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Commit a6984734 authored by dboe's avatar dboe
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renaming 3D -> _3d

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tfields/__init__.py
View file @ a6984734
# flake8: noqa: F401
"""Top-level package of tfields."""
__author__ = """Daniel Böckenhoff"""
......@@ -5,13 +6,13 @@ __email__ = "dboe@ipp.mpg.de"
__version__ = "0.3.3"
# methods:
from tfields.core import dim, rank # NOQA
from tfields.mask import evalf # NOQA
from tfields.core import dim, rank
from tfields.mask import evalf
# classes:
from tfields.core import Tensors, TensorFields, TensorMaps, Container, Maps # NOQA
from tfields.points3D import Points3D # NOQA
from tfields.mesh3D import Mesh3D # NOQA
from tfields.triangles3D import Triangles3D # NOQA
from tfields.planes3D import Planes3D # NOQA
from tfields.bounding_box import Node # NOQA
from tfields.core import Tensors, TensorFields, TensorMaps, Container, Maps
from tfields.points_3d import Points3D
from tfields.mesh_3d import Mesh3D
from tfields.triangles_3d import Triangles3D
from tfields.planes_3d import Planes3D
from tfields.bounding_box import Node
tfields/mesh3D.py → tfields/mesh_3d.py
View file @ a6984734
......@@ -4,48 +4,48 @@
Author: Daniel Boeckenhoff
Mail: daniel.boeckenhoff@ipp.mpg.de
part of tfields library
Triangulated mesh class and methods
"""
import logging
import os
import numpy as np
import rna
import tfields
# obj imports
from tfields.lib.decorators import cached_property
import logging
import os
def _dist_from_plane(point, plane):
return plane["normal"].dot(point) + plane["d"]
def _segment_plane_intersection(p0, p1, plane):
def _segment_plane_intersection(point0, point1, plane):
"""
Get the intersection between the ray spanned by p0 and p1 with the plane.
Get the intersection between the ray spanned by point0 and point1 with the plane.
Args:
p0: array of length 3
p1: array of length 3
point0: array of length 3
point1: array of length 3
plane:
Returns:
points, direction
points (list of arrays of length 3): 3d points
"""
distance0 = _dist_from_plane(p0, plane)
distance1 = _dist_from_plane(p1, plane)
p0_on_plane = abs(distance0) < np.finfo(float).eps
p1_on_plane = abs(distance1) < np.finfo(float).eps
distance0 = _dist_from_plane(point0, plane)
distance1 = _dist_from_plane(point1, plane)
point0_on_plane = abs(distance0) < np.finfo(float).eps
point1_on_plane = abs(distance1) < np.finfo(float).eps
points = []
direction = 0
if p0_on_plane:
points.append(p0)
if point0_on_plane:
points.append(point0)
if p1_on_plane:
points.append(p1)
if point1_on_plane:
points.append(point1)
# remove duplicate points
if len(points) > 1:
points = np.unique(points, axis=0)
if p0_on_plane and p1_on_plane:
if point0_on_plane and point1_on_plane:
return points, direction
if distance0 * distance1 > np.finfo(float).eps:
......@@ -54,14 +54,14 @@ def _segment_plane_intersection(p0, p1, plane):
direction = np.sign(distance0)
if abs(distance0) < np.finfo(float).eps:
return points, direction
elif abs(distance1) < np.finfo(float).eps:
if abs(distance1) < np.finfo(float).eps:
return points, direction
if abs(distance0 - distance1) > np.finfo(float).eps:
t = distance0 / (distance0 - distance1)
else:
return points, direction
points.append(p0 + t * (p1 - p0))
points.append(point0 + t * (point1 - point0))
# remove duplicate points
if len(points) > 1:
points = np.unique(points, axis=0)
......
tfields/planes3D.py → tfields/planes_3d.py
View file @ a6984734
......@@ -31,8 +31,10 @@ class Planes3D(tfields.TensorFields):
Returns:
list: list with sympy.Plane objects
"""
return [sympy.Plane(point, normal_vector=vector)
for point, vector in zip(self, self.fields[0])]
return [
sympy.Plane(point, normal_vector=vector)
for point, vector in zip(self, self.fields[0])
]
def plot(self, **kwargs): # pragma: no cover
"""
......@@ -42,14 +44,11 @@ class Planes3D(tfields.TensorFields):
centers = np.array(self)
norms = np.array(self.fields[0])
for i in range(len(self)):
artists.append(
rna.plotting.plot_plane(
centers[i],
norms[i],
**kwargs))
artists.append(rna.plotting.plot_plane(centers[i], norms[i], **kwargs))
return artists
if __name__ == '__main__': # pragma: no cover
if __name__ == "__main__": # pragma: no cover
import doctest
doctest.testmod()
tfields/points3D.py → tfields/points_3d.py
View file @ a6984734
......@@ -135,9 +135,10 @@ class Points3D(tfields.Tensors):
>>> assert p.equal(p_cart, atol=1e-15)
"""
def __new__(cls, tensors, **kwargs):
if not issubclass(type(tensors), Points3D):
kwargs['dim'] = 3
kwargs["dim"] = 3
return super(Points3D, cls).__new__(cls, tensors, **kwargs)
def balls(self, radius, spacing=(5, 3)):
......@@ -149,13 +150,15 @@ class Points3D(tfields.Tensors):
tfields.Mesh3D: Builds a sphere around each point with a resolution
defined by spacing and given radius
"""
sphere = tfields.Mesh3D.grid((radius, radius, 1),
(-np.pi, np.pi, spacing[0]),
(-np.pi / 2, np.pi / 2, spacing[1]),
coord_sys='spherical')
sphere.transform('cartesian')
sphere = tfields.Mesh3D.grid(
(radius, radius, 1),
(-np.pi, np.pi, spacing[0]),
(-np.pi / 2, np.pi / 2, spacing[1]),
coord_sys="spherical",
)
sphere.transform("cartesian")
balls = []
with self.tmp_transform('cartesian'):
with self.tmp_transform("cartesian"):
for point in self:
ball = sphere.copy()
ball += point
......@@ -163,7 +166,8 @@ class Points3D(tfields.Tensors):
return tfields.Mesh3D.merged(*balls)
if __name__ == '__main__': # pragma: no cover
if __name__ == "__main__": # pragma: no cover
import doctest
doctest.testmod()
# doctest.run_docstring_examples(Points3D, globals())
tfields/triangles3D.py → tfields/triangles_3d.py
View file @ a6984734
......@@ -39,14 +39,15 @@ class Triangles3D(tfields.TensorFields):
"""
def __new__(cls, tensors, *fields, **kwargs):
kwargs['dim'] = 3
kwargs['rigid'] = False
kwargs["dim"] = 3
kwargs["rigid"] = False
obj = super(Triangles3D, cls).__new__(cls, tensors, *fields, **kwargs)
if not len(obj) % 3 == 0:
warnings.warn("Input object of size({0}) has no divider 3 and"
" does not describe triangles."
.format(len(obj)))
warnings.warn(
"Input object of size({0}) has no divider 3 and"
" does not describe triangles.".format(len(obj))
)
return obj
def ntriangles(self):
......@@ -105,13 +106,16 @@ class Triangles3D(tfields.TensorFields):
# apply triangle index to fields
if tri_index is not None:
item.fields = [field.__getitem__(tri_index)
for field in item.fields]
item.fields = [
field.__getitem__(tri_index) for field in item.fields
]
else:
item = tfields.Tensors(item)
except IndexError:
logging.warning("Index error occured for field.__getitem__. Error "
"message: {err}".format(**locals()))
logging.warning(
"Index error occured for field.__getitem__. Error "
"message: {err}".format(**locals())
)
return item
@classmethod
......@@ -121,6 +125,7 @@ class Triangles3D(tfields.TensorFields):
Given a path to a stl file, construct the object
"""
import stl.mesh
triangles = stl.mesh.Mesh.from_file(path)
obj = cls(triangles.vectors.reshape(-1, 3))
return obj
......@@ -128,12 +133,13 @@ class Triangles3D(tfields.TensorFields):
@classmethod
def merged(cls, *objects, **kwargs):
with warnings.catch_warnings():
warnings.filterwarnings('ignore')
warnings.filterwarnings("ignore")
obj = super(Triangles3D, cls).merged(*objects, **kwargs)
if not len(obj) % 3 == 0:
warnings.warn("Input object of size({0}) has no divider 3 and"
" does not describe triangles."
.format(len(obj)))
warnings.warn(
"Input object of size({0}) has no divider 3 and"
" does not describe triangles.".format(len(obj))
)
return obj
def evalf(self, expression=None, coord_sys=None):
......@@ -189,9 +195,7 @@ class Triangles3D(tfields.TensorFields):
Returns:
tfields.Mesh3D
"""
mp = tfields.TensorFields(
np.arange(len(self)).reshape((-1, 3)),
*self.fields)
mp = tfields.TensorFields(np.arange(len(self)).reshape((-1, 3)), *self.fields)
mesh = tfields.Mesh3D(self, maps=[mp])
return mesh.cleaned(stale=False) # stale vertices can not occure here
......@@ -237,30 +241,33 @@ class Triangles3D(tfields.TensorFields):
# define 3 vectors building the triangle, transform it back and take their norm
if not np.array_equal(transform, np.eye(3)):
a = np.linalg.norm(np.linalg.solve(transform.T,
(self[aIndices, :] -
self[bIndices, :]).T),
axis=0)
b = np.linalg.norm(np.linalg.solve(transform.T,
(self[aIndices, :] -
self[cIndices, :]).T),
axis=0)
c = np.linalg.norm(np.linalg.solve(transform.T,
(self[bIndices, :] -
self[cIndices, :]).T),
axis=0)
a = np.linalg.norm(
np.linalg.solve(
transform.T, (self[aIndices, :] - self[bIndices, :]).T
),
axis=0,
)
b = np.linalg.norm(
np.linalg.solve(
transform.T, (self[aIndices, :] - self[cIndices, :]).T
),
axis=0,
)
c = np.linalg.norm(
np.linalg.solve(
transform.T, (self[bIndices, :] - self[cIndices, :]).T
),
axis=0,
)
else:
a = np.linalg.norm(self[aIndices, :] - self[bIndices, :],
axis=1)
b = np.linalg.norm(self[aIndices, :] - self[cIndices, :],
axis=1)
c = np.linalg.norm(self[bIndices, :] - self[cIndices, :],
axis=1)
a = np.linalg.norm(self[aIndices, :] - self[bIndices, :], axis=1)
b = np.linalg.norm(self[aIndices, :] - self[cIndices, :], axis=1)
c = np.linalg.norm(self[bIndices, :] - self[cIndices, :], axis=1)
# sort by length for numerical stability
lengths = np.concatenate(
(a.reshape(-1, 1), b.reshape(-1, 1), c.reshape(-1, 1)),
axis=1)
(a.reshape(-1, 1), b.reshape(-1, 1), c.reshape(-1, 1)), axis=1
)
lengths.sort()
a, b, c = lengths.T
......@@ -300,18 +307,22 @@ class Triangles3D(tfields.TensorFields):
"""
pointA, pointB, pointC = self.corners()
a = np.linalg.norm(pointC - pointB, axis=1) # side length of side opposite to pointA
a = np.linalg.norm(
pointC - pointB, axis=1
) # side length of side opposite to pointA
b = np.linalg.norm(pointC - pointA, axis=1)
c = np.linalg.norm(pointB - pointA, axis=1)
bary1 = a ** 2 * (b ** 2 + c ** 2 - a ** 2)
bary2 = b ** 2 * (a ** 2 + c ** 2 - b ** 2)
bary3 = c ** 2 * (a ** 2 + b ** 2 - c ** 2)
matrices = np.concatenate((pointA, pointB, pointC), axis=1).reshape(pointA.shape + (3,))
matrices = np.concatenate((pointA, pointB, pointC), axis=1).reshape(
pointA.shape + (3,)
)
# transpose the inner matrix
matrices = np.einsum('...ji', matrices)
matrices = np.einsum("...ji", matrices)
vectors = np.array((bary1, bary2, bary3)).T
# matrix vector product for matrices and vectors
P = np.einsum('...ji,...i', matrices, vectors)
P = np.einsum("...ji,...i", matrices, vectors)
P /= vectors.sum(axis=1).reshape((len(vectors), 1))
return tfields.Points3D(P)
......@@ -324,7 +335,9 @@ class Triangles3D(tfields.TensorFields):
nT = self.ntriangles()
mat = np.ones((1, 3)) / 3.0
# matrix product calculatesq center of all triangles
return tfields.Points3D(np.dot(mat, self.reshape(nT, 3, 3))[0], coord_sys=self.coord_sys)
return tfields.Points3D(
np.dot(mat, self.reshape(nT, 3, 3))[0], coord_sys=self.coord_sys
)
"""
Old version:
......@@ -387,7 +400,7 @@ class Triangles3D(tfields.TensorFields):
np.place(norms, norms == 0.0, 1.0)
return vectors / norms
def _baricentric(self, point, delta=0.):
def _baricentric(self, point, delta=0.0):
"""
Determine baricentric coordinates like
......@@ -446,14 +459,22 @@ class Triangles3D(tfields.TensorFields):
ap = point - a
# matrix vector product for matrices and vectors
barCoords = np.einsum('...ji,...i', self._baricentric_matrix, ap)
barCoords = np.einsum("...ji,...i", self._baricentric_matrix, ap)
with warnings.catch_warnings():
# python2.7
warnings.filterwarnings('ignore', message="invalid value encountered in divide")
warnings.filterwarnings('ignore', message="divide by zero encountered in divide")
warnings.filterwarnings(
"ignore", message="invalid value encountered in divide"
)
warnings.filterwarnings(
"ignore", message="divide by zero encountered in divide"
)
# python3.x
warnings.filterwarnings('ignore', message="invalid value encountered in true_divide")
warnings.filterwarnings('ignore', message="divide by zero encountered in true_divide")
warnings.filterwarnings(
"ignore", message="invalid value encountered in true_divide"
)
warnings.filterwarnings(
"ignore", message="divide by zero encountered in true_divide"
)
barCoords[:, 2] /= delta # allow devide by 0.
return barCoords
......@@ -468,15 +489,16 @@ class Triangles3D(tfields.TensorFields):
norm = np.cross(ab, ac)
normLen = np.linalg.norm(norm, axis=1)
normLen = normLen.reshape((1,) + normLen.shape)
colinear_mask = (normLen == 0)
colinear_mask = normLen == 0
with warnings.catch_warnings():
warnings.filterwarnings('ignore', category=np.VisibleDeprecationWarning)
warnings.filterwarnings("ignore", category=np.VisibleDeprecationWarning)
# prevent divide by 0
norm[np.where(~colinear_mask.T)] = \
norm[np.where(~colinear_mask.T)] = (
norm[np.where(~colinear_mask.T)] / normLen.T[np.where(~colinear_mask.T)]
)
matrix = np.concatenate((ab, ac, norm), axis=1).reshape(ab.shape + (3,))
matrix = np.einsum('...ji', matrix) # transpose the inner matrix
matrix = np.einsum("...ji", matrix) # transpose the inner matrix
# invert matrix if possible
# matrixI = np.linalg.inv(matrix) # one line variant without exception
......@@ -486,13 +508,14 @@ class Triangles3D(tfields.TensorFields):
matrixI.append(np.linalg.inv(mat))
except np.linalg.linalg.LinAlgError as e:
if str(e) == "Singular matrix":
warnings.warn("Singular matrix: Could not invert matrix "
"{0}. Return nan matrix."
.format(str(mat).replace('\n', ',')))
warnings.warn(
"Singular matrix: Could not invert matrix "
"{0}. Return nan matrix.".format(str(mat).replace("\n", ","))
)
matrixI.append(np.full((3, 3), np.nan))
return np.array(matrixI)
def _in_triangles(self, point, delta=0.):
def _in_triangles(self, point, delta=0.0):
"""
Barycentric method to optain, wheter a point is in any of the triangles
......@@ -562,46 +585,50 @@ class Triangles3D(tfields.TensorFields):
try:
point = np.reshape(point, 3)
except ValueError:
raise ValueError("point must be castable to shape 3 but is of shape {0}"
.format(point.shape))
raise ValueError(
"point must be castable to shape 3 but is of shape {0}".format(
point.shape
)
)
# min_dist_method switch if delta is None
if delta is None:
delta = 1.
delta = 1.0
min_dist_method = True
else:
min_dist_method = False
u, v, w = self._baricentric(point, delta=delta).T
if delta == 0.:
w[np.isnan(w)] = 0. # division by 0 in baricentric makes w = 0 nan.
if delta == 0.0:
w[np.isnan(w)] = 0.0 # division by 0 in baricentric makes w = 0 nan.
with warnings.catch_warnings():
warnings.filterwarnings(
'ignore',
message="invalid value encountered in less_equal")
barycentric_bools = ((v <= 1.) & (v >= 0.))\
& ((u <= 1.) & (u >= 0.))\
& ((v + u <= 1.0))
"ignore", message="invalid value encountered in less_equal"
)
barycentric_bools = (
((v <= 1.0) & (v >= 0.0)) & ((u <= 1.0) & (u >= 0.0)) & ((v + u <= 1.0))
)
if all(~barycentric_bools):
return barycentric_bools
if min_dist_method:
orthogonal_acceptance = np.full(
barycentric_bools.shape, False, dtype=bool)
barycentric_bools.shape, False, dtype=bool
)
closest_indices = np.argmin(abs(w)[barycentric_bools])
# transform the indices to the whole array, not only the
# barycentric_bools selection
closest_indices = np.arange(
len(barycentric_bools)
)[barycentric_bools][closest_indices]
closest_indices = np.arange(len(barycentric_bools))[barycentric_bools][
closest_indices
]
orthogonal_acceptance[closest_indices] = True
else:
orthogonal_acceptance = (abs(w) <= 1)
orthogonal_acceptance = abs(w) <= 1
return np.array(barycentric_bools & orthogonal_acceptance)
def in_triangles(self, tensors, delta=0., assign_multiple=False):
def in_triangles(self, tensors, delta=0.0, assign_multiple=False):
"""
Barycentric method to obtain, which tensors are containes in any of the triangles
......@@ -654,7 +681,7 @@ class Triangles3D(tfields.TensorFields):
"""
faceMembershipIndices = np.argmax(masks, axis=1)
# True if point lies in any triangle
membershipBools = (masks.sum(axis=1) != 0)
membershipBools = masks.sum(axis=1) != 0
masks = np.full(masks.shape, False, dtype=bool)
for j, valid in enumerate(membershipBools):
......@@ -693,12 +720,14 @@ class Triangles3D(tfields.TensorFields):
... np.array([False, False, True], dtype=bool))
"""
u, v, w = self._baricentric(point, 1.).T
u, v, w = self._baricentric(point, 1.0).T
orthogonal_acceptance = (w == 0) # point should lie in triangle
barycentric_bools = (((0. <= v) & (v <= 1.)) & (u == 0.)) | \
(((0. <= u) & (u <= 1.)) & (v == 0.)) | \
(v + u == 1.0)
orthogonal_acceptance = w == 0 # point should lie in triangle
barycentric_bools = (
(((0.0 <= v) & (v <= 1.0)) & (u == 0.0))
| (((0.0 <= u) & (u <= 1.0)) & (v == 0.0))
| (v + u == 1.0)
)
return np.array(barycentric_bools & orthogonal_acceptance)
def _weights(self, weights, rigid=False):
......@@ -722,6 +751,7 @@ class Triangles3D(tfields.TensorFields):
return super(Triangles3D, self)._weights(weights, rigid=rigid)
if __name__ == '__main__': # pragma: no cover
if __name__ == "__main__": # pragma: no cover
import doctest
doctest.testmod()
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