Add pybind11 interface

python/build.sh

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+#!/bin/bash
+g++ -Wall -fPIC -shared `python3 -m pybind11 --includes` -I../include -I/usr/include/eigen3 pyopenGJK.cpp ../src/openGJK.c -o opengjkc`python3-config --extension-suffix`

python/pyopenGJK.cpp

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+#include "openGJK/openGJK.h"
+#include <pybind11/eigen.h>
+#include <pybind11/pybind11.h>
+namespace py = pybind11;
+
+PYBIND11_MODULE(opengjkc, m)
+{
+  m.def("gjk",
+        [](Eigen::Array<double, Eigen::Dynamic, 3, Eigen::RowMajor>& arr1,
+           Eigen::Array<double, Eigen::Dynamic, 3, Eigen::RowMajor>& arr2)
+            -> double {
+          struct simplex s;
+          struct bd bd1;
+          struct bd bd2;
+          bd1.numpoints = arr1.rows();
+          std::vector<double*> arr1_rows(arr1.rows());
+          for (int i = 0; i < arr1.rows(); ++i)
+            arr1_rows[i] = arr1.row(i).data();
+          bd1.coord = arr1_rows.data();
+
+          bd2.numpoints = arr2.rows();
+          std::vector<double*> arr2_rows(arr2.rows());
+          for (int i = 0; i < arr2.rows(); ++i)
+            arr2_rows[i] = arr2.row(i).data();
+          bd2.coord = arr2_rows.data();
+
+          double a = gjk(bd1, bd2, &s);
+
+          return a;
+        });
+}

python/test.py

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+import opengjkc as opengjk
+from scipy.spatial.transform import Rotation as R
+import numpy as np
+import pytest
+
+
+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=1e-15))
+
+
+@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=1e-15))
+
+
+@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)
+
+    assert(np.isclose(distance, actual_distance, atol=1e-15))
+
+
+@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=1e-15))
+
+
+@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=1e-15))
+
+
+@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=1e-15))
+    else:
+        print("Computed distance ", distance,
+              "Actual distance ", actual_distance)
+        assert(np.isclose(distance, actual_distance, atol=1e-15))
+
+
+@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=1e-15))
+    else:
+        print("Computed distance ", distance,
+              "Actual distance ", actual_distance)
+        assert(np.isclose(distance, actual_distance, atol=1e-15))
+
+
+@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)