code: def fit(self, X, y=None, init=None):
          
          self.fit_transform(X, init=init)
          return self
docs: 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.