
sourceSurface_BVHT = BVHTree.FromObject(particleObj, context.depsgraph)
childStrandsPoints = [] #will contain strands with child points
childStrandRootNormals = []
length_ver_group_index = -1
vertex_group_length_name = psys_active.vertex_group_length
if vertex_group_length_name: # calc weight based on root point
length_ver_group_index = particleObj.vertex_groups[
vertex_group_length_name].index
particleObjMesh = particleObj.to_mesh(context.depsgraph,
apply_modifiers=True,
calc_undeformed=False)
seed(a=self.lenSeed, version=2)
embed = self.embed * 0.04 * diagonal
cpow = calc_power(self.noiseFalloff)
cpowClump = calc_power(self.ClumpingFalloff)
noiseFalloff = [pow(i / self.t_in_y, cpow) for i in range(self.t_in_y)]
ClumpFalloff = [
pow((i + 1) / self.t_in_y, cpowClump) for i in range(self.t_in_y)
]
for i, childRoot in enumerate(
pointsChildRoots
): #for each child find it three parents and genereate strands by barycentric transform
snappedPoint, normalChildRoot, rootHitIndex, distance = sourceSurface_BVHT.find_nearest(
childRoot, searchDistance)
childStrandRootNormals.append(normalChildRoot)
threeClosestParentRoots = kd.find_n(
childRoot, 3) #find three closes parent roots
rootTri_co, ParentRootIndices, distances = zip(
*threeClosestParentRoots) #split it into 3 arrays
sourceTri_BVHT = BVHTree.FromPolygons(
rootTri_co, [(0, 1, 2)],
all_triangles=True) # [0,1,2] - polygon == vert indices list
childRootSnapped, normalChildProjected, index, distance = sourceTri_BVHT.find_nearest(
childRoot, searchDistance
) #snap generated child to parent triangle ares \normals are sometimes flipped
childRootSnapped2, normalChildProjected2, index2, distance2 = sourceSurface_BVHT.find_nearest(
childRootSnapped,
searchDistance) #this gives ok normals always
lenWeight = 1
if length_ver_group_index != -1: # if vg exist
averageWeight = 0
for vertIndex in particleObjMesh.polygons[
rootHitIndex].vertices: #DONE: check if work on mesh with modifiers
for group in particleObjMesh.vertices[vertIndex].groups:
if group.group == length_ver_group_index:
averageWeight += group.weight
break
lenWeight = averageWeight / len(
particleObjMesh.polygons[rootHitIndex].vertices)
ranLen = uniform(-self.RandomizeLengthMinus,
self.RandomizeLengthPlus)
lenWeight *= (1 + ranLen)
# diff = childRoot - childRootSnapped
# mat_loc = Matrix.Translation(childRootSnapped)
# matTriangleSpaceInv = mat_loc #* rotMatrix
# matTriangleSpaceInv.invert()
rotQuat = normalChildProjected2.rotation_difference(
normalChildRoot)
translationMatrix = Matrix.Translation(childRoot)
rotMatrixRot = rotQuat.to_matrix().to_4x4()
mat_sca = Matrix.Scale(lenWeight, 4)
transformMatrix = translationMatrix @ rotMatrixRot
strandPoints = []
#for childRootSnapped points transform them from parent root triangles to parent next segment triangle t1,t2,t3
# and compensate child snapping to root triangle from before
for j, (t1, t2, t3) in enumerate(
zip(pointsList[ParentRootIndices[0]],
pointsList[ParentRootIndices[1]],
pointsList[ParentRootIndices[2]])):
pointTransformed = barycentric_transform(
childRootSnapped, rootTri_co[0], rootTri_co[1],
rootTri_co[2], Vector(t1), Vector(t2), Vector(t3))
childInterpolatedPoint = transformMatrix @ mat_sca @ (
pointTransformed - childRootSnapped
) #rotate child strand to original pos (from before snapt)
#do noise
noise.seed_set(self.Seed + i) # add seed per strand/ring ?
noiseVectorPerStrand = noise.noise_vector(
childInterpolatedPoint * self.freq / diagonal,
noise_basis='PERLIN_ORIGINAL'
) * noiseFalloff[j] * self.noiseAmplitude * diagonal / 10
# childInterpolatedPoint += noiseVectorPerStrand
#do clumping
diff = Vector(
t1
) - childInterpolatedPoint # calculate distance to parent strand (first strand from trio)
# point += noiseVectorPerStrand * noiseFalloff[j] * self.noiseAmplitude * diagonal / 10
# childClumped = childInterpolatedPoint + ClumpFalloff[j] * self.Clumping * diff + noiseVectorPerStrand * (1-ClumpFalloff[j])
childClumped = childInterpolatedPoint + ClumpFalloff[
j] * self.Clumping * diff + noiseVectorPerStrand * (
1 - ClumpFalloff[j] * self.Clumping)
# childClumped = childInterpolatedPoint + noiseVectorPerStrand
strandPoints.append(childClumped)
# embeding roots
diff = strandPoints[0] - strandPoints[1]
diff.normalize()
normalWeight = abs(diff.dot(normalChildRoot))
strandPoints[0] += (
diff * normalWeight - normalChildRoot * (1 - normalWeight)
) * embed # do childStrandRootNormal to move it more into mesh surface
childStrandsPoints.append(strandPoints)
bpy.data.meshes.remove(particleObjMesh)
# create the Curve Datablock
curveData = bpy.data.curves.new(particleObj.name + '_curve',
type='CURVE')
splinePointsNp = np.array(childStrandsPoints, dtype=np.float32)
if self.hairType != 'BEZIER':
splinePointsNpOnes = np.ones(
(len(childStrandsPoints), self.t_in_y, 4),
dtype=np.float32) # 4 coord x,y,z ,1
splinePointsNpOnes[:, :, :-1] = splinePointsNp
splinePointsNp = splinePointsNpOnes
for strandPoints in splinePointsNp: # for strand point
curveLength = len(strandPoints)
polyline = curveData.splines.new(self.hairType)
if self.hairType == 'BEZIER':
polyline.bezier_points.add(curveLength - 1)
elif self.hairType == 'POLY' or self.hairType == 'NURBS':
polyline.points.add(curveLength - 1)
if self.hairType == 'NURBS':
polyline.order_u = 3 # like bezier thing
polyline.use_endpoint_u = True
if self.hairType == 'BEZIER':
# polyline.bezier_points.co = (x, y, z)
polyline.bezier_points.foreach_set("co", strandPoints.ravel())
polyline.bezier_points.foreach_set('handle_left_type', 'AUTO')
polyline.bezier_points.foreach_set('handle_right_type', 'AUTO')
else:
polyline.points.foreach_set("co", strandPoints.ravel())
# polyline.points[i].co = (x, y, z, 1)
curveData.resolution_u = self.strandResU
curveData.dimensions = '3D'
# create Object
curveOB = bpy.data.objects.new(particleObj.name + '_curve', curveData)
curveOB.matrix_world = particleObj.matrix_world
scn = context.scene
scn.collection.objects.link(curveOB)
curveOB.targetObjPointer = particleObj.name # store source surface for snapping oper
context.view_layer.objects.active = curveOB
curveOB.select_set(True)
# curveOB.data.show_normal_face = False
if self.generateRibbons:
bpy.ops.object.generate_ribbons(strandResU=self.strandResU,
strandResV=self.strandResV,
strandWidth=self.strandWidth,
strandPeak=self.strandPeak,
strandUplift=self.strandUplift,
alignToSurface=self.alignToSurface)
HT_OT_CurvesUVRefresh.uvCurveRefresh(curveOB)
context.view_layer.objects.active = particleObj
else:
curveData.fill_mode = 'FULL'
curveData.bevel_depth = 0.004 * diagonal
curveData.bevel_resolution = 2
bpy.ops.object.curve_taper(TipRadiusFalloff=self.RadiusFalloff,
TipRadius=self.TipRadius,
MainRadius=self.Radius)
return {"FINISHED"}
def __init__(self, vertices):
self.kdt = kdtree.KDTree(len(vertices))
for i, v in enumerate(vertices):
self.kdt.insert(v, i)
self.kdt.balance()
self.__description__ = "Voronoi"
def particle_hair_to_points_with_children(self, context):
partsysMod = self.particleObj.particle_systems.active # use last
particle_id = self.particleObj.particle_systems.active_index # use last
particle_modal_settings = context.active_object.modal_hair.particle_system_modal_settings[
particle_id] # cos using self.particleObj gives random settings...
diagonal = self.diagonal
particle_count = len(partsysMod.particles)
if particle_count == 0: #require more that three strands
return self.particle_hair_to_points(context)
pointsList_hair = []
coords = []
global PARTICLE_CO #cache strands for drawing
strands_len = len(partsysMod.particles[0].hair_keys) - 1
for strand in partsysMod.particles: # for strand point
pointsList_hair.append([
hair_key.co for hair_key in strand.hair_keys
]) # DONE: exclude duplicates if first strand[0] in list already
if context.active_object.modal_hair.drawStrands:
for i, point in enumerate(
strand.hair_keys): # create p1,p2, p2,p3, p3,p4
if i == 0 or i == strands_len:
coords.append((point.co[0], point.co[1], point.co[2]))
else:
coords.extend([(point.co[0], point.co[1], point.co[2]),
(point.co[0], point.co[1], point.co[2])
])
else:
coords = [(0, 0, 0)]
PARTICLE_CO = coords
if particle_count == 1: #create two fake strands so that barycentric works
pointsList_hair.append([
x.xyz + Vector((0.01 * diagonal, 0, 0))
for x in pointsList_hair[0]
])
pointsList_hair.append([
x.xyz + Vector((0, 0.01 * diagonal, 0))
for x in pointsList_hair[0]
])
elif particle_count == 2: #create one fake strands so that barycentric works
pointsList_hair.append([
x.xyz + Vector((0.01 * diagonal, 0, 0))
for x in pointsList_hair[0]
])
#TODO: damm it is slow - 0.3 sec - on 3333 particle mesh (while doing sinterpol is just 0.02 sec)
#FIXED: it was here cos particles woudl fail on duplicates.... Fixed by removing duplis in init
# pointsList_uniq = []
# [pointsList_uniq.append(x) for x in pointsList_hair if x not in pointsList_uniq] # removing doubles (can cause zero size tris)
pointsList_uniq = pointsList_hair
# same_point_count cos barycentric transform requires it
pointsList = interpol_Catmull_Rom(
pointsList_uniq,
particle_modal_settings.t_in_y,
uniform_spacing=False,
same_point_count=True) # just gives smoother result on borders
searchDistance = 100 * diagonal
parentRoots = [strand[0]
for strand in pointsList] # first point of roots
# create nnew Part Sytem with uniform points
pointsChildRoots = HT_OT_RibbonsFromParticleHairChild.createUniformParticleSystem(
context, particle_modal_settings.childCount,
particle_modal_settings.PlacementJittering
) # return child part roots positions
kd = kdtree.KDTree(len(parentRoots))
for i, root in enumerate(parentRoots):
kd.insert(root, i)
kd.balance()
sourceSurface_BVHT = self.sourceSurface_BVHT
childStrandsPoints = [] # will contain strands with child points
childStrandRootNormals = []
seed(a=particle_modal_settings.lenSeed, version=2)
for i, childRoot in enumerate(
pointsChildRoots
): # for each child find it three parents and genereate strands by barycentric transform
snappedPoint, normalChildRoot, rootHitIndex, distance = sourceSurface_BVHT.find_nearest(
childRoot, searchDistance)
childStrandRootNormals.append(normalChildRoot)
threeClosestParentRoots = kd.find_n(
childRoot, 3) # find three closes parent roots
rootTri_co, ParentRootIndices, distances = zip(
*threeClosestParentRoots) # split it into 3 arrays
sourceTri_BVHT = BVHTree.FromPolygons(
rootTri_co, [(0, 1, 2)],
all_triangles=True) # [0,1,2] - polygon == vert indices list
childRootSnapped, normalChildProjected, index, distance = sourceTri_BVHT.find_nearest(
childRoot, searchDistance
) # snap generated child to parent triangle ares \normals are sometimes flipped
childRootSnapped2, normalChildProjected2, index2, distance2 = sourceSurface_BVHT.find_nearest(
childRootSnapped,
searchDistance) # this gives ok normals always
lenWeight = 1 + uniform(
-particle_modal_settings.RandomizeLengthMinus,
particle_modal_settings.RandomizeLengthPlus)
rotQuat = normalChildProjected2.rotation_difference(
normalChildRoot)
translationMatrix = Matrix.Translation(childRoot)
rotMatrixRot = rotQuat.to_matrix().to_4x4()
mat_sca = Matrix.Scale(lenWeight, 4)
transformMatrix = translationMatrix @ rotMatrixRot
strandPoints = []
# for childRootSnapped points transform them from parent root triangles to parent next segment triangle t1,t2,t3
# and compensate child snapping to root triangle from before
for j, (t1, t2, t3) in enumerate(
zip(pointsList[ParentRootIndices[0]],
pointsList[ParentRootIndices[1]],
pointsList[ParentRootIndices[2]])):
pointTransformed = barycentric_transform(
childRootSnapped, rootTri_co[0], rootTri_co[1],
rootTri_co[2], Vector(t1), Vector(t2), Vector(t3))
childInterpolatedPoint = transformMatrix @ mat_sca @ (
pointTransformed - childRootSnapped
) # rotate child strand to original pos (from before snapt)
strandPoints.append(childInterpolatedPoint)
childStrandsPoints.append(strandPoints)
if particle_modal_settings.use_parent_strands:
childStrandsPoints.extend(pointsList)
return childStrandsPoints
def create_u_core_vert_groups_vert_lists_2(bm, dimensions, margin, vert_locs,
subdivs):
"""Create vertex group vertex lists for U core sides
Args:
bm (bmesh): bmesh
dimensions (dict{
leg_1_inner: float,
leg_2_inner: float,
base_height: float,
height: float,
x_inner: float,
thickness: float,
thickness_diff: float}): core dimensions
margin (float): margin between textured and blank areas
vert_locs (dict{
Leg 1 Inner: list[Vector(3)]
Leg 2 Inner: list[Vector(3)]
Leg 1 Outer: list[Vector(3)]
Leg 2 Outer: list[Vector(3)]
Leg 1 End: list[Vector(3)]
Leg 2 End: list[Vector(3)]
End Wall Inner': list[Vector(3)]
End Wall Outer': list[Vector(3)]}: vertex locations
subdivs (dict{
leg_1: int,
leg_2: int,
x: int,
width: int,
height: int}): subdivisions
Returns:
dict{
Leg 1 Inner: list[BMVert],
Leg 1 Outer: list[BMVert],
Leg 2 Inner: list[BMVert],
Leg 2 Outer: list[BMVert],
Leg 1 Top: list[BMVert],
Leg 2 Top: list[BMVert],
Leg 1 Bottom: list[BMVert],
Leg 2 Bottom: list[BMVert],
Leg 1 End: list[BMVert],
Leg 2 End: list[BMVert],
End Wall Inner: list[BMVert],
End Wall Outer: list[BMVert],
End Wall Top: list[BMVert]
End Wall Bottom: list[BMVert]}: Verts to assign to vert groups
"""
height = dimensions['height']
thickness_diff = dimensions['thickness_diff']
thickness = dimensions['thickness']
leg_1_inner_len = dimensions['leg_1_inner'] + (thickness_diff / 2)
leg_2_inner_len = dimensions['leg_2_inner'] + (thickness_diff / 2)
leg_1_outer_len = leg_1_inner_len + thickness
leg_2_outer_len = leg_2_inner_len + thickness
vert_groups = {}
# create kdtree
size = len(bm.verts)
kd = kdtree.KDTree(size)
for i, v in enumerate(bm.verts):
kd.insert(v.co, i)
kd.balance()
# leg_sides
leg_sides = {
'Leg 1 Inner': (vert_locs['Leg 1 Inner'][::-1], leg_1_inner_len),
'Leg 2 Inner': (vert_locs['Leg 2 Inner'], leg_2_inner_len),
'Leg 1 Outer': (vert_locs['Leg 1 Outer'], leg_1_outer_len),
'Leg 2 Outer': (vert_locs['Leg 2 Outer'][::-1], leg_2_outer_len)
}
for key, value in leg_sides.items():
vert_groups[key] = select_verts_in_bounds(
lbound=(value[0][0]),
ubound=(value[0][-1][0], value[0][-1][1] + value[1],
value[0][-1][2] + height),
buffer=margin / 2,
bm=bm)
end_wall_sides = {
'End Wall Inner': vert_locs['End Wall Inner'],
'End Wall Outer': vert_locs['End Wall Outer'][::-1]
}
# end_wall_sides
for key, value in end_wall_sides.items():
vert_groups[key] = select_verts_in_bounds(
lbound=(value[0]),
ubound=(value[-1][0], value[-1][1], value[-1][2] + height),
buffer=margin / 2,
bm=bm)
# leg ends
ends = {
'Leg 1 End': vert_locs['Leg 1 End'],
'Leg 2 End': vert_locs['Leg 2 End']
}
for key, value in ends.items():
vert_groups[key] = select_verts_in_bounds(
lbound=(value[0]),
ubound=(value[1][0], value[1][1], value[1][2] + height),
buffer=margin / 2,
bm=bm)
bm_deselect_all(bm)
# bottom
# leg 1
inner_locs = vert_locs['Leg 1 Inner'][::-1]
outer_locs = vert_locs['Leg 1 Outer']
selected_verts = []
i = 0
while i < len(outer_locs) and i < len(inner_locs):
v1_co, v1_index, dist = kd.find(inner_locs[i])
v2_co, v2_index, dist = kd.find(outer_locs[i])
bm.verts.ensure_lookup_table()
v1 = bm.verts[v1_index]
v2 = bm.verts[v2_index]
nodes = bm_shortest_path(bm, v1, v2)
node = nodes[v2]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
selected_verts.extend(verts)
i += 1
vert_groups['Leg 1 Bottom'] = selected_verts
bm_deselect_all(bm)
# leg 2
inner_locs = vert_locs['Leg 2 Inner'][::-1]
outer_locs = vert_locs['Leg 2 Outer']
selected_verts = []
i = 0
while i < len(inner_locs) and i < len(outer_locs):
v1_co, v1_index, dist = kd.find(inner_locs[i])
v2_co, v2_index, dist = kd.find(outer_locs[i])
bm.verts.ensure_lookup_table()
v1 = bm.verts[v1_index]
v2 = bm.verts[v2_index]
nodes = bm_shortest_path(bm, v1, v2)
node = nodes[v2]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
selected_verts.extend(verts)
i += 1
vert_groups['Leg 2 Bottom'] = selected_verts
bm_deselect_all(bm)
# end wall
inner_locs = vert_locs['End Wall Inner'][::-1]
outer_locs = vert_locs['End Wall Outer']
selected_verts = []
i = 0
while i < len(inner_locs) and i < len(outer_locs):
v1_co, v1_index, dist = kd.find(inner_locs[i])
v2_co, v2_index, dist = kd.find(outer_locs[i])
bm.verts.ensure_lookup_table()
v1 = bm.verts[v1_index]
v2 = bm.verts[v2_index]
nodes = bm_shortest_path(bm, v1, v2)
node = nodes[v2]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
selected_verts.extend(verts)
i += 1
vert_groups['End Wall Bottom'] = selected_verts
bm_deselect_all(bm)
# top
vert_groups['Leg 1 Top'] = []
vert_groups['Leg 2 Top'] = []
vert_groups['End Wall Top'] = []
bm.verts.ensure_lookup_table()
for v in vert_groups['Leg 1 Bottom']:
v_co, v_index, dist = kd.find((v.co[0], v.co[1], v.co[2] + height))
vert_groups['Leg 1 Top'].append(bm.verts[v_index])
bm.verts.ensure_lookup_table()
for v in vert_groups['Leg 2 Bottom']:
v_co, v_index, dist = kd.find((v.co[0], v.co[1], v.co[2] + height))
vert_groups['Leg 2 Top'].append(bm.verts[v_index])
bm.verts.ensure_lookup_table()
for v in vert_groups['End Wall Bottom']:
v_co, v_index, dist = kd.find((v.co[0], v.co[1], v.co[2] + height))
vert_groups['End Wall Top'].append(bm.verts[v_index])
return vert_groups
def test_kdtree_invalid_size(self):
with self.assertRaises(ValueError):
kdtree.KDTree(-1)
def get_closest_vertex(self):
if hasattr(self.bm.verts, "ensure_lookup_table"):
self.bm.verts.ensure_lookup_table()
kd = kdtree.KDTree(len(self.bm.verts))
for i, v in enumerate(self.bm.verts):
kd.insert(v.co, i)
kd.balance()
kd_closest_vertex = kd.find_n(self.hit_location, MAX_SEARCH)
#print("kd_closest_vertex ", kd_closest_vertex)
#print(">Av ", self.active_vertex)
neighbors = []
for c in kd_closest_vertex:
v = self.bm.verts[c[1]]
if (len(self.bm.verts) == 1 or v.is_wire or v.is_boundary or v in self.active_solution[1]) and (v != self.active_vertex):
# 0 index, 1 distance, 2 hit distance, 3 score
neighbors.append([v, c[2], 0., [1.]])
#print("neighbors ", neighbors)
# Sort
n = float(len(neighbors))
if(n > 1):
max_hit_distance = -1.
#min_hit_distance = float('inf')
#max_distance = -1.
#min_distance = float('inf')
for i, v in enumerate(neighbors):
c_hit_distance, c_hit_normal = get_closest_ray_hit_test(v[0], self.object, self.snap_obj, self.hit_normal)
#print("c_hit_distance", c_hit_distance)
if(c_hit_normal != None):
v[3].append( (n - i) / n)
v[2] = c_hit_distance + SNAP_TOLERANCE
hit_conform = 1
if(not v[0].is_wire):
conform_angle = v[0].normal.angle(c_hit_normal, pi)
hit_conform = (-(conform_angle / pi)**2 + 1) / 2 + 0.5
v[3].append(hit_conform)
conform = 1
if(not v[0].is_wire):
conform_angle = v[0].normal.angle(self.hit_normal, pi)
conform = (-(conform_angle / pi)**2 + 1) / 2 + 0.5
v[3].append(conform)
#if(v[1] > max_distance): max_distance = v[1]
#if(v[1] < min_distance): min_distance = v[1]
if(v[2] > max_hit_distance): max_hit_distance = v[2]
#if(v[2] < min_hit_distance): min_hit_distance = v[2]
else:
v[3][0] = 0
for v in neighbors:
if ( (1. - v[2]/max_hit_distance) > 0.5):
v[3].append( 1.)
else:
v[3].append(.5)
#v[3].append(v[1] / max_distance)
neighbors.sort(key=lambda x: prod(x[3]), reverse=True)
if (neighbors != []):
#for v in neighbors:
#try:
# print("--- v %5d "% v[0].index, "| [dist %.3f, conform %.3f, snap dist %.3f]"% (v[3][1], v[3][2], v[3][3]))
#except:
# pass
return (neighbors[0][0], neighbors[0][1])
else:
return (None, None)
def add_geometry(self):
DEBUG = False
self.time_it = BL_TOOLS.TimeIt()
BL_DEBUG.clear_marks()
self.bm.verts.ensure_lookup_table()
self.bm.edges.ensure_lookup_table()
self.bm.faces.ensure_lookup_table()
# create a kd tree with the vertex positions
vertex = []
for v in self.selected_vertex:
if v.is_valid:
vertex.append(v.index)
# remove dupes
vertex = list(set(vertex))
kd = kdtree.KDTree(len(vertex))
for v in vertex:
##BL_DEBUG.set_mark(self.bm.verts[v].co,kind="CUBE",scale=0.2)
kd.insert(self.bm.verts[v].co, v)
kd.balance()
def nearest_points(kd, edge, v0, side, Nitems=7):
nearest = []
for (co, index, dist) in kd.find_n(v0, Nitems):
# calculate normals
A = self.obj_t.matrix_world @ edge[0].co
B = self.obj_t.matrix_world @ edge[1].co
C = self.obj_t.matrix_world @ co
normal_vec = Vector(B-A).cross(Vector(C-A))
normal_rl = normal_vec.z
if normal_rl < 0.0 and side.upper() == 'RIGHT':
nearest.append( (co, index, dist) )
if normal_rl > 0.0 and side.upper() == 'LEFT':
nearest.append( (co, index, dist) )
return(nearest)
# iterate my vertex, and find the nearest point my vertex
side_keys = { 0: 'right', 1: 'left', 'right': 0, 'left': 1}
count = 0
B = C = None
for plane in self.mesh_vertex:
print(plane)
nearest = {}
# calculate the nearest point for each point, for each side
for i in range(len(plane)):
if i == 0:
#right ARROWS->CUBES
kind = 'ARROWS'
else:
#left AXES->SPHERES
kind = 'PLAIN_AXES'
#BL_DEBUG.set_mark(self.obj_t.matrix_world @ plane[i][0].co,kind=kind)
#BL_DEBUG.set_mark(self.obj_t.matrix_world @ plane[i][1].co,kind=kind)
nearest[side_keys[i]] = [
nearest_points(kd, plane[i], self.obj_t.matrix_world @ plane[i][0].co, side_keys[i]),
nearest_points(kd, plane[i], self.obj_t.matrix_world @ plane[i][1].co, side_keys[i])
]
A = plane[0][1]
D = plane[0][0]
# lower point
if not C:
_,C,_ = nearest['right'][0][0]
_,B,_ = nearest['right'][1][0]
if B == C:
_,B,_ = nearest['right'][1][1]
else:
C = B
_,B,_ = nearest['right'][1][0]
if B == C:
_,B,_ = nearest['right'][1][1]
print(A,B,C,D)
# if not B in used_points.keys(): used_points[B] = 1
# if not C in used_points.keys(): used_points[C] = 1
# if B in used_points.keys() and used_points[B] < 2:
# used_points[B] += 1
# else:
# B = None
# if C in used_points.keys() and used_points[C] < 2:
# used_points[C] += 1
# else:
# C = None
# first point: nearest from top, and in nearest of bottom one.
a = nearest['right'][0]
print("r0-")
for i in a:
co,idx,dist = i
print(co,idx,dist)
DEBUG and BL_DEBUG.set_mark(co,kind="ARROWS")
a = nearest['right'][1]
print("r1-")
for i in a:
co,idx,dist = i
print(co,idx,dist)
DEBUG and BL_DEBUG.set_mark(co,kind="ARROWS")
a = nearest['left'][0]
print("l0-")
for i in a:
co,idx,dist = i
print(co,idx,dist)
DEBUG and BL_DEBUG.set_mark(co,kind="PLAIN_AXES")
a = nearest['left'][1]
print("l1-")
for i in a:
co,idx,dist = i
print(co,idx,dist)
DEBUG and BL_DEBUG.set_mark(co,kind="PLAIN_AXES")
## right side
# top_vertex_list = []
# for _,idx,_ in nearest['right'][1]:
# top_vertex_list.append(idx)
# bottom_vertex_list = []
# for _,idx,_ in nearest['right'][0]:
# bottom_vertex_list.append(idx)
# # default, first item
# # bottom
# pB = None
# get_next = False
# _,pA,_ = nearest['right'][0][0]
# for data in nearest['right'][0]:
# co,idx,dist = data
# if get_next:
# pA = idx
# break
# if idx in top_vertex_list and not pB:
# pB = pA
# get_next = True
# if not pB:
# _,pB,_ = nearest['right'][1][0]
# for data in nearest['right'][1]:
# co,idx,dist = data
# pB = idx
# break
if B and C:
pBv = self.bm.verts[B]
pCv = self.bm.verts[C]
DEBUG and BL_DEBUG.set_mark(pBv.co,kind="CUBE")
DEBUG and BL_DEBUG.set_mark(pCv.co,kind="CUBE")
bmesh.ops.contextual_create(self.bm, geom=[A, pBv, pCv, D])
self.bm.faces.index_update()
# ## left side
# top_vertex_list = []
# for i in nearest['left'][1]:
# co,idx,dist = i
# top_vertex_list.append(idx)
# bottom_vertex_list = []
# for i in nearest['left'][0]:
# co,idx,dist = i
# bottom_vertex_list.append(idx)
# # default, first item
# # bottom
# pD = None
# get_next = False
# _,pC,_ = nearest['left'][0][0]
# for data in nearest['left'][0]:
# co,idx,dist = data
# if get_next:
# pC = idx
# break
# if idx in top_vertex_list and not pD:
# pD = pC
# get_next = True
# if not pD:
# _,pD,_ = nearest['left'][1][0]
# for data in nearest['left'][1]:
# co,idx,dist = data
# pD = idx
# break
# pCv = self.bm.verts[pC]
# pDv = self.bm.verts[pD]
# DEBUG and BL_DEBUG.set_mark(pCv.co,kind="SPHERE")
# DEBUG and BL_DEBUG.set_mark(pDv.co,kind="SPHERE")
# if plane[0][1] != pBv and pBv != pAv and pAv != plane[0][0]:
# bmesh.ops.contextual_create(self.bm, geom=[plane[0][0], pAv, pBv, plane[0][1]])
# self.bm.faces.index_update()
# if plane[1][1] != pCv and pCv != pDv and pDv != plane[1][0]:
# bmesh.ops.contextual_create(self.bm, geom=[plane[1][1], plane[1][0], pDv, pCv])
# self.bm.faces.index_update()
# do just ones
count +=1
if count > 5:
break
# update the index of the new created verts. WTF ???
self.update_bm()
self.time_it.stop()
print("[t] add_geometry(): ", self.time_it)
#return(("ERROR", "Can't found terrain below the curve"))
return(("INFO", "Done"))
def update(self):
if 'vec' in self.inputs and 'edg' in self.inputs:
print(self.name, 'is starting')
if self.inputs['vec'].links and self.inputs['edg'].links:
vec = self.inputs['vec'].sv_get()
edg = self.inputs['edg'].sv_get()
vecplan = self.inputs['vecplan'].sv_get()
edgplan = self.inputs['edgplan'].sv_get()
loc = self.inputs['loc'].sv_get()
norm = self.inputs['norm'].sv_get()
thick = self.inputs['thick'].sv_get()[0][0]
sinuso60 = 0.8660254037844386
sinuso60_minus = 0.133974596
sinuso30 = 0.5
sinuso45 = 0.7071067811865475
if 'loccont' in self.inputs and self.inputs['loccont'].links and \
'normcont' in self.inputs and self.inputs['normcont'].links:
vecont = self.inputs['vecont'].sv_get()
loccont = self.inputs['loccont'].sv_get()
normcont = self.inputs['normcont'].sv_get()
vec_cont = Vector_generate(vecont)
loc_cont = Vector_generate(loccont)
norm_cont = Vector_generate(normcont)
else:
norm_cont = [[Vector((0,0,1)) for i in range(len(norm[0]))]]
loc_cont = [[Vector((0,0,10000)) for i in range(len(norm[0]))]]
vec_cont = [[Vector((1000,0,1))] for i in range(len(norm[0]))]
outeup = []
outelo = []
vupper = []
vlower = []
vec_ = Vector_generate(vec)
loc_ = Vector_generate(loc)
norm_ = Vector_generate(norm)
vecplan_ = Vector_generate(vecplan)
#print(self.name, 'veriables: \n', \
# vec_,'\n',
# vecplan_,'\n',
# loc_,'\n',
# loc_cont)
for l,n,vecp, edgp in zip(loc_[0],norm_[0],vecplan_,edgplan):
newinds1 = edgp.copy()
newinds2 = edgp.copy()
vupperob = vecp.copy()
vlowerob = vecp.copy()
deledges1 = []
deledges2 = []
k = 0
lenvep = len(vecp)
# KDtree collections closest to join edges to sockets
tree = KDT.KDTree(lenvep)
for i,v in enumerate(vecp):
tree.insert(v,i)
tree.balance()
# to define bounds
x = [i[0] for i in vecp]
y = [i[1] for i in vecp]
m1x,m2x,m1y,m2y = max(x), min(x), max(y), min(y)
# vertical edges iterations
# every edge is object - two points, one edge
for v in vec_:
# sort vertices by Z value
# find two vertices - one lower, two upper
vlist = [v[0],v[1]]
vlist.sort(key=lambda x: x[2], reverse=False)
# flip if coplanar to enemy plane
# flip plane coplanar
fliped = self.get_coplanar(v[0], loc_cont,norm_cont, vec_cont)
if fliped:
two, one = vlist
else:
one, two = vlist
# coplanar to owner
cop = abs(D2P(one,l,n))
# defining bounds
inside = one[0]<m1x and one[0]>m2x and one[1]<m1y and one[1]>m2y
# if in bounds and coplanar do:
#print(self.name,l, cop, inside)
if cop < 0.001 and inside:
'''
huge calculations. if we can reduce...
'''
# find shift for thickness in sockets
angle = radians(degrees(atan(n.y/n.x))+90)
thick_2 = thick/2
direction = Vector((cos(angle),sin(angle),0))*thick_2
#matr = Euler((0,0,angle),'YZX').to_matrix().to_4x4()
#matr.translation =
#direction = matr
# вектор, индекс, расстояние
# запоминаем порядок
# находим какие удалить рёбра
# делаем выборку левая-правая точка
nearv_1, near_1 = tree.find(one)[:2]
nearv_2, near_2 = tree.find(two)[:2]
# indexes of two nearest points
# удалить рёбра что мешают спать заодно
en_0, en_1, de1 = self.calc_indexes(edgp, near_1)
deledges1.extend(de1)
en_2, en_3, de2 = self.calc_indexes(edgp, near_2)
deledges2.extend(de2)
# old delete
# en_0,en_1 = [[t for t in i if t != near_1] for i in edgp if near_1 in i]
# en_2,en_3 = [[t for t in i if t != near_2] for i in edgp if near_2 in i]
# print(vecp, one, direction, en_0, en_1)
# left-right indexes and vectors
# с учётом интерполяций по высоте
left1, right1, l1, r1, lz1, rz1 = \
self.calc_leftright(vecp, one, direction, en_0, en_1, thick_2)
left2, right2, l2, r2, lz2, rz2 = \
self.calc_leftright(vecp, two, direction, en_2, en_3, thick_2)
# средняя точка и её смещение по толщине материала
three = (one-two)/2 + two
if self.rounded:
'''рёбра'''
if fliped:
doflip = -1
else:
doflip = 1
# пазы формируем независимо от верх низ
outeob1 = [[lenvep+k+8,lenvep+k],[lenvep+k+1,lenvep+k+2],
[lenvep+k+2,lenvep+k+3],[lenvep+k+3,lenvep+k+4],
[lenvep+k+4,lenvep+k+5],[lenvep+k+5,lenvep+k+6],
[lenvep+k+6,lenvep+k+7],[lenvep+k+7,lenvep+k+8],
[lenvep+k+9,lenvep+k+1]]
outeob2 = [[lenvep+k,lenvep+k+1],[lenvep+k+1,lenvep+k+2],
[lenvep+k+2,lenvep+k+3],[lenvep+k+3,lenvep+k+4],
[lenvep+k+4,lenvep+k+5],[lenvep+k+5,lenvep+k+6],
[lenvep+k+6,lenvep+k+7],[lenvep+k+7,lenvep+k+8],
[lenvep+k+8,lenvep+k+9]]
# наполнение списков lenvep = length(vecp)
newinds1.extend([[l1, lenvep+k], [lenvep+k+9, r1]])
newinds2.extend([[l2, lenvep+k+9], [lenvep+k, r2]])
'''Вектора'''
thick_3 = thick/3
thick_6 = thick/6
round1 = Vector((0,0,doflip*thick_3))
round2 = Vector((0,0,doflip*thick_3*sinuso30))
round2_= direction/3 + direction*(2*sinuso60/3)
round3 = Vector((0,0,doflip*thick_3*sinuso60_minus))
round3_= direction/3 + direction*(2*sinuso30/3)
round4 = direction/3
vupperob.extend([two-direction-Vector((0,0,lz2)),
three+round1-direction, three+round2-round2_,
three+round3-round3_, three-round4,
three+round4, three+round3+round3_,
three+round2+round2_, three+round1+direction,
two+direction-Vector((0,0,rz2))])
vlowerob.extend([one+direction-Vector((0,0,rz1)),
three-round1-direction, three-round2-round2_,
three-round3-round3_, three-round4,
three+round4, three-round3+round3_,
three-round2+round2_, three-round1+direction,
one-direction-Vector((0,0,lz1))])
k += 10
else:
'''рёбра'''
# пазы формируем независимо от верх низ
outeob1 = [[lenvep+k,lenvep+k+1],[lenvep+k+1,lenvep+k+2],[lenvep+k+2,lenvep+k+3]]
outeob2 = [[lenvep+k,lenvep+k+1],[lenvep+k+1,lenvep+k+2],[lenvep+k+2,lenvep+k+3]]
# наполнение списков lenvep = length(vecp)
newinds1.extend([[l1, lenvep+k], [lenvep+k+3, r1]])
newinds2.extend([[l2, lenvep+k+3], [lenvep+k, r2]])
'''Вектора'''
vupperob.extend([two-direction-Vector((0,0,lz2)), three-direction,
three+direction, two+direction-Vector((0,0,rz2))])
vlowerob.extend([one+direction-Vector((0,0,rz1)), three+direction,
three-direction, one-direction-Vector((0,0,lz1))])
k += 4
newinds1.extend(outeob1)
newinds2.extend(outeob2)
del tree
for e in deledges1:
if e in newinds1:
newinds1.remove(e)
for e in deledges2:
if e in newinds2:
newinds2.remove(e)
if vupperob or vlowerob:
outeup.append(newinds2)
outelo.append(newinds1)
vupper.append(vupperob)
vlower.append(vlowerob)
vupper = Vector_degenerate(vupper)
vlower = Vector_degenerate(vlower)
if 'vupper' in self.outputs and self.outputs['vupper'].links:
out = dataCorrect(vupper)
SvSetSocketAnyType(self, 'vupper', out)
if 'outeup' in self.outputs and self.outputs['outeup'].links:
SvSetSocketAnyType(self, 'outeup', outeup)
if 'vlower' in self.outputs and self.outputs['vlower'].links:
SvSetSocketAnyType(self, 'vlower', vlower)
if 'outelo' in self.outputs and self.outputs['outelo'].links:
SvSetSocketAnyType(self, 'outelo', outelo)
print(self.name, 'is finishing')
def __init__(self, context, cut_object, ui_type='DENSE_POLY'):
self.cut_ob = cut_object
self.bme = bmesh.new()
self.bme.from_mesh(cut_object.data)
self.bme.verts.ensure_lookup_table()
self.bme.edges.ensure_lookup_table()
self.bme.faces.ensure_lookup_table()
non_tris = [f for f in self.bme.faces if len(f.verts) > 3]
#if len(non_tris):
#geom = bmesh.ops.connect_verts_concave(self.bme, non_tris)
#self.bme.verts.ensure_lookup_table()
#self.bme.edges.ensure_lookup_table()
#self.bme.faces.ensure_lookup_table()
self.bvh = BVHTree.FromBMesh(self.bme)
self.cyclic = False
self.start_edge = None
self.end_edge = None
self.pts = []
self.cut_pts = [] #local points
self.normals = []
self.face_map = [] #all the faces that user drawn poly line fall upon
self.face_changes = [
] #the indices where the next point lies on a different face
self.face_groups = dict(
) #maps bmesh face index to all the points in user drawn polyline which fall upon it
self.new_ed_face_map = dict(
) #maps face index in bmesh to new edges created by bisecting
self.ed_map = [] #existing edges in bmesh crossed by cut line
self.new_cos = [] #location of crosses
self.non_man_eds = [
ed.index for ed in self.bme.edges if not ed.is_manifold
]
self.non_man_ed_loops = edge_loops_from_bmedges(
self.bme, self.non_man_eds)
#print(self.non_man_ed_loops)
self.non_man_points = []
self.non_man_bmverts = []
for loop in self.non_man_ed_loops:
self.non_man_points += [
self.cut_ob.matrix_world * self.bme.verts[ind].co
for ind in loop
]
self.non_man_bmverts += [self.bme.verts[ind].index for ind in loop]
if len(self.non_man_points):
kd = kdtree.KDTree(len(self.non_man_points))
for i, v in enumerate(self.non_man_points):
kd.insert(v, i)
kd.balance()
self.kd = kd
else:
self.kd = None
self.face_chain = set() #all faces crossed by the cut curve
if ui_type not in {'SPARSE_POLY', 'DENSE_POLY', 'BEZIER'}:
self.ui_type = 'SPARSE_POLY'
else:
self.ui_type = ui_type
self.selected = -1
self.hovered = [None, -1]
self.grab_undo_loc = None
self.start_edge_undo = None
self.end_edge_undo = None
self.mouse = (None, None)
#keep up with these to show user
self.bad_segments = []
self.split = False
self.face_seed = None
def add_geometry_edge(self):
"try to match near edges"
def edge_median(edge):
v0,v1 = edge.verts
median = v0.co + ((v0.co-v1.co)/2.0)
return(median)
def nearest_points(kd, edge, v0, side, Nitems=7):
nearest = []
for (co, index, dist) in kd.find_n(v0, Nitems):
# calculate normals
A = self.obj_t.matrix_world @ edge[0].co
B = self.obj_t.matrix_world @ edge[1].co
C = self.obj_t.matrix_world @ co
normal_vec = Vector(B-A).cross(Vector(C-A))
normal_rl = normal_vec.z
if normal_rl < 0.0 and side.upper() == 'RIGHT':
nearest.append( (co, index, dist) )
if normal_rl > 0.0 and side.upper() == 'LEFT':
nearest.append( (co, index, dist) )
return(nearest)
def nearest_edge(kd, edge, side, Nitems=7):
nearest = []
median = edge_median(edge)
for (co, index, dist) in kd.find_n(self.obj_t.matrix_world @ median, Nitems):
# calculate normals
A = self.obj_t.matrix_world @ edge.verts[0].co
B = self.obj_t.matrix_world @ edge.verts[1].co
C = self.obj_t.matrix_world @ co
normal_vec = Vector(B-A).cross(Vector(C-A))
normal_rl = normal_vec.z
if normal_rl < 0.0 and side.upper() == 'RIGHT':
nearest.append( (co, index, dist) )
if normal_rl > 0.0 and side.upper() == 'LEFT':
nearest.append( (co, index, dist) )
return(nearest)
DEBUG = False
self.time_it = BL_TOOLS.TimeIt()
BL_DEBUG.clear_marks()
self.bm.verts.ensure_lookup_table()
self.bm.edges.ensure_lookup_table()
self.bm.faces.ensure_lookup_table()
# create a kd tree with the median edge positions.
median_edges = []
for edge in self.inner_edges:
if edge.is_valid and edge.is_boundary:
median = edge_median(edge)
median_edges.append( (median, edge.index) )
kd = kdtree.KDTree(len(median_edges))
for median,idx in median_edges:
kd.insert(median, idx)
kd.balance()
# iterate my vertex, and find the nearest point my vertex
side_keys = { 0: 'right', 1: 'left', 'right': 0, 'left': 1}
count = 0
for plane in self.mesh_vertex:
print("plane", plane)
nearest = {}
# calculate the nearest point for each point, for each side
for i in range(len(plane)):
if i == 0:
#right ARROWS->CUBES
kind = 'ARROWS'
else:
#left AXES->SPHERES
kind = 'PLAIN_AXES'
#nearest[side_keys[i]] = [
# nearest_points(kd, plane[i], self.obj_t.matrix_world @ plane[i][0].co, side_keys[i]),
# nearest_points(kd, plane[i], self.obj_t.matrix_world @ plane[i][1].co, side_keys[i])
#]
# create the working edge
edge = [ plane[i][0], plane[i][1] ]
ret_geom = bmesh.ops.contextual_create(self.bm, geom= edge)
self.bm.edges.index_update()
self.update_bm()
for f in ret_geom['edges']:
if isinstance(f, bmesh.types.BMEdge):
edge = f
median = edge_median(edge)
BL_DEBUG.set_mark(self.obj_t.matrix_world @ median,kind='CUBE') ## mesh edge
n_edge = nearest_edge(kd, edge, side_keys[i])
# build the face, rebuild the tree
co,idx,_ = n_edge[0]
self.bm.verts.ensure_lookup_table()
self.bm.edges.ensure_lookup_table()
self.bm.faces.ensure_lookup_table()
BL_DEBUG.set_mark(self.obj_t.matrix_world @ co,kind='SPHERE') ## found edge
#ret_geom = bmesh.ops.contextual_create(self.bm, geom= [edge, self.bm.edges[idx]])
self.bm.edges.index_update()
self.update_bm()
# remove the edge from the table.
edges_tmp = []
for edge in self.inner_edges:
if edge.is_valid and edge.index != idx:
edges_tmp.append(edge)
self.inner_edges = edges_tmp
median_edges = []
for edge in self.inner_edges:
if edge.is_valid and edge.is_boundary:
median = edge_median(edge)
median_edges.append( (median, edge.index) )
kd = kdtree.KDTree(len(median_edges))
for median,idx in median_edges:
kd.insert(median, idx)
kd.balance()
# do just ones
count +=1
if count >=1:
break
# update the index of the new created verts. WTF ???
self.update_bm()
self.time_it.stop()
print("[t] add_geometry_edges(): ", self.time_it)
#return(("ERROR", "Can't found terrain below the curve"))
return(("INFO", "Done"))
def do_holes(self):
"get the plane, generate the info to raycast in the grid, select the matching faces"
self.time_it = BL_TOOLS.TimeIt()
EXTEND_SELECTION = True
TRIANGULATE_FACES = False # True
SUBDIVIDE_INNER_FACES = False
EXTEND_DELETE_SELECTION = False
SUBDIVIDE_INNER_EDGES = True
CALCULATE_NEAR_FACES = True
MIN_FACE_DIST = 3
BL_DEBUG.clear_marks()
# at this point XD point_data has
# terrain_up/down, face_index, point, location)
self.unselect_all()
self.selected_faces = []
# select faces tracked
for point in self.raycast_points:
terrain_down, index, point, location = point
self.bm.faces[index].select = True
if self.bm.faces[index] not in self.selected_faces:
self.selected_faces.append(self.bm.faces[index])
if EXTEND_SELECTION:
ret_geom = bmesh.ops.region_extend(self.bm,
geom=self.selected_faces,
use_faces=True,
use_face_step=False,
use_contract=False)
for f in ret_geom['geom']:
if isinstance(f, bmesh.types.BMFace):
f.select = True
self.selected_faces.append(f)
if SUBDIVIDE_INNER_FACES:
# subdivide the inner faces
#el_faces = [f for f in self.bm.faces if f.select]
face_edges = []
for f in self.selected_faces:
for e in f.edges:
face_edges.append(e.index)
face_edges = list(set(face_edges))
face_edges_geom = [self.bm.edges[i] for i in face_edges]
ret = bmesh.ops.subdivide_edges(self.bm, edges=face_edges_geom, cuts=2, use_grid_fill=True)
for f in ret['geom']:
if isinstance(f, bmesh.types.BMFace):
f.select = True
self.selected_faces.append(f)
if TRIANGULATE_FACES:
#triangulate
geom = [f for f in self.bm.faces if f.select]
ret_trig = bmesh.ops.triangulate(self.bm, faces=geom)
# select the new created triangles
for f in ret_trig['faces']:
f.select = True
self.selected_faces.append(f)
# 0. at this point, faces are triangulated, and selected
##############################################################
#
# 1. delete the faces recalculate again the faces
# this version only deletes the nearest faces from the
# road. Maybe it's a little narrow
#
##############################################################
self.update_bm()
#self.bm.verts.ensure_lookup_table()
#self.bm.edges.ensure_lookup_table()
self.bm.faces.ensure_lookup_table()
#
# I have to CHANGE to OBJECT in order to keep working on that
# and update the structure. After change, return to edit and
# keep working, it works.
#
# after triangulate, or adding more faces, there's a need of recalculate again the affected
# faces to make the hole
self.raycast_points = BL_TOOLS.get_raycast(self.plane, self.terrain,
vertices = self.plane_points,
DEBUG=self.DEBUG, LIMIT=self.LIMIT)
# at this point XD point_data has
# terrain_up/down, face_index, point, location)
BL_DEBUG.clear_marks()
faces_to_delete = {}
for item in self.raycast_points:
terrain_down, index, point, location = item
#print(terrain_down,index, point, location)
#BL_DEBUG.set_mark( obj_t.matrix_world @ location.xyz, kind="PLAIN_AXES" )
if index not in faces_to_delete.keys():
faces_to_delete[index] = self.bm.faces[index]
if EXTEND_DELETE_SELECTION:
for face in self.bm.faces: face.select = False
for f in faces_to_delete.keys():
self.bm.faces[f].select = True
#sel_verts = [v for v in self.bm.verts if v.select]
#sel_edges = [e for e in self.bm.edges if e.select]
selected_faces_local = [f for f in self.bm.faces if f.select]
geom = selected_faces_local
ret_geom = bmesh.ops.region_extend(self.bm,
geom=selected_faces_local,
use_faces=True,
use_face_step=False,
use_contract=False)
for f in ret_geom['geom']:
if isinstance(f, bmesh.types.BMFace):
faces_to_delete[f.index] = self.bm.faces[f.index]
# delete the result faces
faces_to_delete = list(faces_to_delete.values())
deleted_geom_edges = []
for f in faces_to_delete:
deleted_geom_edges += [e for e in f.edges]
bmesh.ops.delete(self.bm, geom=faces_to_delete, context='FACES_KEEP_BOUNDARY') # FACES_ONLY
# remove deleted faces from the selected container
#temp_faces = [f for f in self.selected_faces if f.is_valid]
#self.selected_faces = temp_faces
# this creates a subdivision of the inner vertex.
if SUBDIVIDE_INNER_EDGES:
# subdivide existing edges
keep_edges = []
for edge in deleted_geom_edges:
if edge.is_valid:
keep_edges.append(edge)
self.inner_edges = []
print("Inner edges: %d" % (len(keep_edges)*2))
geom_created = bmesh.ops.subdivide_edges(self.bm, edges=keep_edges, cuts=1, use_grid_fill=True)
for item in geom_created['geom_split']:
if isinstance(item, bmesh.types.BMVert):
pass
#item.select = True
#print(item.index)
#self.inner_edges.append(item)
if isinstance(item, bmesh.types.BMEdge):
#item.select = True
#print(item.index)
self.inner_edges.append(item)
if isinstance(item, bmesh.types.BMFace):
#item.select = True
print(item.index)
item.select = True
self.selected_faces.append(item)
print("Inner edges Subdivide: %d" % (len(self.inner_edges)*2) )
self.update_bm()
# create a KD tree for faces. add the center, and get only faces that are "near" in radious
if CALCULATE_NEAR_FACES:
valid_faces = [face for face in self.selected_faces if face.is_valid]
kd = kdtree.KDTree(len(valid_faces))
for face in valid_faces:
kd.insert(face.calc_center_median(), face.index)
kd.balance()
faces_to_delete = {}
verts_to_delete = {}
edges_to_delete = {}
self.bm.faces.ensure_lookup_table()
self.bm.verts.ensure_lookup_table()
self.bm.edges.ensure_lookup_table()
for item in self.raycast_points:
terrain_down, index, point, location = item
local_faces = []
local_point = self.plane_to_terrain_point(point.co)
for (co, index, dist) in kd.find_range(local_point, 200):
#print("face_local", index)
local_faces.append(self.bm.faces[index])
for f in local_faces:
# check for deleted faces!
if f.is_valid and f.index not in faces_to_delete.keys():
#center = BL_FLATTEN.DummyVector(f.calc_center_median())
for fv in f.verts:
#for fv in [center]:
vpw = self.obj_s.matrix_world @ point.co
vtw = self.obj_t.matrix_world @ fv.co
dist = (vpw.xy - vtw.xy).length
if dist < MIN_FACE_DIST:
#print("Face too near: ",f.index,dist)
faces_to_delete[f.index] = self.bm.faces[f.index]
for e in f.edges:
edges_to_delete[e.index] = self.bm.edges[e.index]
for v in f.verts:
verts_to_delete[v.index] = self.bm.verts[v.index]
faces_to_delete = list(faces_to_delete.values())
verts_to_delete = list(verts_to_delete.values())
edges_to_delete = list(edges_to_delete.values())
# FACES_ONLY
bmesh.ops.delete(self.bm, geom=verts_to_delete + edges_to_delete + faces_to_delete, context='FACES')
self.update_bm()
# now, just select the faces that are not select, but are in the edges.
# also select all the vertex in the keep edges that are not selected by default.
for e in self.inner_edges:
if not e.is_valid:
continue
for v in e.verts:
if not v.is_valid:
continue
v.select = True
for f in v.link_faces:
f.select = True
if f not in self.selected_faces:
self.selected_faces.append(f)
# select vertex that are in a boundary (internal)
self.selected_vertex = []
for e in self.bm.edges:
if e.is_valid and e.is_boundary:
for v in e.verts:
self.selected_vertex.append(v)
##############################################################
#
# End
# update the meshes
#
##############################################################
self.time_it.stop()
self.update_bm()
print("[t] do_holes(): ", self.time_it)
#return(("ERROR", "Can't found terrain below the curve"))
return(("INFO", "Done"))
def align_curve_tilt(context,
Curve,
align_target_bvht,
resetTilt=False,
onlySelection=False):
if Curve.mode == 'EDIT': # to make transfrom() work in edit mode
bpy.ops.object.mode_set(mode="OBJECT")
Curve.data.transform(Curve.matrix_world)
bpy.ops.object.mode_set(mode="EDIT")
else:
Curve.data.transform(Curve.matrix_world)
if resetTilt:
HT_OT_CurvesTiltAlign.resetTiltFunction(Curve.data, onlySelection)
curveBevelObj = Curve.data.bevel_object # backup
context.active_object.data.bevel_object = None # zero out to prevent changing default one
curveResU = Curve.data.resolution_u # backup
context.depsgraph.scene.update()
if 'Align_curve_helper' in bpy.data.objects.keys():
Curve.data.bevel_object = bpy.data.objects['Align_curve_helper']
else:
bpy.ops.object.generate_ribbons(
strandResV=2,
strandResU=curveResU,
strandWidth=0.01,
strandPeak=0,
skipInitProps=True) # for temp curve for tangent and normals
Curve.data.bevel_object.name = 'Align_curve_helper'
meFromCurve = Curve.to_mesh(context.depsgraph,
True,
calc_undeformed=False)
meshVertCount = len(meFromCurve.vertices)
kdMeshFromCurve = kdtree.KDTree(meshVertCount)
for i, v in enumerate(meFromCurve.vertices):
kdMeshFromCurve.insert(v.co, i)
kdMeshFromCurve.balance()
curveData = Curve.data
unitsScale = context.scene.unit_settings.scale_length
searchDistance = 10 / unitsScale
angleFlipFix = [-2 * math.pi, -math.pi, 2 * math.pi, math.pi]
for i, polyline in enumerate(curveData.splines): # for strand point
pointsNumber = len(
polyline.bezier_points) if polyline.type == 'BEZIER' else len(
polyline.points)
if polyline.type == 'NURBS' or polyline.type == 'POLY':
if onlySelection:
spline_selection_mask = np.zeros(pointsNumber,
dtype=np.bool)
polyline.points.foreach_get('select',
spline_selection_mask)
if not any(spline_selection_mask):
continue # if not even one pointis selected
points = polyline.points
else:
if onlySelection:
spline_selection_mask = np.zeros(pointsNumber,
dtype=np.bool)
polyline.bezier_points.foreach_get('select_control_point',
spline_selection_mask)
if not any(spline_selection_mask):
continue # if not even one point is selected
points = polyline.bezier_points
# helper for tangetnt function (to detect last point on cuve)
prevAngle = 0
corrective_angles = np.zeros(pointsNumber, dtype=np.float16)
current_tilt = np.zeros(pointsNumber, dtype=np.float16)
points.foreach_get('tilt', current_tilt)
for j, curvePoint in enumerate(points): # for strand point
pointOnMeshLoc, normSnapTarget, face_index, distance, isInside = \
HT_OT_CurvesTiltAlign.find_nearest(curvePoint.co.xyz, align_target_bvht, searchDistance)
# get vertex closest to spline point (for normal) from temp spline representation
co, index, dist = kdMeshFromCurve.find(curvePoint.co.xyz)
curveNormal = meFromCurve.vertices[index].normal
vecSurfaceHit = curvePoint.co.xyz - pointOnMeshLoc
if isInside: # if curve point is outside snapSurface flip it
vecSurfaceHit *= -1
# vecSurfaceHit = normSnapTarget * -1 # less accurate but faster...
if index + 3 < meshVertCount: # for last spline just use prvevangle
tangent = HT_OT_CurvesTiltAlign.get_tangents(
meFromCurve, index, j == pointsNumber -
1) # for bezier we can gets handles for tanget
biTangentCurve = tangent.cross(curveNormal)
vectSurfHitProjected90 = tangent.cross(vecSurfaceHit)
vectSurfHitProjectedToTangent = vectSurfHitProjected90.cross(
tangent)
# angle = biTangentCurve.angle(vectSurfHitProjectedToTangent) #unsigned angle 0 - 180
angle = angle_signed(
biTangentCurve, vectSurfHitProjectedToTangent,
tangent) - math.pi / 2 # a,b, vN - signed -180 to 180
if j > 1 and abs(
prevAngle - angle
) > math.pi / 2: # try fixing random flips in ribbons surface
fix = [
fix_angle for fix_angle in angleFlipFix
if abs(prevAngle - fix_angle - angle) < math.pi / 2
]
if len(fix) > 0:
angle += fix[0]
corrective_angles[j] = angle
prevAngle = angle
else:
corrective_angles[j] = prevAngle
# current_tilt = current_tilt + corrective_angles
if pointsNumber >= 4:
corrective_angles[1] = (corrective_angles[2] +
corrective_angles[3]) / 2
corrective_angles[0] = (corrective_angles[1] +
corrective_angles[2]) / 2
elif pointsNumber == 3:
corrective_angles[0] = (corrective_angles[1] +
corrective_angles[2]) / 2
if onlySelection:
current_tilt[spline_selection_mask] += corrective_angles[
spline_selection_mask]
else:
current_tilt += corrective_angles
points.foreach_set('tilt', current_tilt.ravel()) # in radians
# manually smooth first two points cos they are usually broken
bpy.data.meshes.remove(meFromCurve)
Curve.data.bevel_object = curveBevelObj # restore old bevel obj
was_edit = False
if Curve.mode == 'EDIT': # to make transfrom() work in edit mode
was_edit = True
bpy.ops.object.mode_set(mode="OBJECT")
Curve.data.transform(Curve.matrix_world.inverted())
if Curve.rotation_euler != Euler((0.0, 0.0, 0.0), 'XYZ') or min(
Curve.scale[:]
) < 0: # fix rot if curve rot is non 0,0,0, or scele x,y,z <0
override = {'selected_editable_objects': [Curve]}
if Curve.data.users > 1:
Curve.data = Curve.data.copy()
bpy.ops.object.transform_apply(override,
location=False,
rotation=True,
scale=True)
if was_edit:
bpy.ops.object.mode_set(mode="EDIT")
def __init__(self, points):
self.kdtree = kdtree.KDTree(len(points))
for i, v in enumerate(points):
self.kdtree.insert(v, i)
self.kdtree.balance()
def get_closest_vertex(self):
if hasattr(self.bm.verts, "ensure_lookup_table"):
self.bm.verts.ensure_lookup_table()
kd = kdtree.KDTree(len(self.bm.verts))
for i, v in enumerate(self.bm.verts):
kd.insert(v.co, i)
kd.balance()
kd_closest_vertex = kd.find_n(self.hit_location, MAX_SEARCH)
#print("kd_closest_vertex ", [v[1] for v in kd_closest_vertex])
#if(self.closest_vertex != None): print("Closest: ", self.closest_vertex.index)
neighbors = []
for c in kd_closest_vertex:
v = self.bm.verts[c[1]]
if (len(self.bm.verts) == 1 or v.is_wire or v.is_boundary or v
in self.active_solution[1]) and (v != self.active_vertex):
# 0 index, 1 distance, 2 hit distance, 3 score
neighbors.append([v, c[2], 0., []])
#print("neighbors ", neighbors)
# Sort
n = float(len(neighbors))
if (n > 1):
max_hit_distance = -1.
for i, v in enumerate(neighbors):
c_hit_distance, c_hit_normal = get_closest_ray_hit_test(
v[0], self.object, self.snap_obj, self.hit_normal)
#print("c_hit_distance", c_hit_distance)
if (c_hit_normal != None):
v[3].append((n - i) / n)
v[2] = c_hit_distance + SNAP_TOLERANCE
hit_conform = 1
conform_angle = v[0].normal.angle(c_hit_normal, pi)
hit_conform = (-(conform_angle / pi)**2 + 1) / 2 + 0.5
v[3].append(hit_conform)
conform = 1
conform_angle = v[0].normal.angle(self.hit_normal, pi)
conform = (-(conform_angle / pi)**2 + 1) / 2 + 0.5
v[3].append(conform)
if (v[0].is_wire):
v[3].append(0.8)
if (v[2] > max_hit_distance): max_hit_distance = v[2]
else:
v[3].append(0.)
for v in neighbors:
if ((1. - v[2] / max_hit_distance) > 0.5):
v[3].append(1.)
else:
v[3].append(.5)
##### Closest on surface # 0 index, 1 distance, 2 hit distance, 3 score
plane_distances = [
abs((v[0].co - self.hit_location).dot(self.hit_normal))
for v in neighbors
]
max_distance_to_plane = max(plane_distances)
for v, d in zip(neighbors, plane_distances):
v[3].append(cos(d * pi / 2 / max_distance_to_plane) / 2 + 0.5)
#####
neighbors.sort(key=lambda x: prod(x[3]), reverse=True)
if (neighbors != []):
#for v in neighbors:
#try:
#print("--- v %5d "% v[0].index, "| [dist %.3f, conform %.3f, conform self %.3f, proj %.3f]"% (v[3][0], v[3][1], v[3][2], v[3][4]), " | ", str(v[3]))
#except:
# pass
return (neighbors[0][0], neighbors[0][1])
else:
return (None, None)
def transfer(self, target, operator = None, transfer_type='Shape'):
context = bpy.context
s = self.get_shape_settings(target)
obj = self.id_data.dp_helper
ob = self.id_data
me = ob.data
source = context.selected_objects[:]
source.remove(ob)
if operator:
transfer_type = operator.transfer_type
#with obj.bm(1) as bm:
if transfer_type == 'Shape':
if not me.shape_keys:
ob.shape_key_add("Basis")
kb = me.shape_keys.key_blocks
for sk in s.transferable:
key = kb.get(sk.name)
if not key:
key = ob.shape_key_add(sk.name)
me.update()
source_ob = source[0].dp_helper
#print(operator,transfer_type)
with obj.bm(1) as bm:
indices_id = bm.verts.layers.int.get("indices_save")
if transfer_type == 'ID' and not indices_id:
indices_id = bm.verts.layers.int.new('indices_save')
with source_ob.bm() as sbm:
source_verts = sbm.verts
indices_id2 = sbm.verts.layers.int.get("indices_save")
if not indices_id2 or not indices_id :
operator.report({"ERROR"},"Store indices first in source AND target")
return
if transfer_type == 'ID':
from mathutils import kdtree
size = len(source_verts)
kd = kdtree.KDTree(size)
for i,v in enumerate(source_verts):
kd.insert(v.co, i)
kd.balance()
for i,v in enumerate(bm.verts):
if not v.select:continue
closest = kd.find_n(v.co,2)
#print(closest)
v[indices_id] = source_verts[closest[1][1]][indices_id2]
elif transfer_type == 'Shape':
mapped_source = { v[indices_id2]:v for v in source_verts }
for k in s.transferable:
source_shape_lay = sbm.verts.layers.shape.get(k.name)
target_lay = bm.verts.layers.shape.get(k.name)
#source_v = {
for v in bm.verts:
if mapped_source.get(v[indices_id]):
v[target_lay] = mapped_source[v[indices_id]][source_shape_lay]
me.update()
def process(self):
if 'vecLine' in self.inputs and \
'vecPlane' in self.inputs and \
'edgPlane' in self.inputs:
print(self.name, 'is starting')
if self.inputs['vecLine'].links and \
self.inputs['vecPlane'].links and \
self.inputs['edgPlane'].links:
if self.bindCircle:
circle = [ (Vector((sin(radians(i)),cos(radians(i)),0))*self.circle_rad)/4 \
for i in range(0,360,30) ]
vec = self.inputs['vecLine'].sv_get()
vecplan = self.inputs['vecPlane'].sv_get()
edgplan = self.inputs['edgPlane'].sv_get()
if len(edgplan[0][0]) > 2:
edgplan = pols_edges(edgplan)
thick = self.inputs['thick'].sv_get()[0][0]
threshold_coplanar = 0.005
sinuso60 = 0.8660254037844386
sinuso60_minus = 0.133974596
sinuso30 = 0.5
sinuso45 = 0.7071067811865475
thick_2 = thick / 2
thick_3 = thick / 3
thick_6 = thick / 6
threshold = self.threshold
if 'vecContr' in self.inputs and self.inputs['vecContr'].links:
vecont = self.inputs['vecContr'].sv_get()
#edgcont = self.inputs['edgContr'].sv_get()
vec_cont = Vector_generate(vecont)
loc_cont = [[i[0]] for i in vec_cont]
norm_cont = [[NM(i[0], i[len(i) // 2], i[-1])]
for i in vec_cont] # довести до ума
else:
vec_cont = []
if 'vecTube' in self.inputs and self.inputs['vecTube'].links:
vectube = self.inputs['vecTube'].sv_get()
vec_tube = Vector_generate(vectube)
tube_radius = self.inputs['radTube'].sv_get()[0][0]
circle_tube = [ (Vector((sin(radians(i)),cos(radians(i)),0))*tube_radius) \
for i in range(0,360,15) ]
else:
vec_tube = []
outeup = []
outelo = []
vupper = []
vlower = []
centers = []
vec_ = Vector_generate(vec)
vecplan_ = Vector_generate(vecplan)
for centersver, vecp, edgp in zip(vecplan, vecplan_, edgplan):
tubes_flag_bed_solution_i_know = False
newinds1 = [list(e) for e in edgp]
newinds2 = newinds1.copy()
vupperob = vecp.copy()
vlowerob = vecp.copy()
deledges1 = []
deledges2 = []
# to define bounds
x = [i[0] for i in vecp]
y = [i[1] for i in vecp]
z = [i[2] for i in vecp]
m1x, m2x, m1y, m2y, m1z, m2z = max(x), min(x), max(y), min(
y), max(z), min(z)
l = Vector(
(sum(x) / len(x), sum(y) / len(y), sum(z) / len(z)))
n_select = [vecp[0], vecp[len(vecp) // 2],
vecp[-1]] # довести до ума
n_select.sort(key=lambda x: sum(x[:]), reverse=False)
n_ = NM(n_select[0], n_select[1], n_select[2])
n_.normalize()
# а виновта ли нормаль?
if n_[0] < 0:
n = n_ * -1
else:
n = n_
cen = [sum(i) for i in zip(*centersver)]
centers.append(Vector(cen) / len(centersver))
k = 0
lenvep = len(vecp)
# KDtree collections closest to join edges to sockets
tree = KDT.KDTree(lenvep)
for i, v in enumerate(vecp):
tree.insert(v, i)
tree.balance()
# vertical edges iterations
# every edge is object - two points, one edge
for v in vec_:
if not v: continue
# sort vertices by Z value
# find two vertices - one lower, two upper
vlist = [v[0], v[1]]
vlist.sort(key=lambda x: x[2], reverse=False)
# flip if coplanar to enemy plane
# flip plane coplanar
if vec_cont:
fliped = self.get_coplanar(v[0], loc_cont,
norm_cont, vec_cont)
else:
fliped = False
shortedge = (vlist[1] - vlist[0]).length
if fliped:
two, one = vlist
else:
one, two = vlist
# coplanar to owner
cop = abs(D2P(one, l, n))
# defining bounds
inside = one[0]<m1x and one[0]>m2x and one[1]<m1y and one[1]>m2y \
and one[2]<=m1z and one[2]>=m2z
# if in bounds and coplanar do:
#print(self.name,l, cop, inside)
if cop < threshold_coplanar and inside and shortedge > thick * threshold:
'''
huge calculations. if we can reduce...
'''
# find shift for thickness in sockets
diry = two - one
diry.normalize()
# solution for vertical wafel - cool but not in diagonal case
# angle = radians(degrees(atan(n.y/n.x))+90)
dirx_ = self.rotation_on_axis(diry, n, radians(90))
dirx = dirx_ * thick_2
# вектор, индекс, расстояние
# запоминаем порядок находим какие удалить рёбра
# делаем выборку левая-правая точка
nearv_1, near_1 = tree.find(one)[:2]
nearv_2, near_2 = tree.find(two)[:2]
# indexes of two nearest points
# удалить рёбра что мешают спать заодно
en_0, en_1, de1 = self.calc_indexes(edgp, near_1)
deledges1.extend(de1)
en_2, en_3, de2 = self.calc_indexes(edgp, near_2)
deledges2.extend(de2)
# print(vecp, one, dirx, en_0, en_1)
# left-right indexes and vectors
# с учётом интерполяций по высоте
l1, r1, lz1, rz1 = \
self.calc_leftright(vecp, one, dirx, en_0, en_1, thick_2, diry)
l2, r2, lz2, rz2 = \
self.calc_leftright(vecp, two, dirx, en_2, en_3, thick_2, diry)
# print(left2, right2, l2, r2, lz2, rz2)
# средняя точка и её смещение по толщине материала
three = (one - two) / 2 + two
# rounded section
if self.rounded:
'''рёбра'''
# пазы формируем независимо от верх низ
outeob1 = [[lenvep + k + 8, lenvep + k],
[lenvep + k + 1, lenvep + k + 2],
[lenvep + k + 2, lenvep + k + 3],
[lenvep + k + 3, lenvep + k + 4],
[lenvep + k + 4, lenvep + k + 5],
[lenvep + k + 5, lenvep + k + 6],
[lenvep + k + 6, lenvep + k + 7],
[lenvep + k + 7, lenvep + k + 8],
[lenvep + k + 9, lenvep + k + 1]]
outeob2 = [[lenvep + k, lenvep + k + 1],
[lenvep + k + 1, lenvep + k + 2],
[lenvep + k + 2, lenvep + k + 3],
[lenvep + k + 3, lenvep + k + 4],
[lenvep + k + 4, lenvep + k + 5],
[lenvep + k + 5, lenvep + k + 6],
[lenvep + k + 6, lenvep + k + 7],
[lenvep + k + 7, lenvep + k + 8],
[lenvep + k + 8, lenvep + k + 9]]
# наполнение списков lenvep = length(vecp)
newinds1.extend([[l1, lenvep + k],
[lenvep + k + 9, r1]])
newinds2.extend([[l2, lenvep + k + 9],
[lenvep + k, r2]])
'''Вектора'''
round1 = diry * thick_3
round2 = diry * thick_3 * sinuso30
round2_ = dirx / 3 + dirx * (2 * sinuso60 / 3)
round3 = diry * thick_3 * sinuso60_minus
round3_ = dirx / 3 + dirx * (2 * sinuso30 / 3)
round4 = dirx / 3
vupperob.extend([
lz2, three + round1 - dirx,
three + round2 - round2_,
three + round3 - round3_, three - round4,
three + round4, three + round3 + round3_,
three + round2 + round2_,
three + round1 + dirx, rz2
])
vlowerob.extend([
rz1, three - round1 - dirx,
three - round2 - round2_,
three - round3 - round3_, three - round4,
three + round4, three - round3 + round3_,
three - round2 + round2_,
three - round1 + dirx, lz1
])
k += 10
# streight section
else:
'''рёбра'''
# пазы формируем независимо от верх низ
outeob1 = [[lenvep + k, lenvep + k + 1],
[lenvep + k + 1, lenvep + k + 2],
[lenvep + k + 2, lenvep + k + 3]]
outeob2 = [[lenvep + k, lenvep + k + 1],
[lenvep + k + 1, lenvep + k + 2],
[lenvep + k + 2, lenvep + k + 3]]
# наполнение списков lenvep = length(vecp)
newinds1.extend([[l1, lenvep + k],
[lenvep + k + 3, r1]])
newinds2.extend([[l2, lenvep + k + 3],
[lenvep + k, r2]])
'''Вектора'''
vupperob.extend(
[lz2, three - dirx, three + dirx, rz2])
vlowerob.extend(
[rz1, three + dirx, three - dirx, lz1])
k += 4
newinds1.extend(outeob1)
newinds2.extend(outeob2)
# circles to bing panels section
if self.bindCircle:
CP = self.circl_place
if CP == 'Midl':
crcl_cntr = IL2P(one, two, Vector(
(0, 0, 0)), Vector((0, 0, -1)))
elif CP == 'Up' and not fliped:
crcl_cntr = two - diry * self.circle_rad * 2
elif CP == 'Down' and not fliped:
crcl_cntr = one + diry * self.circle_rad * 2
elif CP == 'Up' and fliped:
crcl_cntr = one + diry * self.circle_rad * 2
elif CP == 'Down' and fliped:
crcl_cntr = two - diry * self.circle_rad * 2
# forgot howto 'else' in line iteration?
outeob1 = [[
lenvep + k + i, lenvep + k + i + 1
] for i in range(0, 11)]
outeob1.append([lenvep + k, lenvep + k + 11])
outeob2 = [[
lenvep + k + i, lenvep + k + i + 1
] for i in range(12, 23)]
outeob2.append(
[lenvep + k + 12, lenvep + k + 23])
newinds1.extend(outeob1 + outeob2)
newinds2.extend(outeob1 + outeob2)
mat_rot_cir = n.rotation_difference(
Vector((0, 0, 1))).to_matrix().to_4x4()
circle_to_add_1 = [vecir*mat_rot_cir+crcl_cntr+ \
dirx_*self.circle_rad for vecir in circle ]
circle_to_add_2 = [vecir*mat_rot_cir+crcl_cntr- \
dirx_*self.circle_rad for vecir in circle ]
vupperob.extend(circle_to_add_1 +
circle_to_add_2)
vlowerob.extend(circle_to_add_1 +
circle_to_add_2)
k += 24
# TUBE section
if vec_tube and not tubes_flag_bed_solution_i_know:
for v in vec_tube:
tubeverlength = len(v)
if tubeverlength == 2:
crcl_cntr = IL2P(v[0], v[1], l, n)
if crcl_cntr:
inside = crcl_cntr[0]<m1x and crcl_cntr[0]>m2x and crcl_cntr[1]<m1y \
and crcl_cntr[1]>m2y and crcl_cntr[2]<=m1z and crcl_cntr[2]>=m2z
if inside:
outeob = [[
lenvep + k + i,
lenvep + k + i + 1
] for i in range(0, 23)]
outeob.append([
lenvep + k, lenvep + k + 23
])
newinds1.extend(outeob)
newinds2.extend(outeob)
mat_rot_cir = n.rotation_difference(
Vector(
(0, 0, 1))).to_matrix(
).to_4x4()
circle_to_add = [
vecir * mat_rot_cir +
crcl_cntr
for vecir in circle_tube
]
vupperob.extend(circle_to_add)
vlowerob.extend(circle_to_add)
k += 24
else:
tubeshift = tubeverlength // 2
crcl_cntr = IL2P(
v[0], v[tubeshift], l, n)
if crcl_cntr:
inside = crcl_cntr[0]<m1x and crcl_cntr[0]>m2x and crcl_cntr[1]<m1y \
and crcl_cntr[1]>m2y and crcl_cntr[2]<=m1z and crcl_cntr[2]>=m2z
if inside:
outeob = [[
lenvep + k + i,
lenvep + k + i + 1
] for i in range(tubeshift - 1)
]
outeob.append([
lenvep + k,
lenvep + k + tubeshift - 1
])
newinds1.extend(outeob)
newinds2.extend(outeob)
for tubevert in range(
tubeshift):
tubevert_out = IL2P(
v[tubevert],
v[tubevert +
tubeshift], l, n)
vupperob.append(
tubevert_out)
vlowerob.append(
tubevert_out)
k += tubeshift
tubes_flag_bed_solution_i_know = True
elif cop < threshold_coplanar and inside and shortedge <= thick * threshold:
vupperob.extend([one, two])
vlowerob.extend([one, two])
newinds1.append([lenvep + k, lenvep + k + 1])
newinds2.append([lenvep + k, lenvep + k + 1])
k += 2
del tree
for e in deledges1:
if e in newinds1:
newinds1.remove(e)
for e in deledges2:
if e in newinds2:
newinds2.remove(e)
if vupperob or vlowerob:
outeup.append(newinds2)
outelo.append(newinds1)
vupper.append(vupperob)
vlower.append(vlowerob)
vupper = Vector_degenerate(vupper)
vlower = Vector_degenerate(vlower)
centers = Vector_degenerate([centers])
if 'vert' in self.outputs:
if self.out_up_down == 'Up':
out = dataCorrect(vupper)
else:
out = dataCorrect(vlower)
self.outputs['vert'].sv_set(out)
if 'edge' in self.outputs and self.outputs['edge'].links:
if self.out_up_down == 'Up':
self.outputs['edge'].sv_set(outeup)
else:
self.outputs['edge'].sv_set(outelo)
if 'centers' in self.outputs and self.outputs['centers'].links:
self.outputs['centers'].sv_set(centers)
print(self.name, 'is finishing')
def __init__(self, vertices):
self.kdt = kdtree.KDTree(len(vertices))
for i, v in enumerate(vertices):
self.kdt.insert(v, i)
self.kdt.balance()
def create_corner_vert_groups_vert_lists(bm, height, margin, vert_locs):
"""Return a dict containing lists of BMVerts to be added to vert groups
Args:
bm (bmesh): bmesh
obj (bpy.types.Object): Object
height (float): height
margin (float): margin size of untextured bit
deform_groups (bm.verts.layers.deform): deform groups - correspond to vertex groups
dict {
'Leg 1 Inner': list[Vector(3)],
'Leg 2 Inner': list[Vector(3)],
'Leg 1 Outer': list[Vector(3)],
'Leg 2 Outer': list[Vector(3)],
'Leg 1 End': list[Vector(3)],
'Leg 2 End': list[Vector(3)]} : Locations of bottom verts in each group
Returns:
dict {
'Leg 1 Inner': list[BMVert],
'Leg 2 Inner': list[BMVert],
'Leg 1 Outer': list[BMVert],
'Leg 2 Outer': list[BMVert],
'Leg 1 End': list[BMVert],
'Leg 2 End': list[BMVert]} : verts in each group
"""
# sides
sides = {
'Leg 1 Inner': vert_locs['Leg 1 Inner'],
'Leg 2 Inner': vert_locs['Leg 2 Inner'],
'Leg 1 Outer': vert_locs['Leg 1 Outer'],
'Leg 2 Outer': vert_locs['Leg 2 Outer']
}
vert_groups = {}
# create kdtree
size = len(bm.verts)
kd = kdtree.KDTree(size)
for i, v in enumerate(bm.verts):
kd.insert(v.co, i)
kd.balance()
for key, value in sides.items():
vert_group = []
for loc in value:
bottom_vert_co, index, dist = kd.find(loc)
verts = select_verts_in_bounds(lbound=bottom_vert_co,
ubound=(bottom_vert_co[0],
bottom_vert_co[1],
bottom_vert_co[2] + height),
buffer=margin / 2,
bm=bm)
vert_group.extend(verts)
vert_groups[key] = vert_group
bm_deselect_all(bm)
# ends
ends = {
'Leg 1 End': vert_locs['Leg 1 End'],
'Leg 2 End': vert_locs['Leg 2 End']
}
for key, value in ends.items():
v1_co, v1_index, dist = kd.find(value[0])
v2_co, v2_index, dist = kd.find(value[1])
bm.verts.ensure_lookup_table()
v1 = bm.verts[v1_index]
v2 = bm.verts[v2_index]
# select shortest path
nodes = bm_shortest_path(bm, v1, v2)
node = nodes[v2]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
selected_verts = []
for v in verts:
selected = select_verts_in_bounds(
v.co, (v.co[0], v.co[1], v.co[2] + height), margin / 2, bm)
selected_verts.extend(selected)
vert_groups[key] = selected_verts
bm_deselect_all(bm)
# bottom
# leg 1
inner_locs = vert_locs['Leg 1 Inner'][::-1]
outer_locs = vert_locs['Leg 1 Outer']
selected_verts = []
i = 0
while i < len(outer_locs) and i < len(inner_locs):
v1_co, v1_index, dist = kd.find(inner_locs[i])
v2_co, v2_index, dist = kd.find(outer_locs[i])
bm.verts.ensure_lookup_table()
v1 = bm.verts[v1_index]
v2 = bm.verts[v2_index]
nodes = bm_shortest_path(bm, v1, v2)
node = nodes[v2]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
selected_verts.extend(verts)
i += 1
vert_groups['Leg 1 Bottom'] = selected_verts
bm_deselect_all(bm)
# leg 2
inner_locs = vert_locs['Leg 2 Inner'][::-1]
outer_locs = vert_locs['Leg 2 Outer']
selected_verts = []
i = 0
while i < len(inner_locs) and i < len(outer_locs):
v1_co, v1_index, dist = kd.find(inner_locs[i])
v2_co, v2_index, dist = kd.find(outer_locs[i])
bm.verts.ensure_lookup_table()
v1 = bm.verts[v1_index]
v2 = bm.verts[v2_index]
nodes = bm_shortest_path(bm, v1, v2)
node = nodes[v2]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
selected_verts.extend(verts)
i += 1
vert_groups['Leg 2 Bottom'] = selected_verts
# assign_verts_to_group(selected_verts, obj, deform_groups, 'Leg 2 Bottom')
# top
# leg 1
inner_locs = vert_locs['Leg 1 Inner'][::-1]
outer_locs = vert_locs['Leg 1 Outer']
leg_1_top_verts = []
i = 0
while i < len(inner_locs) and i < len(outer_locs):
v1 = select_verts_in_bounds(
(inner_locs[i][0], inner_locs[i][1], inner_locs[i][2] + height),
(inner_locs[i][0], inner_locs[i][1], inner_locs[i][2] + height),
margin / 2, bm)
v2 = select_verts_in_bounds(
(outer_locs[i][0], outer_locs[i][1], outer_locs[i][2] + height),
(outer_locs[i][0], outer_locs[i][1], outer_locs[i][2] + height),
margin / 2, bm)
nodes = bm_shortest_path(bm, v1[0], v2[0])
node = nodes[v2[0]]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
leg_1_top_verts.extend(verts)
i += 1
vert_groups['Leg 1 Top'] = leg_1_top_verts
bm_deselect_all(bm)
# leg 2
inner_locs = vert_locs['Leg 2 Inner'][::-1]
outer_locs = vert_locs['Leg 2 Outer']
leg_2_top_verts = []
i = 0
while i < len(inner_locs) and i < len(outer_locs):
v1 = select_verts_in_bounds(
(inner_locs[i][0], inner_locs[i][1], inner_locs[i][2] + height),
(inner_locs[i][0], inner_locs[i][1], inner_locs[i][2] + height),
margin / 2, bm)
v2 = select_verts_in_bounds(
(outer_locs[i][0], outer_locs[i][1], outer_locs[i][2] + height),
(outer_locs[i][0], outer_locs[i][1], outer_locs[i][2] + height),
margin / 2, bm)
nodes = bm_shortest_path(bm, v1[0], v2[0])
node = nodes[v2[0]]
for e in node.shortest_path:
e.select_set(True)
bm.select_flush(True)
verts = [v for v in bm.verts if v.select]
leg_2_top_verts.extend(verts)
i += 1
vert_groups['Leg 2 Top'] = leg_2_top_verts
bm_deselect_all(bm)
return vert_groups
def execute(self, context):
sourceObj = context.active_object
TargetObjs = [
obj for obj in context.selected_objects
if obj != sourceObj and obj.type == 'MESH'
]
if not TargetObjs:
self.report({
'ERROR'
}, 'You seed to select two mesh objects (source then target that will receive vert order)! Cancelling'
)
return {'CANCELLED'}
bm = bmesh.new() # load mesh
bm.from_mesh(sourceObj.data)
src_obj_kd_verts = kdtree.KDTree(len(bm.verts))
for i, v in enumerate(bm.verts):
src_obj_kd_verts.insert(v.co, i)
src_obj_kd_verts.balance()
src_obj_kd_edges = kdtree.KDTree(len(bm.edges))
for i, edge in enumerate(bm.edges):
src_obj_kd_edges.insert((edge.verts[0].co + edge.verts[1].co) / 2,
i)
src_obj_kd_edges.balance()
src_obj_kd_faces = kdtree.KDTree(len(bm.faces))
for i, f in enumerate(bm.faces):
src_obj_kd_faces.insert(f.calc_center_median(), i)
src_obj_kd_faces.balance()
bm.free()
processedVertsIdDict = {}
processedEdgesIdDict = {}
processedFacesIdDict = {}
for target in TargetObjs:
copiedCount = 0
processedVertsIdDict.clear()
bm = bmesh.new() # load mesh
bm.from_mesh(target.data)
for vert in bm.verts:
co, index, dist = src_obj_kd_verts.find(vert.co)
if dist < self.delta: # delta
copiedCount += 1
vert.index = index
processedVertsIdDict[vert] = index
for edge in bm.edges:
co, index, dist = src_obj_kd_edges.find(
(edge.verts[0].co + edge.verts[1].co) / 2)
if dist < self.delta: #delta
copiedCount += 1
edge.index = index
processedEdgesIdDict[edge] = index
for face in bm.faces:
co, index, dist = src_obj_kd_faces.find(
face.calc_center_median())
if dist < self.delta: #delta
copiedCount += 1
face.index = index
processedFacesIdDict[face] = index
VOT_OT_PasteVertID.sortOtherVerts(processedVertsIdDict,
processedEdgesIdDict,
processedFacesIdDict, bm)
bm.verts.sort()
bm.edges.sort()
bm.faces.sort()
bm.to_mesh(target.data)
bm.free()
self.report({'INFO'},
'Pasted ' + str(copiedCount) + ' vert id\'s ')
return {"FINISHED"}