Remove cache files
Mattia Montanari
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ea94e24da4
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1122ef3ea6
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Cython/test.py
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Cython/test.py
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import openGJKpy as opengjk
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from scipy.spatial.transform import Rotation as R
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import numpy as np
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import pytest
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def distance_point_to_line_3D(P1, P2, point):
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"""
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distance from point to line
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"""
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return np.linalg.norm(np.cross(P2-P1, P1-point))/np.linalg.norm(P2-P1)
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def distance_point_to_plane_3D(P1, P2, P3, point):
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"""
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Distance from point to plane
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"""
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return np.abs(np.dot(np.cross(P2-P1, P3-P1) /
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np.linalg.norm(np.cross(P2-P1, P3-P1)), point-P2))
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@pytest.mark.parametrize("delta", [0.1, 1e-12, 0, -2])
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def test_line_point_distance(delta):
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line = np.array([[0.1, 0.2, 0.3], [0.5, 0.8, 0.7]], dtype=np.float64) #
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point_on_line = line[0] + 0.27*(line[1]-line[0])
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normal = np.cross(line[0], line[1])
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point = point_on_line + delta * normal
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distance = opengjk.pygjk(line, point)
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actual_distance = distance_point_to_line_3D(
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line[0], line[1], point)
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print(distance, actual_distance)
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assert(np.isclose(distance, actual_distance, atol=1e-15))
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@pytest.mark.parametrize("delta", [0.1, 1e-12, 0])
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def test_line_line_distance(delta):
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line = np.array([[-0.5, -0.7, -0.3], [1, 2, 3]], dtype=np.float64)
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point_on_line = line[0] + 0.38*(line[1]-line[0])
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normal = np.cross(line[0], line[1])
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point = point_on_line + delta * normal
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line_2 = np.array([point, [2, 5, 6]], dtype=np.float64)
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distance = opengjk.pygjk(line, line_2)
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actual_distance = distance_point_to_line_3D(
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line[0], line[1], line_2[0])
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print(distance, actual_distance)
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assert(np.isclose(distance, actual_distance, atol=1e-15))
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@pytest.mark.parametrize("delta", [0.1**(3*i) for i in range(6)])
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def test_tri_distance(delta):
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tri_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0]], dtype=np.float64)
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tri_2 = np.array([[1, delta, 0], [3, 1.2, 0], [1, 1, 0]], dtype=np.float64)
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P1 = tri_1[2]
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P2 = tri_1[1]
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point = tri_2[0]
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actual_distance = distance_point_to_line_3D(P1, P2, point)
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distance = opengjk.pygjk(tri_1, tri_2)
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print("Computed distance ", distance, "Actual distance ", actual_distance)
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assert(np.isclose(distance, actual_distance, atol=1e-15))
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@pytest.mark.parametrize("delta", [0.1*0.1**(3*i) for i in range(6)])
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def test_quad_distance2d(delta):
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quad_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0],
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[1, 1, 0]], dtype=np.float64)
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quad_2 = np.array([[0, 1+delta, 0], [2, 2, 0],
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[2, 4, 0], [4, 4, 0]], dtype=np.float64)
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P1 = quad_1[2]
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P2 = quad_1[3]
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point = quad_2[0]
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actual_distance = distance_point_to_line_3D(P1, P2, point)
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distance = opengjk.pygjk(quad_1, quad_2)
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print("Computed distance ", distance, "Actual distance ", actual_distance)
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assert(np.isclose(distance, actual_distance, atol=1e-15))
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@pytest.mark.parametrize("delta", [1*0.5**(3*i) for i in range(7)])
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def test_tetra_distance_3d(delta):
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tetra_1 = np.array([[0, 0, 0.2], [1, 0, 0.1], [0, 1, 0.3],
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[0, 0, 1]], dtype=np.float64)
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tetra_2 = np.array([[0, 0, -3], [1, 0, -3], [0, 1, -3],
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[0.5, 0.3, -delta]], dtype=np.float64)
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actual_distance = distance_point_to_plane_3D(tetra_1[0], tetra_1[1],
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tetra_1[2], tetra_2[3])
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distance = opengjk.pygjk(tetra_1, tetra_2)
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print("Computed distance ", distance, "Actual distance ", actual_distance)
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assert(np.isclose(distance, actual_distance, atol=1e-15))
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@pytest.mark.parametrize("delta", [(-1)**i*np.sqrt(2)*0.1**(3*i)
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for i in range(6)])
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def test_tetra_collision_3d(delta):
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tetra_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0],
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[0, 0, 1]], dtype=np.float64)
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tetra_2 = np.array([[0, 0, -3], [1, 0, -3], [0, 1, -3],
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[0.5, 0.3, -delta]], dtype=np.float64)
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actual_distance = distance_point_to_plane_3D(tetra_1[0], tetra_1[1],
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tetra_1[2], tetra_2[3])
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distance = opengjk.pygjk(tetra_1, tetra_2)
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if delta < 0:
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assert(np.isclose(distance, 0, atol=1e-15))
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else:
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print("Computed distance ", distance,
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"Actual distance ", actual_distance)
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assert(np.isclose(distance, actual_distance, atol=1e-15))
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@pytest.mark.parametrize("delta", [0, -0.1, -0.49, -0.51])
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def test_hex_collision_3d(delta):
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hex_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [1, 1, 0],
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[0, 0, 1], [1, 0, 1], [0, 1, 1], [1, 1, 1]],
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dtype=np.float64)
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P0 = np.array([1.5+delta, 1.5+delta, 0.5], dtype=np.float64)
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P1 = np.array([2, 2, 1], dtype=np.float64)
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P2 = np.array([2, 1.25, 0.25], dtype=np.float64)
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P3 = P1 + P2 - P0
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quad_1 = np.array([P0, P1, P2, P3], dtype=np.float64)
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n = (np.cross(quad_1[1]-quad_1[0], quad_1[2]-quad_1[0]) /
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np.linalg.norm(
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np.cross(quad_1[1]-quad_1[0],
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quad_1[2]-quad_1[0])))
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quad_2 = quad_1 + n
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hex_2 = np.zeros((8, 3), dtype=np.float64)
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hex_2[:4, :] = quad_1
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hex_2[4:, :] = quad_2
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actual_distance = np.linalg.norm(
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np.array([1, 1, P0[2]], dtype=np.float64)-hex_2[0])
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distance = opengjk.pygjk(hex_1, hex_2)
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if P0[0] < 1:
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assert(np.isclose(distance, 0, atol=1e-15))
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else:
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print("Computed distance ", distance,
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"Actual distance ", actual_distance)
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assert(np.isclose(distance, actual_distance, atol=1e-15))
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@pytest.mark.parametrize("c0", [0, 1, 2, 3])
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@pytest.mark.parametrize("c1", [0, 1, 2, 3])
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def test_cube_distance(c0, c1):
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cubes = [np.array([[-1, -1, -1], [1, -1, -1], [-1, 1, -1], [1, 1, -1],
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[-1, -1, 1], [1, -1, 1], [-1, 1, 1], [1, 1, 1]],
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dtype=np.float64)]
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r = R.from_euler('z', 45, degrees=True)
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cubes.append(r.apply(cubes[0]))
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r = R.from_euler('y', np.arctan2(1.0, np.sqrt(2)))
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cubes.append(r.apply(cubes[1]))
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r = R.from_euler('y', 45, degrees=True)
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cubes.append(r.apply(cubes[0]))
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dx = cubes[c0][:,0].max() - cubes[c1][:,0].min()
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cube0 = cubes[c0]
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for delta in [1e8, 1.0, 1e-4, 1e-8, 1e-12]:
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cube1 = cubes[c1] + np.array([dx + delta, 0, 0])
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distance = opengjk.pygjk(cube0, cube1)
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print(distance, delta)
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assert(np.isclose(distance, delta))
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def test_random_objects():
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for i in range(1, 8):
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for j in range(1, 8):
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for k in range(1000):
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arr1 = np.random.rand(i, 3)
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arr2 = np.random.rand(j, 3)
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opengjk.pygjk(arr1, arr2)
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def test_large_random_objects():
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for i in range(1, 8):
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for j in range(1, 8):
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for k in range(1000):
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arr1 = 10000.0*np.random.rand(i, 3)
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arr2 = 10000.0*np.random.rand(j, 3)
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opengjk.pygjk(arr1, arr2)
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