'Recover the sources from X (apply the unmixing matrix).
Parameters
X : array-like, shape (n_samples, n_features)
Data to transform, where n_samples is the number of samples
and n_features is the number of features.
y : (ignored)
.. deprecated:: 0.19
This parameter will be removed in 0.21.
copy : bool (optional)
If False, data passed to fit are overwritten. Defaults to True.
Returns
X_new : array-like, shape (n_samples, n_components)'

def transform(self, X, y='deprecated', copy=True):

    if ((not isinstance(y, string_types)) or (y != 'deprecated')):
        warnings.warn('The    parameter    y    on    transform()    is    deprecated    since    0.19    and    will    be    removed    in    0.21', DeprecationWarning)
    check_is_fitted(self, 'mixing_')
    X = check_array(X, copy=copy, dtype=FLOAT_DTYPES)
    if self.whiten:
        X -= self.mean_
    return np.dot(X, self.components_.T)
