def fit(self, X, y=None, init=None):
        """
        Computes the position of the points in the embedding space

        Parameters
        ----------
        X : array, shape=[n_samples, n_features], or [n_samples, n_samples] \
                if dissimilarity='precomputed'
            Input data.

        init : {None or ndarray, shape (n_samples,)}, optional
            If None, randomly chooses the initial configuration
            if ndarray, initialize the SMACOF algorithm with this array.
        """
        self.fit_transform(X, init=init)
        return self
Computes the position of the points in the embedding space

        Parameters
        ----------
        X : array, shape=[n_samples, n_features], or [n_samples, n_samples] \
                if dissimilarity='precomputed'
            Input data.

        init : {None or ndarray, shape (n_samples,)}, optional
            If None, randomly chooses the initial configuration
            if ndarray, initialize the SMACOF algorithm with this array.