static PyObject *SCMcolumn
(PyObject *self, PyObject *args)
{
PyObject *H,*Av,*Ip,*Jp,*V;
int_t m,n,K;
int_t i,j,k,l,p,q,r,c;
if(!PyArg_ParseTuple(args,"OOOOOn",&H,&Av,&V,&Ip,&Jp,&j)) return NULL;
m = MAT_NCOLS(H);
n = MAT_NROWS(V);
K = MAT_NCOLS(V)/2;
//#pragma omp parallel for shared(m,n,K,Av,Ip,Jp,H,V,j) private(i,l,k,r,c,q,p)
for (i=j;i<m;i++) {
p = SP_COL(Av)[i];
MAT_BUFD(H)[j*m+i] = 0;
for (l=0;l<SP_COL(Av)[i+1]-p;l++) {
q = SP_ROW(Av)[p+l];
r = MAT_BUFI(Ip)[q];
c = MAT_BUFI(Jp)[q];
for (k=0;k<K;k++) {
MAT_BUFD(H)[j*m+i] += SP_VALD(Av)[p+l]*
MAT_BUFD(V)[k*n+r]*MAT_BUFD(V)[(K+k)*n+c];
if (r != c)
MAT_BUFD(H)[j*m+i] += SP_VALD(Av)[p+l]*
MAT_BUFD(V)[k*n+c]*MAT_BUFD(V)[(K+k)*n+r];
}
}
}
Py_RETURN_NONE;
}
static PyObject *toeplitz
(PyObject *self, PyObject *args, PyObject *kwrds) {
PyObject *r=NULL, *c=NULL;
int_t m,n,i,j;
char *kwlist[] = {"c","r",NULL};
if (!PyArg_ParseTupleAndKeywords(args,kwrds,"O|O",kwlist,&c,&r)) return NULL;
if (!Matrix_Check(c))
return NULL;
if (r==NULL)
r = c;
else if (!Matrix_Check(r))
return NULL;
if (MAT_ID(r) != DOUBLE || MAT_ID(c) != DOUBLE)
return NULL;
if (MAT_NCOLS(r) > 1 || MAT_NCOLS(c) > 1)
return NULL;
m = MAT_NROWS(c);
n = MAT_NROWS(r);
// build dense toeplitz matrix, column by column
matrix *T = Matrix_New(m,n,DOUBLE);
if (!T) return PyErr_NoMemory();
for(j=0;j<n;j++) {
for(i=0;i<(m>j?j:m);i++) {
MAT_BUFD(T)[j*m+i] = MAT_BUFD(r)[j-i];
}
for(i=j;i<m;i++) {
MAT_BUFD(T)[j*m+i] = MAT_BUFD(c)[i-j];
}
}
return (PyObject*) T;
}
static PyObject *SCMcolumn2
(PyObject *self, PyObject *args)
{
PyObject *H,*Av,*Ip,*Jp,*V,*Kl;
int_t m,n;
int_t i,j,k,p,q,r,c,r1,c1,pj,pi;
double alpha,beta;
if(!PyArg_ParseTuple(args,"OOOOOOn",&H,&Av,&V,&Ip,&Jp,&Kl,&j)) return NULL;
m = MAT_NCOLS(H);
n = MAT_NROWS(V);
for (i=j;i<m;i++) MAT_BUFD(H)[j*m+i] = 0;
//#pragma omp parallel for shared(m,n,K,Av,Ip,Jp,H,V,j) private(i,l,k,r,c,q,p)
pj = SP_COL(Av)[j];
for (p=0;p<SP_COL(Av)[j+1]-pj;p++) {
alpha = SP_VALD(Av)[pj+p];
k = SP_ROW(Av)[pj+p];
r = MAT_BUFI(Ip)[k];
c = MAT_BUFI(Jp)[k];
if (r!=c) alpha*=2;
// look up columns in V
r = MAT_BUFI(Kl)[r];
c = MAT_BUFI(Kl)[c];
for(i=j;i<m;i++) {
pi = SP_COL(Av)[i];
for (q=0;q<SP_COL(Av)[i+1]-pi;q++) {
beta = SP_VALD(Av)[pi+q];
k = SP_ROW(Av)[pi+q];
r1 = MAT_BUFI(Ip)[k];
c1 = MAT_BUFI(Jp)[k];
MAT_BUFD(H)[j*m+i] += alpha*beta*MAT_BUFD(V)[n*r+r1]*MAT_BUFD(V)[n*c+c1];
if (r1!=c1)
MAT_BUFD(H)[j*m+i] += alpha*beta*MAT_BUFD(V)[n*r+c1]*MAT_BUFD(V)[n*c+r1];
}
}
}
Py_RETURN_NONE;
}
static PyObject* linsolve(PyObject *self, PyObject *args,
PyObject *kwrds)
{
spmatrix *A;
matrix *B, *P=NULL;
int i, n, nnz, oB=0, ldB=0, nrhs=-1;
cholmod_sparse *Ac=NULL;
cholmod_factor *L=NULL;
cholmod_dense *x=NULL, *b=NULL;
void *b_old;
#if PY_MAJOR_VERSION >= 3
int uplo_ = 'L';
#endif
char uplo='L';
char *kwlist[] = {"A", "B", "p", "uplo", "nrhs", "ldB", "offsetB",
NULL};
if (!set_options()) return NULL;
#if PY_MAJOR_VERSION >= 3
if (!PyArg_ParseTupleAndKeywords(args, kwrds, "OO|OCiii", kwlist,
&A, &B, &P, &uplo_, &nrhs, &ldB, &oB)) return NULL;
uplo = (char) uplo_;
#else
if (!PyArg_ParseTupleAndKeywords(args, kwrds, "OO|Ociii", kwlist,
&A, &B, &P, &uplo, &nrhs, &ldB, &oB)) return NULL;
#endif
if (!SpMatrix_Check(A) || SP_NROWS(A) != SP_NCOLS(A))
PY_ERR_TYPE("A is not a sparse matrix");
n = SP_NROWS(A);
nnz = SP_NNZ(A);
if (!Matrix_Check(B) || MAT_ID(B) != SP_ID(A))
PY_ERR_TYPE("B must be a dense matrix of the same numerical "
"type as A");
if (nrhs < 0) nrhs = MAT_NCOLS(B);
if (n == 0 || nrhs == 0) return Py_BuildValue("");
if (ldB == 0) ldB = MAX(1,MAT_NROWS(B));
if (ldB < MAX(1,n)) err_ld("ldB");
if (oB < 0) err_nn_int("offsetB");
if (oB + (nrhs-1)*ldB + n > MAT_LGT(B)) err_buf_len("B");
if (P) {
if (!Matrix_Check(P) || MAT_ID(P) != INT) err_int_mtrx("p");
if (MAT_LGT(P) != n) err_buf_len("p");
if (!CHOL(check_perm)(P->buffer, n, n, &Common))
PY_ERR(PyExc_ValueError, "not a valid permutation");
}
if (uplo != 'U' && uplo != 'L') err_char("uplo", "'L', 'U'");
if (!(Ac = pack(A, uplo))) return PyErr_NoMemory();
L = CHOL(analyze_p)(Ac, P ? MAT_BUFI(P): NULL, NULL, 0, &Common);
if (Common.status != CHOLMOD_OK){
free_matrix(Ac);
CHOL(free_sparse)(&Ac, &Common);
CHOL(free_factor)(&L, &Common);
if (Common.status == CHOLMOD_OUT_OF_MEMORY)
return PyErr_NoMemory();
else {
PyErr_SetString(PyExc_ValueError, "symbolic factorization "
"failed");
return NULL;
}
}
CHOL(factorize) (Ac, L, &Common);
CHOL(free_sparse)(&Ac, &Common);
if (Common.status < 0) {
CHOL(free_factor)(&L, &Common);
switch (Common.status) {
case CHOLMOD_OUT_OF_MEMORY:
return PyErr_NoMemory();
default:
PyErr_SetString(PyExc_ValueError, "factorization "
"failed");
return NULL;
}
}
if (Common.status > 0) switch (Common.status) {
case CHOLMOD_NOT_POSDEF:
PyErr_SetObject(PyExc_ArithmeticError,
Py_BuildValue("i", L->minor));
CHOL(free_factor)(&L, &Common);
return NULL;
break;
case CHOLMOD_DSMALL:
/* This never happens unless we change the default value
* of Common.dbound (0.0). */
if (L->is_ll)
PyErr_Warn(PyExc_RuntimeWarning, "tiny diagonal "
"elements in L");
else
PyErr_Warn(PyExc_RuntimeWarning, "tiny diagonal "
"elements in D");
break;
default:
PyErr_Warn(PyExc_UserWarning, "");
}
if (L->minor<n) {
CHOL(free_factor)(&L, &Common);
PY_ERR(PyExc_ArithmeticError, "singular matrix");
}
b = CHOL(allocate_dense)(n, 1, n, (MAT_ID(B) == DOUBLE ?
CHOLMOD_REAL : CHOLMOD_COMPLEX) , &Common);
if (Common.status == CHOLMOD_OUT_OF_MEMORY) {
CHOL(free_factor)(&L, &Common);
CHOL(free_dense)(&b, &Common);
return PyErr_NoMemory();
}
b_old = b->x;
for (i=0; i<nrhs; i++) {
b->x = MAT_BUF(B) + (i*ldB + oB)*E_SIZE[MAT_ID(B)];
x = CHOL(solve) (CHOLMOD_A, L, b, &Common);
if (Common.status != CHOLMOD_OK){
PyErr_SetString(PyExc_ValueError, "solve step failed");
CHOL(free_factor)(&L, &Common);
b->x = b_old;
CHOL(free_dense)(&b, &Common);
CHOL(free_dense)(&x, &Common);
return NULL;
}
memcpy(b->x, x->x, SP_NROWS(A)*E_SIZE[MAT_ID(B)]);
CHOL(free_dense)(&x, &Common);
}
b->x = b_old;
CHOL(free_dense)(&b, &Common);
CHOL(free_factor)(&L, &Common);
return Py_BuildValue("");
}
static PyObject* solve(PyObject *self, PyObject *args, PyObject *kwrds)
{
matrix *B;
PyObject *F;
int i, n, oB=0, ldB=0, nrhs=-1, sys=0;
#if PY_MAJOR_VERSION >= 3
const char *descr;
#else
char *descr;
#endif
char *kwlist[] = {"F", "B", "sys", "nrhs", "ldB", "offsetB", NULL};
int sysvalues[] = { CHOLMOD_A, CHOLMOD_LDLt, CHOLMOD_LD,
CHOLMOD_DLt, CHOLMOD_L, CHOLMOD_Lt, CHOLMOD_D, CHOLMOD_P,
CHOLMOD_Pt };
if (!set_options()) return NULL;
if (!PyArg_ParseTupleAndKeywords(args, kwrds, "OO|iiii", kwlist,
&F, &B, &sys, &nrhs, &ldB, &oB)) return NULL;
#if PY_MAJOR_VERSION >= 3
if (!PyCapsule_CheckExact(F) || !(descr = PyCapsule_GetName(F)))
err_CO("F");
if (strncmp(descr, "CHOLMOD FACTOR", 14))
PY_ERR_TYPE("F is not a CHOLMOD factor");
cholmod_factor *L = (cholmod_factor *) PyCapsule_GetPointer(F, descr);
#else
if (!PyCObject_Check(F)) err_CO("F");
descr = PyCObject_GetDesc(F);
if (!descr || strncmp(descr, "CHOLMOD FACTOR", 14))
PY_ERR_TYPE("F is not a CHOLMOD factor");
cholmod_factor *L = (cholmod_factor *) PyCObject_AsVoidPtr(F);
#endif
if (L->xtype == CHOLMOD_PATTERN)
PY_ERR(PyExc_ValueError, "called with symbolic factor");
n = L->n;
if (L->minor<n) PY_ERR(PyExc_ArithmeticError, "singular matrix");
if (sys < 0 || sys > 8)
PY_ERR(PyExc_ValueError, "invalid value for sys");
if (!Matrix_Check(B) || MAT_ID(B) == INT ||
(MAT_ID(B) == DOUBLE && L->xtype == CHOLMOD_COMPLEX) ||
(MAT_ID(B) == COMPLEX && L->xtype == CHOLMOD_REAL))
PY_ERR_TYPE("B must a dense matrix of the same numerical "
"type as F");
if (nrhs < 0) nrhs = MAT_NCOLS(B);
if (n == 0 || nrhs == 0) return Py_BuildValue("");
if (ldB == 0) ldB = MAX(1,MAT_NROWS(B));
if (ldB < MAX(1,n)) err_ld("ldB");
if (oB < 0) err_nn_int("offsetB");
if (oB + (nrhs-1)*ldB + n > MAT_LGT(B)) err_buf_len("B");
cholmod_dense *x;
cholmod_dense *b = CHOL(allocate_dense)(n, 1, n,
(MAT_ID(B) == DOUBLE ? CHOLMOD_REAL : CHOLMOD_COMPLEX),
&Common);
if (Common.status == CHOLMOD_OUT_OF_MEMORY) return PyErr_NoMemory();
void *b_old = b->x;
for (i=0; i<nrhs; i++){
b->x = MAT_BUF(B) + (i*ldB + oB)*E_SIZE[MAT_ID(B)];
x = CHOL(solve) (sysvalues[sys], L, b, &Common);
if (Common.status != CHOLMOD_OK){
PyErr_SetString(PyExc_ValueError, "solve step failed");
CHOL(free_dense)(&x, &Common);
CHOL(free_dense)(&b, &Common);
return NULL;
}
memcpy(b->x, x->x, n*E_SIZE[MAT_ID(B)]);
CHOL(free_dense)(&x, &Common);
}
b->x = b_old;
CHOL(free_dense)(&b, &Common);
return Py_BuildValue("");
}
static PyObject *robustLS_to_sdp
(PyObject *self, PyObject *args, PyObject *kwrds) {
PyObject *Alist,*bt, *Ai;
spmatrix *A,*b;
int_t m,n,mp,np,pt,i,j,k,N,nnz=0,ri=0;
char *kwlist[] = {"Alist","bt",NULL};
if(!PyArg_ParseTupleAndKeywords(args,kwrds,"OO",kwlist,&Alist,&bt)) return NULL;
if(!PyList_Check(Alist)) {
PyErr_SetString(PyExc_TypeError,"Alist must be a list of matrices");
return NULL;
}
// get pt = p + 1
pt = PyList_Size(Alist);
// get size of bt
if(Matrix_Check(bt)){
m = MAT_NROWS(bt);
np = MAT_NCOLS(bt);
}
else if (SpMatrix_Check(bt)){
m = SP_NROWS(bt);
np = SP_NCOLS(bt);
}
else {
PyErr_SetString(PyExc_TypeError,"b must be a vector");
return NULL;
}
if (np!=1) {
PyErr_SetString(PyExc_TypeError,"b must be a vector");
return NULL;
}
// get n and check A0
if (!(Ai = PyList_GetItem(Alist,0))) return NULL;
if (Matrix_Check(Ai)) {
n = MAT_NCOLS(Ai);
nnz += m*n;
}
else if (SpMatrix_Check(Ai)) {
n = SP_NCOLS(Ai);
nnz += SP_NNZ(Ai);
}
else {
PyErr_SetString(PyExc_TypeError,"only spmatrix and matrix types allowed");
return NULL;
}
// check remaining matrices in Alist
for (i=1;i<pt;i++) {
if (!(Ai = PyList_GetItem(Alist,i))) return NULL;
if (Matrix_Check(Ai)) {
mp = MAT_NROWS(Ai);
np = MAT_NCOLS(Ai);
nnz += m*n;
}
else if (SpMatrix_Check(Ai)) {
mp = SP_NROWS(Ai);
np = SP_NCOLS(Ai);
nnz += SP_NNZ(Ai);
}
else {
PyErr_SetString(PyExc_TypeError,"only spmatrix and matrix types allowed");
return NULL;
}
if (!(mp==m && np==n)){
PyErr_SetString(PyExc_TypeError,"matrices in Alist must have same size");
return NULL;
}
}
nnz += 2*m + pt;
// generate b
b = SpMatrix_New(n+2,1,2,DOUBLE);
if (!b) return PyErr_NoMemory();
SP_COL(b)[0] = 0;
SP_VALD(b)[0] = -1;
SP_ROW(b)[0] = 0;
SP_VALD(b)[1] = -1;
SP_ROW(b)[1] = 1;
SP_COL(b)[1] = 2;
// generate A
N = m+pt;
A = SpMatrix_New(N*N,n+3,nnz,DOUBLE);
if (!A) return PyErr_NoMemory();
// build A0
SP_COL(A)[0] = ri;
for(i=0;i<m;i++){
if(SpMatrix_Check(bt)){
SP_VALD(A)[ri] = -SP_VALD(bt)[i];
SP_ROW(A)[ri++] = pt+i;
}
else{
SP_VALD(A)[ri] = -MAT_BUFD(bt)[i];
SP_ROW(A)[ri++] = pt+i;
}
}
for(i=0;i<m;i++) {
SP_VALD(A)[ri] = 1;
SP_ROW(A)[ri++] = (N+1)*pt + i*N+i;
}
// build A1
SP_COL(A)[1] = ri;
for(i=0;i<pt-1;i++){
SP_VALD(A)[ri] = -1;
SP_ROW(A)[ri++] = N+1 + i*N+i;
}
// build A2
SP_COL(A)[2] = ri;
SP_VALD(A)[ri] = -1;
SP_ROW(A)[ri++] = 0;
SP_COL(A)[3] = ri;
// build A3,...
for(j=0;j<n;j++){
// generate col. i
for(i=0;i<pt;i++){
Ai = PyList_GetItem(Alist,i);
if(SpMatrix_Check(Ai)) {
nnz = SP_COL(Ai)[j+1]-SP_COL(Ai)[j];
for(k=0;k<nnz;k++) {
SP_VALD(A)[ri] = -SP_VALD(Ai)[SP_COL(Ai)[j]+k];
SP_ROW(A)[ri++] = pt+i*N + SP_ROW(Ai)[SP_COL(Ai)[j]+k];
}
}
else {
for (k=0;k<m;k++) {
SP_VALD(A)[ri] = -MAT_BUFD(Ai)[j*m+k];
SP_ROW(A)[ri++] = pt+i*N + k;
}
}
}
SP_COL(A)[j+4] = ri;
}
return Py_BuildValue("NN",A,b);
}
static PyObject *integer(PyObject *self, PyObject *args,
PyObject *kwrds)
{
matrix *c, *h, *b=NULL, *x=NULL;
PyObject *G, *A=NULL, *IntSet=NULL, *BinSet = NULL;
PyObject *t=NULL;
pyiocp *iocpParm = NULL;;
glp_iocp *options = NULL;
glp_prob *lp;
int m, n, p, i, j, k, nnz, nnzmax, *rn=NULL, *cn=NULL;
double *a=NULL, val;
char *kwlist[] = {"c", "G", "h", "A", "b", "I", "B","iocp", NULL};
if (!PyArg_ParseTupleAndKeywords(args, kwrds, "OOO|OOOOO!", kwlist, &c,
&G, &h, &A, &b, &IntSet, &BinSet,iocp_t,&iocpParm)) return NULL;
if(!iocpParm)
{
iocpParm = (pyiocp*)malloc(sizeof(*iocpParm));
glp_init_iocp(&(iocpParm->obj));
}
if(iocpParm)
{
Py_INCREF(iocpParm);
options = &iocpParm->obj;
options->presolve = 1;
}
if ((Matrix_Check(G) && MAT_ID(G) != DOUBLE) ||
(SpMatrix_Check(G) && SP_ID(G) != DOUBLE) ||
(!Matrix_Check(G) && !SpMatrix_Check(G))){
PyErr_SetString(PyExc_TypeError, "G must be a 'd' matrix");
return NULL;
}
if ((m = Matrix_Check(G) ? MAT_NROWS(G) : SP_NROWS(G)) <= 0)
err_p_int("m");
if ((n = Matrix_Check(G) ? MAT_NCOLS(G) : SP_NCOLS(G)) <= 0)
err_p_int("n");
if (!Matrix_Check(h) || h->id != DOUBLE) err_dbl_mtrx("h");
if (h->nrows != m || h->ncols != 1){
PyErr_SetString(PyExc_ValueError, "incompatible dimensions");
return NULL;
}
if (A){
if ((Matrix_Check(A) && MAT_ID(A) != DOUBLE) ||
(SpMatrix_Check(A) && SP_ID(A) != DOUBLE) ||
(!Matrix_Check(A) && !SpMatrix_Check(A))){
PyErr_SetString(PyExc_ValueError, "A must be a dense "
"'d' matrix or a general sparse matrix");
return NULL;
}
if ((p = Matrix_Check(A) ? MAT_NROWS(A) : SP_NROWS(A)) < 0)
err_p_int("p");
if ((Matrix_Check(A) ? MAT_NCOLS(A) : SP_NCOLS(A)) != n){
PyErr_SetString(PyExc_ValueError, "incompatible "
"dimensions");
return NULL;
}
}
else p = 0;
if (b && (!Matrix_Check(b) || b->id != DOUBLE)) err_dbl_mtrx("b");
if ((b && (b->nrows != p || b->ncols != 1)) || (!b && p !=0 )){
PyErr_SetString(PyExc_ValueError, "incompatible dimensions");
return NULL;
}
if ((IntSet) && (!PyAnySet_Check(IntSet)))
PY_ERR_TYPE("invalid integer index set");
if ((BinSet) && (!PyAnySet_Check(BinSet)))
PY_ERR_TYPE("invalid binary index set");
lp = glp_create_prob();
glp_add_rows(lp, m+p);
glp_add_cols(lp, n);
for (i=0; i<n; i++){
glp_set_obj_coef(lp, i+1, MAT_BUFD(c)[i]);
glp_set_col_bnds(lp, i+1, GLP_FR, 0.0, 0.0);
}
for (i=0; i<m; i++)
glp_set_row_bnds(lp, i+1, GLP_UP, 0.0, MAT_BUFD(h)[i]);
for (i=0; i<p; i++)
glp_set_row_bnds(lp, i+m+1, GLP_FX, MAT_BUFD(b)[i],
MAT_BUFD(b)[i]);
nnzmax = (SpMatrix_Check(G) ? SP_NNZ(G) : m*n ) +
((A && SpMatrix_Check(A)) ? SP_NNZ(A) : p*n);
a = (double *) calloc(nnzmax+1, sizeof(double));
rn = (int *) calloc(nnzmax+1, sizeof(int));
cn = (int *) calloc(nnzmax+1, sizeof(int));
if (!a || !rn || !cn){
free(a); free(rn); free(cn); glp_delete_prob(lp);
return PyErr_NoMemory();
}
nnz = 0;
if (SpMatrix_Check(G)) {
for (j=0; j<n; j++) for (k=SP_COL(G)[j]; k<SP_COL(G)[j+1]; k++)
if ((val = SP_VALD(G)[k]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = SP_ROW(G)[k]+1;
cn[1+nnz] = j+1;
nnz++;
}
}
else for (j=0; j<n; j++) for (i=0; i<m; i++)
if ((val = MAT_BUFD(G)[i+j*m]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = i+1;
cn[1+nnz] = j+1;
nnz++;
}
if (A && SpMatrix_Check(A)){
for (j=0; j<n; j++) for (k=SP_COL(A)[j]; k<SP_COL(A)[j+1]; k++)
if ((val = SP_VALD(A)[k]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = m+SP_ROW(A)[k]+1;
cn[1+nnz] = j+1;
nnz++;
}
}
else for (j=0; j<n; j++) for (i=0; i<p; i++)
if ((val = MAT_BUFD(A)[i+j*p]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = m+i+1;
cn[1+nnz] = j+1;
nnz++;
}
glp_load_matrix(lp, nnz, rn, cn, a);
free(rn); free(cn); free(a);
if (!(t = PyTuple_New(2))) {
glp_delete_prob(lp);
return PyErr_NoMemory();
}
if (IntSet) {
PyObject *iter = PySequence_Fast(IntSet, "Critical error: not sequence");
for (i=0; i<PySet_GET_SIZE(IntSet); i++) {
PyObject *tmp = PySequence_Fast_GET_ITEM(iter, i);
#if PY_MAJOR_VERSION >= 3
if (!PyLong_Check(tmp)) {
#else
if (!PyInt_Check(tmp)) {
#endif
glp_delete_prob(lp);
Py_DECREF(iter);
PY_ERR_TYPE("non-integer element in I");
}
#if PY_MAJOR_VERSION >= 3
int k = PyLong_AS_LONG(tmp);
#else
int k = PyInt_AS_LONG(tmp);
#endif
if ((k < 0) || (k >= n)) {
glp_delete_prob(lp);
Py_DECREF(iter);
PY_ERR(PyExc_IndexError, "index element out of range in I");
}
glp_set_col_kind(lp, k+1, GLP_IV);
}
Py_DECREF(iter);
}
if (BinSet) {
PyObject *iter = PySequence_Fast(BinSet, "Critical error: not sequence");
for (i=0; i<PySet_GET_SIZE(BinSet); i++) {
PyObject *tmp = PySequence_Fast_GET_ITEM(iter, i);
#if PY_MAJOR_VERSION >= 3
if (!PyLong_Check(tmp)) {
#else
if (!PyInt_Check(tmp)) {
#endif
glp_delete_prob(lp);
Py_DECREF(iter);
PY_ERR_TYPE("non-binary element in I");
}
#if PY_MAJOR_VERSION >= 3
int k = PyLong_AS_LONG(tmp);
#else
int k = PyInt_AS_LONG(tmp);
#endif
if ((k < 0) || (k >= n)) {
glp_delete_prob(lp);
Py_DECREF(iter);
PY_ERR(PyExc_IndexError, "index element out of range in B");
}
glp_set_col_kind(lp, k+1, GLP_BV);
}
Py_DECREF(iter);
}
switch (glp_intopt(lp,options)){
case 0:
x = (matrix *) Matrix_New(n,1,DOUBLE);
if (!x) {
Py_XDECREF(iocpParm);
Py_XDECREF(t);
glp_delete_prob(lp);
return PyErr_NoMemory();
}
set_output_string(t,"optimal");
set_output_string(t,"optimal");
for (i=0; i<n; i++)
MAT_BUFD(x)[i] = glp_mip_col_val(lp, i+1);
PyTuple_SET_ITEM(t, 1, (PyObject *) x);
Py_XDECREF(iocpParm);
glp_delete_prob(lp);
return (PyObject *) t;
case GLP_ETMLIM:
x = (matrix *) Matrix_New(n,1,DOUBLE);
if (!x) {
Py_XDECREF(t);
Py_XDECREF(iocpParm);
glp_delete_prob(lp);
return PyErr_NoMemory();
}
set_output_string(t,"time limit exceeded");
for (i=0; i<n; i++)
MAT_BUFD(x)[i] = glp_mip_col_val(lp, i+1);
PyTuple_SET_ITEM(t, 1, (PyObject *) x);
Py_XDECREF(iocpParm);
glp_delete_prob(lp);
return (PyObject *) t;
case GLP_EBOUND:
set_output_string(t,"incorrect bounds");
break;
case GLP_EFAIL:
set_output_string(t,"invalid MIP formulation");
break;
case GLP_ENOPFS:
set_output_string(t,"primal infeasible");
break;
case GLP_ENODFS:
set_output_string(t,"dual infeasible");
break;
case GLP_EMIPGAP:
set_output_string(t,"Relative mip gap tolerance reached");
break;
/*case LPX_E_ITLIM:
set_output_string(t,"maxiters exceeded");
break;*/
/*case LPX_E_SING:
set_output_string(t,"singular or ill-conditioned basis");
break;*/
default:
set_output_string(t,"unknown");
}
Py_XDECREF(iocpParm);
glp_delete_prob(lp);
PyTuple_SET_ITEM(t, 1, Py_BuildValue(""));
return (PyObject *) t;
}
static PyMethodDef glpk_functions[] = {
{"lp", (PyCFunction) simplex, METH_VARARGS|METH_KEYWORDS,
doc_simplex},
{"ilp", (PyCFunction) integer, METH_VARARGS|METH_KEYWORDS,
doc_integer},
{NULL} /* Sentinel */
};
#if PY_MAJOR_VERSION >= 3
static PyModuleDef glpk_module_def = {
PyModuleDef_HEAD_INIT,
"glpk",
glpk__doc__,
-1,
glpk_functions,
NULL, NULL, NULL, NULL
};
void addglpkConstants (void)
{
PyModule_AddIntMacro(glpk_module, GLP_ON);
PyModule_AddIntMacro(glpk_module,GLP_OFF);
/* reason codes: */
PyModule_AddIntMacro(glpk_module,GLP_IROWGEN);
PyModule_AddIntMacro(glpk_module,GLP_IBINGO);
PyModule_AddIntMacro(glpk_module,GLP_IHEUR);
PyModule_AddIntMacro(glpk_module,GLP_ICUTGEN);
PyModule_AddIntMacro(glpk_module,GLP_IBRANCH);
PyModule_AddIntMacro(glpk_module,GLP_ISELECT);
PyModule_AddIntMacro(glpk_module,GLP_IPREPRO);
/* branch selection indicator: */
PyModule_AddIntMacro(glpk_module,GLP_NO_BRNCH);
PyModule_AddIntMacro(glpk_module,GLP_DN_BRNCH);
PyModule_AddIntMacro(glpk_module,GLP_UP_BRNCH);
/* return codes: */
PyModule_AddIntMacro(glpk_module,GLP_EBADB);
PyModule_AddIntMacro(glpk_module,GLP_ESING);
PyModule_AddIntMacro(glpk_module,GLP_ECOND);
PyModule_AddIntMacro(glpk_module,GLP_EBOUND);
PyModule_AddIntMacro(glpk_module,GLP_EFAIL);
PyModule_AddIntMacro(glpk_module,GLP_EOBJLL);
PyModule_AddIntMacro(glpk_module,GLP_EOBJUL);
PyModule_AddIntMacro(glpk_module,GLP_EITLIM);
PyModule_AddIntMacro(glpk_module,GLP_ETMLIM);
PyModule_AddIntMacro(glpk_module,GLP_ENOPFS);
PyModule_AddIntMacro(glpk_module,GLP_ENODFS);
PyModule_AddIntMacro(glpk_module,GLP_EROOT);
PyModule_AddIntMacro(glpk_module,GLP_ESTOP);
PyModule_AddIntMacro(glpk_module,GLP_EMIPGAP);
PyModule_AddIntMacro(glpk_module,GLP_ENOFEAS);
PyModule_AddIntMacro(glpk_module,GLP_ENOCVG);
PyModule_AddIntMacro(glpk_module,GLP_EINSTAB);
PyModule_AddIntMacro(glpk_module,GLP_EDATA);
PyModule_AddIntMacro(glpk_module,GLP_ERANGE);
/* condition indicator: */
PyModule_AddIntMacro(glpk_module,GLP_KKT_PE);
PyModule_AddIntMacro(glpk_module,GLP_KKT_PB);
PyModule_AddIntMacro(glpk_module,GLP_KKT_DE);
PyModule_AddIntMacro(glpk_module,GLP_KKT_DB);
PyModule_AddIntMacro(glpk_module,GLP_KKT_CS);
/* MPS file format: */
PyModule_AddIntMacro(glpk_module,GLP_MPS_DECK);
PyModule_AddIntMacro(glpk_module,GLP_MPS_FILE);
/* simplex method control parameters */
/* message level: */
PyModule_AddIntMacro(glpk_module,GLP_MSG_OFF);
PyModule_AddIntMacro(glpk_module,GLP_MSG_ERR);
PyModule_AddIntMacro(glpk_module,GLP_MSG_ON);
PyModule_AddIntMacro(glpk_module,GLP_MSG_ALL);
PyModule_AddIntMacro(glpk_module,GLP_MSG_DBG);
/* simplex method option: */
PyModule_AddIntMacro(glpk_module,GLP_PRIMAL);
PyModule_AddIntMacro(glpk_module,GLP_DUALP);
PyModule_AddIntMacro(glpk_module,GLP_DUAL);
/* pricing technique: */
PyModule_AddIntMacro(glpk_module,GLP_PT_STD);
PyModule_AddIntMacro(glpk_module,GLP_PT_PSE);
/* ratio test technique: */
PyModule_AddIntMacro(glpk_module,GLP_RT_STD);
PyModule_AddIntMacro(glpk_module,GLP_RT_HAR);
/* interior-point solver control parameters */
/* ordering algorithm: */
PyModule_AddIntMacro(glpk_module,GLP_ORD_NONE);
PyModule_AddIntMacro(glpk_module,GLP_ORD_QMD);
PyModule_AddIntMacro(glpk_module,GLP_ORD_AMD);
PyModule_AddIntMacro(glpk_module,GLP_ORD_SYMAMD);
}
PyMODINIT_FUNC PyInit_glpk(void)
{
if (!(glpk_module = PyModule_Create(&glpk_module_def))) return NULL;
if (PyType_Ready(&iocp_t) < 0 || (PyType_Ready(&smcp_t) < 0)) return NULL;
/* Adding macros */
addglpkConstants();
/* Adding option lists as objects */
Py_INCREF(&smcp_t);
PyModule_AddObject(glpk_module,"smcp",(PyObject*)&smcp_t);
Py_INCREF(&iocp_t);
PyModule_AddObject(glpk_module,"iocp",(PyObject*)&iocp_t);
if (import_cvxopt() < 0) return NULL;
return glpk_module;
}
#else
PyMODINIT_FUNC initglpk(void)
{
glpk_module = Py_InitModule3("cvxopt.glpk", glpk_functions,
glpk__doc__);
if (PyType_Ready(&iocp_t) < 0 || (PyType_Ready(&smcp_t) < 0)) return NULL;
addglpkConstants();
Py_INCREF(&smcp_t);
PyModule_AddObject(glpk_module,"smcp",(PyObject*)&smcp_t);
Py_INCREF(&iocp_t);
PyModule_AddObject(glpk_module,"iocp",(PyObject*)&iocp_t);
if (import_cvxopt() < 0) return;
}
static PyObject *simplex(PyObject *self, PyObject *args,
PyObject *kwrds)
{
matrix *c, *h, *b=NULL, *x=NULL, *z=NULL, *y=NULL;
PyObject *G, *A=NULL, *t=NULL;
glp_prob *lp;
glp_smcp *options = NULL;
pysmcp *smcpParm = NULL;
int m, n, p, i, j, k, nnz, nnzmax, *rn=NULL, *cn=NULL;
double *a=NULL, val;
char *kwlist[] = {"c", "G", "h", "A", "b","options", NULL};
if (!PyArg_ParseTupleAndKeywords(args, kwrds, "OOO|OOO!", kwlist, &c,
&G, &h, &A, &b,&smcp_t,&smcpParm)) return NULL;
if ((Matrix_Check(G) && MAT_ID(G) != DOUBLE) ||
(SpMatrix_Check(G) && SP_ID(G) != DOUBLE) ||
(!Matrix_Check(G) && !SpMatrix_Check(G))){
PyErr_SetString(PyExc_TypeError, "G must be a 'd' matrix");
return NULL;
}
if ((m = Matrix_Check(G) ? MAT_NROWS(G) : SP_NROWS(G)) <= 0)
err_p_int("m");
if ((n = Matrix_Check(G) ? MAT_NCOLS(G) : SP_NCOLS(G)) <= 0)
err_p_int("n");
if (!Matrix_Check(h) || h->id != DOUBLE) err_dbl_mtrx("h");
if (h->nrows != m || h->ncols != 1){
PyErr_SetString(PyExc_ValueError, "incompatible dimensions");
return NULL;
}
if (A){
if ((Matrix_Check(A) && MAT_ID(A) != DOUBLE) ||
(SpMatrix_Check(A) && SP_ID(A) != DOUBLE) ||
(!Matrix_Check(A) && !SpMatrix_Check(A))){
PyErr_SetString(PyExc_ValueError, "A must be a dense "
"'d' matrix or a general sparse matrix");
return NULL;
}
if ((p = Matrix_Check(A) ? MAT_NROWS(A) : SP_NROWS(A)) < 0)
err_p_int("p");
if ((Matrix_Check(A) ? MAT_NCOLS(A) : SP_NCOLS(A)) != n){
PyErr_SetString(PyExc_ValueError, "incompatible "
"dimensions");
return NULL;
}
}
else p = 0;
if (b && (!Matrix_Check(b) || b->id != DOUBLE)) err_dbl_mtrx("b");
if ((b && (b->nrows != p || b->ncols != 1)) || (!b && p !=0 )){
PyErr_SetString(PyExc_ValueError, "incompatible dimensions");
return NULL;
}
if(!smcpParm)
{
smcpParm = (pysmcp*)malloc(sizeof(*smcpParm));
glp_init_smcp(&(smcpParm->obj));
}
if(smcpParm)
{
Py_INCREF(smcpParm);
options = &smcpParm->obj;
options->presolve = 1;
}
lp = glp_create_prob();
glp_add_rows(lp, m+p);
glp_add_cols(lp, n);
for (i=0; i<n; i++){
glp_set_obj_coef(lp, i+1, MAT_BUFD(c)[i]);
glp_set_col_bnds(lp, i+1, GLP_FR, 0.0, 0.0);
}
for (i=0; i<m; i++)
glp_set_row_bnds(lp, i+1, GLP_UP, 0.0, MAT_BUFD(h)[i]);
for (i=0; i<p; i++)
glp_set_row_bnds(lp, i+m+1, GLP_FX, MAT_BUFD(b)[i],
MAT_BUFD(b)[i]);
nnzmax = (SpMatrix_Check(G) ? SP_NNZ(G) : m*n ) +
((A && SpMatrix_Check(A)) ? SP_NNZ(A) : p*n);
a = (double *) calloc(nnzmax+1, sizeof(double));
rn = (int *) calloc(nnzmax+1, sizeof(int));
cn = (int *) calloc(nnzmax+1, sizeof(int));
if (!a || !rn || !cn){
free(a); free(rn); free(cn); glp_delete_prob(lp);
return PyErr_NoMemory();
}
nnz = 0;
if (SpMatrix_Check(G)) {
for (j=0; j<n; j++) for (k=SP_COL(G)[j]; k<SP_COL(G)[j+1]; k++)
if ((val = SP_VALD(G)[k]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = SP_ROW(G)[k]+1;
cn[1+nnz] = j+1;
nnz++;
}
}
else for (j=0; j<n; j++) for (i=0; i<m; i++)
if ((val = MAT_BUFD(G)[i+j*m]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = i+1;
cn[1+nnz] = j+1;
nnz++;
}
if (A && SpMatrix_Check(A)){
for (j=0; j<n; j++) for (k=SP_COL(A)[j]; k<SP_COL(A)[j+1]; k++)
if ((val = SP_VALD(A)[k]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = m+SP_ROW(A)[k]+1;
cn[1+nnz] = j+1;
nnz++;
}
}
else for (j=0; j<n; j++) for (i=0; i<p; i++)
if ((val = MAT_BUFD(A)[i+j*p]) != 0.0){
a[1+nnz] = val;
rn[1+nnz] = m+i+1;
cn[1+nnz] = j+1;
nnz++;
}
glp_load_matrix(lp, nnz, rn, cn, a);
free(rn); free(cn); free(a);
if (!(t = PyTuple_New(A ? 4 : 3))){
glp_delete_prob(lp);
return PyErr_NoMemory();
}
switch (glp_simplex(lp,options)){
case 0:
x = (matrix *) Matrix_New(n,1,DOUBLE);
z = (matrix *) Matrix_New(m,1,DOUBLE);
if (A) y = (matrix *) Matrix_New(p,1,DOUBLE);
if (!x || !z || (A && !y)){
Py_XDECREF(x);
Py_XDECREF(z);
Py_XDECREF(y);
Py_XDECREF(t);
Py_XDECREF(smcpParm);
glp_delete_prob(lp);
return PyErr_NoMemory();
}
set_output_string(t,"optimal");
for (i=0; i<n; i++)
MAT_BUFD(x)[i] = glp_get_col_prim(lp, i+1);
PyTuple_SET_ITEM(t, 1, (PyObject *) x);
for (i=0; i<m; i++)
MAT_BUFD(z)[i] = -glp_get_row_dual(lp, i+1);
PyTuple_SET_ITEM(t, 2, (PyObject *) z);
if (A){
for (i=0; i<p; i++)
MAT_BUFD(y)[i] = -glp_get_row_dual(lp, m+i+1);
PyTuple_SET_ITEM(t, 3, (PyObject *) y);
}
Py_XDECREF(smcpParm);
glp_delete_prob(lp);
return (PyObject *) t;
case GLP_EBADB:
set_output_string(t,"incorrect initial basis");
break;
case GLP_ESING:
set_output_string(t,"singular initial basis matrix");
break;
case GLP_ECOND:
set_output_string(t,"ill-conditioned initial basis matrix");
break;
case GLP_EBOUND:
set_output_string(t,"incorrect bounds");
break;
case GLP_EFAIL:
set_output_string(t,"solver failure");
break;
case GLP_EOBJLL:
set_output_string(t,"objective function reached lower limit");
break;
case GLP_EOBJUL:
set_output_string(t,"objective function reached upper limit");
break;
case GLP_EITLIM:
set_output_string(t,"iteration limit exceeded");
break;
case GLP_ETMLIM:
set_output_string(t,"time limit exceeded");
break;
case GLP_ENOPFS:
set_output_string(t,"primal infeasible");
break;
case GLP_ENODFS:
set_output_string(t,"dual infeasible");
break;
default:
set_output_string(t,"unknown");
break;
}
Py_XDECREF(smcpParm);
glp_delete_prob(lp);
PyTuple_SET_ITEM(t, 1, Py_BuildValue(""));
PyTuple_SET_ITEM(t, 2, Py_BuildValue(""));
if (A) PyTuple_SET_ITEM(t, 3, Py_BuildValue(""));
return (PyObject *) t;
}
