def test_distances_periodic():
coords = np.array([[0.0, 0.0, 0.0], [0.0, 0.9, 0.0], [0.0, 0.2, 0.0]])
coords = np.random.random((1000, 3))
periodic = np.array([1.0, 1.0, 1.0])
cutoff = 0.1
# Consistency checks
dist_simple = distance_matrix(coords, coords, periodic=periodic)
dist_dask = distance_matrix(da.from_array(coords, chunks=100),
da.from_array(coords, chunks=100),
da.from_array(periodic, chunks=3))
assert np.allclose(dist_dask, dist_simple)
def test_distances_periodic():
coords = np.array([[0.0, 0.0, 0.0],
[0.0, 0.9, 0.0],
[0.0, 0.2, 0.0]])
coords = np.random.random((1000, 3))
periodic = np.array([1.0, 1.0, 1.0])
cutoff = 0.1
# Consistency checks
dist_simple = distance_matrix(coords, coords, periodic=periodic)
dist_dask = distance_matrix(da.from_array(coords, chunks=100),
da.from_array(coords, chunks=100),
da.from_array(periodic, chunks=3))
assert np.allclose(dist_dask, dist_simple)
def test_distances_periodic():
coords = np.array([[0.0, 0.0, 0.0], [0.0, 0.9, 0.0], [0.0, 0.2, 0.0]])
coords = np.random.random((1000, 3))
periodic = np.array([1.0, 1.0, 1.0])
cutoff = 0.1
# Consistency checks
dist_simple = distance_matrix(coords, coords, periodic=periodic)
def test_distances_periodic():
coords = np.array([[0.0, 0.0, 0.0],
[0.0, 0.9, 0.0],
[0.0, 0.2, 0.0]])
coords = np.random.random((1000, 3))
periodic = np.array([1.0, 1.0, 1.0])
cutoff = 0.1
# Consistency checks
dist_simple = distance_matrix(coords, coords, periodic=periodic)