def inverse_transform(self, X, y=None):
        """Transform data back to its original space.

        In other words, return an input X_original whose transform would be X.

        Parameters
        ----------
        X : array-like, shape (n_samples, n_components)
            New data, where n_samples is the number of samples
            and n_components is the number of components.

        Returns
        -------
        X_original array-like, shape (n_samples, n_features)

        Notes
        -----
        If whitening is enabled, inverse_transform will compute the
        exact inverse operation, which includes reversing whitening.
        """
        if self.whiten:
            return fast_dot(X, np.sqrt(self.explained_variance_[:, np.newaxis]) /
                            self.components_) + self.mean_
        else:
            return fast_dot(X, self.components_) + self.mean_
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/decomposition/base.py/_BasePCA.inverse_transform/operator `*` -> `/`