int SMScaleAddNew_Band(realtype c, SUNMatrix A, SUNMatrix B)
{
sunindextype i, j, ml, mu, smu;
realtype *A_colj, *B_colj, *C_colj;
SUNMatrix C;
/* create new matrix large enough to hold both A and B */
ml = SUNMAX(SM_LBAND_B(A),SM_LBAND_B(B));
mu = SUNMAX(SM_UBAND_B(A),SM_UBAND_B(B));
smu = SUNMIN(SM_COLUMNS_B(A)-1, mu + ml);
C = SUNBandMatrix(SM_COLUMNS_B(A), mu, ml, smu);
/* scale/add c*A into new matrix */
for (j=0; j<SM_COLUMNS_B(A); j++) {
A_colj = SM_COLUMN_B(A,j);
C_colj = SM_COLUMN_B(C,j);
for (i=-SM_UBAND_B(A); i<=SM_LBAND_B(A); i++)
C_colj[i] = c*A_colj[i];
}
/* add B into new matrix */
for (j=0; j<SM_COLUMNS_B(B); j++) {
B_colj = SM_COLUMN_B(B,j);
C_colj = SM_COLUMN_B(C,j);
for (i=-SM_UBAND_B(B); i<=SM_LBAND_B(B); i++)
C_colj[i] += B_colj[i];
}
/* replace A contents with C contents, nullify C content pointer, destroy C */
free(SM_DATA_B(A)); SM_DATA_B(A) = NULL;
free(SM_COLS_B(A)); SM_COLS_B(A) = NULL;
free(A->content); A->content = NULL;
A->content = C->content;
C->content = NULL;
SUNMatDestroy_Band(C);
return 0;
}
int main(int argc, char *argv[])
{
UserData data;
void *cvode_mem;
SUNMatrix A, AB;
SUNLinearSolver LS, LSB;
realtype dx, dy, reltol, abstol, t;
N_Vector u;
int indexB;
realtype reltolB, abstolB;
N_Vector uB;
int retval, ncheck;
data = NULL;
cvode_mem = NULL;
u = uB = NULL;
LS = LSB = NULL;
A = AB = NULL;
/* Allocate and initialize user data memory */
data = (UserData) malloc(sizeof *data);
if(check_retval((void *)data, "malloc", 2)) return(1);
dx = data->dx = XMAX/(MX+1);
dy = data->dy = YMAX/(MY+1);
data->hdcoef = ONE/(dx*dx);
data->hacoef = RCONST(1.5)/(TWO*dx);
data->vdcoef = ONE/(dy*dy);
/* Set the tolerances for the forward integration */
reltol = ZERO;
abstol = ATOL;
/* Allocate u vector */
u = N_VNew_Serial(NEQ);
if(check_retval((void *)u, "N_VNew", 0)) return(1);
/* Initialize u vector */
SetIC(u, data);
/* Create and allocate CVODES memory for forward run */
printf("\nCreate and allocate CVODES memory for forward runs\n");
cvode_mem = CVodeCreate(CV_BDF);
if(check_retval((void *)cvode_mem, "CVodeCreate", 0)) return(1);
retval = CVodeSetUserData(cvode_mem, data);
if(check_retval(&retval, "CVodeSetUserData", 1)) return(1);
retval = CVodeInit(cvode_mem, f, T0, u);
if(check_retval(&retval, "CVodeInit", 1)) return(1);
retval = CVodeSStolerances(cvode_mem, reltol, abstol);
if(check_retval(&retval, "CVodeSStolerances", 1)) return(1);
/* Create banded SUNMatrix for the forward problem */
A = SUNBandMatrix(NEQ, MY, MY);
if(check_retval((void *)A, "SUNBandMatrix", 0)) return(1);
/* Create banded SUNLinearSolver for the forward problem */
LS = SUNLinSol_Band(u, A);
if(check_retval((void *)LS, "SUNLinSol_Band", 0)) return(1);
/* Attach the matrix and linear solver */
retval = CVodeSetLinearSolver(cvode_mem, LS, A);
if(check_retval(&retval, "CVodeSetLinearSolver", 1)) return(1);
/* Set the user-supplied Jacobian routine for the forward problem */
retval = CVodeSetJacFn(cvode_mem, Jac);
if(check_retval(&retval, "CVodeSetJacFn", 1)) return(1);
/* Allocate global memory */
printf("\nAllocate global memory\n");
retval = CVodeAdjInit(cvode_mem, NSTEP, CV_HERMITE);
if(check_retval(&retval, "CVodeAdjInit", 1)) return(1);
/* Perform forward run */
printf("\nForward integration\n");
retval = CVodeF(cvode_mem, TOUT, u, &t, CV_NORMAL, &ncheck);
if(check_retval(&retval, "CVodeF", 1)) return(1);
printf("\nncheck = %d\n", ncheck);
/* Set the tolerances for the backward integration */
reltolB = RTOLB;
abstolB = ATOL;
/* Allocate uB */
uB = N_VNew_Serial(NEQ);
if(check_retval((void *)uB, "N_VNew", 0)) return(1);
/* Initialize uB = 0 */
N_VConst(ZERO, uB);
/* Create and allocate CVODES memory for backward run */
printf("\nCreate and allocate CVODES memory for backward run\n");
retval = CVodeCreateB(cvode_mem, CV_BDF, &indexB);
if(check_retval(&retval, "CVodeCreateB", 1)) return(1);
retval = CVodeSetUserDataB(cvode_mem, indexB, data);
if(check_retval(&retval, "CVodeSetUserDataB", 1)) return(1);
retval = CVodeInitB(cvode_mem, indexB, fB, TOUT, uB);
if(check_retval(&retval, "CVodeInitB", 1)) return(1);
retval = CVodeSStolerancesB(cvode_mem, indexB, reltolB, abstolB);
if(check_retval(&retval, "CVodeSStolerancesB", 1)) return(1);
/* Create banded SUNMatrix for the backward problem */
AB = SUNBandMatrix(NEQ, MY, MY);
if(check_retval((void *)AB, "SUNBandMatrix", 0)) return(1);
/* Create banded SUNLinearSolver for the backward problem */
LSB = SUNLinSol_Band(uB, AB);
if(check_retval((void *)LSB, "SUNLinSol_Band", 0)) return(1);
/* Attach the matrix and linear solver */
retval = CVodeSetLinearSolverB(cvode_mem, indexB, LSB, AB);
if(check_retval(&retval, "CVodeSetLinearSolverB", 1)) return(1);
/* Set the user-supplied Jacobian routine for the backward problem */
retval = CVodeSetJacFnB(cvode_mem, indexB, JacB);
if(check_retval(&retval, "CVodeSetJacFnB", 1)) return(1);
/* Perform backward integration */
printf("\nBackward integration\n");
retval = CVodeB(cvode_mem, T0, CV_NORMAL);
if(check_retval(&retval, "CVodeB", 1)) return(1);
retval = CVodeGetB(cvode_mem, indexB, &t, uB);
if(check_retval(&retval, "CVodeGetB", 1)) return(1);
PrintOutput(uB, data);
N_VDestroy(u); /* Free the u vector */
N_VDestroy(uB); /* Free the uB vector */
CVodeFree(&cvode_mem); /* Free the CVODE problem memory */
SUNLinSolFree(LS); /* Free the forward linear solver memory */
SUNMatDestroy(A); /* Free the forward matrix memory */
SUNLinSolFree(LSB); /* Free the backward linear solver memory */
SUNMatDestroy(AB); /* Free the backward matrix memory */
free(data); /* Free the user data */
return(0);
}
void OpenSMOKE_CVODE_Sundials<T>::Solve(const double xend)
{
int flag;
this->x_ = this->x0_;
this->xend_ = xend;
for(int i=0;i<this->n_;i++)
NV_Ith_S(y0Sundials_,i) = this->y0_[i];
if (firstCall_ == true)
{
firstCall_ = false;
/* Call CVodeCreate to create the solver memory and specify the
* Backward Differentiation Formula and the use of a Newton iteration */
cvode_mem_ = CVodeCreate(CV_BDF, CV_NEWTON);
if (check_flag((void *)cvode_mem_, std::string("CVodeCreate"), 0)) exit(-1);
/* Call CVodeInit to initialize the integrator memory and specify the
* user's right hand side function in y'=f(t,y), the inital time t0, and
* the initial dependent variable vector y0Sundials_. */
flag = CVodeInit(cvode_mem_, this->odeSystem_->GetSystemFunctionsStatic, this->odeSystem_->GetWriteFunctionStatic, this->x0_, y0Sundials_);
if (check_flag(&flag, std::string("CVodeInit"), 1)) exit(-1);
/* Call CVodeSVtolerances to specify the scalar relative tolerance
* and vector absolute tolerances */
flag = CVodeSStolerances(cvode_mem_, this->relTolerance_[0], this->absTolerance_[0]);
if (check_flag(&flag, std::string("CVodeSVtolerances"), 1)) exit(-1);
/* Call Solver */
if (this->iUseLapack_ == false)
{
if (this->mUpper_ == 0 && this->mLower_ == 0)
{
// std::cout << "CVODE Solver: Dense Jacobian (without Lapack)..." << std::endl;
/* Create dense SUNMatrix for use in linear solves */
A = SUNDenseMatrix(this->n_, this->n_);
if (check_flag((void *)A, std::string("SUNDenseMatrix"), 0)) exit(-1);
/* Create SUNDenseLinearSolver solver object for use by CVode */
LS = SUNDenseLinearSolver(ySundials_, A);
if (check_flag((void *)LS, std::string("SUNDenseLinearSolver"), 0)) exit(-1);
}
else
{
// std::cout << "CVODE Solver: Band Jacobian (without Lapack)..." << std::endl;
/* Create banded SUNMatrix for use in linear solves -- since this will be factored,
set the storage bandwidth to be the sum of upper and lower bandwidths */
A = SUNBandMatrix(this->n_, this->mUpper_, this->mLower_, (this->mUpper_+this->mLower_) );
if (check_flag((void *)A, std::string("SUNBandMatrix"), 0)) exit(-1);
/* Create banded SUNLinearSolver object for use by CVode */
LS = SUNBandLinearSolver(ySundials_, A);
if (check_flag((void *)LS, std::string("SUNBandLinearSolver"), 0)) exit(-1);
}
}
else
{
if (this->mUpper_ == 0 && this->mLower_ == 0)
{
// std::cout << "CVODE Solver: Dense Jacobian (with Lapack)..." << std::endl;
/* Create dense SUNMatrix for use in linear solves */
A = SUNDenseMatrix(this->n_, this->n_);
if (check_flag((void *)A, std::string("SUNDenseMatrix"), 0)) exit(-1);
/* Create SUNLapackDense solver object for use by CVode */
LS = SUNLapackDense(ySundials_, A);
if (check_flag((void *)LS, std::string("SUNLapackDense"), 0)) exit(-1);
}
else
{
// std::cout << "CVODE Solver: Band Jacobian (with Lapack)..." << std::endl;
/* Create banded SUNMatrix for use in linear solves -- since this will be factored,
set the storage bandwidth to be the sum of upper and lower bandwidths */
A = SUNBandMatrix(this->n_, this->mUpper_, this->mLower_, (this->mUpper_ + this->mLower_));
if (check_flag((void *)A, std::string("SUNBandMatrix"), 0)) exit(-1);
/* Create banded SUNLapackBand solver object for use by CVode */
LS = SUNLapackBand(ySundials_, A);
if (check_flag((void *)LS, std::string("SUNLapackBand"), 0)) exit(-1);
}
}
/* Call CVDlsSetLinearSolver to attach the matrix and linear solver to CVode */
flag = CVDlsSetLinearSolver(cvode_mem_, LS, A);
if (check_flag(&flag, std::string("CVDlsSetLinearSolver"), 1)) exit(-1);
}
else
{
flag = CVodeReInit(cvode_mem_, this->x0_, y0Sundials_);
if (check_flag(&flag, std::string("CVodeReInit"), 1)) exit(-1);
}
AnalyzeUserOptions();
/* Solving */
this->tStart_ = this->GetClockTime();
flag = CVode(cvode_mem_, this->xend_, ySundials_, &this->x_, CV_NORMAL);
this->tEnd_ = this->GetClockTime();
this->x0_ = this->x_;
for(int i=0;i<this->n_;i++)
NV_Ith_S(y0Sundials_,i) = NV_Ith_S(ySundials_,i);
for(int i=0;i<this->n_;i++)
this->y_[i] = NV_Ith_S(ySundials_,i);
}
int main(int argc, char *argv[])
{
void *ida_mem;
SUNMatrix A;
SUNLinearSolver LS;
UserData webdata;
N_Vector cc, cp, id;
int iout, retval;
sunindextype mu, ml;
realtype rtol, atol, t0, tout, tret;
int num_threads;
ida_mem = NULL;
A = NULL;
LS = NULL;
webdata = NULL;
cc = cp = id = NULL;
/* Set the number of threads to use */
num_threads = 1; /* default value */
#ifdef _OPENMP
num_threads = omp_get_max_threads(); /* overwrite with OMP_NUM_THREADS enviroment variable */
#endif
if (argc > 1) /* overwrite with command line value, if supplied */
num_threads = strtol(argv[1], NULL, 0);
/* Allocate and initialize user data block webdata. */
webdata = (UserData) malloc(sizeof *webdata);
webdata->rates = N_VNew_OpenMP(NEQ, num_threads);
webdata->acoef = newDenseMat(NUM_SPECIES, NUM_SPECIES);
webdata->nthreads = num_threads;
InitUserData(webdata);
/* Allocate N-vectors and initialize cc, cp, and id. */
cc = N_VNew_OpenMP(NEQ, num_threads);
if(check_retval((void *)cc, "N_VNew_OpenMP", 0)) return(1);
cp = N_VNew_OpenMP(NEQ, num_threads);
if(check_retval((void *)cp, "N_VNew_OpenMP", 0)) return(1);
id = N_VNew_OpenMP(NEQ, num_threads);
if(check_retval((void *)id, "N_VNew_OpenMP", 0)) return(1);
SetInitialProfiles(cc, cp, id, webdata);
/* Set remaining inputs to IDAMalloc. */
t0 = ZERO;
rtol = RTOL;
atol = ATOL;
/* Call IDACreate and IDAMalloc to initialize IDA. */
ida_mem = IDACreate();
if(check_retval((void *)ida_mem, "IDACreate", 0)) return(1);
retval = IDASetUserData(ida_mem, webdata);
if(check_retval(&retval, "IDASetUserData", 1)) return(1);
retval = IDASetId(ida_mem, id);
if(check_retval(&retval, "IDASetId", 1)) return(1);
retval = IDAInit(ida_mem, resweb, t0, cc, cp);
if(check_retval(&retval, "IDAInit", 1)) return(1);
retval = IDASStolerances(ida_mem, rtol, atol);
if(check_retval(&retval, "IDASStolerances", 1)) return(1);
/* Setup band matrix and linear solver, and attach to IDA. */
mu = ml = NSMX;
A = SUNBandMatrix(NEQ, mu, ml);
if(check_retval((void *)A, "SUNBandMatrix", 0)) return(1);
LS = SUNLinSol_Band(cc, A);
if(check_retval((void *)LS, "SUNLinSol_Band", 0)) return(1);
retval = IDASetLinearSolver(ida_mem, LS, A);
if(check_retval(&retval, "IDASetLinearSolver", 1)) return(1);
/* Call IDACalcIC (with default options) to correct the initial values. */
tout = RCONST(0.001);
retval = IDACalcIC(ida_mem, IDA_YA_YDP_INIT, tout);
if(check_retval(&retval, "IDACalcIC", 1)) return(1);
/* Print heading, basic parameters, and initial values. */
PrintHeader(mu, ml, rtol, atol);
PrintOutput(ida_mem, cc, ZERO);
/* Loop over iout, call IDASolve (normal mode), print selected output. */
for (iout = 1; iout <= NOUT; iout++) {
retval = IDASolve(ida_mem, tout, &tret, cc, cp, IDA_NORMAL);
if(check_retval(&retval, "IDASolve", 1)) return(retval);
PrintOutput(ida_mem, cc, tret);
if (iout < 3) tout *= TMULT; else tout += TADD;
}
/* Print final statistics and free memory. */
PrintFinalStats(ida_mem);
printf("num_threads = %i\n\n", num_threads);
/* Free memory */
IDAFree(&ida_mem);
SUNLinSolFree(LS);
SUNMatDestroy(A);
N_VDestroy_OpenMP(cc);
N_VDestroy_OpenMP(cp);
N_VDestroy_OpenMP(id);
destroyMat(webdata->acoef);
N_VDestroy_OpenMP(webdata->rates);
free(webdata);
return(0);
}
SUNMatrix SUNMatClone_Band(SUNMatrix A)
{
SUNMatrix B = SUNBandMatrix(SM_COLUMNS_B(A), SM_UBAND_B(A),
SM_LBAND_B(A), SM_SUBAND_B(A));
return(B);
}
/* ----------------------------------------------------------------------
* Main SUNMatrix Testing Routine
* --------------------------------------------------------------------*/
int main(int argc, char *argv[])
{
int fails=0; /* counter for test failures */
sunindextype matrows, matcols; /* matrix dims */
int mattype; /* matrix storage type */
N_Vector x, y, z; /* test vectors */
realtype* vecdata; /* pointers to vector data */
SUNMatrix A, B, C, D, I; /* test matrices */
realtype* matdata; /* pointer to matrix data */
sunindextype i, j, k, kstart, kend, N, uband, lband;
sunindextype *colptrs, *rowindices;
sunindextype *rowptrs, *colindices;
int print_timing, square;
/* check input and set vector length */
if (argc < 5){
printf("ERROR: FOUR (4) Input required: matrix rows, matrix cols, matrix type (0/1), print timing \n");
return(-1);
}
matrows = atol(argv[1]);
if (matrows < 1) {
printf("ERROR: number of rows must be a positive integer\n");
return(-1);
}
matcols = atol(argv[2]);
if (matcols < 1) {
printf("ERROR: number of cols must be a positive integer\n");
return(-1);
}
k = atol(argv[3]);
if ((k != 0) && (k != 1)) {
printf("ERROR: matrix type must be 0 or 1\n");
return(-1);
}
mattype = (k == 0) ? CSC_MAT : CSR_MAT;
print_timing = atoi(argv[4]);
SetTiming(print_timing);
square = (matrows == matcols) ? 1 : 0;
printf("\nSparse matrix test: size %ld by %ld, type = %i\n\n",
(long int) matrows, (long int) matcols, mattype);
/* Initialize vectors and matrices to NULL */
x = NULL;
y = NULL;
z = NULL;
A = NULL;
B = NULL;
C = NULL;
D = NULL;
I = NULL;
/* check creating sparse matrix from dense matrix */
B = SUNDenseMatrix(5,6);
matdata = SUNDenseMatrix_Data(B);
matdata[2] = RCONST(1.0); /* [ 0 2 0 0 7 0 ] */
matdata[5] = RCONST(2.0); /* [ 0 0 4 0 8 0 ] */
matdata[9] = RCONST(3.0); /* [ 1 0 0 0 0 0 ] */
matdata[11] = RCONST(4.0); /* [ 0 0 5 6 0 0 ] */
matdata[13] = RCONST(5.0); /* [ 0 3 0 0 0 9 ] */
matdata[18] = RCONST(6.0);
matdata[20] = RCONST(7.0);
matdata[21] = RCONST(8.0);
matdata[29] = RCONST(9.0);
if (mattype == CSR_MAT) {
/* Check CSR */
C = SUNSparseMatrix(5, 6, 9, CSR_MAT);
rowptrs = SUNSparseMatrix_IndexPointers(C);
colindices = SUNSparseMatrix_IndexValues(C);
matdata = SUNSparseMatrix_Data(C);
rowptrs[0] = 0;
matdata[0] = RCONST(2.0); colindices[0] = 1;
matdata[1] = RCONST(7.0); colindices[1] = 4;
rowptrs[1] = 2;
matdata[2] = RCONST(4.0); colindices[2] = 2;
matdata[3] = RCONST(8.0); colindices[3] = 4;
rowptrs[2] = 4;
matdata[4] = RCONST(1.0); colindices[4] = 0;
rowptrs[3] = 5;
matdata[5] = RCONST(5.0); colindices[5] = 2;
matdata[6] = RCONST(6.0); colindices[6] = 3;
rowptrs[4] = 7;
matdata[7] = RCONST(3.0); colindices[7] = 1;
matdata[8] = RCONST(9.0); colindices[8] = 5;
rowptrs[5] = 9;
A = SUNSparseFromDenseMatrix(B, ZERO, CSR_MAT);
fails += check_matrix(A, C, 1e-15);
if (fails) {
printf("FAIL: SUNMatrix SparseFromDense CSR conversion failed\n");
return(1);
}
SUNMatDestroy(A);
SUNMatDestroy(C);
} else {
/* Check CSC */
D = SUNSparseMatrix(5, 6, 9, CSC_MAT);
colptrs = SUNSparseMatrix_IndexPointers(D);
rowindices = SUNSparseMatrix_IndexValues(D);
matdata = SUNSparseMatrix_Data(D);
colptrs[0] = 0;
matdata[0] = RCONST(1.0); rowindices[0] = 2;
colptrs[1] = 1;
matdata[1] = RCONST(2.0); rowindices[1] = 0;
matdata[2] = RCONST(3.0); rowindices[2] = 4;
colptrs[2] = 3;
matdata[3] = RCONST(4.0); rowindices[3] = 1;
matdata[4] = RCONST(5.0); rowindices[4] = 3;
colptrs[3] = 5;
matdata[5] = RCONST(6.0); rowindices[5] = 3;
colptrs[4] = 6;
matdata[6] = RCONST(7.0); rowindices[6] = 0;
matdata[7] = RCONST(8.0); rowindices[7] = 1;
colptrs[5] = 8;
matdata[8] = RCONST(9.0); rowindices[8] = 4;
colptrs[6] = 9;
A = SUNSparseFromDenseMatrix(B, 1e-15, CSC_MAT);
fails += check_matrix(A, D, 1e-15);
if (fails) {
printf("FAIL: SUNMatrix SparseFromDense CSC conversion failed\n");
return(1);
}
SUNMatDestroy(A);
SUNMatDestroy(D);
}
SUNMatDestroy(B);
/* check creating sparse matrix from banded matrix */
N = 7;
uband = 1;
lband = 2; /* B(i,j) = j + (j-i) */
B = SUNBandMatrix(N, uband, lband); /* B = [ 0 2 0 0 0 0 0 ] */
for (j=0; j<N; j++) { /* [ -1 1 3 0 0 0 0 ] */
matdata = SUNBandMatrix_Column(B, j); /* [ -2 0 2 4 0 0 0 ] */
kstart = (j<uband) ? -j : -uband; /* [ 0 -1 1 3 5 0 0 ] */
kend = (j>N-1-lband) ? N-1-j: lband; /* [ 0 0 0 2 4 6 0 ] */
for (k=kstart; k<=kend; k++) /* [ 0 0 0 1 3 5 7 ] */
matdata[k] = j - k; /* [ 0 0 0 0 2 4 6 ] */
}
if (mattype == CSR_MAT) {
/* CSR */
C = SUNSparseMatrix(7, 7, 21, CSR_MAT);
rowptrs = SUNSparseMatrix_IndexPointers(C);
colindices = SUNSparseMatrix_IndexValues(C);
matdata = SUNSparseMatrix_Data(C);
rowptrs[ 0] = 0;
matdata[ 0] = RCONST(2.0); colindices[ 0] = 1;
rowptrs[ 1] = 1;
matdata[ 1] = RCONST(-1.0); colindices[ 1] = 0;
matdata[ 2] = RCONST(1.0); colindices[ 2] = 1;
matdata[ 3] = RCONST(3.0); colindices[ 3] = 2;
rowptrs[ 2] = 4;
matdata[ 4] = RCONST(-2.0); colindices[ 4] = 0;
matdata[ 5] = RCONST(2.0); colindices[ 5] = 2;
matdata[ 6] = RCONST(4.0); colindices[ 6] = 3;
rowptrs[ 3] = 7;
matdata[ 7] = RCONST(-1.0); colindices[ 7] = 1;
matdata[ 8] = RCONST(1.0); colindices[ 8] = 2;
matdata[ 9] = RCONST(3.0); colindices[ 9] = 3;
matdata[10] = RCONST(5.0); colindices[10] = 4;
rowptrs[ 4] = 11;
matdata[11] = RCONST(2.0); colindices[11] = 3;
matdata[12] = RCONST(4.0); colindices[12] = 4;
matdata[13] = RCONST(6.0); colindices[13] = 5;
rowptrs[ 5] = 14;
matdata[14] = RCONST(1.0); colindices[14] = 3;
matdata[15] = RCONST(3.0); colindices[15] = 4;
matdata[16] = RCONST(5.0); colindices[16] = 5;
matdata[17] = RCONST(7.0); colindices[17] = 6;
rowptrs[ 6] = 18;
matdata[18] = RCONST(2.0); colindices[18] = 4;
matdata[19] = RCONST(4.0); colindices[19] = 5;
matdata[20] = RCONST(6.0); colindices[20] = 6;
rowptrs[ 7] = 21;
A = SUNSparseFromBandMatrix(B, ZERO, CSR_MAT);
fails += check_matrix(A, C, 1e-15);
if (fails) {
printf("FAIL: SUNMatrix SparseFromBand CSR conversion failed\n");
return(1);
}
SUNMatDestroy(A);
SUNMatDestroy(C);
} else {
/* Check CSC */
D = SUNSparseMatrix(7, 7, 21, CSC_MAT);
colptrs = SUNSparseMatrix_IndexPointers(D);
rowindices = SUNSparseMatrix_IndexValues(D);
matdata = SUNSparseMatrix_Data(D);
colptrs[ 0] = 0;
matdata[ 0] = RCONST(-1.0); rowindices[ 0] = 1;
matdata[ 1] = RCONST(-2.0); rowindices[ 1] = 2;
colptrs[ 1] = 2;
matdata[ 2] = RCONST(2.0); rowindices[ 2] = 0;
matdata[ 3] = RCONST(1.0); rowindices[ 3] = 1;
matdata[ 4] = RCONST(-1.0); rowindices[ 4] = 3;
colptrs[ 2] = 5;
matdata[ 5] = RCONST(3.0); rowindices[ 5] = 1;
matdata[ 6] = RCONST(2.0); rowindices[ 6] = 2;
matdata[ 7] = RCONST(1.0); rowindices[ 7] = 3;
colptrs[ 3] = 8;
matdata[ 8] = RCONST(4.0); rowindices[ 8] = 2;
matdata[ 9] = RCONST(3.0); rowindices[ 9] = 3;
matdata[10] = RCONST(2.0); rowindices[10] = 4;
matdata[11] = RCONST(1.0); rowindices[11] = 5;
colptrs[ 4] = 12;
matdata[12] = RCONST(5.0); rowindices[12] = 3;
matdata[13] = RCONST(4.0); rowindices[13] = 4;
matdata[14] = RCONST(3.0); rowindices[14] = 5;
matdata[15] = RCONST(2.0); rowindices[15] = 6;
colptrs[ 5] = 16;
matdata[16] = RCONST(6.0); rowindices[16] = 4;
matdata[17] = RCONST(5.0); rowindices[17] = 5;
matdata[18] = RCONST(4.0); rowindices[18] = 6;
colptrs[ 6] = 19;
matdata[19] = RCONST(7.0); rowindices[19] = 5;
matdata[20] = RCONST(6.0); rowindices[20] = 6;
colptrs[ 7] = 21;
A = SUNSparseFromBandMatrix(B, 1e-15, CSC_MAT);
fails += check_matrix(A, D, 1e-15);
if (fails) {
printf("FAIL: SUNMatrix SparseFromBand CSC conversion failed\n");
return(1);
}
SUNMatDestroy(A);
SUNMatDestroy(D);
}
SUNMatDestroy(B);
/* Create/fill I matrix */
I = NULL;
if (square) {
I = SUNSparseMatrix(matrows, matcols, matcols, mattype);
matdata = SUNSparseMatrix_Data(I);
colindices = SUNSparseMatrix_IndexValues(I);
rowptrs = SUNSparseMatrix_IndexPointers(I);
for(i=0; i<matrows; i++) {
matdata[i] = ONE;
colindices[i] = i;
rowptrs[i] = i;
}
rowptrs[matrows] = matrows;
}
/* Create/fill random dense matrices, create sparse from them */
C = SUNDenseMatrix(matrows, matcols);
D = SUNDenseMatrix(matrows, matcols);
for (k=0; k<3*matrows; k++) {
i = rand() % matrows;
j = rand() % matcols;
matdata = SUNDenseMatrix_Column(D,j);
matdata[i] = (realtype) rand() / (realtype) RAND_MAX;
}
for (k=0; k<matrows; k++) {
i = rand() % matrows;
j = rand() % matcols;
matdata = SUNDenseMatrix_Column(C,j);
matdata[i] = (realtype) rand() / (realtype) RAND_MAX;
}
A = SUNSparseFromDenseMatrix(C, ZERO, mattype);
B = SUNSparseFromDenseMatrix(D, ZERO, mattype);
/* Create vectors and fill */
x = N_VNew_Serial(matcols);
y = N_VNew_Serial(matrows);
z = N_VNew_Serial(matrows);
vecdata = N_VGetArrayPointer(x);
for(i=0; i<matcols; i++)
vecdata[i] = (realtype) rand() / (realtype) RAND_MAX;
if (SUNMatMatvec(C, x, y) != 0) {
printf("FAIL: SUNMatrix module Dense matvec failure \n \n");
SUNMatDestroy(A); SUNMatDestroy(B);
SUNMatDestroy(C); SUNMatDestroy(D);
N_VDestroy(x); N_VDestroy(y); N_VDestroy(z);
if (square)
SUNMatDestroy(I);
return(1);
}
if (SUNMatMatvec(D, x, z) != 0) {
printf("FAIL: SUNMatrix module Dense matvec failure \n \n");
SUNMatDestroy(A); SUNMatDestroy(B);
SUNMatDestroy(C); SUNMatDestroy(D);
N_VDestroy(x); N_VDestroy(y); N_VDestroy(z);
if (square)
SUNMatDestroy(I);
return(1);
}
/* SUNMatrix Tests */
fails += Test_SUNMatGetID(A, SUNMATRIX_SPARSE, 0);
fails += Test_SUNMatClone(A, 0);
fails += Test_SUNMatCopy(A, 0);
fails += Test_SUNMatZero(A, 0);
fails += Test_SUNMatScaleAdd(A, I, 0);
fails += Test_SUNMatScaleAdd2(A, B, x, y, z);
if (square) {
fails += Test_SUNMatScaleAddI(A, I, 0);
fails += Test_SUNMatScaleAddI2(A, x, y);
}
fails += Test_SUNMatMatvec(A, x, y, 0);
fails += Test_SUNMatSpace(A, 0);
/* Print result */
if (fails) {
printf("FAIL: SUNMatrix module failed %i tests \n \n", fails);
printf("\nA =\n");
SUNSparseMatrix_Print(A,stdout);
printf("\nB =\n");
SUNSparseMatrix_Print(B,stdout);
if (square) {
printf("\nI =\n");
SUNSparseMatrix_Print(I,stdout);
}
printf("\nx =\n");
N_VPrint_Serial(x);
printf("\ny =\n");
N_VPrint_Serial(y);
printf("\nz =\n");
N_VPrint_Serial(z);
} else {
printf("SUCCESS: SUNMatrix module passed all tests \n \n");
}
/* Free vectors and matrices */
N_VDestroy(x);
N_VDestroy(y);
N_VDestroy(z);
SUNMatDestroy(A);
SUNMatDestroy(B);
SUNMatDestroy(C);
SUNMatDestroy(D);
if (square)
SUNMatDestroy(I);
return(fails);
}
