def voxel_matches_polygon(self, coordinate_list):
for voxel_coords in coordinate_list:
voxel_coords = np.asarray(voxel_coords)
rmax = voxel_coords[:, 0].max()
rmin = voxel_coords[:, 0].min()
zmax = voxel_coords[:, 1].max()
zmin = voxel_coords[:, 1].min()
router = 1.5 * rmax
rinner = 0.5 * rmin
zupper = 1.5 * zmax if zmax > 0 else 0.5 * zmax
zlower = 0.5 * zmin if zmin > 0 else 1.5 * zmin
test_rs = np.linspace(rinner, router, int(100 * (router - rinner)))
test_zs = np.linspace(zlower, zupper, int(100 * (zupper - zlower)))
voxel_vertex_points = [Point2D(*v) for v in voxel_coords]
voxel = AxisymmetricVoxel(voxel_vertex_points,
parent=None,
primitive_type='csg')
polygon = Polygon(voxel_coords, closed=True)
test_verts = list(itertools.product(test_rs, test_zs))
try:
inside_poly = polygon.contains_points(test_verts)
except AttributeError:
# Polygon.contains_points was only introduced in Matplotlib 2.2.
# Before that we need to convert to Path
inside_poly = Path(
polygon.get_verts()).contains_points(test_verts)
inside_csg = [
any(
child.contains(Point3D(r, 0, z))
for child in voxel.children) for (r, z) in test_verts
]
self.assertSequenceEqual(inside_csg, inside_poly.tolist())
def voxel_matches_polygon(self, coordinate_list):
for voxel_coords in coordinate_list:
voxel_coords = np.asarray(voxel_coords)
rmax = voxel_coords[:, 0].max()
rmin = voxel_coords[:, 0].min()
zmax = voxel_coords[:, 1].max()
zmin = voxel_coords[:, 1].min()
router = 1.5 * rmax
rinner = 0.5 * rmin
zupper = 1.5 * zmax if zmax > 0 else 0.5 * zmax
zlower = 0.5 * zmin if zmin > 0 else 1.5 * zmin
test_rs = np.linspace(rinner, router, int(50 * (router - rinner)))
test_zs = np.linspace(zlower, zupper, int(50 * (zupper - zlower)))
# Test for 0 area: not supported by mesh representation
x, y = voxel_coords.T
area = 0.5 * np.abs(np.dot(x, np.roll(y, 1)) - np.dot(y, np.roll(x, 1)))
if area == 0:
continue
voxel = AxisymmetricVoxel(voxel_coords, primitive_type='mesh')
polygon = Polygon(voxel_coords, closed=True).get_path()
test_verts = list(itertools.product(test_rs, test_zs))
inside_poly = polygon.contains_points(test_verts)
inside_voxel = [any(child.contains(Point3D(r, 0, z)) for child in voxel.children)
for (r, z) in test_verts]
# Due to numerical precision, some points may be inside the
# Matplotlib polygon but not the Mesh. Check in this case that the
# "failing" points are just very close to the edge of the polygon
fails = np.nonzero(np.not_equal(inside_voxel, inside_poly))[0]
for fail in fails:
if inside_voxel[fail] and not inside_poly[fail]:
# Polygon should be made slightly bigger
inside_poly[fail] = polygon.contains_point(test_verts[fail], radius=-0.01)
elif inside_poly[fail] and not inside_voxel[fail]:
# Polygon should be made slightly smaller
inside_poly[fail] = polygon.contains_point(test_verts[fail], radius=0.01)
self.assertSequenceEqual(inside_voxel, inside_poly.tolist(),
"Failed for vertices {}".format(voxel_coords))
def _is_isolated(points, compare_id, event_region_coordinates, idx):
if idx == 0:
return True
polygon = Polygon(event_region_coordinates)
return not np.any(polygon.contains_points(points[:idx][compare_id[:idx] == compare_id[idx]]))
