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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def inverse(self):
 """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` """

        # 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)