code: def inverse(self):
          
          # Lazy import to improve `import odl` time
          import scipy.sparse
  
          if scipy.sparse.isspmatrix(self.matrix):
              dense_matrix = self.matrix.toarray()
          else:
              dense_matrix = self.matrix
  
          return MatrixOperator(np.linalg.inv(dense_matrix),
                                domain=self.range, range=self.domain,
                                axis=self.axis)
docs: Inverse operator represented by the inverse matrix.
  
          Taking the inverse causes sparse matrices to become dense and is
          generally very heavy computationally since the matrix is inverted
          numerically (an O(n^3) operation). It is recommended to instead
          use one of the solvers available in the ``odl.solvers`` package.
  
          Returns
          -------
          inverse : `MatrixOperator`