def test_dist_double_float_1():
# test without X_indices
for metric in VECTOR_METRICS:
for X, Y in ((X_double, Y_double), (X_float, Y_float)):
dist_1 = dist(X, Y[0], metric)
dist_2 = scipy.spatial.distance.cdist(X, [Y[0]], metric)[:, 0]
yield lambda: np.testing.assert_almost_equal(
dist_1, dist_2, decimal=5 if X.dtype == np.float32 else 10)
def test_dist_double_float_1():
# test without X_indices
for metric in VECTOR_METRICS:
for X, Y in ((X_double, Y_double), (X_float, Y_float)):
dist_1 = dist(X, Y[0], metric)
dist_2 = cdist(X, Y, metric)[:, 0]
yield lambda: np.testing.assert_almost_equal(
dist_1, dist_2,
decimal=5 if X.dtype == np.float32 else 10)
def test_dist_double_float_2():
# test with X_indices
for metric in VECTOR_METRICS:
for X, Y in ((X_double, Y_double), (X_float, Y_float)):
dist_1 = dist(X, Y[0], metric, X_indices)
dist_2 = scipy.spatial.distance.cdist(X, [Y[0]], metric)[X_indices,0]
yield lambda : np.testing.assert_almost_equal(
dist_1,
dist_2,
decimal=5 if X.dtype == np.float32 else 10)
def test_dist_double_float_2():
# test with X_indices
for metric in VECTOR_METRICS:
for X, Y in ((X_double, Y_double), (X_float, Y_float)):
dist_1 = dist(X, Y[0], metric, X_indices)
dist_2 = cdist(X, Y, metric)[X_indices, 0]
yield lambda: np.testing.assert_almost_equal(
dist_1,
dist_2,
decimal=5 if X.dtype == np.float32 else 10)
def test_dist_rmsd_2():
d = dist(X_rmsd, Y_rmsd[0], "rmsd", X_indices)
ref = md.rmsd(X_rmsd, Y_rmsd[0], precentered=True).astype(np.double)[X_indices]
np.testing.assert_array_almost_equal(d, ref)
def test_dist_rmsd_2():
d = dist(X_rmsd, Y_rmsd[0], "rmsd", X_indices)
ref = md.rmsd(X_rmsd, Y_rmsd[0],
precentered=True).astype(np.double)[X_indices]
np.testing.assert_array_almost_equal(d, ref)
def f(X, Y):
return libdistance.dist(X, Y, metric)
