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plane.py
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plane.py
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import six
import numpy as np
from blmath.numerics import vx
class Plane(object):
'''
A 2-D plane in 3-space (not a hyperplane).
Params:
- point_on_plane, plane_normal:
1 x 3 np.arrays
'''
def __init__(self, point_on_plane, unit_normal):
if vx.almost_zero(unit_normal):
raise ValueError('unit_normal should not be the zero vector')
unit_normal = vx.normalize(unit_normal)
self._r0 = np.asarray(point_on_plane)
self._n = np.asarray(unit_normal)
def __repr__(self):
return "<Plane of {} through {}>".format(self.normal, self.reference_point)
@classmethod
def from_points(cls, p1, p2, p3):
'''
If the points are oriented in a counterclockwise direction, the plane's
normal extends towards you.
'''
from blmath.numerics import as_numeric_array
p1 = as_numeric_array(p1, shape=(3,))
p2 = as_numeric_array(p2, shape=(3,))
p3 = as_numeric_array(p3, shape=(3,))
v1 = p2 - p1
v2 = p3 - p1
normal = np.cross(v1, v2)
return cls(point_on_plane=p1, unit_normal=normal)
@classmethod
def from_points_and_vector(cls, p1, p2, vector):
'''
Compute a plane which contains two given points and the given
vector. Its reference point will be p1.
For example, to find the vertical plane that passes through
two landmarks:
from_points_and_normal(p1, p2, vector)
Another way to think about this: identify the plane to which
your result plane should be perpendicular, and specify vector
as its normal vector.
'''
from blmath.numerics import as_numeric_array
p1 = as_numeric_array(p1, shape=(3,))
p2 = as_numeric_array(p2, shape=(3,))
v1 = p2 - p1
v2 = as_numeric_array(vector, shape=(3,))
normal = np.cross(v1, v2)
return cls(point_on_plane=p1, unit_normal=normal)
@classmethod
def fit_from_points(cls, points):
'''
Fits a plane whose normal is orthgonal to the first two principal axes
of variation in the data and centered on the points' centroid.
'''
eigval, eigvec = np.linalg.eig(np.cov(points.T))
ordering = np.argsort(eigval)[::-1]
normal = np.cross(eigvec[:, ordering[0]], eigvec[:, ordering[1]])
return cls(points.mean(axis=0), normal)
@property
def equation(self):
'''
Returns parameters A, B, C, D as a 1 x 4 np.array, where
Ax + By + Cz + D = 0
defines the plane.
params:
- normalized:
Boolean, indicates whether or not the norm of the vector [A, B, C] is 1.
Useful when computing the distance from a point to the plane.
'''
A, B, C = self._n
D = -self._r0.dot(self._n)
return np.array([A, B, C, D])
@property
def reference_point(self):
'''
The point used to create this plane.
'''
return self._r0
@property
def canonical_point(self):
'''
A canonical point on the plane, the one at which the normal
would intersect the plane if drawn from the origin (0, 0, 0).
This is computed by projecting the reference point onto the
normal.
This is useful for partitioning the space between two planes,
as we do when searching for planar cross sections.
'''
return self._r0.dot(self._n) * self._n
@property
def normal(self):
'''
Return the plane's normal vector.
'''
return self._n
def flipped(self):
'''
Creates a new Plane with an inverted orientation.
'''
normal = self._n * -1
return Plane(self._r0, normal)
def sign(self, points):
'''
Given an array of points, return an array with +1 for points in front
of the plane (in the direction of the normal), -1 for points behind
the plane (away from the normal), and 0 for points on the plane.
'''
return np.sign(self.signed_distance(points))
def points_in_front(self, points, inverted=False, ret_indices=False):
'''
Given an array of points, return the points which lie either on the
plane or in the half-space in front of it (i.e. in the direction of
the plane normal).
points: An array of points.
inverted: When `True`, invert the logic. Return the points that lie
behind the plane instead.
ret_indices: When `True`, return the indices instead of the points
themselves.
'''
sign = self.sign(points)
if inverted:
mask = np.less_equal(sign, 0)
else:
mask = np.greater_equal(sign, 0)
indices = np.flatnonzero(mask)
return indices if ret_indices else points[indices]
def signed_distance(self, points):
'''
Returns the signed distances given an np.array of 3-vectors.
Params:
- points:
V x 3 np.array
'''
return np.dot(points, self.equation[:3]) + self.equation[3]
def distance(self, points):
return np.absolute(self.signed_distance(points))
def project_point(self, point):
'''
Project a given point to the plane.
'''
# Translate the point back to the plane along the normal.
signed_distance_to_point = self.signed_distance(point.reshape((-1, 3)))[0]
return point - signed_distance_to_point * self._n
def polyline_xsection(self, polyline, ret_edge_indices=False):
'''
Deprecated.
'''
return polyline.intersect_plane(self, ret_edge_indices=ret_edge_indices)
def line_xsection(self, pt, ray):
return self._line_xsection(np.asarray(pt).ravel(), np.asarray(ray).ravel())
def _line_xsection(self, pt, ray):
denom = np.dot(ray, self.normal)
if denom == 0:
return None # parallel, either coplanar or non-intersecting
p = np.dot(self.reference_point - pt, self.normal) / denom
return p * ray + pt
def line_segment_xsection(self, a, b):
return self._line_segment_xsection(np.asarray(a).ravel(), np.asarray(b).ravel())
def _line_segment_xsection(self, a, b):
pt = self._line_xsection(a, b-a)
if pt is not None:
if any(np.logical_and(pt > a, pt > b)) or any(np.logical_and(pt < a, pt < b)):
return None
return pt
def line_xsections(self, pts, rays):
denoms = np.dot(rays, self.normal)
denom_is_zero = denoms == 0
denoms[denom_is_zero] = np.nan
p = np.dot(self.reference_point - pts, self.normal) / denoms
return np.vstack([p, p, p]).T * rays + pts, ~denom_is_zero
def line_segment_xsections(self, a, b):
pts, pt_is_valid = self.line_xsections(a, b-a)
pt_is_out_of_bounds = np.logical_or(np.any(np.logical_and(pts[pt_is_valid] > a[pt_is_valid], pts[pt_is_valid] > b[pt_is_valid]), axis=1),
np.any(np.logical_and(pts[pt_is_valid] < a[pt_is_valid], pts[pt_is_valid] < b[pt_is_valid]), axis=1))
pt_is_valid[pt_is_valid] = ~pt_is_out_of_bounds
pts[~pt_is_valid] = np.nan
return pts, pt_is_valid
def mesh_xsection(self, m, neighborhood=None):
'''
Backwards compatible.
Returns one polyline that may connect supposedly disconnected components.
Returns an empty Polyline if there's no intersection.
'''
from blmath.geometry import Polyline
components = self.mesh_xsections(m, neighborhood)
if len(components) == 0:
return Polyline(None)
return Polyline(np.vstack([x.v for x in components]), closed=True)
def mesh_intersecting_faces(self, m):
sgn_dists = self.signed_distance(m.v)
which_fs = np.abs(np.sign(sgn_dists)[m.f].sum(axis=1)) != 3
return m.f[which_fs]
def mesh_xsections(self, m, neighborhood=None):
'''
Takes a cross section of planar point cloud with a Mesh object.
Ignore those points which intersect at a vertex - the probability of
this event is small, and accounting for it complicates the algorithm.
If 'neighborhood' is provided, use a KDTree to constrain the
cross section to the closest connected component to 'neighborhood'.
Params:
- m:
Mesh object
- neigbhorhood:
M x 3 np.array
Returns a list of Polylines.
'''
from blmath.geometry import Polyline
# 1: Select those faces that intersect the plane, fs
fs = self.mesh_intersecting_faces(m)
if len(fs) == 0:
return [] # Nothing intersects
# and edges of those faces
es = np.vstack((fs[:, (0, 1)], fs[:, (1, 2)], fs[:, (2, 0)]))
# 2: Find the edges where each of those faces actually cross the plane
class EdgeMap(object):
# A quick two level dictionary where the two keys are interchangeable (i.e. a symmetric graph)
def __init__(self):
self.d = {} # store indicies into self.values here, to make it easier to get inds or values
self.values = []
def _order(self, u, v):
if u < v:
return u, v
else:
return v, u
def add(self, u, v, val):
low, high = self._order(u, v)
if low not in self.d:
self.d[low] = {}
self.values.append(val)
self.d[low][high] = len(self.values) - 1
def contains(self, u, v):
low, high = self._order(u, v)
if low in self.d and high in self.d[low]:
return True
return False
def index(self, u, v):
low, high = self._order(u, v)
try:
return self.d[low][high]
except KeyError:
return None
def get(self, u, v):
ii = self.index(u, v)
if ii is not None:
return self.values[ii]
else:
return None
intersection_map = EdgeMap()
pts, pt_is_valid = self.line_segment_xsections(m.v[es[:, 0]], m.v[es[:, 1]])
valid_pts = pts[pt_is_valid]
valid_es = es[pt_is_valid]
for val, e in zip(valid_pts, valid_es):
if not intersection_map.contains(e[0], e[1]):
intersection_map.add(e[0], e[1], val)
verts = np.array(intersection_map.values)
class Graph(object):
# A little utility class to build a symmetric graph and calculate Euler Paths
def __init__(self, size):
self.size = size
self.d = {}
def __len__(self):
return len(self.d)
def add_edges(self, edges):
for u, v in edges:
self.add_edge(u, v)
def add_edge(self, u, v):
assert u >= 0 and u < self.size
assert v >= 0 and v < self.size
if u not in self.d:
self.d[u] = set()
if v not in self.d:
self.d[v] = set()
self.d[u].add(v)
self.d[v].add(u)
def remove_edge(self, u, v):
if u in self.d and v in self.d[u]:
self.d[u].remove(v)
if v in self.d and u in self.d[v]:
self.d[v].remove(u)
if v in self.d and len(self.d[v]) == 0:
del self.d[v]
if u in self.d and len(self.d[u]) == 0:
del self.d[u]
def pop_euler_path(self, allow_multiple_connected_components=True):
# Based on code from Przemek Drochomirecki, Krakow, 5 Nov 2006
# http://code.activestate.com/recipes/498243-finding-eulerian-path-in-undirected-graph/
# Under PSF License
# NB: MUTATES d
# counting the number of vertices with odd degree
odd = [x for x in self.d if len(self.d[x])&1]
odd.append(next(six.iterkeys(self.d)))
if not allow_multiple_connected_components and len(odd) > 3:
return None
stack = [odd[0]]
path = []
# main algorithm
while stack:
v = stack[-1]
if v in self.d:
u = self.d[v].pop()
stack.append(u)
self.remove_edge(u, v)
else:
path.append(stack.pop())
return path
# 4: Build the edge adjacency graph
G = Graph(verts.shape[0])
for f in fs:
# Since we're dealing with a triangle that intersects the plane, exactly two of the edges
# will intersect (note that the only other sorts of "intersections" are one edge in
# plane or all three edges in plane, which won't be picked up by mesh_intersecting_faces).
e0 = intersection_map.index(f[0], f[1])
e1 = intersection_map.index(f[0], f[2])
e2 = intersection_map.index(f[1], f[2])
if e0 is None:
G.add_edge(e1, e2)
elif e1 is None:
G.add_edge(e0, e2)
else:
G.add_edge(e0, e1)
# 5: Find the paths for each component
components = []
components_closed = []
while len(G) > 0:
path = G.pop_euler_path()
if path is None:
raise ValueError("mesh slice has too many odd degree edges; can't find a path along the edge")
component_verts = verts[path]
if np.all(component_verts[0] == component_verts[-1]):
# Because the closed polyline will make that last link:
component_verts = np.delete(component_verts, 0, axis=0)
components_closed.append(True)
else:
components_closed.append(False)
components.append(component_verts)
if neighborhood is None or len(components) == 1:
return [Polyline(v, closed=closed) for v, closed in zip(components, components_closed)]
# 6 (optional - only if 'neighborhood' is provided): Use a KDTree to select the component with minimal distance to 'neighborhood'
from scipy.spatial import cKDTree # First thought this warning was caused by a pythonpath problem, but it seems more likely that the warning is caused by scipy import hackery. pylint: disable=no-name-in-module
kdtree = cKDTree(neighborhood)
# number of components will not be large in practice, so this loop won't hurt
means = [np.mean(kdtree.query(component)[0]) for component in components]
return [Polyline(components[np.argmin(means)], closed=True)]
def main():
import argparse
from lace.mesh import Mesh
parser = argparse.ArgumentParser()
parser.add_argument('-p', '--path', help='filepath to mesh', required=True)
parser.add_argument('-c', '--cloud', help='display point cloud', required=False, default=False, action='store_true')
parser.add_argument('-d', '--direction', help='direction of connected component',
choices=['N', 'S', 'E', 'W'], default=None, required=False)
args = parser.parse_args()
path_to_mesh = args.path
mesh = Mesh(filename=path_to_mesh, vc='SteelBlue')
point_on_plane = np.array([0., 1., 0.])
n1 = np.array([0., 1., 0.])
p1 = Plane(point_on_plane, n1)
n2 = np.array([1., 0., 0.])
p2 = Plane(point_on_plane, n2)
n3 = np.array([1., 1., 0.])
n3 /= np.linalg.norm(n3)
p3 = Plane(point_on_plane, n3)
n4 = np.array([-1., 1., 0.])
n4 /= np.linalg.norm(n4)
p4 = Plane(point_on_plane, n4)
dirmap = {
'N': [0., +100., 0.],
'S': [0., -100., 0.],
'E': [+100., 0., 0.],
'W': [-100., 0., 0.],
None: None,
}
neighborhood = dirmap[args.direction]
if neighborhood != None:
neighborhood = np.array([neighborhood])
xs1 = p1.mesh_xsection(mesh, neighborhood=neighborhood)
xs2 = p2.mesh_xsection(mesh, neighborhood=neighborhood)
xs3 = p3.mesh_xsection(mesh, neighborhood=neighborhood)
xs4 = p4.mesh_xsection(mesh, neighborhood=neighborhood)
lines = [
polyline.as_lines()
for polyline in [xs1, xs2, xs3, xs4]
]
if args.cloud:
mesh.f = []
from lace.meshviewer import MeshViewer
mv = MeshViewer(keepalive=True)
mv.set_dynamic_meshes([mesh], blocking=True)
mv.set_dynamic_lines(lines)
if __name__ == '__main__':
main()