def test_superlu_2_dense(small_superlu):
""" Tests the superlu wrapper to dense matrix function. """
superlu_mat = small_superlu
dense_mat = LinearAlgebraTools.superlu_sparse_2_dense(superlu_mat)
comparison_mat = numpy.loadtxt(
os.path.join(os.path.dirname(__file__), 'sparse_mat_1.txt'))
assert numpy.allclose(dense_mat, comparison_mat)
def test_superlu_2_dense(small_superlu):
""" Tests the superlu wrapper to dense matrix function. """
superlu_mat = small_superlu
dense_mat = LinearAlgebraTools.superlu_sparse_2_dense(superlu_mat)
comparison_mat = numpy.loadtxt(os.path.join(os.path.dirname(__file__),
'sparse_mat_1.txt'))
assert numpy.allclose(dense_mat,comparison_mat)
def test_1(self):
""" Initial test to check whether this is working """
self.laplace_object.modelList[0].levelModelList[0].calculateCoefficients()
rowptr, colind, nzval = self.laplace_object.modelList[0].levelModelList[0].jacobian.getCSRrepresentation()
self.laplace_object.modelList[0].levelModelList[0].scale_dt = False
self.Asys_rowptr = rowptr.copy()
self.Asys_colptr = colind.copy()
self.Asys_nzval = nzval.copy()
nn = len(self.Asys_rowptr)-1
self.Asys = LinearAlgebraTools.SparseMatrix(nn,nn,
self.Asys_nzval.shape[0],
self.Asys_nzval,
self.Asys_colptr,
self.Asys_rowptr)
self.petsc4py_A = self.laplace_object.modelList[0].levelModelList[0].getSpatialJacobian(self.Asys)
laplace_mat = LinearAlgebraTools.superlu_sparse_2_dense(self.petsc4py_A)
expected_output = os.path.dirname(os.path.abspath(__file__)) + '/comparison_files/laplace_reference_c0p1_2D.txt'
comparison_mat = numpy.loadtxt(expected_output)
assert numpy.allclose(laplace_mat,comparison_mat)
def test_superlu_2_dense():
""" Tests the superlu wrapper to dense matrix function. """
vals = numpy.array([
10., -2., 3., 9., 3., 7., 8., 7., 3., 8., 7., 5., 8., 9., 9., 13., 4.,
2., -1.
])
col_idx = numpy.array(
[0, 4, 0, 1, 5, 1, 2, 3, 0, 2, 3, 4, 1, 3, 4, 5, 1, 4, 5],
dtype='int32')
row_idx = numpy.array([0, 2, 5, 8, 12, 16, 19], dtype='int32')
size_n = len(row_idx) - 1
superlu_mat = LinearAlgebraTools.SparseMat(size_n, size_n, len(vals), vals,
col_idx, row_idx)
dense_mat = LinearAlgebraTools.superlu_sparse_2_dense(superlu_mat)
comparison_mat = numpy.loadtxt(
os.path.join(os.path.dirname(__file__), 'sparse_mat_1.txt'))
assert numpy.allclose(dense_mat, comparison_mat)
def test_superlu_2_dense():
""" Tests the superlu wrapper to dense matrix function. """
vals = numpy.array([10.,-2.,3.,9.,3.,7.,8.,7.,3.,
8.,7.,5.,8.,9.,9.,13.,4.,2.,-1.])
col_idx = numpy.array([0, 4 ,0 ,1 ,5 ,1 ,2 ,3 ,0 ,2 ,
3 ,4 ,1 ,3 ,4 ,5 ,1 ,4 , 5 ],
dtype='int32')
row_idx = numpy.array([0, 2, 5, 8, 12, 16, 19],
dtype='int32')
size_n = len(row_idx)-1
superlu_mat = LinearAlgebraTools.SparseMat(size_n,
size_n,
len(vals),
vals,
col_idx,
row_idx)
dense_mat = LinearAlgebraTools.superlu_sparse_2_dense(superlu_mat)
comparison_mat = numpy.loadtxt(os.path.join(os.path.dirname(__file__),
'sparse_mat_1.txt'))
assert numpy.allclose(dense_mat,comparison_mat)
def test_1(self):
""" Initial test to check whether this is working """
self.laplace_object.modelList[0].levelModelList[
0].calculateCoefficients()
rowptr, colind, nzval = self.laplace_object.modelList[
0].levelModelList[0].jacobian.getCSRrepresentation()
self.laplace_object.modelList[0].levelModelList[0].scale_dt = False
self.Asys_rowptr = rowptr.copy()
self.Asys_colptr = colind.copy()
self.Asys_nzval = nzval.copy()
nn = len(self.Asys_rowptr) - 1
self.Asys = LinearAlgebraTools.SparseMatrix(nn, nn,
self.Asys_nzval.shape[0],
self.Asys_nzval,
self.Asys_colptr,
self.Asys_rowptr)
self.petsc4py_A = self.laplace_object.modelList[0].levelModelList[
0].getSpatialJacobian(self.Asys)
laplace_mat = LinearAlgebraTools.superlu_sparse_2_dense(
self.petsc4py_A)
expected_output = os.path.dirname(os.path.abspath(
__file__)) + '/comparison_files/laplace_reference_c0p1_3D.txt'
comparison_mat = numpy.loadtxt(expected_output)
assert numpy.allclose(laplace_mat, comparison_mat)