'Feature-wise transformation of the data.
Parameters
X : ndarray or sparse matrix, shape (n_samples, n_features)
The data used to scale along the features axis. If a sparse
matrix is provided, it will be converted into a sparse
``csc_matrix``. Additionally, the sparse matrix needs to be
nonnegative if `ignore_implicit_zeros` is False.
Returns
Xt : ndarray or sparse matrix, shape (n_samples, n_features)
The projected data.'

def transform(self, X):

    X = self._check_inputs(X)
    self._check_is_fitted(X)
    return self._transform(X, inverse=False)
