========================================================================================= 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