def function():
covmat1 = CovMat.random(100)
covmat2 = CovMat.random(100)
a = Distance.euclidean(covmat1, covmat2)
b = Distance.log_euclidean(covmat1, covmat2)
c = Distance.log_determinant(covmat1, covmat2)
d = Distance.riemannian(covmat1, covmat2)
e = Distance.wasserstein(covmat1, covmat2)
f = Distance.kullback(covmat1, covmat2)
g = Distance.kullback_right(covmat1, covmat2)
h = Distance.kullback_sym(covmat1, covmat2)
def test_euclidean():
m1 = CovMat.random(10)
m2 = CovMat.random(10)
old_dist = distance_euclid(m1.numpy_array, m2.numpy_array)
m1.reset_fields()
m2.reset_fields()
new_dist = Distance.euclidean(m1, m2)
if abs( old_dist - new_dist ) < 1e-10:
print("euclid: PASS")
return True
else:
print("euclid: FAIL")
return False
def test_euclidean():
m1 = CovMat.random(10)
m2 = CovMat.random(10)
old_dist = distance_euclid(m1.numpy_array, m2.numpy_array)
m1.reset_fields()
m2.reset_fields()
new_dist = Distance.euclidean(m1, m2)
if abs(old_dist - new_dist) < 1e-10:
print("euclid: PASS")
return True
else:
print("euclid: FAIL")
return False
