int main(void)
{
/*char ver[7];*/
idxint exitflag = ECOS_FATAL;
pwork* mywork;
#if PROFILING > 0
double ttotal, tsolve, tsetup;
#endif
#if PROFILING > 1
double torder, tkktcreate, ttranspose, tfactor, tkktsolve;
#endif
/* set up data */
mywork = ECOS_setup(n, m, p, l, ncones, q, Gpr, Gjc, Gir, Apr, Ajc, Air, c, h, b);
if( mywork != NULL ){
/* solve */
exitflag = ECOS_solve(mywork);
/* test second solve
exitflag = ECOS_solve(mywork); */
/* some statistics in milliseconds */
#if PROFILING > 0
tsolve = mywork->info->tsolve * 1000;
tsetup = mywork->info->tsetup * 1000;
ttotal = tsetup + tsolve;
#endif
#if PROFILING > 1
torder = mywork->info->torder * 1000;
tkktcreate = mywork->info->tkktcreate * 1000;
ttranspose = mywork->info->ttranspose * 1000;
tfactor = mywork->info->tfactor * 1000;
tkktsolve = mywork->info->tkktsolve * 1000;
#endif
#if PRINTLEVEL > 2
#if PROFILING > 1
printf("ECOS timings (all times in milliseconds):\n\n");
printf("1. Setup: %7.3f (%4.1f%%)\n", tsetup, tsetup / ttotal*100);
printf("2. Solve: %7.3f (%4.1f%%)\n", tsolve, tsolve / ttotal*100);
printf("----------------------------------\n");
printf(" Total solve time: %7.3f ms\n\n", ttotal);
printf("Detailed timings in SETUP:\n");
printf("Create transposes: %7.3f (%4.1f%%)\n", ttranspose, ttranspose / tsetup*100);
printf("Create KKT Matrix: %7.3f (%4.1f%%)\n", tkktcreate, tkktcreate / tsetup*100);
printf(" Compute ordering: %7.3f (%4.1f%%)\n", torder, torder / tsetup*100);
printf(" Other: %7.3f (%4.1f%%)\n", tsetup-torder-tkktcreate-ttranspose, (tsetup-torder-tkktcreate-ttranspose) / tsetup*100);
printf("\n");
printf("Detailed timings in SOLVE:\n");
printf(" Factorizations: %7.3f (%4.1f%% of tsolve / %4.1f%% of ttotal)\n", tfactor, tfactor / tsolve*100, tfactor / ttotal*100);
printf(" KKT solves: %7.3f (%4.1f%% of tsolve / %4.1f%% of ttotal)\n", tkktsolve, tkktsolve / tsolve*100, tfactor / ttotal*100);
printf(" Other: %7.3f (%4.1f%% of tsolve / %4.1f%% of ttotal)\n", tsolve-tkktsolve-tfactor, (tsolve-tkktsolve-tfactor) / tsolve*100, (tsolve-tkktsolve-tfactor) / ttotal*100);
printf("\n");
#endif
#endif
/* clean up memory */
ECOS_cleanup(mywork, 0);
}
/* test version number
ECOS_ver(ver);
printf("This test has been run on ECOS version %s\n", ver);
*/
/* explicitly truncate exit code */
return (int)exitflag;
}
void cleanup(pwork *w)
{
ECOS_cleanup(w,0);
}
static PyObject *csolve(PyObject* self, PyObject *args, PyObject *kwargs)
{
/* Expects a function call
* sol = csolve((m,n,p),c,Gx,Gi,Gp,h,dims,Ax,Ai,Ap,b,verbose)
* where
*
* the triple (m,n,p) corresponds to:
* `m`: the rows of G
* `n`: the cols of G and A, must agree with the length of c
* `p`: the rows of A
* `c` is a Numpy array of doubles
* "G" is a sparse matrix in column compressed storage. "Gx" are the values,
* "Gi" are the rows, and "Gp" are the column pointers.
* `Gx` is a Numpy array of doubles
* `Gi` is a Numpy array of ints
* `Gp` is a Numpy array of ints
* `h` is a Numpy array
* `dims` is a dictionary with
* `dims['l']` an integer specifying the dimension of positive orthant cone
* `dims['q']` an *list* specifying dimensions of second-order cones
*
* "A" is an optional sparse matrix in column compressed storage. "Ax" are
* the values, "Ai" are the rows, and "Ap" are the column pointers.
* `Ax` is a Numpy array of doubles
* `Ai` is a Numpy array of ints
* `Ap` is a Numpy array of ints
* `b` is an optional argument, which is a Numpy array of doubles
* `verbose` is an optional bool signaling whether to print info
*
* This call will solve the problem
*
* minimize c'*x
* subject to A*x = b
* h - G*x \in K
*
* The code returns a Python dictionary with five keys, 'x', 'y', 'info', 's',
* and 'z'. These correspond to the following:
*
* `x`: primal variables
* `y`: dual variables for equality constraints
* `s`: slacks for Gx + s <= h, s \in K
* `z`: dual variables for inequality constraints s \in K
* `info`: another dictionary with the following fields:
* exitflag: 0=OPTIMAL, 1=PRIMAL INFEASIBLE, 2=DUAL INFEASIBLE, -1=MAXIT REACHED
* infostring: gives information about the status of solution
* pcost: value of primal objective
* dcost: value of dual objective
* pres: primal residual on inequalities and equalities
* dres: dual residual
* pinf: primal infeasibility measure
* dinf: dual infeasibility measure
* pinfres: NaN
* dinfres: 3.9666e+15
* gap: duality gap
* relgap: relative duality gap
* r0: ???
* numerr: numerical error?
* iter: number of iterations
* timing: dictionary with timing information
*/
/* data structures for arguments */
//matrix *c, *h, *b = NULL;
//spmatrix *G, *A = NULL;
PyArrayObject *Gx, *Gi, *Gp, *c, *h;
PyArrayObject *Ax = NULL;
PyArrayObject *Ai = NULL;
PyArrayObject *Ap = NULL;
PyArrayObject *b = NULL;
PyObject *dims, *verbose = NULL;
idxint n; // number or variables
idxint m; // number of conic variables
idxint p = 0; // number of equality constraints
idxint ncones = 0; // number of cones
idxint numConicVariables = 0;
/* ECOS data structures */
idxint l = 0;
idxint *q = NULL;
pfloat *Gpr = NULL;
idxint *Gjc = NULL;
idxint *Gir = NULL;
pfloat *Apr = NULL;
idxint *Ajc = NULL;
idxint *Air = NULL;
pfloat *cpr = NULL;
pfloat *hpr = NULL;
pfloat *bpr = NULL;
pwork* mywork;
idxint i;
static char *kwlist[] = {"shape", "c", "Gx", "Gi", "Gp", "h", "dims", "Ax", "Ai", "Ap", "b", "verbose", NULL};
// parse the arguments and ensure they are the correct type
#ifdef DLONG
static char *argparse_string = "(lll)O!O!O!O!O!O!|O!O!O!O!O!";
#else
static char *argparse_string = "(iii)O!O!O!O!O!O!|O!O!O!O!O!";
#endif
if( !PyArg_ParseTupleAndKeywords(args, kwargs, argparse_string, kwlist,
&m, &n, &p,
&PyArray_Type, &c,
&PyArray_Type, &Gx,
&PyArray_Type, &Gi,
&PyArray_Type, &Gp,
&PyArray_Type, &h,
&PyDict_Type, &dims,
&PyArray_Type, &Ax,
&PyArray_Type, &Ai,
&PyArray_Type, &Ap,
&PyArray_Type, &b,
&PyBool_Type, &verbose)
) { return NULL; }
if (m < 0) {
PyErr_SetString(PyExc_ValueError, "m must be a positive integer");
return NULL;
}
if (n < 0) {
PyErr_SetString(PyExc_ValueError, "n must be a positive integer");
return NULL;
}
if (p < 0) {
PyErr_SetString(PyExc_ValueError, "p must be a positive integer");
return NULL;
}
/* get the typenum for the primitive int and double types */
int intType = getIntType();
int doubleType = getDoubleType();
/* set G */
if( !PyArray_ISFLOAT(Gx) || PyArray_NDIM(Gx) != 1) {
PyErr_SetString(PyExc_TypeError, "Gx must be a numpy array of floats");
return NULL;
}
if( !PyArray_ISINTEGER(Gi) || PyArray_NDIM(Gi) != 1) {
PyErr_SetString(PyExc_TypeError, "Gi must be a numpy array of ints");
return NULL;
}
if( !PyArray_ISINTEGER(Gp) || PyArray_NDIM(Gp) != 1) {
PyErr_SetString(PyExc_TypeError, "Gp must be a numpy array of ints");
return NULL;
}
PyArrayObject *Gx_arr = getContiguous(Gx, doubleType);
PyArrayObject *Gi_arr = getContiguous(Gi, intType);
PyArrayObject *Gp_arr = getContiguous(Gp, intType);
Gpr = (pfloat *) PyArray_DATA(Gx_arr);
Gir = (idxint *) PyArray_DATA(Gi_arr);
Gjc = (idxint *) PyArray_DATA(Gp_arr);
/* set c */
if (!PyArray_ISFLOAT(c) || PyArray_NDIM(c) != 1) {
PyErr_SetString(PyExc_TypeError, "c must be a dense numpy array with one dimension");
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
return NULL;
}
if (PyArray_DIM(c,0) != n){
PyErr_SetString(PyExc_ValueError, "c has incompatible dimension with G");
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
return NULL;
}
PyArrayObject *c_arr = getContiguous(c, doubleType);
cpr = (pfloat *) PyArray_DATA(c_arr);
/* set h */
if (!PyArray_ISFLOAT(h) || PyArray_NDIM(h) != 1) {
PyErr_SetString(PyExc_TypeError, "h must be a dense numpy array with one dimension");
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr);
return NULL;
}
if (PyArray_DIM(h,0) != m){
PyErr_SetString(PyExc_ValueError, "h has incompatible dimension with G");
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr);
return NULL;
}
PyArrayObject *h_arr = getContiguous(h, doubleType);
hpr = (pfloat *) PyArray_DATA(h_arr);
/* get dims['l'] */
PyObject *linearObj = PyDict_GetItemString(dims, "l");
if(linearObj) {
if(PyInt_Check(linearObj) && ((l = (idxint) PyInt_AsLong(linearObj)) >= 0)) {
numConicVariables += l;
} else {
PyErr_SetString(PyExc_TypeError, "dims['l'] ought to be a nonnegative integer");
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
return NULL;
}
}
/* get dims['q'] */
PyObject *socObj = PyDict_GetItemString(dims, "q");
if(socObj) {
if (PyList_Check(socObj)) {
ncones = PyList_Size(socObj);
q = calloc(ncones, sizeof(idxint));
for (i = 0; i < ncones; ++i) {
PyObject *qi = PyList_GetItem(socObj, i);
if(PyInt_Check(qi) && ((q[i] = (idxint) PyInt_AsLong(qi)) > 0)) {
numConicVariables += q[i];
} else {
PyErr_SetString(PyExc_TypeError, "dims['q'] ought to be a list of positive integers");
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
return NULL;
}
}
} else {
PyErr_SetString(PyExc_TypeError, "dims['q'] ought to be a list");
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
return NULL;
}
}
PyArrayObject *Ax_arr = NULL;
PyArrayObject *Ai_arr = NULL;
PyArrayObject *Ap_arr = NULL;
PyArrayObject *b_arr = NULL;
if(Ax && Ai && Ap && b) {
/* set A */
if( !PyArray_ISFLOAT(Ax) || PyArray_NDIM(Ax) != 1 ) {
PyErr_SetString(PyExc_TypeError, "Ax must be a numpy array of floats");
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
return NULL;
}
if( !PyArray_ISINTEGER(Ai) || PyArray_NDIM(Ai) != 1) {
PyErr_SetString(PyExc_TypeError, "Ai must be a numpy array of ints");
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
return NULL;
}
if( !PyArray_ISINTEGER(Ap) || PyArray_NDIM(Ap) != 1) {
PyErr_SetString(PyExc_TypeError, "Ap must be a numpy array of ints");
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
return NULL;
}
// if ((SpMatrix_Check(A) && SP_ID(A) != DOUBLE)){
// PyErr_SetString(PyExc_TypeError, "A must be a sparse 'd' matrix");
// if(q) free(q);
// Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
// Py_DECREF(c_arr); Py_DECREF(h_arr);
// return NULL;
// }
// if ((p = SP_NROWS(A)) < 0) {
// PyErr_SetString(PyExc_ValueError, "p must be a nonnegative integer");
// if(q) free(q);
// Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
// Py_DECREF(c_arr); Py_DECREF(h_arr);
// return NULL;
// }
// if (SP_NCOLS(A) != n) {
// PyErr_SetString(PyExc_ValueError, "A has incompatible dimension with c");
// if(q) free(q);
// Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
// Py_DECREF(c_arr); Py_DECREF(h_arr);
// return NULL;
// }
// if (p != 0) {
// Apr = SP_VALD(A);
// Air = SP_ROW(A);
// Ajc = SP_COL(A);
// }
Ax_arr = getContiguous(Ax, doubleType);
Ai_arr = getContiguous(Ai, intType);
Ap_arr = getContiguous(Ap, intType);
Apr = (pfloat *) PyArray_DATA(Ax_arr);
Air = (idxint *) PyArray_DATA(Ai_arr);
Ajc = (idxint *) PyArray_DATA(Ap_arr);
/* set b */
// if (!Matrix_Check(b) || MAT_NCOLS(b) != 1 || MAT_ID(b) != DOUBLE) {
// PyErr_SetString(PyExc_TypeError, "b must be a dense 'd' matrix with one column");
// if(q) free(q);
// return NULL;
// }
// if (MAT_NROWS(b) != p){
// PyErr_SetString(PyExc_ValueError, "b has incompatible dimension with A");
// if(q) free(q);
// return NULL;
// }
// if (p != 0) {
// bpr = MAT_BUFD(b);
// }
if (!PyArray_ISFLOAT(b) || PyArray_NDIM(b) != 1) {
PyErr_SetString(PyExc_TypeError, "b must be a dense numpy array with one dimension");
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
Py_DECREF(Ax_arr); Py_DECREF(Ai_arr); Py_DECREF(Ap_arr);
return NULL;
}
if (PyArray_DIM(b,0) != p){
PyErr_SetString(PyExc_ValueError, "b has incompatible dimension with A");
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
Py_DECREF(Ax_arr); Py_DECREF(Ai_arr); Py_DECREF(Ap_arr);
return NULL;
}
b_arr = getContiguous(b, doubleType);
bpr = (pfloat *) PyArray_DATA(b_arr);
} else if (Ax || Ai || Ap || b) {
// check that A and b are both supplied
PyErr_SetString(PyExc_ValueError, "A and b arguments must be supplied together");
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
return NULL;
}
/* check that sum(q) + l = m */
if( numConicVariables != m ){
PyErr_SetString(PyExc_ValueError, "Number of rows of G does not match dims.l+sum(dims.q)");
if (q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
if (b_arr) Py_DECREF(b_arr);
if (Ax_arr) Py_DECREF(Ax_arr);
if (Ai_arr) Py_DECREF(Ai_arr);
if (Ap_arr) Py_DECREF(Ap_arr);
return NULL;
}
/* This calls ECOS setup function. */
mywork = ECOS_setup(n, m, p, l, ncones, q, Gpr, Gjc, Gir, Apr, Ajc, Air, cpr, hpr, bpr);
if( mywork == NULL ){
PyErr_SetString(PyExc_RuntimeError, "Internal problem occurred in ECOS while setting up the problem.\nPlease send a bug report with data to Alexander Domahidi.\nEmail: [email protected]");
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
if (b_arr) Py_DECREF(b_arr);
if (Ax_arr) Py_DECREF(Ax_arr);
if (Ai_arr) Py_DECREF(Ai_arr);
if (Ap_arr) Py_DECREF(Ap_arr);
return NULL;
}
/* Set settings for ECOS. */
if(verbose) {
mywork->stgs->verbose = (idxint) PyObject_IsTrue(verbose);
}
/* Solve! */
idxint exitcode = ECOS_solve(mywork);
/* create output (all data is *deep copied*) */
// TODO: request CVXOPT API for constructing from existing pointer
/* x */
// matrix *x;
// if(!(x = Matrix_New(n,1,DOUBLE)))
// return PyErr_NoMemory();
// memcpy(MAT_BUFD(x), mywork->x, n*sizeof(double));
npy_intp veclen[1];
veclen[0] = n;
PyObject *x = PyArray_SimpleNewFromData(1, veclen, NPY_DOUBLE, mywork->x);
/* y */
// matrix *y;
// if(!(y = Matrix_New(p,1,DOUBLE)))
// return PyErr_NoMemory();
// memcpy(MAT_BUFD(y), mywork->y, p*sizeof(double));
veclen[0] = p;
PyObject *y = PyArray_SimpleNewFromData(1, veclen, NPY_DOUBLE, mywork->y);
/* info dict */
// infostring
const char* infostring;
switch( exitcode ){
case ECOS_OPTIMAL:
infostring = "Optimal solution found";
break;
case ECOS_MAXIT:
infostring = "Maximum number of iterations reached";
break;
case ECOS_PINF:
infostring = "Primal infeasible";
break;
case ECOS_DINF:
infostring = "Dual infeasible";
break;
case ECOS_NUMERICS:
infostring = "Run into numerical problems";
break;
case ECOS_OUTCONE:
infostring = "PROBLEM: Multipliers leaving the cone";
break;
default:
infostring = "UNKNOWN PROBLEM IN SOLVER";
}
// numerical errors
idxint numerr = 0;
if( (exitcode == ECOS_NUMERICS) || (exitcode == ECOS_OUTCONE) || (exitcode == ECOS_FATAL) ){
numerr = 1;
}
// timings
#if PROFILING > 0
PyObject *tinfos = Py_BuildValue(
#if PROFILING > 1
"{s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d}",
#else
"{s:d,s:d,s:d}",
#endif
#if PROFILING > 1
"tkktcreate",(double)mywork->info->tkktcreate,
"tkktsolve",(double)mywork->info->tkktsolve,
"tkktfactor",(double)mywork->info->tfactor,
"torder",(double)mywork->info->torder,
"ttranspose",(double)mywork->info->ttranspose,
#endif
"runtime",(double)mywork->info->tsolve + (double)mywork->info->tsetup,
"tsetup",(double)mywork->info->tsetup,
"tsolve",(double)mywork->info->tsolve);
#endif
PyObject *infoDict = Py_BuildValue(
#if PROFILING > 0
"{s:l,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:l,s:s,s:O,s:l}",
#else
"{s:l,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:l,s:s,s:l}",
#endif
"exitFlag", exitcode,
"pcost", (double)mywork->info->pcost,
"dcost", (double)mywork->info->dcost,
"pres", (double)mywork->info->pres,
"dres", (double)mywork->info->dres,
"pinf", (double)mywork->info->pinf,
"dinf", (double)mywork->info->dinf,
"pinfres",(double)mywork->info->pinfres,
"dinfres",(double)mywork->info->dinfres,
"gap",(double)mywork->info->gap,
"relgap",(double)mywork->info->relgap,
"r0",(double)mywork->stgs->feastol,
"iter",mywork->info->iter,
"infostring",infostring,
#if PROFILING > 0
"timing", tinfos,
#endif
"numerr",numerr);
#if PROFILING > 0
// give reference to infoDict
Py_DECREF(tinfos);
#endif
/* s */
// matrix *s;
// if(!(s = Matrix_New(m,1,DOUBLE)))
// return PyErr_NoMemory();
// memcpy(MAT_BUFD(s), mywork->s, m*sizeof(double));
veclen[0] = m;
PyObject *s = PyArray_SimpleNewFromData(1, veclen, NPY_DOUBLE, mywork->s);
/* z */
// matrix *z;
// if(!(z = Matrix_New(m,1,DOUBLE)))
// return PyErr_NoMemory();
// memcpy(MAT_BUFD(z), mywork->z, m*sizeof(double));
veclen[0] = m;
PyObject *z = PyArray_SimpleNewFromData(1, veclen, NPY_DOUBLE, mywork->z);
/* cleanup */
ECOS_cleanup(mywork, 4);
PyObject *returnDict = Py_BuildValue(
"{s:O,s:O,s:O,s:O,s:O}",
"x",x,
"y",y,
"z",z,
"s",s,
"info",infoDict);
// give up ownership to the return dictionary
Py_DECREF(x); Py_DECREF(y); Py_DECREF(z); Py_DECREF(s); Py_DECREF(infoDict);
// no longer need pointers to arrays that held primitives
if(q) free(q);
Py_DECREF(Gx_arr); Py_DECREF(Gi_arr); Py_DECREF(Gp_arr);
Py_DECREF(c_arr); Py_DECREF(h_arr);
if (b_arr) Py_DECREF(b_arr);
if (Ax_arr) Py_DECREF(Ax_arr);
if (Ai_arr) Py_DECREF(Ai_arr);
if (Ap_arr) Py_DECREF(Ap_arr);
return returnDict;
}
/* THE mex-function */
void mexFunction( int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[] )
{
idxint i, n, m, p;
idxint exitcode;
idxint numerr = 0;
const mxArray* c;
const mxArray* G;
const mxArray* h;
const mxArray* A = NULL;
const mxArray* b = NULL;
const mxArray* dims;
const mxArray* dims_l;
const mxArray* dims_q;
const mxArray* opts = NULL;
const mxArray* opts_verbose = NULL;
const mxArray* opts_feastol = NULL;
const mxArray* opts_reltol = NULL;
const mxArray* opts_abstol = NULL;
const mxArray* opts_feastol_inacc = NULL;
const mxArray* opts_reltol_inacc = NULL;
const mxArray* opts_abstol_inacc = NULL;
const mxArray* opts_maxit = NULL;
const mwSize *size_c;
const mwSize *size_G;
const mwSize *size_h;
const mwSize *size_A;
const mwSize *size_b;
const mwSize *size_q;
const mwSize ZERO[2] = {0, 0};
mxArray* outvar;
mxArray* tinfos;
/* change number of infofields according to profiling setting */
#if PROFILING > 0
#define NINFOFIELDS 16
#else
#define NINFOFIELDS 15
#endif
const char *infofields[NINFOFIELDS] = { "exitflag",
"infostring",
"pcost",
"dcost",
"pres",
"dres",
"pinf",
"dinf",
"pinfres",
"dinfres",
"gap",
"relgap",
"r0",
"numerr",
"iter"
#if PROFILING > 0
,"timing"
#endif
};
#if PROFILING == 1
#define NTFIELDS 3
const char *tinfo[NTFIELDS] = {"runtime", "tsolve", "tsetup"};
#endif
#if PROFILING == 2
#define NTFIELDS 10
const char *tinfo[NTFIELDS] = {"runtime", "tsolve", "tsetup", "tkktcreate", "tkktfactor", "tkktsolve", "torder", "ttranspose","tfactor_t1","tfactor_t2"};
#endif
idxint l;
double *q;
idxint *qint;
idxint ncones;
idxint numConicVariables = 0;
/* options */
idxint verbose;
pfloat abstol;
pfloat reltol;
pfloat feastol;
idxint maxit;
pfloat *Gpr = NULL;
idxint *Gjc = NULL;
idxint *Gir = NULL;
pfloat *Apr = NULL;
idxint *Ajc = NULL;
idxint *Air = NULL;
pfloat *cpr = NULL;
pfloat *hpr = NULL;
pfloat *bpr = NULL;
pwork* mywork;
#ifdef MEXARGMUENTCHECKS
if( !(nrhs >= 4 && nrhs <= 7) )
{
mexPrintf("ECOS %s - (c) A. Domahidi, Automatic Control Laboratory, ETH Zurich, 2012-14.\n", ECOS_VERSION);
mexErrMsgTxt("ECOS takes 4 to 7 arguments: ECOS(c,G,h,dims), ECOS(c,G,h,dims,opts), ECOS(c,G,h,dims,A,b), or ECOS(c,G,h,dims,A,b,opts)");
}
#endif
/* get pointers to data */
c = prhs[0]; size_c = c ? mxGetDimensions(c) : (const mwSize *) &ZERO;
G = prhs[1]; size_G = G ? mxGetDimensions(G) : (const mwSize *) &ZERO;
h = prhs[2]; size_h = h ? mxGetDimensions(h) : (const mwSize *) &ZERO;
dims = prhs[3];
dims_l = dims ? mxGetField(dims, 0, "l") : NULL;
dims_q = dims ? mxGetField(dims, 0, "q") : NULL;
size_q = dims_q ? mxGetDimensions(dims_q) : (const mwSize *) &ZERO;
if( nrhs >= 6 )
{
A = prhs[4]; size_A = A ? mxGetDimensions(A) : (const mwSize *) &ZERO;
b = prhs[5]; size_b = b ? mxGetDimensions(b) : (const mwSize *) &ZERO;
}
if( nrhs == 5 || nrhs == 7 )
{
opts = nrhs==5 ? prhs[4] : prhs[6];
opts_verbose = opts ? mxGetField(opts, 0, "verbose") : 0;
opts_abstol = opts ? mxGetField(opts, 0, "abstol") : 0;
opts_feastol = opts ? mxGetField(opts, 0, "feastol") : 0;
opts_reltol = opts ? mxGetField(opts, 0, "reltol") : 0;
opts_abstol_inacc = opts ? mxGetField(opts, 0, "abstol_inacc") : 0;
opts_feastol_inacc = opts ? mxGetField(opts, 0, "feastol_inacc") : 0;
opts_reltol_inacc = opts ? mxGetField(opts, 0, "reltol_inacc") : 0;
opts_maxit = opts ? mxGetField(opts, 0, "maxit") : 0;
}
/* determine sizes */
n = (idxint)size_c[0];
m = (idxint)size_G[0];
p = (nrhs >= 6) ? (idxint)size_A[0] : 0;
/* argument checking */
#ifdef MEXARGMUENTCHECKS
if( !mxIsDouble(c) || size_c[1] > 1 )
{
mexErrMsgTxt("First argument needs to be a column vector");
}
if( !mxIsDouble(G) )
{
mexErrMsgTxt("Second argument needs to be a matrix");
}
if( !mxIsSparse(G) )
{
mexErrMsgTxt("Second argument needs to be a sparse matrix");
}
if( size_G[1] != n )
{
mexErrMsgTxt("c and G do not match in dimension");
}
if( m > 0 ){
if( size_h[0] != m )
{
mexErrMsgTxt("G and h do not match in dimension");
}
if( size_h[1] != 1 )
{
mexErrMsgTxt("h is expected to be a column vector");
}
}
if( !mxIsStruct(dims) )
{
mexErrMsgTxt("Struct dims expected as 4th argument");
}
if( dims_l == NULL && dims_q == NULL ) {
mexErrMsgTxt("Neither dims.l nor dims.q exist - unconstrained problem?");
}
if( mxIsSparse(c) )
{
mexErrMsgTxt("c must be a dense vector");
}
if( mxIsSparse(h) )
{
mexErrMsgTxt("h must be a dense vector");
}
if( nrhs >= 6 )
{
if( size_A[1] != n )
{
mexErrMsgTxt("c and A dimension mismatch");
}
if( !mxIsDouble(A) )
{
mexErrMsgTxt("Fifth argument needs to be a matrix");
}
if( !mxIsSparse(A) )
{
mexErrMsgTxt("Fifth argument (A) needs to be a sparse matrix");
}
if( size_b[0] != p )
{
mexErrMsgTxt("b and A dimension mismatch");
}
if( size_b[1] != 1 )
{
mexErrMsgTxt("b is expected to be a column vector");
}
if( mxIsSparse(b) )
{
mexErrMsgTxt("b must be a dense vector");
}
}
if( nrhs == 7 || nrhs == 5 )
{
if( !mxIsStruct(opts) )
{
mexErrMsgTxt("Struct opts expected as last argument");
}
}
if( nlhs > 5 ){
mexErrMsgTxt("ECOS has up to 5 output arguments only");
}
#endif
/* find out dimensions of cones */
l = (idxint)(*mxGetPr(dims_l)); numConicVariables += l;
if( dims_q != NULL) {
q = mxGetPr(dims_q);
} else {
q = NULL;
}
if( q == NULL || size_q[0] == 0 || size_q[1]==0 ){
ncones = 0;
} else {
ncones = size_q[1] > size_q[0] ? size_q[1] : size_q[0];
}
/* get problem data in right format matrices */
if( m > 0){
Gpr = (pfloat *)mxGetPr(G);
Gjc = (idxint *)mxGetJc(G);
Gir = (idxint *)mxGetIr(G);
} else { mexErrMsgTxt( "ECOS does not support equality constrained problems without inequalities yet." ); }
if( p > 0 ){
Apr = (pfloat *)mxGetPr(A);
Ajc = (idxint *)mxGetJc(A);
Air = (idxint *)mxGetIr(A);
}
cpr = (pfloat *)mxGetPr(c);
hpr = (pfloat *)mxGetPr(h);
if ( p > 0 ) {
bpr = (pfloat *)mxGetPr(b);
}
/* we have to copy the number of cones since Matlab gives us double
* values but the C version of ECOS expects idxint values */
qint = (idxint *)mxMalloc(ncones*sizeof(idxint));
for( i=0; i < ncones; i++ ){ qint[i] = (idxint)q[i]; numConicVariables += qint[i]; }
/* check that number of rows matches info defined in dims */
if ( numConicVariables != m ) {
mexErrMsgTxt("Number of rows does not match information given in dims");
}
/* This calls ECOS setup function. */
mywork = ECOS_setup(n, m, p, l, ncones, qint, Gpr, Gjc, Gir, Apr, Ajc, Air, cpr, hpr, bpr);
if( mywork == NULL ){
mexErrMsgTxt("Internal problem occurred in ECOS while setting up the problem.\nPlease send a bug report with data to Alexander Domahidi.\nEmail: [email protected]");
}
/* Set options */
if( opts != NULL ) {
if(opts_verbose != NULL )
{
mywork->stgs->verbose = mxIsLogical(opts_verbose) ? (idxint) (*mxGetLogicals(opts_verbose)) : (idxint)(*mxGetPr(opts_verbose));
}
if(opts_feastol != NULL )
{
mywork->stgs->feastol = (pfloat)(*mxGetPr(opts_feastol));
}
if(opts_abstol != NULL )
{
mywork->stgs->abstol = (pfloat)(*mxGetPr(opts_abstol));
}
if(opts_reltol != NULL )
{
mywork->stgs->reltol = (pfloat)(*mxGetPr(opts_reltol));
}
if(opts_feastol_inacc != NULL )
{
mywork->stgs->feastol_inacc = (pfloat)(*mxGetPr(opts_feastol_inacc));
}
if(opts_abstol_inacc != NULL )
{
mywork->stgs->abstol_inacc = (pfloat)(*mxGetPr(opts_abstol_inacc));
}
if(opts_reltol_inacc != NULL )
{
mywork->stgs->reltol_inacc = (pfloat)(*mxGetPr(opts_reltol_inacc));
}
if(opts_maxit != NULL )
{
mywork->stgs->maxit = (idxint)(*mxGetPr(opts_maxit));
}
}
/* Solve! */
exitcode = ECOS_solve(mywork);
/* create output */
/* x */
if( nlhs > 0 ){
plhs[0] = mxCreateDoubleMatrix(0, 0, mxREAL);
mxSetPr(plhs[0], mywork->x);
mxSetM(plhs[0], n);
mxSetN(plhs[0], 1);
}
/* y */
if( nlhs > 1 ){
plhs[1] = mxCreateDoubleMatrix(0, 0, mxREAL);
mxSetPr(plhs[1], mywork->y);
mxSetM(plhs[1], mywork->p);
mxSetN(plhs[1], 1);
}
if( nlhs > 2 ){
plhs[2] = mxCreateStructMatrix(1, 1, NINFOFIELDS, infofields);
/* 0. exitflag */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)exitcode;
mxSetField(plhs[2], 0, "exitflag", outvar);
/* 1. primal objective */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->pcost;
mxSetField(plhs[2], 0, "pcost", outvar);
/* 2. dual objective */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->dcost;
mxSetField(plhs[2], 0, "dcost", outvar);
/* 3. primal residual */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->pres;
mxSetField(plhs[2], 0, "pres", outvar);
/* 4. dual residual */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->dres;
mxSetField(plhs[2], 0, "dres", outvar);
/* 5. primal infeasible? */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->pinf;
mxSetField(plhs[2], 0, "pinf", outvar);
/* 6. dual infeasible? */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->dinf;
mxSetField(plhs[2], 0, "dinf", outvar);
/* 7. primal infeasibility measure */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->pinfres;
mxSetField(plhs[2], 0, "pinfres", outvar);
/* 8. dual infeasibility measure */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->dinfres;
mxSetField(plhs[2], 0, "dinfres", outvar);
/* 9. duality gap */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->gap;
mxSetField(plhs[2], 0, "gap", outvar);
/* 10. relative duality gap */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->relgap;
mxSetField(plhs[2], 0, "relgap", outvar);
/* 11. feasibility tolerance??? */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->stgs->feastol;
mxSetField(plhs[2], 0, "r0", outvar);
/* 12. iterations */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->iter;
mxSetField(plhs[2], 0, "iter", outvar);
/* 13. infostring */
switch( exitcode ){
case ECOS_OPTIMAL:
outvar = mxCreateString("Optimal solution found");
break;
case (ECOS_OPTIMAL + ECOS_INACC_OFFSET):
outvar = mxCreateString("Optimal solution found within reduced tolerances");
break;
case ECOS_MAXIT:
outvar = mxCreateString("Maximum number of iterations reached");
break;
case ECOS_PINF:
outvar = mxCreateString("Certificate of primal infeasibility found");
break;
case (ECOS_PINF + ECOS_INACC_OFFSET):
outvar = mxCreateString("Certificate of primal infeasibility found within reduced tolerances");
break;
case ECOS_DINF:
outvar = mxCreateString("Certificate of dual infeasibility found");
break;
case (ECOS_DINF + ECOS_INACC_OFFSET):
outvar = mxCreateString("Certificate of dual infeasibility found within reduced tolerances");
break;
case ECOS_NUMERICS:
outvar = mxCreateString("Numerical problems");
break;
case ECOS_OUTCONE:
outvar = mxCreateString("PROBLEM: Mulitpliers leaving the cone");
break;
default:
outvar = mxCreateString("UNKNOWN PROBLEM IN SOLVER");
}
mxSetField(plhs[2], 0, "infostring", outvar);
#if PROFILING > 0
/* 14. timing information */
tinfos = mxCreateStructMatrix(1, 1, NTFIELDS, tinfo);
/* 14.1 --> runtime */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tsolve + (double)mywork->info->tsetup;
mxSetField(tinfos, 0, "runtime", outvar);
/* 14.2 --> setup time */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tsetup;
mxSetField(tinfos, 0, "tsetup", outvar);
/* 14.3 --> solve time */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tsolve;
mxSetField(tinfos, 0, "tsolve", outvar);
#if PROFILING > 1
/* 14.4 time to create KKT matrix */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tkktcreate;
mxSetField(tinfos, 0, "tkktcreate", outvar);
/* 14.5 time for kkt solve */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tkktsolve;
mxSetField(tinfos, 0, "tkktsolve", outvar);
/* 14.6 time for kkt factor */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tfactor;
mxSetField(tinfos, 0, "tkktfactor", outvar);
/* 14.7 time for ordering */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->torder;
mxSetField(tinfos, 0, "torder", outvar);
/* 14.8 time for transposes */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->ttranspose;
mxSetField(tinfos, 0, "ttranspose", outvar);
/* 14.9 time for factoring, part 1 */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tfactor_t1;
mxSetField(tinfos, 0, "tfactor_t1", outvar);
/* 14.10 time for transposes */
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)mywork->info->tfactor_t2;
mxSetField(tinfos, 0, "tfactor_t2", outvar);
#endif
mxSetField(plhs[2], 0, "timing", tinfos);
#endif
/* 15. numerical error? */
if( (exitcode == ECOS_NUMERICS) || (exitcode == ECOS_OUTCONE) || (exitcode == ECOS_FATAL) ){
numerr = 1;
}
outvar = mxCreateDoubleMatrix(1, 1, mxREAL);
*mxGetPr(outvar) = (double)numerr;
mxSetField(plhs[2], 0, "numerr", outvar);
}
/* s */
if( nlhs > 3 ){
plhs[3] = mxCreateDoubleMatrix(0, 0, mxREAL);
mxSetPr(plhs[3], mywork->s);
mxSetM(plhs[3], m);
mxSetN(plhs[3], 1);
}
/* z */
if( nlhs > 4 ){
plhs[4] = mxCreateDoubleMatrix(0, 0, mxREAL);
mxSetPr(plhs[4], mywork->z);
mxSetM(plhs[4], m);
mxSetN(plhs[4], 1);
}
/* cleanup */
ECOS_cleanup(mywork, nlhs > 2? nlhs-1 : nlhs);
mxFree(qint);
}
