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..can't get ipython installed in this CI

fixes-turtlebasket
MattiaMontanari 2020-05-05 17:08:42 +01:00
parent 38ee3fbe58
commit df822d1556
2 changed files with 203 additions and 203 deletions
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36
.github/workflows/ccpp.yml vendored
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name: C/C++ CI name: C/C++ CI
on: [push] on: [push]
jobs: jobs:
build: build:
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2
- name: Install Eigen and Pybind11 - name: Install Eigen and Pybind11
run: sudo apt update && sudo apt install -y libeigen3-dev && pip3 install pybind11 pytest numpy scipy ipython run: sudo apt update && sudo apt install -y libeigen3-dev && pip3 install pybind11 pytest numpy scipy
- name: Compile - name: Compile
run: export CPATH=/usr/include/eigen3 && cd python && source build.sh run: export CPATH=/usr/include/eigen3 && cd python && source build.sh
- name: Test - name: Test
run: | run: |
cd python cd python
python3 -m pytest -s -v test.py python3 -m pytest -s -v test.py

370
python/test.py
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import opengjkc as opengjk import opengjkc as opengjk
from scipy.spatial.transform import Rotation as R from scipy.spatial.transform import Rotation as R
import numpy as np import numpy as np
import pytest import pytest
from IPython import embed #from IPython import embed
def settol(): def settol():
return 1e-12 return 1e-12
def distance_point_to_line_3D(P1, P2, point): def distance_point_to_line_3D(P1, P2, point):
""" """
distance from point to line distance from point to line
""" """
return np.linalg.norm(np.cross(P2-P1, P1-point))/np.linalg.norm(P2-P1) 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): def distance_point_to_plane_3D(P1, P2, P3, point):
""" """
Distance from point to plane Distance from point to plane
""" """
return np.abs(np.dot(np.cross(P2-P1, P3-P1) / return np.abs(np.dot(np.cross(P2-P1, P3-P1) /
np.linalg.norm(np.cross(P2-P1, P3-P1)), point-P2)) np.linalg.norm(np.cross(P2-P1, P3-P1)), point-P2))
@pytest.mark.parametrize("delta", [0.1, 1e-12, 0, -2]) @pytest.mark.parametrize("delta", [0.1, 1e-12, 0, -2])
def test_line_point_distance(delta): def test_line_point_distance(delta):
line = np.array([[0.1, 0.2, 0.3], [0.5, 0.8, 0.7]], dtype=np.float64) 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]) point_on_line = line[0] + 0.27*(line[1]-line[0])
normal = np.cross(line[0], line[1]) normal = np.cross(line[0], line[1])
point = point_on_line + delta * normal point = point_on_line + delta * normal
distance = opengjk.gjk(line, point) distance = opengjk.gjk(line, point)
actual_distance = distance_point_to_line_3D( actual_distance = distance_point_to_line_3D(
line[0], line[1], point) line[0], line[1], point)
print(distance, actual_distance) print(distance, actual_distance)
assert(np.isclose(distance, actual_distance, atol=settol() )) assert(np.isclose(distance, actual_distance, atol=settol() ))
@pytest.mark.parametrize("delta", [0.1, 1e-12, 0]) @pytest.mark.parametrize("delta", [0.1, 1e-12, 0])
def test_line_line_distance(delta): def test_line_line_distance(delta):
line = np.array([[-0.5, -0.7, -0.3], [1, 2, 3]], dtype=np.float64) 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]) point_on_line = line[0] + 0.38*(line[1]-line[0])
normal = np.cross(line[0], line[1]) normal = np.cross(line[0], line[1])
point = point_on_line + delta * normal point = point_on_line + delta * normal
line_2 = np.array([point, [2, 5, 6]], dtype=np.float64) line_2 = np.array([point, [2, 5, 6]], dtype=np.float64)
distance = opengjk.gjk(line, line_2) distance = opengjk.gjk(line, line_2)
actual_distance = distance_point_to_line_3D( actual_distance = distance_point_to_line_3D(
line[0], line[1], line_2[0]) line[0], line[1], line_2[0])
print(distance, actual_distance) print(distance, actual_distance)
assert(np.isclose(distance, actual_distance, atol=settol() )) assert(np.isclose(distance, actual_distance, atol=settol() ))
@pytest.mark.parametrize("delta", [0.1**(3*i) for i in range(6)]) @pytest.mark.parametrize("delta", [0.1**(3*i) for i in range(6)])
def test_tri_distance(delta): def test_tri_distance(delta):
tri_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0]], dtype=np.float64) 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], [ tri_2 = np.array([[1, delta, 0], [3, 1.2, 0], [
1, 1, 0]], dtype=np.float64) 1, 1, 0]], dtype=np.float64)
P1 = tri_1[2] P1 = tri_1[2]
P2 = tri_1[1] P2 = tri_1[1]
point = tri_2[0] point = tri_2[0]
actual_distance = distance_point_to_line_3D(P1, P2, point) actual_distance = distance_point_to_line_3D(P1, P2, point)
distance = opengjk.gjk(tri_1, tri_2) distance = opengjk.gjk(tri_1, tri_2)
print("Computed distance ", distance, "Actual distance ", actual_distance) print("Computed distance ", distance, "Actual distance ", actual_distance)
#embed() #embed()
assert(np.isclose(distance, actual_distance, atol=settol() )) assert(np.isclose(distance, actual_distance, atol=settol() ))
@pytest.mark.parametrize("delta", [0.1*0.1**(3*i) for i in range(6)]) @pytest.mark.parametrize("delta", [0.1*0.1**(3*i) for i in range(6)])
def test_quad_distance2d(delta): def test_quad_distance2d(delta):
quad_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], quad_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0],
[1, 1, 0]], dtype=np.float64) [1, 1, 0]], dtype=np.float64)
quad_2 = np.array([[0, 1+delta, 0], [2, 2, 0], quad_2 = np.array([[0, 1+delta, 0], [2, 2, 0],
[2, 4, 0], [4, 4, 0]], dtype=np.float64) [2, 4, 0], [4, 4, 0]], dtype=np.float64)
P1 = quad_1[2] P1 = quad_1[2]
P2 = quad_1[3] P2 = quad_1[3]
point = quad_2[0] point = quad_2[0]
actual_distance = distance_point_to_line_3D(P1, P2, point) actual_distance = distance_point_to_line_3D(P1, P2, point)
distance = opengjk.gjk(quad_1, quad_2) distance = opengjk.gjk(quad_1, quad_2)
print("Computed distance ", distance, "Actual distance ", actual_distance) print("Computed distance ", distance, "Actual distance ", actual_distance)
assert(np.isclose(distance, actual_distance, atol=settol() )) assert(np.isclose(distance, actual_distance, atol=settol() ))
@pytest.mark.parametrize("delta", [1*0.5**(3*i) for i in range(7)]) @pytest.mark.parametrize("delta", [1*0.5**(3*i) for i in range(7)])
def test_tetra_distance_3d(delta): def test_tetra_distance_3d(delta):
tetra_1 = np.array([[0, 0, 0.2], [1, 0, 0.1], [0, 1, 0.3], tetra_1 = np.array([[0, 0, 0.2], [1, 0, 0.1], [0, 1, 0.3],
[0, 0, 1]], dtype=np.float64) [0, 0, 1]], dtype=np.float64)
tetra_2 = np.array([[0, 0, -3], [1, 0, -3], [0, 1, -3], tetra_2 = np.array([[0, 0, -3], [1, 0, -3], [0, 1, -3],
[0.5, 0.3, -delta]], dtype=np.float64) [0.5, 0.3, -delta]], dtype=np.float64)
actual_distance = distance_point_to_plane_3D(tetra_1[0], tetra_1[1], actual_distance = distance_point_to_plane_3D(tetra_1[0], tetra_1[1],
tetra_1[2], tetra_2[3]) tetra_1[2], tetra_2[3])
distance = opengjk.gjk(tetra_1, tetra_2) distance = opengjk.gjk(tetra_1, tetra_2)
print("Computed distance ", distance, "Actual distance ", actual_distance) print("Computed distance ", distance, "Actual distance ", actual_distance)
assert(np.isclose(distance, actual_distance, atol=settol() )) assert(np.isclose(distance, actual_distance, atol=settol() ))
@pytest.mark.parametrize("delta", [(-1)**i*np.sqrt(2)*0.1**(3*i) @pytest.mark.parametrize("delta", [(-1)**i*np.sqrt(2)*0.1**(3*i)
for i in range(6)]) for i in range(6)])
def test_tetra_collision_3d(delta): def test_tetra_collision_3d(delta):
tetra_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], tetra_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0],
[0, 0, 1]], dtype=np.float64) [0, 0, 1]], dtype=np.float64)
tetra_2 = np.array([[0, 0, -3], [1, 0, -3], [0, 1, -3], tetra_2 = np.array([[0, 0, -3], [1, 0, -3], [0, 1, -3],
[0.5, 0.3, -delta]], dtype=np.float64) [0.5, 0.3, -delta]], dtype=np.float64)
actual_distance = distance_point_to_plane_3D(tetra_1[0], tetra_1[1], actual_distance = distance_point_to_plane_3D(tetra_1[0], tetra_1[1],
tetra_1[2], tetra_2[3]) tetra_1[2], tetra_2[3])
distance = opengjk.gjk(tetra_1, tetra_2) distance = opengjk.gjk(tetra_1, tetra_2)
if delta < 0: if delta < 0:
assert(np.isclose(distance, 0, atol=settol())) assert(np.isclose(distance, 0, atol=settol()))
else: else:
print("Computed distance ", distance, print("Computed distance ", distance,
"Actual distance ", actual_distance) "Actual distance ", actual_distance)
assert(np.isclose(distance, actual_distance, atol=settol())) assert(np.isclose(distance, actual_distance, atol=settol()))
@pytest.mark.parametrize("delta", [0, -0.1, -0.49, -0.51]) @pytest.mark.parametrize("delta", [0, -0.1, -0.49, -0.51])
def test_hex_collision_3d(delta): def test_hex_collision_3d(delta):
hex_1 = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [1, 1, 0], 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]], [0, 0, 1], [1, 0, 1], [0, 1, 1], [1, 1, 1]],
dtype=np.float64) dtype=np.float64)
P0 = np.array([1.5+delta, 1.5+delta, 0.5], 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) P1 = np.array([2, 2, 1], dtype=np.float64)
P2 = np.array([2, 1.25, 0.25], dtype=np.float64) P2 = np.array([2, 1.25, 0.25], dtype=np.float64)
P3 = P1 + P2 - P0 P3 = P1 + P2 - P0
quad_1 = np.array([P0, P1, P2, P3], dtype=np.float64) 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]) / n = (np.cross(quad_1[1]-quad_1[0], quad_1[2]-quad_1[0]) /
np.linalg.norm( np.linalg.norm(
np.cross(quad_1[1]-quad_1[0], np.cross(quad_1[1]-quad_1[0],
quad_1[2]-quad_1[0]))) quad_1[2]-quad_1[0])))
quad_2 = quad_1 + n quad_2 = quad_1 + n
hex_2 = np.zeros((8, 3), dtype=np.float64) hex_2 = np.zeros((8, 3), dtype=np.float64)
hex_2[:4, :] = quad_1 hex_2[:4, :] = quad_1
hex_2[4:, :] = quad_2 hex_2[4:, :] = quad_2
actual_distance = np.linalg.norm( actual_distance = np.linalg.norm(
np.array([1, 1, P0[2]], dtype=np.float64)-hex_2[0]) np.array([1, 1, P0[2]], dtype=np.float64)-hex_2[0])
distance = opengjk.gjk(hex_1, hex_2) distance = opengjk.gjk(hex_1, hex_2)
if P0[0] < 1: if P0[0] < 1:
assert(np.isclose(distance, 0, atol=settol())) assert(np.isclose(distance, 0, atol=settol()))
else: else:
print("Computed distance ", distance, print("Computed distance ", distance,
"Actual distance ", actual_distance) "Actual distance ", actual_distance)
assert(np.isclose(distance, actual_distance, atol=settol())) assert(np.isclose(distance, actual_distance, atol=settol()))
@pytest.mark.parametrize("c0", [0, 1, 2, 3]) @pytest.mark.parametrize("c0", [0, 1, 2, 3])
@pytest.mark.parametrize("c1", [0, 1, 2, 3]) @pytest.mark.parametrize("c1", [0, 1, 2, 3])
def test_cube_distance(c0, c1): def test_cube_distance(c0, c1):
cubes = [np.array([[-1, -1, -1], [1, -1, -1], [-1, 1, -1], [1, 1, -1], 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]], [-1, -1, 1], [1, -1, 1], [-1, 1, 1], [1, 1, 1]],
dtype=np.float64)] dtype=np.float64)]
r = R.from_euler('z', 45, degrees=True) r = R.from_euler('z', 45, degrees=True)
cubes.append(r.apply(cubes[0])) cubes.append(r.apply(cubes[0]))
r = R.from_euler('y', np.arctan2(1.0, np.sqrt(2))) r = R.from_euler('y', np.arctan2(1.0, np.sqrt(2)))
cubes.append(r.apply(cubes[1])) cubes.append(r.apply(cubes[1]))
r = R.from_euler('y', 45, degrees=True) r = R.from_euler('y', 45, degrees=True)
cubes.append(r.apply(cubes[0])) cubes.append(r.apply(cubes[0]))
dx = cubes[c0][:,0].max() - cubes[c1][:,0].min() dx = cubes[c0][:,0].max() - cubes[c1][:,0].min()
cube0 = cubes[c0] cube0 = cubes[c0]
for delta in [1e8, 1.0, 1e-4, 1e-8, 1e-12]: for delta in [1e8, 1.0, 1e-4, 1e-8, 1e-12]:
cube1 = cubes[c1] + np.array([dx + delta, 0, 0]) cube1 = cubes[c1] + np.array([dx + delta, 0, 0])
distance = opengjk.gjk(cube0, cube1) distance = opengjk.gjk(cube0, cube1)
print(distance, delta) print(distance, delta)
assert(np.isclose(distance, delta)) assert(np.isclose(distance, delta))
def test_random_objects(): def test_random_objects():
for i in range(1, 8): for i in range(1, 8):
for j in range(1, 8): for j in range(1, 8):
for k in range(1000): for k in range(1000):
arr1 = np.random.rand(i, 3) arr1 = np.random.rand(i, 3)
arr2 = np.random.rand(j, 3) arr2 = np.random.rand(j, 3)
opengjk.gjk(arr1, arr2) opengjk.gjk(arr1, arr2)
def test_large_random_objects(): def test_large_random_objects():
for i in range(1, 8): for i in range(1, 8):
for j in range(1, 8): for j in range(1, 8):
for k in range(1000): for k in range(1000):
arr1 = 10000.0*np.random.rand(i, 3) arr1 = 10000.0*np.random.rand(i, 3)
arr2 = 10000.0*np.random.rand(j, 3) arr2 = 10000.0*np.random.rand(j, 3)
opengjk.gjk(arr1, arr2) opengjk.gjk(arr1, arr2)