def fit(self, X):
"""Fit the parameters of the model.
Parameters
----------
X : array_like
Array of shape ``(n_samples, n_inpt)`` used for training."""
if self.zscores:
self.mean = X.mean(axis=0)
self.std = X.std(axis=0)
X -= self.mean
X /= self.std
if self.whiten:
self.zca = Zca(self.c_zca)
self.zca.fit(X)
X = self.zca.transform(X)
self.prepare(X.shape[1])
for i, info in enumerate(self.iter_fit(X)):
if i + 1 >= self.max_iter:
break
