4 tests fail: TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'

[yurivict]

========================================================================================= FAILURES ==========================================================================================
__________________________________________________________________________________ solve_ls.test_basic_ls ___________________________________________________________________________________

self = <tests.test_solve_ls.solve_ls testMethod=test_basic_ls>

    def test_basic_ls(self):
        np.random.seed(2)
        n = 5
        A = random_psd(n, n)
        B = random_psd(n, n)
        C = - random_psd(n, n)
        M = spa.bmat([[A, B.T], [B, C]], format='csc')
        b = np.random.randn(n + n)
    
        #  import ipdb; ipdb.set_trace()
        m = qdldl.Solver(M)
    
        x_qdldl = m.solve(b)
>       x_scipy = sla.spsolve(M, b)

tests/test_solve_ls.py:32: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/local/lib/python3.11/site-packages/scipy/sparse/linalg/_dsolve/linsolve.py:259: in spsolve
    x = umf.linsolve(umfpack.UMFPACK_A, A, b_vec,
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:770: in linsolve
    self.numeric(mtx)
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:555: in numeric
    self.symbolic(mtx)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <scikits.umfpack.umfpack.UmfpackContext object at 0x112b8ba19310>
mtx = <10x10 sparse matrix of type '<class 'numpy.float64'>'
        with 100 stored elements in Compressed Sparse Column format>

    def symbolic(self, mtx):
        """
        Perform symbolic object (symbolic LU decomposition) computation for a given
        sparsity pattern.
        """
        self.free_symbolic()
    
        indx = self._getIndx(mtx)
    
        if not assumeSortedIndices:
            # row/column indices cannot be assumed to be sorted
            mtx.sort_indices()
    
        if self.isReal:
            status, self._symbolic\
>                   = self.funs.symbolic(mtx.shape[0], mtx.shape[1],
                                          mtx.indptr,
                                          indx,
                                          mtx.data,
                                          self.control, self.info)
E           TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'

/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:522: TypeError
__________________________________________________________________________________ solve_ls.test_scalar_ls __________________________________________________________________________________

self = <tests.test_solve_ls.solve_ls testMethod=test_scalar_ls>

    def test_scalar_ls(self):
        M = spa.csc_matrix(np.random.randn(1, 1))
        b = np.random.randn(1)
    
        F = qdldl.Solver(M)
        x_qdldl = F.solve(b)
>       x_scipy = sla.spsolve(M, b)

tests/test_solve_ls.py:43: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/local/lib/python3.11/site-packages/scipy/sparse/linalg/_dsolve/linsolve.py:259: in spsolve
    x = umf.linsolve(umfpack.UMFPACK_A, A, b_vec,
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:770: in linsolve
    self.numeric(mtx)
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:555: in numeric
    self.symbolic(mtx)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <scikits.umfpack.umfpack.UmfpackContext object at 0x112b8bd48290>
mtx = <1x1 sparse matrix of type '<class 'numpy.float64'>'
        with 1 stored elements in Compressed Sparse Column format>

    def symbolic(self, mtx):
        """
        Perform symbolic object (symbolic LU decomposition) computation for a given
        sparsity pattern.
        """
        self.free_symbolic()
    
        indx = self._getIndx(mtx)
    
        if not assumeSortedIndices:
            # row/column indices cannot be assumed to be sorted
            mtx.sort_indices()
    
        if self.isReal:
            status, self._symbolic\
>                   = self.funs.symbolic(mtx.shape[0], mtx.shape[1],
                                          mtx.indptr,
                                          indx,
                                          mtx.data,
                                          self.control, self.info)
E           TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'

/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:522: TypeError
___________________________________________________________________________________ solve_ls.test_thread ____________________________________________________________________________________

self = <tests.test_solve_ls.solve_ls testMethod=test_thread>

    def test_thread(self):
    
        n = 100
        N = 400
    
        def get_random_ls(n):
            A = random_psd(n, n)
            B = random_psd(n, n)
            C = - random_psd(n, n)
            M = spa.bmat([[A, B.T], [B, C]], format='csc')
            b = np.random.randn(n + n)
            return M, b
    
        ls = [get_random_ls(n) for _ in range(N)]
    
        # Solve in loop with scipy
        res_scipy = []
        for (M, b) in ls:
>           res_scipy.append(sla.spsolve(M, b))

tests/test_solve_ls.py:66: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/local/lib/python3.11/site-packages/scipy/sparse/linalg/_dsolve/linsolve.py:259: in spsolve
    x = umf.linsolve(umfpack.UMFPACK_A, A, b_vec,
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:770: in linsolve
    self.numeric(mtx)
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:555: in numeric
    self.symbolic(mtx)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <scikits.umfpack.umfpack.UmfpackContext object at 0x112b8c4d8c90>
mtx = <200x200 sparse matrix of type '<class 'numpy.float64'>'
        with 40000 stored elements in Compressed Sparse Column format>

    def symbolic(self, mtx):
        """
        Perform symbolic object (symbolic LU decomposition) computation for a given
        sparsity pattern.
        """
        self.free_symbolic()
    
        indx = self._getIndx(mtx)
    
        if not assumeSortedIndices:
            # row/column indices cannot be assumed to be sorted
            mtx.sort_indices()
    
        if self.isReal:
            status, self._symbolic\
>                   = self.funs.symbolic(mtx.shape[0], mtx.shape[1],
                                          mtx.indptr,
                                          indx,
                                          mtx.data,
                                          self.control, self.info)
E           TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'

/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:522: TypeError
___________________________________________________________________________________ solve_ls.test_update ____________________________________________________________________________________

self = <tests.test_solve_ls.solve_ls testMethod=test_update>

    def test_update(self):
        n = 5
        A = random_psd(n, n)
        B = random_psd(n, n)
        C = - random_psd(n, n)
        M = spa.bmat([[A, B.T], [B, C]], format='csc')
    
        b = np.random.randn(n + n)
    
        F = qdldl.Solver(M)
    
>       x_first_scipy = sla.spsolve(M, b)

tests/test_solve_ls.py:106: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/local/lib/python3.11/site-packages/scipy/sparse/linalg/_dsolve/linsolve.py:259: in spsolve
    x = umf.linsolve(umfpack.UMFPACK_A, A, b_vec,
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:770: in linsolve
    self.numeric(mtx)
/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:555: in numeric
    self.symbolic(mtx)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <scikits.umfpack.umfpack.UmfpackContext object at 0x112b8c4d8890>
mtx = <10x10 sparse matrix of type '<class 'numpy.float64'>'
        with 100 stored elements in Compressed Sparse Column format>

    def symbolic(self, mtx):
        """
        Perform symbolic object (symbolic LU decomposition) computation for a given
        sparsity pattern.
        """
        self.free_symbolic()
    
        indx = self._getIndx(mtx)
    
        if not assumeSortedIndices:
            # row/column indices cannot be assumed to be sorted
            mtx.sort_indices()
    
        if self.isReal:
            status, self._symbolic\
>                   = self.funs.symbolic(mtx.shape[0], mtx.shape[1],
                                          mtx.indptr,
                                          indx,
                                          mtx.data,
                                          self.control, self.info)
E           TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'

/usr/local/lib/python3.11/site-packages/scikits/umfpack/umfpack.py:522: TypeError
================================================================================== short test summary info ==================================================================================
FAILED tests/test_solve_ls.py::solve_ls::test_basic_ls - TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'
FAILED tests/test_solve_ls.py::solve_ls::test_scalar_ls - TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'
FAILED tests/test_solve_ls.py::solve_ls::test_thread - TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'
FAILED tests/test_solve_ls.py::solve_ls::test_update - TypeError: umfpack_dl_symbolic() missing 1 required positional argument: 'Info'
=============================================================================== 4 failed, 5 passed in 12.28s ================================================================================

Version: 0.1.7.post5
Python-3.11