def test_distance_generic_euclid():
"""Test euclidean distance for generic function"""
A = 2*np.eye(3)
B = 2*np.eye(3)
assert_equal(distance(A, B, metric='euclid'), distance_euclid(A, B))
def test_distance_euclid():
"""Test euclidean distance"""
A = 2*np.eye(3)
B = 2*np.eye(3)
assert_equal(distance_euclid(A, B), 0)
def test_distance_generic_euclid():
"""Test euclidean distance for generic function"""
A = 2 * np.eye(3)
B = 2 * np.eye(3)
assert_equal(distance(A, B, metric='euclid'), distance_euclid(A, B))
def test_distance_euclid():
"""Test euclidean distance"""
A = 2 * np.eye(3)
B = 2 * np.eye(3)
assert_equal(distance_euclid(A, B), 0)
cov_u3 = rotMatrix.dot(LambdaMatrix.dot(rotMatrix.transpose()))
LambdaMatrix = _draw_eigenvalues(dim=args.dim, b=args.b, distribution="unif", overlap=args.overlap_eigenvalues)
rotMatrix = _draw_rotation_matrix(args.dim)
cov_u4 = rotMatrix.dot(LambdaMatrix.dot(rotMatrix.transpose()))
covs_u = [cov_u1, cov_u2, cov_u3, cov_u4]
est_covsu = []
eucl_mean = []
riemann_mean = []
for i, cu in enumerate(covs_u):
our, eucl, riemann = _draw_subject_specific_and_estimate(cu, args.dim,
args.vnum, args.outliers,
args.b, args.show_corrs,
args.repeat_one, i)
est_covsu.append(our)
print("Estimation " + str(i) + " : Euclidean distance between our estimator and ground thruth is : " + str(distance_euclid(our, cu)))
eucl_mean.append(eucl)
print("Estimation " + str(i) + " : Euclidean distance between euclidean mean and ground thruth is : " + str(distance_euclid(eucl, cu)))
riemann_mean.append(riemann)
print("Estimation " + str(i) + " : Euclidean distance between riemannian mean and ground thruth is : " + str(distance_euclid(riemann, cu)))
if (args.visual):
f, axarr = plt.subplots(4, 4, figsize=(11, 5))
for i, cu in enumerate(covs_u):
# -----covariances---#
margins = 1
upper_bound = cu.max()+margins
lower_bound = cu.min()-margins
middle = (upper_bound+lower_bound)*0.5
im = axarr[i, 0].pcolormesh(np.flipud(cu.T),
def test_distance_euclid():
"""Test euclidean distance"""
A = 2 * np.eye(3)
B = 2 * np.eye(3)
assert distance_euclid(A, B) == 0
