def fit(self, X, y):
"""Compute Frechet mean of each class.
Parameters
----------
X : array-like, shape=[n_samples, dim]
if point_type='vector'
shape=[n_samples, n, n]
if point_type='matrix'
Training data, where n_samples is the number of samples
and n_features is the number of features.
y : array-like, shape=[n_samples,]
Training labels.
"""
self.classes_ = gs.unique(y)
mean_estimator = FrechetMean(metric=self.riemannian_metric,
point_type=self.point_type)
frechet_means = []
for c in self.classes_:
X_c = X[gs.where(y == c, True, False)]
frechet_means.append(mean_estimator.fit(X_c).estimate_)
self.mean_estimates_ = gs.array(frechet_means)
def test_unique(self):
vec = gs.array([-1, 0, 1, 1, 0, -1])
result = gs.unique(vec)
expected = gs.array([-1, 0, 1])
self.assertAllClose(result, expected)