class ImplicitSurface(object):
def __init__(self, points, normals):
self._log = logging.getLogger('ImplicitSurface')
self.points = points
self.normals = normals
self.tree = cKDTree(self.points)
# choose distance threshold and eps depending on bbox diameter
min_point, max_point = self.get_bounding_box()
self.box_diag = norm(max_point - min_point)
self.eps = self.box_diag * 0.1
self.center = min_point + 0.5 * (max_point - min_point)
# cache mls results
self.mls_subdivisions = None
self.mls_distances = []
self.mls_normals = []
self.mls_points = []
@classmethod
def from_file(cls, filename):
logging.getLogger('SurfaceFactory').info(u"Reading surface from '%s'..." % filename)
vertices = []
normals = []
for vertex, normal in openOff(filename).iter_vertices_and_normals():
vertices.append(vertex)
normals.append(normal)
return cls(points=vertices, normals=normals)
def get_bounding_box(self, expansion_factor=0.2):
"""Returns the minumum and maximum corners of the bounding box.
:Parameters:
expansion_factor : float
The factor by which to enlarge the bounding box.
:return: (min_point, max_point)
"""
min_point = min(self.points, 0)
max_point = max(self.points, 0)
diff = max_point - min_point
min_point -= diff*expansion_factor
max_point += diff*expansion_factor
return (min_point, max_point)
def get_parameter_grid(self, subdivisions, degree=None):
if degree:
self.calculate_mls_values(subdivisions, degree)
if self.mls_subdivisions:
self._log.debug(u"Calculating colors...")
colors = zeros(((subdivisions+2)**3,), dtype='4f')
max_abs_distance = max([abs(min(self.mls_distances)), abs(max(self.mls_distances))])
for index, distance in enumerate(self.mls_distances):
if distance < 0:
colors[index] = (0.0, 0.0, 1.0, 0.0)
else:
colors[index] = (0.0, 1.0, 0.0, 0.0)
colors[index] *= (1.0 - abs(float(distance)/max_abs_distance))**4
colors[index] += (0.0, 0.0, 0.0, 1.0)
else:
self._log.debug(u"Using plain colors...")
colors = None
return PointCloudNode(
name = 'parameter grid',
points = [(x,y,z) for x,y,z in self.iter_regular_xyz_grid_points(subdivisions)],
color = (0.0,1.0,0.0,0.6),
colors = colors)
def get_original_point_cloud(self):
return PointCloudNode(
name = 'point cloud',
points = self.points,
color = (1.0, 1.0, 1.0, 1.0))
def calculate_mls_values(self, subdivisions, degree):
if self.mls_subdivisions != subdivisions:
self.distance_threshold = self.box_diag / float(subdivisions + 1)
self.square_solver = MinSquares(self)
self._log.debug(u"Calculating mls grid values...")
self.mls_subdivisions = subdivisions
self.mls_distances = zeros(((subdivisions+2)**3,), dtype='f')
self.mls_normals = zeros(((subdivisions+2)**3,), dtype='3f')
self.mls_points = zeros(((subdivisions+2)**3,), dtype='3f')
for index, point in enumerate(self.iter_regular_xyz_grid_points(subdivisions)):
distance, normal = self.square_solver.solveEquations(point, degree)
self.mls_distances[index] = distance
self.mls_normals[index] = normal
self.mls_points[index] = point
else:
self._log.debug(u"Using cached mls grid values...")
def get_implicit_surface(self, subdivisions, degree):
self.calculate_mls_values(subdivisions, degree)
return MarchingCubeNode(
name = "implicit_surface",
surface = self,
color = (1.0, 0.0, 0.0, 1.0),
wireframe = False)
# TODO: perform marching cubes algorithm
# return SurfaceNode(
# name = 'mls surface',
# width = subdivisions+2,
# height = subdivisions+2,
# points = self.mls_points,
# normals= self.mls_normals,
# color = (1.0,0.0,0.0,0.9))
def iter_regular_xyz_grid_points(self, subdivisions):
min_point, max_point = self.get_bounding_box()
for x in linspace(min_point[0], max_point[0], subdivisions+2):
for y in linspace(min_point[1], max_point[1], subdivisions+2):
for z in linspace(min_point[2], max_point[2], subdivisions+2):
#self._log.debug(u"Yielding (%f, %f)..." % (x, y))
yield (x, y, z)
class Surface(object):
def __init__(self, points):
self._log = logging.getLogger('Surface')
self.mapping = {}
for point in points:
self.mapping[point[0:2]] = point[2]
self.points = self.mapping.keys()
self.tree = KDTree(self.points)
self.square_solver = MinSquares(self)
# cache mls results
self.mls_subdivisions = None
self.mls_points = None
@classmethod
def from_file(cls, filename):
logging.getLogger('SurfaceFactory').info(u"Reading surface from '%s'..." % filename)
return cls(openOff(filename).iter_vertices())
def get_parameter_plane(self, subdivisions):
return SurfaceNode(
name = 'parameter plane',
width = subdivisions+2,
height = subdivisions+2,
points = [(x,y,0) for x,y in self.iter_regular_xy_grid_points(subdivisions)],
color = (1.0,1.0,1.0,0.9),
wireframe = True)
def get_original_point_cloud(self):
return PointCloudNode(
name = 'point cloud',
points = self.mapping,
color = (1.0, 1.0, 1.0, 0.9))
def get_mls_interpolated_surface(self, subdivisions):
if self.mls_subdivisions != subdivisions:
points_normals = [(x,y) + self.square_solver.solveEquations((x,y)) for x,y in self.iter_regular_xy_grid_points(subdivisions)]
self.mls_points = [(x,y,z) for x,y,z,n in points_normals]
self.mls_normals = [n for x,y,z,n in points_normals]
self.mls_subdivisions = subdivisions
return SurfaceNode(
name = 'mls surface',
width = subdivisions+2,
height = subdivisions+2,
points = self.mls_points,
normals= self.mls_normals,
color = (1.0,0.0,0.0,0.9))
def get_bezier_interpolated_surface(self, mls_subdivisions, bezier_factor):
self._log.debug(u"Creating surface using grid %d and bezier factor %d" % (mls_subdivisions, bezier_factor))
if self.mls_subdivisions != mls_subdivisions:
self.get_mls_interpolated_surface(mls_subdivisions)
value_matrix = transpose(reshape(array(self.mls_points)[:,2], (mls_subdivisions+2, mls_subdivisions+2)), (1,0))
casteljau = Casteljau(value_matrix)
points_normals = [(x,y) + casteljau.evaluate_point((x,y)) for x,y in self.iter_regular_xy_grid_points(mls_subdivisions*bezier_factor)]
return SurfaceNode(
name = 'bezier surface',
width = mls_subdivisions*bezier_factor+2,
height = mls_subdivisions*bezier_factor+2,
points = [(x,y,z) for x,y,z,n in points_normals],
normals= [n for x,y,z,n in points_normals],
color = (0.0,1.0,0.0,0.5))
def iter_regular_xy_grid_points(self, subdivisions):
min_point = min(self.points, 0)
max_point = max(self.points, 0)
for x in linspace(min_point[0], max_point[0], subdivisions+2):
for y in linspace(min_point[1], max_point[1], subdivisions+2):
#self._log.debug(u"Yielding (%f, %f)..." % (x, y))
yield (x, y)
