def from_points(cls, points):
if points.ndim != 2:
raise ValueError('"points" should have two dimensions.')
if points.shape[0] < 3:
raise ValueError('"points" should contain at least 3 points.')
if points.shape[1] != 3:
raise ValueError('"points" should be X*3 (x,y,z).')
return cls(points, points.shape[0], DistanceMatrix.from_points(points))
def test_get_flatten_upper_triangular_matrix(self):
points = np.array([
[1, 0, 0],
[2, 0, 0],
[3, 0, 0],
[4, 0, 0],
])
distance_matrix = DistanceMatrix.from_points(points)
flatten_upper_triangular_matrix = distance_matrix.get_futm()
correct_flatten_upper_triangular_matrix = [
1.0, 2.0, 3.0, 1.0, 2.0, 1.0
]
self.assertEqual(flatten_upper_triangular_matrix,
correct_flatten_upper_triangular_matrix)
def test___init__(self):
points = np.array([
[1, 0, 0],
[2, 0, 0],
[3, 0, 0],
[4, 0, 0],
])
distance_matrix = DistanceMatrix.from_points(points)
correct_distance_matrix = np.array([
[0, 1, 2, 3],
[1, 0, 1, 2],
[2, 1, 0, 1],
[3, 2, 1, 0],
])
self.assertEqual(distance_matrix.size, 4)
self.assertTrue(
np.array_equal(distance_matrix.distance_matrix_nparray,
correct_distance_matrix))