def rotate2d(vec: Vector, ang: Angle):
x = vec[0] * ang.cos() - vec[1] * ang.sin()
y = vec[0] * ang.sin() + vec[1] * ang.cos()
if vec.dimension == 3:
return Vector([x, y, vec[3]])
else:
return Vector([x, y])
def test_side_vector(array_a, array_b, value_expected):
if value_expected is None:
with pytest.raises(ValueError):
Vector(array_a).side_vector(array_b)
else:
assert Vector(array_a).side_vector(array_b) == value_expected
def test_angle_signed(array_u, array_v, angle_expected):
if angle_expected is None:
with pytest.raises(ValueError, match="The vectors must be 2D."):
Vector(array_u).angle_signed(array_v)
else:
angle = Vector(array_u).angle_signed(array_v)
assert math.isclose(angle, angle_expected)
def test_unit(array, array_unit_expected):
if array_unit_expected is None:
with pytest.raises(ValueError,
match="The magnitude must not be zero."):
Vector(array).unit()
else:
assert Vector(array).unit().is_close(array_unit_expected)
def test_cosine_similarity(array_u, array_v, similarity_expected):
if similarity_expected is None:
with pytest.raises(ValueError,
match="The vectors must have non-zero magnitudes."):
Vector(array_u).cosine_similarity(array_v)
else:
similarity = Vector(array_u).cosine_similarity(array_v)
assert math.isclose(similarity, similarity_expected)
def compute_basis(points_stacked: xr.DataArray) -> Tuple[Basis, xr.DataArray]:
"""
Return origin and basis vectors of new coordinate system found with RANSAC.
Parameters
----------
points_stacked : xarray.DataArray
(N_frames, N_dims, N_layers) array of points.
Returns
-------
basis : namedtuple
Basis of new coordinate system (origin point and three unit vectors).
Fields include 'origin', 'forward', 'up', 'perp'.
points_grouped_inlier : xarray.DataArray
(N_frames, N_dims) array.
Grouped foot points that are marked inliers by RANSAC.
"""
frames = points_stacked.coords['frames'].values
points_head = points_stacked.sel(layers='points_head').values
points_a = points_stacked.sel(layers='points_a').values
points_b = points_stacked.sel(layers='points_b').values
points_foot_mean = (points_a + points_b) / 2
vectors_up = points_head - points_foot_mean
vector_up = Vector(np.median(vectors_up, axis=0)).unit()
frames_grouped = np.repeat(frames, 2)
points_grouped = nf.interweave_rows(points_a, points_b)
model_ransac, is_inlier = fit_ransac(points_grouped)
point_origin, vector_forward = model_ransac.params
vector_perp = Vector(vector_up).cross(vector_forward)
frames_grouped_inlier = frames_grouped[is_inlier]
points_grouped_inlier = points_grouped[is_inlier]
points_grouped_inlier = xr.DataArray(
points_grouped_inlier,
coords={
'frames': frames_grouped_inlier,
'cols': range(3)
},
dims=('frames', 'cols'),
)
basis = Basis(point_origin, vector_forward, vector_up, vector_perp)
return basis, points_grouped_inlier
def test_is_close(array):
vector = Vector(array)
point = Point(array)
assert point.size == vector.size
assert point.is_close(vector)
assert vector.is_close(point)
assert point.is_close(array)
assert vector.is_close(array)
def test_add_subtract(arrays):
array_point, array_vector = arrays
point = Point(array_point)
vector = Vector(array_vector)
point_2 = point + array_vector
assert math.isclose(point.distance_point(point_2), vector.norm())
point_3 = point_2 - array_vector
assert point.is_close(point_3)
def test_unit(array):
vector = Vector(array)
vector_unit = vector.unit()
assert math.isclose(vector_unit.norm(), 1)
assert (vector.norm() * vector_unit).is_close(array)
assert vector_unit.is_parallel(vector)
angle = vector.angle_between(vector_unit)
assert math.isclose(angle, 0, abs_tol=ATOL)
def volume_tetrahedron(
point_a: array_like,
point_b: array_like,
point_c: array_like,
point_d: array_like,
) -> np.float64:
"""
Return the volume of a tetrahedron defined by four points.
The points are the vertices of the tetrahedron. They must be 3D or less.
Parameters
----------
point_a, point_b, point_c, point_d : array_like
The four vertices of the tetrahedron.
Returns
-------
np.float64
The volume of the tetrahedron.
References
----------
http://mathworld.wolfram.com/Tetrahedron.html
Examples
--------
>>> from skspatial.measurement import volume_tetrahedron
>>> volume_tetrahedron([0, 0], [3, 2], [-3, 5], [1, 8])
0.0
>>> volume_tetrahedron([0, 0, 0], [2, 0, 0], [1, 1, 0], [0, 0, 1]).round(3)
0.333
>>> volume_tetrahedron([0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 1]).round(3)
0.167
"""
vector_ab = Vector.from_points(point_a, point_b)
vector_ac = Vector.from_points(point_a, point_c)
vector_ad = Vector.from_points(point_a, point_d)
vector_cross = vector_ac.cross(vector_ad)
# Set the dimension to 3 so it matches the cross product.
vector_ab = vector_ab.set_dimension(3)
return 1 / 6 * abs(vector_ab.dot(vector_cross))
def test_project_point(lines_or_planes, data):
"""Test projecting a point onto a line or plane."""
dim = data.draw(st.integers(min_value=DIM_MIN, max_value=DIM_MAX))
array = data.draw(arrays_fixed(dim))
line_or_plane = data.draw(lines_or_planes(dim))
point_projected = line_or_plane.project_point(array)
# The projected point should lie on the line/plane.
assert line_or_plane.contains_point(point_projected, abs_tol=ATOL)
# The vector from the point to its projection
# should be perpendicular to the line/plane.
vector_projection = Vector.from_points(array, point_projected)
# The distance from the point to its projection
# should equal the distance to the line/plane.
distance_projection = vector_projection.norm()
distance_to_object = abs(line_or_plane.distance_point(array))
assert math.isclose(distance_to_object, distance_projection, rel_tol=1e-6)
# The distance of the projection should be the
# shortest distance from the point to the object.
distance_points = line_or_plane.point.distance_point(array)
assert distance_projection < distance_points or math.isclose(
distance_projection, distance_points)
def test_from_points(arrays):
array_a, array_b = arrays
point_a = Point(array_a)
vector_ab = Vector.from_points(array_a, array_b)
assert (point_a + vector_ab).is_close(array_b)
def area_triangle(point_a: array_like, point_b: array_like,
point_c: array_like) -> np.float64:
"""
Return the area of a triangle defined by three points.
The points are the vertices of the triangle. They must be 3D or less.
Parameters
----------
point_a, point_b, point_c : array_like
The three vertices of the triangle.
Returns
-------
np.float64
The area of the triangle.
References
----------
http://mathworld.wolfram.com/TriangleArea.html
Examples
--------
>>> from skspatial.measurement import area_triangle
>>> area_triangle([0, 0], [0, 1], [1, 0])
0.5
>>> area_triangle([0, 0], [0, 2], [1, 1])
1.0
>>> area_triangle([3, -5, 1], [5, 2, 1], [9, 4, 2]).round(2)
12.54
"""
vector_ab = Vector.from_points(point_a, point_b)
vector_ac = Vector.from_points(point_a, point_c)
# Normal vector of plane defined by the three points.
vector_normal = vector_ab.cross(vector_ac)
return 0.5 * vector_normal.norm()
def test_scale(array, scalar):
assume(abs(scalar) > ATOL)
vector = Vector(array)
vector_scaled = scalar * vector
assert vector_scaled.is_parallel(array)
angle = vector_scaled.angle_between(array)
if scalar > 0:
assert math.isclose(angle, 0, abs_tol=ATOL)
else:
assert math.isclose(angle, np.pi, rel_tol=1e-6)
def vectors_nonzero(draw, dim):
"""
Return a strategy which generates nonzero Vector objects.
Parameters
----------
dim : int
Dimension of the object.
Returns
-------
LazyStrategy
Hypothesis strategy.
"""
return Vector(draw(arrays_fixed_nonzero(dim)))
def vectors(draw, dim):
"""
Return a strategy which generates Vector objects.
Parameters
----------
dim : int
Dimension of the object.
Returns
-------
LazyStrategy
Hypothesis strategy.
Examples
--------
>>> from hypothesis import find
>>> from tests.property.strategies import vectors
>>> find(vectors(2), lambda x: True)
Vector([0., 0.])
"""
return Vector(draw(arrays_fixed(dim)))
def test_from_points(array_a, array_b, vector_expected):
assert_array_equal(Vector.from_points(array_a, array_b), vector_expected)
"""
Vector-Plane Projection
=======================
Project a vector onto a plane.
"""
from skspatial.objects import Plane
from skspatial.objects import Vector
from skspatial.plotting import plot_3d
plane = Plane([0, 0, 0], [0, 0, 1])
vector = Vector([1, 1, 1])
vector_projected = plane.project_vector(vector)
_, ax = plot_3d(
plane.plotter(lims_x=(-5, 5), lims_y=(-5, 5), alpha=0.3),
vector.plotter(point=plane.point, color='k'),
vector_projected.plotter(point=plane.point,
color='r',
linewidth=2,
zorder=3),
)
ax.set_zlim([-1, 1])
def test_equality(array):
assert_array_equal(array, Point(array))
assert_array_equal(array, Vector(array))
assert_array_equal(array, np.array(array))
"""
3D Vector-Line Projection
=========================
Project a vector onto a line.
"""
from skspatial.objects import Vector, Line
from skspatial.plotting import plot_3d
line = Line([0, 0, 0], [1, 1, 2])
vector = Vector([1, 1, 0.1])
vector_projected = line.project_vector(vector)
plot_3d(
line.plotter(t_1=-1, c='k', linestyle='--'),
vector.plotter(point=line.point, color='k'),
vector_projected.plotter(point=line.point,
color='r',
linewidth=2,
zorder=3),
)
def test_is_perpendicular(array_u, array_v, bool_expected):
"""Test checking if vector u is perpendicular to vector v."""
vector_u = Vector(array_u)
assert vector_u.is_perpendicular(array_v) == bool_expected
def test_two_vectors(arrays):
array_a, array_b = arrays
vector_a = Vector(array_a)
is_perpendicular = vector_a.is_perpendicular(array_b)
is_parallel = vector_a.is_parallel(array_b)
# Two non-zero vectors cannot be both perpendicular and parallel.
assert not (is_perpendicular and is_parallel)
angle = vector_a.angle_between(array_b)
if is_perpendicular:
assert math.isclose(angle, np.pi / 2)
if is_parallel:
assert math.isclose(angle, 0, abs_tol=ATOL) or math.isclose(
angle, np.pi, rel_tol=1e-6)
# The zero vector is perpendicular and parallel to any other vector.
vector_zero = np.zeros(vector_a.size)
assert vector_a.is_perpendicular(vector_zero)
assert vector_a.is_parallel(vector_zero)
# The angle with the zero vector is undefined.
with pytest.raises(Exception):
vector_a.angle_between(vector_zero)
# The projection of vector B onto A is parallel to A.
vector_b_projected = vector_a.project_vector(array_b)
assert vector_a.is_parallel(vector_b_projected)
# The projection is zero if vectors A and B are perpendicular.
if is_perpendicular:
assert vector_b_projected.is_zero(abs_tol=ATOL)
from skspatial.objects import Plane
from skspatial.objects import Point
from skspatial.objects import Points
from skspatial.objects import Sphere
from skspatial.objects import Triangle
from skspatial.objects import Vector
@pytest.mark.parametrize(
("obj_spatial", "repr_expected"),
[
(Point([0]), "Point([0])"),
(Point([0, 0]), "Point([0, 0])"),
(Point([0.5, 0]), "Point([0.5, 0. ])"),
(Point([-11, 0]), "Point([-11, 0])"),
(Vector([-11, 0]), "Vector([-11, 0])"),
(Vector([-11.0, 0.0]), "Vector([-11., 0.])"),
(Vector([0, 0]), "Vector([0, 0])"),
(Vector([0.5, 0]), "Vector([0.5, 0. ])"),
(Points([[1.5, 2], [5, 3]]), "Points([[1.5, 2. ],\n [5. , 3. ]])"),
(Line([0, 0], [1, 0]), "Line(point=Point([0, 0]), direction=Vector([1, 0]))"),
(Line([-1, 2, 3], [5, 4, 2]), "Line(point=Point([-1, 2, 3]), direction=Vector([5, 4, 2]))"),
(Line(np.zeros(2), [1, 0]), "Line(point=Point([0., 0.]), direction=Vector([1, 0]))"),
(Plane([0, 0], [1, 0]), "Plane(point=Point([0, 0]), normal=Vector([1, 0]))"),
(Plane([-1, 2, 3], [5, 4, 2]), "Plane(point=Point([-1, 2, 3]), normal=Vector([5, 4, 2]))"),
(Circle([0, 0], 1), "Circle(point=Point([0, 0]), radius=1)"),
(Circle([0, 0], 2.5), "Circle(point=Point([0, 0]), radius=2.5)"),
(Sphere([0, 0, 0], 1), "Sphere(point=Point([0, 0, 0]), radius=1)"),
(
Triangle([0, 0], [0, 1], [1, 0]),
"Triangle(point_a=Point([0, 0]), point_b=Point([0, 1]), point_c=Point([1, 0]))",
def test_is_parallel(array_u, array_v, bool_expected):
"""Test checking if vector u is parallel to vector v."""
vector_u = Vector(array_u)
assert vector_u.is_parallel(array_v) == bool_expected
def test_add_subtract(array):
vector = Vector(array)
assert (vector + array - array).is_close(array)
def test_is_zero(array, kwargs, bool_expected):
assert Vector(array).is_zero(**kwargs) == bool_expected
import math
import pytest
from numpy.testing import assert_array_equal
from skspatial.objects import Vector
@pytest.mark.parametrize(
"array_a, array_b, vector_expected",
[
([0, 0], [1, 0], Vector([1, 0])),
([1, 0], [1, 0], Vector([0, 0])),
([1, 0], [2, 0], Vector([1, 0])),
([8, 3, -5], [3, 7, 1], Vector([-5, 4, 6])),
([5, 7, 8, 9], [2, 5, 3, -4], Vector([-3, -2, -5, -13])),
],
)
def test_from_points(array_a, array_b, vector_expected):
assert_array_equal(Vector.from_points(array_a, array_b), vector_expected)
@pytest.mark.parametrize(
"array, array_unit_expected",
[
([1, 0], [1, 0]),
([2, 0], [1, 0]),
([-1, 0], [-1, 0]),
([0, 0, 5], [0, 0, 1]),
([1, 1], [math.sqrt(2) / 2, math.sqrt(2) / 2]),
def test_different_direction_failure(array):
message_expected = "The vector must not be the zero vector."
with pytest.raises(ValueError, match=message_expected):
Vector(array).different_direction()
def test_project_vector(vector_u, vector_v, vector_expected):
"""Test projecting vector u onto vector v."""
vector_u_projected = Vector(vector_v).project_vector(vector_u)
assert vector_u_projected.is_close(vector_expected)
"""
Point-Plane Projection
======================
Project a point onto a plane.
"""
from skspatial.objects import Plane
from skspatial.objects import Point
from skspatial.objects import Vector
from skspatial.plotting import plot_3d
plane = Plane(point=[0, 0, 2], normal=[1, 0, 2])
point = Point([5, 9, 3])
point_projected = plane.project_point(point)
vector_projection = Vector.from_points(point, point_projected)
plot_3d(
plane.plotter(lims_x=(0, 10), lims_y=(0, 15), alpha=0.3),
point.plotter(s=75, c='k'),
point_projected.plotter(c='r', s=75, zorder=3),
vector_projection.plotter(point=point, c='k', linestyle='--'),
)
