def test_path_extrude(self):
try:
import meshpy
except ImportError:
g.log.error("no meshpy: skipping test")
return
# Create base polygon
vec = g.np.array([0, 1]) * 0.2
n_comps = 100
angle = g.np.pi * 2.0 / n_comps
rotmat = g.np.array([
[g.np.cos(angle), -g.np.sin(angle)],
[g.np.sin(angle), g.np.cos(angle)]])
perim = []
for i in range(n_comps):
perim.append(vec)
vec = g.np.dot(rotmat, vec)
poly = g.Polygon(perim)
# Create 3D path
angles = g.np.linspace(0, 8 * g.np.pi, 1000)
x = angles / 10.0
y = g.np.cos(angles)
z = g.np.sin(angles)
path = g.np.c_[x, y, z]
# Extrude
mesh = g.trimesh.creation.sweep_polygon(poly, path)
self.assertTrue(mesh.is_volume)
def test_path_sweep(self):
if len(self.engines) == 0:
return
# Create base polygon
vec = g.np.array([0, 1]) * 0.2
n_comps = 100
angle = g.np.pi * 2.0 / n_comps
rotmat = g.np.array([[g.np.cos(angle), -g.np.sin(angle)],
[g.np.sin(angle),
g.np.cos(angle)]])
perim = []
for i in range(n_comps):
perim.append(vec)
vec = g.np.dot(rotmat, vec)
poly = g.Polygon(perim)
# Create 3D path
angles = g.np.linspace(0, 8 * g.np.pi, 1000)
x = angles / 10.0
y = g.np.cos(angles)
z = g.np.sin(angles)
path = g.np.c_[x, y, z]
# Extrude
mesh = g.trimesh.creation.sweep_polygon(poly, path)
assert mesh.is_volume
def check_nearest_point_function(self, fun):
def plot_tri(tri, color='g'):
plottable = g.np.vstack((tri, tri[0]))
plt.plot(plottable[:, 0], plottable[:, 1], color=color)
def points_on_circle(count):
theta = g.np.linspace(0, g.np.pi * 2, count + 1)[:count]
s = g.np.column_stack((theta, [g.np.pi / 2] * count))
t = g.trimesh.util.spherical_to_vector(s)
return t
# inscribed triangle on a circle on the XY plane
triangle = points_on_circle(3)
# a circle of points surrounding the triangle
query = points_on_circle(63) * 2
# set the points up in space
query[:, 2] = 10
# a circle of points inside the triangle
query = g.np.vstack((query, query * .1))
mesh = g.Trimesh(**g.trimesh.triangles.to_kwargs([triangle]))
result, result_distance, result_tid = fun(mesh, query)
polygon = g.Polygon(triangle[:, 0:2])
polygon_buffer = polygon.buffer(1e-5)
# all of the points returned should be on the triangle we're querying
broken = g.np.array([not polygon_buffer.intersects(
g.Point(i)) for i in result[:, 0:2]])
# see what distance shapely thinks the nearest point is for the 2D triangle
# and the query points
distance_shapely = g.np.array(
[polygon.distance(g.Point(i)) for i in query[:, 0:2]])
# see what distance our function returned for the nearest point
distance_ours = ((query[:, 0:2] - result[:, 0:2])
** 2).sum(axis=1) ** .5
# how far was our distance from the one shapely gave
distance_test = g.np.abs(distance_shapely - distance_ours)
'''
# plot test to debug failures
import matplotlib.pyplot as plt
plottable = g.np.column_stack((result[:,0:2], query[:,0:2])).reshape((-1,2,2))
plot_tri(triangle, color='g')
for i in plottable:
plt.plot(*i.T, color='b')
plt.scatter(*result[:,0:2].T, color='k')
plt.scatter(*result[broken][:,0:2].T, color='r')
plt.show()
'''
self.assertFalse(broken.any())
self.assertTrue(distance_test.max() < g.trimesh.constants.tol.merge)
return result, result_distance
def check_nearest_point_function(self, fun):
# def plot_tri(tri, color='g'):
# plottable = g.np.vstack((tri, tri[0]))
# plt.plot(plottable[:, 0], plottable[:, 1], color=color)
def points_on_circle(count):
theta = g.np.linspace(0, g.np.pi * 2, count + 1)[:count]
s = g.np.column_stack((theta, [g.np.pi / 2] * count))
t = g.trimesh.util.spherical_to_vector(s)
return t
# generate some pseudorandom triangles
# use our random to avoid spurious failures
triangles = g.random((100, 3, 3)) - 0.5
# put them on- plane
triangles[:, :, 2] = 0.0
# make one of the triangles equilaterial
triangles[-1] = points_on_circle(3)
# a circle of points surrounding the triangle
query = points_on_circle(63) * 2
# set the points up in space
query[:, 2] = 10
# a circle of points inside-ish the triangle
query = g.np.vstack((query, query * .1))
# loop through each triangle
for triangle in triangles:
# create a mesh with one triangle
mesh = g.Trimesh(**g.trimesh.triangles.to_kwargs([triangle]))
result, result_distance, result_tid = fun(mesh, query)
polygon = g.Polygon(triangle[:, 0:2])
polygon_buffer = polygon.buffer(1e-5)
# all of the points returned should be on the triangle we're
# querying
assert all(polygon_buffer.intersects(
g.Point(i)) for i in result[:, 0:2])
# see what distance shapely thinks the nearest point
# is for the 2D triangle and the query points
distance_shapely = g.np.array([polygon.distance(g.Point(i))
for i in query[:, :2]])
# see what distance our function returned for the nearest point
distance_ours = ((query[:, :2] - result[:, :2])
** 2).sum(axis=1) ** .5
# how far was our distance from the one shapely gave
distance_test = g.np.abs(distance_shapely - distance_ours) # NOQA
# we should have calculated the same distance as shapely
assert g.np.allclose(distance_ours, distance_shapely)
# now check to make sure closest point doesn't depend on
# the frame, IE the results should be the same after
# any rigid transform
# chop query off to same length as triangles
assert len(query) > len(triangles)
query = query[:len(triangles)]
# run the closest point query as a corresponding query
close = g.trimesh.triangles.closest_point(triangles=triangles,
points=query)
# distance between closest point and query point
# this should stay the same regardless of frame
distance = g.np.linalg.norm(close - query, axis=1)
for T in g.transforms:
# transform the query points
points = g.trimesh.transform_points(query, T)
# transform the triangles we're checking
tri = g.trimesh.transform_points(
triangles.reshape((-1, 3)), T).reshape((-1, 3, 3))
# run the closest point check
check = g.trimesh.triangles.closest_point(triangles=tri,
points=points)
check_distance = g.np.linalg.norm(check - points, axis=1)
# should be the same in any frame
assert g.np.allclose(check_distance, distance)
return result, result_distance
