static PyObject *
Py_gstrf(PyObject *self, PyObject *args, PyObject *keywds)
{
/* default value for SuperLU parameters*/
int N, nnz;
PyArrayObject *rowind, *colptr, *nzvals;
SuperMatrix A;
PyObject *result;
PyObject *option_dict = NULL;
int type;
int ilu = 0;
static char *kwlist[] = {"N","nnz","nzvals","colind","rowptr",
"options", "ilu",
NULL};
int res = PyArg_ParseTupleAndKeywords(
args, keywds, "iiO!O!O!|Oi", kwlist,
&N, &nnz,
&PyArray_Type, &nzvals,
&PyArray_Type, &rowind,
&PyArray_Type, &colptr,
&option_dict,
&ilu);
if (!res)
return NULL;
if (!_CHECK_INTEGER(colptr) || !_CHECK_INTEGER(rowind)) {
PyErr_SetString(PyExc_TypeError,
"rowind and colptr must be of type cint");
return NULL;
}
type = PyArray_TYPE(nzvals);
if (!CHECK_SLU_TYPE(type)) {
PyErr_SetString(PyExc_TypeError,
"nzvals is not of a type supported by SuperLU");
return NULL;
}
if (NCFormat_from_spMatrix(&A, N, N, nnz, nzvals, rowind, colptr,
type)) {
goto fail;
}
result = newSciPyLUObject(&A, option_dict, type, ilu);
if (result == NULL) {
goto fail;
}
/* arrays of input matrix will not be freed */
Destroy_SuperMatrix_Store(&A);
return result;
fail:
/* arrays of input matrix will not be freed */
Destroy_SuperMatrix_Store(&A);
return NULL;
}
static PyObject *
Py_sgstrf(PyObject *self, PyObject *args, PyObject *keywds) {
/* default value for SuperLU parameters*/
double diag_pivot_thresh = 1.0;
double drop_tol = 0.0;
int relax = 1;
int panel_size = 10;
int permc_spec = 2;
int N, nnz;
PyArrayObject *rowind, *colptr, *nzvals;
SuperMatrix A;
PyObject *result;
static char *kwlist[] = {"N","nnz","nzvals","rowind","colptr","permc_spec","diag_pivot_thresh", "drop_tol", "relax", "panel_size", NULL};
int res = PyArg_ParseTupleAndKeywords(args, keywds, "iiO!O!O!|iddii", kwlist,
&N, &nnz,
&PyArray_Type, &nzvals,
&PyArray_Type, &rowind,
&PyArray_Type, &colptr,
&permc_spec,
&diag_pivot_thresh,
&drop_tol,
&relax,
&panel_size);
if (!res)
return NULL;
if (!_CHECK_INTEGER(colptr) || !_CHECK_INTEGER(rowind)) {
PyErr_SetString(PyExc_TypeError, "colptr and rowind must be of type cint");
return NULL;
}
if (NCFormat_from_spMatrix(&A, N, N, nnz, nzvals, rowind, colptr, PyArray_FLOAT)) goto fail;
result = newSciPyLUObject(&A, diag_pivot_thresh, drop_tol, relax, panel_size,\
permc_spec, PyArray_FLOAT);
if (result == NULL) goto fail;
Destroy_SuperMatrix_Store(&A); /* arrays of input matrix will not be freed */
return result;
fail:
Destroy_SuperMatrix_Store(&A); /* arrays of input matrix will not be freed */
return NULL;
}
static PyObject *
Py_gssv(PyObject *self, PyObject *args, PyObject *kwdict)
{
PyObject *Py_B=NULL, *Py_X=NULL;
PyArrayObject *nzvals=NULL;
PyArrayObject *colind=NULL, *rowptr=NULL;
int N, nnz;
int info;
int csc=0;
int *perm_r=NULL, *perm_c=NULL;
SuperMatrix A, B, L, U;
superlu_options_t options;
SuperLUStat_t stat;
PyObject *option_dict = NULL;
int type;
int ssv_finished = 0;
static char *kwlist[] = {"N","nnz","nzvals","colind","rowptr","B", "csc",
"options",NULL};
/* Get input arguments */
if (!PyArg_ParseTupleAndKeywords(args, kwdict, "iiO!O!O!O|iO", kwlist,
&N, &nnz, &PyArray_Type, &nzvals,
&PyArray_Type, &colind, &PyArray_Type,
&rowptr, &Py_B, &csc, &option_dict)) {
return NULL;
}
if (!_CHECK_INTEGER(colind) || !_CHECK_INTEGER(rowptr)) {
PyErr_SetString(PyExc_TypeError,
"colind and rowptr must be of type cint");
return NULL;
}
type = PyArray_TYPE(nzvals);
if (!CHECK_SLU_TYPE(type)) {
PyErr_SetString(PyExc_TypeError,
"nzvals is not of a type supported by SuperLU");
return NULL;
}
if (!set_superlu_options_from_dict(&options, 0, option_dict, NULL, NULL)) {
return NULL;
}
/* Create Space for output */
Py_X = PyArray_CopyFromObject(Py_B, type, 1, 2);
if (Py_X == NULL) return NULL;
if (csc) {
if (NCFormat_from_spMatrix(&A, N, N, nnz, nzvals, colind, rowptr,
type)) {
Py_DECREF(Py_X);
return NULL;
}
}
else {
if (NRFormat_from_spMatrix(&A, N, N, nnz, nzvals, colind, rowptr,
type)) {
Py_DECREF(Py_X);
return NULL;
}
}
if (DenseSuper_from_Numeric(&B, Py_X)) {
Destroy_SuperMatrix_Store(&A);
Py_DECREF(Py_X);
return NULL;
}
/* B and Py_X share same data now but Py_X "owns" it */
/* Setup options */
if (setjmp(_superlu_py_jmpbuf)) {
goto fail;
}
else {
perm_c = intMalloc(N);
perm_r = intMalloc(N);
StatInit(&stat);
/* Compute direct inverse of sparse Matrix */
gssv(type, &options, &A, perm_c, perm_r, &L, &U, &B, &stat, &info);
}
ssv_finished = 1;
SUPERLU_FREE(perm_r);
SUPERLU_FREE(perm_c);
Destroy_SuperMatrix_Store(&A); /* holds just a pointer to the data */
Destroy_SuperMatrix_Store(&B);
Destroy_SuperNode_Matrix(&L);
Destroy_CompCol_Matrix(&U);
StatFree(&stat);
return Py_BuildValue("Ni", Py_X, info);
fail:
SUPERLU_FREE(perm_r);
SUPERLU_FREE(perm_c);
Destroy_SuperMatrix_Store(&A); /* holds just a pointer to the data */
Destroy_SuperMatrix_Store(&B);
if (ssv_finished) {
/* Avoid trying to free partially initialized matrices;
might leak some memory, but avoids a crash */
Destroy_SuperNode_Matrix(&L);
Destroy_CompCol_Matrix(&U);
}
StatFree(&stat);
Py_XDECREF(Py_X);
return NULL;
}
static PyObject *Py_sgssv (PyObject *self, PyObject *args, PyObject *kwdict)
{
PyObject *Py_B=NULL, *Py_X=NULL;
PyArrayObject *nzvals=NULL;
PyArrayObject *colind=NULL, *rowptr=NULL;
int N, nnz;
int info;
int csc=0, permc_spec=2;
int *perm_r=NULL, *perm_c=NULL;
SuperMatrix A, B, L, U;
superlu_options_t options;
SuperLUStat_t stat;
static char *kwlist[] = {"N","nnz","nzvals","colind","rowptr","B", "csc", "permc_spec",NULL};
/* Get input arguments */
if (!PyArg_ParseTupleAndKeywords(args, kwdict, "iiO!O!O!O|ii", kwlist, &N, &nnz, &PyArray_Type, &nzvals, &PyArray_Type, &colind, &PyArray_Type, &rowptr, &Py_B, &csc, &permc_spec))
return NULL;
if (!_CHECK_INTEGER(colind) || !_CHECK_INTEGER(rowptr)) {
PyErr_SetString(PyExc_TypeError, "colind and rowptr must be of type cint");
return NULL;
}
/* Create Space for output */
Py_X = PyArray_CopyFromObject(Py_B,PyArray_FLOAT,1,2);
if (Py_X == NULL) return NULL;
if (csc) {
if (NCFormat_from_spMatrix(&A, N, N, nnz, nzvals, colind, rowptr, PyArray_FLOAT)) {
Py_DECREF(Py_X);
return NULL;
}
}
else {
if (NRFormat_from_spMatrix(&A, N, N, nnz, nzvals, colind, rowptr, PyArray_FLOAT)) {
Py_DECREF(Py_X);
return NULL;
}
}
if (DenseSuper_from_Numeric(&B, Py_X)) {
Destroy_SuperMatrix_Store(&A);
Py_DECREF(Py_X);
return NULL;
}
/* B and Py_X share same data now but Py_X "owns" it */
/* Setup options */
if (setjmp(_superlu_py_jmpbuf)) goto fail;
else {
perm_c = intMalloc(N);
perm_r = intMalloc(N);
set_default_options(&options);
options.ColPerm=superlu_module_getpermc(permc_spec);
StatInit(&stat);
/* Compute direct inverse of sparse Matrix */
sgssv(&options, &A, perm_c, perm_r, &L, &U, &B, &stat, &info);
}
SUPERLU_FREE(perm_r);
SUPERLU_FREE(perm_c);
Destroy_SuperMatrix_Store(&A);
Destroy_SuperMatrix_Store(&B);
Destroy_SuperNode_Matrix(&L);
Destroy_CompCol_Matrix(&U);
StatFree(&stat);
return Py_BuildValue("Ni", Py_X, info);
fail:
SUPERLU_FREE(perm_r);
SUPERLU_FREE(perm_c);
Destroy_SuperMatrix_Store(&A);
Destroy_SuperMatrix_Store(&B);
Destroy_SuperNode_Matrix(&L);
Destroy_CompCol_Matrix(&U);
StatFree(&stat);
Py_XDECREF(Py_X);
return NULL;
}
