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