Trac #4932: remove solve_left_LU for matrices

Author: jdemeyer

src/sage/matrix/matrix_double_dense.pyx

@@ -1619,70 +1619,6 @@ cdef class Matrix_double_dense(matrix_dense.Matrix_dense):
 
     eigenvectors_right = right_eigenvectors
 
-    def solve_left_LU(self, b):
-        """
-        Solve the equation `A x = b` using LU decomposition.
-
-        .. WARNING::
-
-            This function is broken. See trac 4932.
-
-        INPUT:
-
-        - self -- an invertible matrix
-        - b -- a vector
-
-        .. NOTE::
-
-            This method precomputes and stores the LU decomposition
-            before solving. If many equations of the form Ax=b need to be
-            solved for a singe matrix A, then this method should be used
-            instead of solve. The first time this method is called it will
-            compute the LU decomposition.  If the matrix has not changed
-            then subsequent calls will be very fast as the precomputed LU
-            decomposition will be reused.
-
-        EXAMPLES::
-
-            sage: A = matrix(RDF, 3,3, [1,2,5,7.6,2.3,1,1,2,-1]); A
-            [ 1.0  2.0  5.0]
-            [ 7.6  2.3  1.0]
-            [ 1.0  2.0 -1.0]
-            sage: b = vector(RDF,[1,2,3])
-            sage: x = A.solve_left_LU(b); x
-            Traceback (most recent call last):
-            ...
-            NotImplementedError: this function is not finished (see trac 4932)
-
-
-        TESTS:
-
-        We test two degenerate cases::
-
-            sage: A = matrix(RDF, 0, 3, [])
-            sage: A.solve_left_LU(vector(RDF,[]))
-            (0.0, 0.0, 0.0)
-            sage: A = matrix(RDF, 3, 0, [])
-            sage: A.solve_left_LU(vector(RDF,3, [1,2,3]))
-            ()
-
-        """
-        if self._nrows != b.degree():
-            raise ValueError("number of rows of self must equal degree of b")
-        if self._nrows == 0 or self._ncols == 0:
-            return self._row_ambient_module().zero_vector()
-
-        raise NotImplementedError("this function is not finished (see trac 4932)")
-        self._c_compute_LU()  # so self._L_M and self._U_M are defined below.
-        cdef Matrix_double_dense M = self._new()
-        lu = self._L_M*self._U_M
-        global scipy
-        if scipy is None:
-            import scipy
-        import scipy.linalg
-        M._matrix_numpy = scipy.linalg.lu_solve((lu, self._P_M), b)
-        return M
-
     def solve_right(self, b):
         r"""
         Solve the vector equation ``A*x = b`` for a nonsingular ``A``.