static int LU1(ATL_CINT M, ATL_CINT N, ATL_CINT j, TYPE *A, ATL_CINT lda,
int *ipiv)
/*
* Performs an LU factorization on jth column. N is the full width of
* column panel, A is ptr to beginning of panel.
* RETURNS: 0 on success, non-zero if no non-zero pivot exists
*/
{
#ifdef TCPLX
ATL_CINT lda2 = lda+lda;
TYPE invs[2];
const TYPE none[2] = {ATL_rnone, ATL_rzero};
#else
#define lda2 lda
#define none ATL_rnone
#endif
TYPE *Ac = A + j*lda2; /* active column */
TYPE pivval=Ac[j];
ATL_INT ip;
ipiv[j] = ip = j + cblas_iamax(M-j, Ac+(j SHIFT), 1);
#ifdef TCPLX
pivval = Mabs(Ac[ip+ip]) + Mabs(Ac[ip+ip+1]);
#else
pivval = Ac[ip];
#endif
if (pivval != ATL_rzero)
{
if (ip != j)
cblas_swap(N, A+(j SHIFT), lda, A+(ip SHIFT), lda);
#ifdef TCPLX
if (pivval >= ATL_laSAFMIN)
{
TYPE invs[2];
Mjoin(PATL,cplxinvert)(1, Ac+j+j, 1, invs, 1);
cblas_scal(M-j-1, invs, Ac+j+j+2, 1);
}
else
Mjoin(PATL,cplxdivide)(M-j-1, Ac+j+j, Ac+j+j+2, 1, Ac+j+j+2, 1);
#else
if (Mabs(pivval) >= ATL_laSAFMIN)
cblas_scal(M-j-1, ATL_rone/pivval, Ac+j+1, 1);
else
{
ATL_INT i;
for (i=j+1; i < M; i++)
Ac[j] /= pivval;
}
#endif
return(0);
}
return(1);
}
/*
* Automatically Tuned Linear Algebra Software v3.10.2
* (C) Copyright 1999 R. Clint Whaley
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions, and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* 3. The name of the ATLAS group or the names of its contributers may
* not be used to endorse or promote products derived from this
* software without specific written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
* TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE ATLAS GROUP OR ITS CONTRIBUTORS
* BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
*/
#ifdef TCPLX
static int ATL_potrf2(const int N, TYPE *A, const int lda)
{
int j, k;
static const TYPE one[2] = {ATL_rone, ATL_rzero};
static const TYPE none[2] = {ATL_rnone, ATL_rzero};
const size_t lda2 = lda+lda;
TYPE Ajj, *Ac=A, *An=A+lda2;
for (k=j=0; j != N; j++, k += 2)
{
Ajj = Ac[k] - llt_dot(k, Ac, 1, Ac, 1);
Ac[k+1] = ATL_rzero;
if (Ajj > ATL_rzero)
{
Ac[k] = Ajj = sqrt(Ajj);
if (j != N-1)
{
llt_scal(j, ATL_rnone, Ac+1, 2);
cblas_gemv(CblasColMajor, CblasTrans, j, N-j-1, none,
An, lda, Ac, 1, one, An+k, lda);
llt_scal(j, ATL_rnone, Ac+1, 2);
llt_rscal(N-j-1, ATL_rone/Ajj, An+k, lda);
Ac = An;
An += lda2;
}
}
else
{
Ac[k] = Ajj;
return(j+1);
}
}
return(0);
}
#else /* real version */
static int ATL_potrf2(const int N, TYPE *A, const int lda)
{
int j;
TYPE Ajj, *Ac=A, *An=A+lda;
for (j=0; j != N; j++)
{
Ajj = Ac[j] - cblas_dot(j, Ac, 1, Ac, 1);
if (Ajj > ATL_rzero)
{
Ac[j] = Ajj = sqrt(Ajj);
if (j != N-1)
{
cblas_gemv(CblasColMajor, CblasTrans, j, N-j-1, ATL_rnone,
An, lda, Ac, 1, ATL_rone, An+j, lda);
cblas_scal(N-j-1, ATL_rone/Ajj, An+j, lda);
Ac = An;
An += lda;
}
}
else
{
Ac[j] = Ajj;
return(j+1);
}
}
return(0);
}
static int L2LU(const int M, const int N, TYPE *A, const int lda, int *ipiv)
/*
* Complex Level 2 based left-looking LU
*/
{
TYPE *Ac=A;
TYPE t0, tmp[2];
const TYPE one[2] = {ATL_rone, ATL_rzero}, none[2] = {ATL_rnone, ATL_rzero};
const int MN=Mmin(M,N), MN_1=MN-1, lda2=lda+lda;
int ip, ip2, j, j2, jn, jn2, iret=0;
for (j=0, j2=0, jn=1, jn2=2; j != MN; j=jn++, j2 += 2, jn2 += 2)
{
ipiv[j] = ip = j + cblas_iamax(M-j, Ac+j2, 1);
ip2 = ip + ip;
if (Ac[ip2] != ATL_rzero || Ac[ip2+1] != ATL_rzero)
{
Mjoin(PATL,cplxinvert)(1, Ac+ip2, 1, tmp, 1);
cblas_swap(N, A+j2, lda, A+ip2, lda);
cblas_scal(M-jn, tmp, Ac+jn2, 1);
if (j != MN_1)
{
Ac += lda2;
cblas_trsv(CblasColMajor, CblasLower, CblasNoTrans, CblasUnit, jn,
A, lda, Ac, 1);
cblas_gemv(CblasColMajor, CblasNoTrans, M-jn, jn, none,
A+jn2, lda, Ac, 1, one, Ac+jn2, 1);
}
}
else if (!iret) iret = jn;
}
return(iret);
}
static int L2LU(const int M, const int N, TYPE *A, const int lda, int *ipiv)
/*
* Level 2 based left-looking LU
*/
{
TYPE *Ac=A;
TYPE t0;
const int MN=Mmin(M,N), MN_1=MN-1;
int ip, j, jn, iret=0;
if (N == 2) return(LU2(M, A, lda, ipiv));
for (j=0, jn=1; j != MN; j=jn++)
{
ipiv[j] = ip = j + cblas_iamax(M-j, Ac+j, 1);
t0 = Ac[ip];
if (t0 != ATL_rzero)
{
MySwap(N, A+j, lda, ip-j);
cblas_scal(M-jn, ATL_rone/t0, Ac+jn, 1);
if (j != MN_1)
{
Ac += lda;
cblas_trsv(CblasColMajor, CblasLower, CblasNoTrans, CblasUnit, jn,
A, lda, Ac, 1);
cblas_gemv(CblasColMajor, CblasNoTrans, M-jn, jn, ATL_rnone,
A+jn, lda, Ac, 1, ATL_rone, Ac+jn, 1);
}
}
else if (!iret) iret = jn;
}
return(iret);
}
void ATL_larfg(ATL_CINT N, TYPE *ALPHA, TYPE *X, ATL_CINT INCX, TYPE *TAU)
{
#ifdef TREAL
TYPE ONE=1.0, ZERO=0.0, BETA, BETAp, RSAFMN, SAFMAX, XNORM;
int j, KNT;
if (N < 1)
{
*TAU = ZERO;
return;
}
XNORM = cblas_nrm2(N-1, X, INCX); /* Get the norm2 . */
if (XNORM == ZERO)
{
/*
* H = I
*/
*TAU = ZERO;
} else
{
BETAp = ATL_lapy2((*ALPHA), XNORM);/* Get sqrt(a^2+b^2) */
BETA = BETAp; /* Assume ALPHA < 0 */
if ((*ALPHA) > 0) BETA = 0.-BETAp; /* Change if assumed wrong. */
if (BETAp < ATL_laSAFMIN)
{
/*
* XNORM, BETA may be inaccurate; scale X and recompute them
*/
RSAFMN = ONE / ATL_laSAFMIN; /* Set a maximum */
KNT = 0;
while (BETAp < ATL_laSAFMIN)
{
KNT++;
cblas_scal(N-1, RSAFMN, X, INCX);
BETA *= RSAFMN;
BETAp *= RSAFMN;
*ALPHA *= RSAFMN;
}
/*
* New BETA is at most 1, at least SAFMIN
*/
XNORM = cblas_nrm2(N-1, X, INCX);
BETA = ATL_lapy2((*ALPHA), XNORM); /* Will always be positive */
if ((*ALPHA) > 0) BETA = -BETA; /* -SIGN(BETA, ALPHA) */
*TAU = (BETA-(*ALPHA)) / BETA;
cblas_scal(N-1, ONE/((*ALPHA)-BETA), X, INCX);
/*
* If ALPHA is subnormal, it may lose relative accuracy
*/
*ALPHA = BETA;
for (j=0; j<KNT; j++)
{
(*ALPHA) *= ATL_laSAFMIN;
}
} else /* General case */
{
*TAU = (BETA-(*ALPHA)) / BETA;
cblas_scal(N-1, ONE / ((*ALPHA)-BETA), X, INCX);
*ALPHA = BETA;
}
}
return;
/*
* End of Real Precision ATL_larfg
*/
#else
/*
* Beginning of Complex Precision ATL_larfg
*/
TYPE ONE=1.0, ZERO=0.0, BETA, BETAp, RSAFMN, SAFMAX, XNORM, ALPHI, ALPHR;
TYPE ONEVAL[2] = {ATL_rone, ATL_rzero};
int j, KNT;
if ( N < 0)
{
/*
* H = I
*/
*(TAU) = 0.0;
*(TAU + 1) = 0.0;
return;
}
XNORM = cblas_nrm2(N-1, X, INCX); /* Get the nrm2 */
ALPHR = *( ALPHA) ;
ALPHI = *( ALPHA + 1) ;
if ( (XNORM == ZERO) && (ALPHI == ZERO) )
{
/*
* H = I
*/
*(TAU) = 0.0;
*(TAU + 1) = 0.0;
}
else
{
BETAp = ATL_lapy3(ALPHR, ALPHI, XNORM); /* Get sqrt(a^2 + b^2 + c^2) */
BETA = BETAp; /* Assume ALPHA < 0 */
if ( (*ALPHA) > 0) BETA = 0. - BETAp; /* Change if assumed wrong */
RSAFMN = ONE / ATL_laSAFMIN ;
if ( BETAp < ATL_laSAFMIN )
{
/*
* XNORM, BETA may be inaccurate; scale X and recompute them
*/
KNT = 0;
while ( BETAp < ATL_laSAFMIN )
{
KNT++;
#ifdef DCPLX
cblas_zdscal(N-1, RSAFMN, X, INCX);
#else
cblas_csscal(N-1, RSAFMN, X, INCX);
#endif
BETA *= RSAFMN;
BETAp *= RSAFMN;
ALPHI = ALPHI*RSAFMN;
ALPHR = ALPHR*RSAFMN;
}
/*
* New BETA is at most 1, at least SAFMIN
*/
XNORM = cblas_nrm2(N-1, X, INCX);
*(ALPHA) = ALPHR;
*(ALPHA + 1) = ALPHI;
BETA = ATL_lapy3(ALPHR, ALPHI,
XNORM);/* Will always be positive */
if (ALPHR > 0) BETA = -BETA; /* -SIGN(BETA, ALPHR) */
*(TAU) = ( BETA-ALPHR ) / BETA ;
*(TAU + 1) = (-1.0 * ALPHI) / BETA ;
/* Modify alpha to alpha - beta, which is equal to alphar -beta */
*(ALPHA) = *(ALPHA) - BETA;
/* Perform complex division before scaling the X vector */
ATL_ladiv( ONEVAL, ALPHA, ALPHA); /* ALPHA will have the result*/
cblas_scal(N-1, ALPHA, X, INCX);
/*
* If ALPHA is subnormal, it may lose relative accuracy
*/
*(ALPHA) = BETA; /* Real Part of alpha */
for (j=0; j<KNT; j++)
{
(*ALPHA) *= ATL_laSAFMIN;
}
*(ALPHA + 1) = 0.0; /* Set Imaginary part to Zero */
}
else /* BETA > SAFMIN */
{
*(TAU) = ( BETA-ALPHR ) / BETA ;
*(TAU + 1) = (-1.0 * ALPHI) / BETA ;
/* Modify alpha to alpha - beta, which is equal to alphar -beta */
*(ALPHA) = *(ALPHA) - BETA ;
/* Perform complex division before scaling the X vector */
ATL_ladiv( ONEVAL, ALPHA, ALPHA);
cblas_scal(N-1, ALPHA, X, INCX);
*(ALPHA) = BETA; /* Real Part of alpha */
*(ALPHA + 1) = 0.0; /* Set Imaginary part to Zero */
}
}
return;
#endif
} /* END ATL_larfg */
/*
* Automatically Tuned Linear Algebra Software v3.11.28
* (C) Copyright 1999 R. Clint Whaley
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions, and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* 3. The name of the ATLAS group or the names of its contributers may
* not be used to endorse or promote products derived from this
* software without specific written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
* TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE ATLAS GROUP OR ITS CONTRIBUTORS
* BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
*/
static int ATL_potrf2(const int N, TYPE *A, const int lda)
{
#ifdef TREAL
TYPE Ajj, *Ac=A;
const int N_1 = N-1;
int j;
for (j=0; j != N_1; j++, Ac += lda)
{
Ajj = Ac[j] - cblas_dot(j, A+j, lda, A+j, lda);
if (Ajj > ATL_rzero)
{
Ac[j] = Ajj = sqrt(Ajj);
cblas_gemv(CblasColMajor, CblasNoTrans, N-j-1, j, ATL_rnone,
A+j+1, lda, A+j, lda, ATL_rone, Ac+j+1, 1);
cblas_scal(N-j-1, ATL_rone/Ajj, Ac+j+1, 1);
}
else
{
Ac[j] = Ajj;
return(j+1);
}
}
Ajj = Ac[j] - cblas_dot(j, A+j, lda, A+j, lda);
if (Ajj > ATL_rzero) Ac[j] = Ajj = sqrt(Ajj);
else
{
Ac[j] = Ajj;
return(N);
}
#else
TYPE Ajj, *Ac=A;
TYPE one[2] = {ATL_rone, ATL_rzero};
TYPE none[2] = {ATL_rnone, ATL_rzero};
const int N_1 = N-1, lda2 = lda<<1;
int j, j2;
for (j2=j=0; j != N_1; j++, j2 += 2, Ac += lda2)
{
Ajj = Ac[j2];
cblas_dotc_sub(j, A+j2, lda, A+j2, lda, Ac+j2);
Ajj -= Ac[j2];
if (Ajj > ATL_rzero)
{
Ac[j2] = Ajj = sqrt(Ajj);
llt_scal(j, ATL_rnone, A+j2+1, lda2);
cblas_gemv(CblasColMajor, CblasNoTrans, N-j-1, j, none,
A+j2+2, lda, A+j2, lda, one, Ac+j2+2, 1);
llt_scal(j, ATL_rnone, A+j2+1, lda2);
llt_scal((N-j-1)<<1, ATL_rone/Ajj, Ac+j2+2, 1);
}
else
{
Ac[j2] = Ajj;
return(j+1);
}
}
Ajj = Ac[j2];
cblas_dotc_sub(j, A+j2, lda, A+j2, lda, Ac+j2);
Ajj -= Ac[j2];
if (Ajj > ATL_rzero) Ac[j2] = sqrt(Ajj);
else
{
Ac[j2] = Ajj;
return(N);
}
#endif
return(0);
}
static int LU2(const int M, TYPE *A, const int lda, int *ipiv)
/*
* factors 2 cols of LU, applies all updated to 2nd call during ininitial
* iamax to save time
*/
{
int ip, iret=0;
TYPE *A1 = A + lda;
register TYPE t0, t1, scal0, scal1, amax=ATL_rzero;
int i, imax=(-1);
*ipiv = ip = cblas_iamax(M, A, 1);
t0 = A[ip];
if (t0 != ATL_rzero)
{
if (Mabs(t0) >= ATL_laSAFMIN)
{
t1 = A1[ip];
A[ip] = *A; A1[ip] = *A1;
*A = t0; *A1 = t1;
scal0 = ATL_rone / t0; scal1 = -t1;
for (i=1; i != M; i++)
{
t0 = A[i]; t1 = A1[i];
t0 *= scal0;
t1 += t0 * scal1;
A[i] = t0; A1[i] = t1;
if (t1 < ATL_rzero) t1 = -t1;
if (t1 > amax) { amax = t1; imax = i; }
}
}
else /* can't safely invert pivot, so must actually divide */
{
t1 = A1[ip];
A[ip] = *A; A1[ip] = *A1;
*A = t0; *A1 = t1;
scal0 = t0; scal1 = -t1;
for (i=1; i != M; i++)
{
t0 = A[i]; t1 = A1[i];
t0 /= scal0;
t1 += t0 * scal1;
A[i] = t0; A1[i] = t1;
if (t1 < ATL_rzero) t1 = -t1;
if (t1 > amax) { amax = t1; imax = i; }
}
}
if (amax != ATL_rzero)
{
ipiv[1] = imax;
t0 = A[imax]; t1 = A1[imax];
A[imax] = A[1]; A1[imax] = A1[1];
A[1] = t0; A1[1] = t1;
if (Mabs(t1) >= ATL_laSAFMIN)
cblas_scal(M-2, ATL_rone/t1, A1+2, 1);
else
for (i=2; i < M; i++)
A1[i] /= t1;
}
else
{
if (imax != -1) ipiv[1] = imax;
else ipiv[1] = 1;
iret = 2;
}
}
else
{
imax = 1 + cblas_iamax(M-1, A1+1, 1);
amax = A1[imax];
iret=1;
if (amax != ATL_rzero)
{
ipiv[1] = imax;
t0 = A[imax]; t1 = A1[imax];
A[imax] = A[1]; A1[imax] = A1[1];
A[1] = t0; A1[1] = t1;
if (Mabs(t1) >= ATL_laSAFMIN)
cblas_scal(M-2, ATL_rone/t1, A1+2, 1);
else
for (i=2; i < M; i++)
A1[i] /= t1;
}
else
{
if (imax != -1) ipiv[1] = imax;
else ipiv[1] = 1;
}
}
return(iret);
}
template <typename IndexType, typename ValueType> void proj_to_lp_cpu(csr_matrix<IndexType, ValueType> &inputSet,
ValueType * minNormVector, IndexType inSetDim, IndexType vectorDim, ValueType tollerance) {
ValueType lpShift = (ValueType) 10; //Установим начальное смещение, оно должно быть очень большим
//переместим наш политоп в соответствии с этим смещением, это будет означать
//что мы переместили начало координат в эту точку, что соответствует тому что мы отнимим
//от вектора b из уравнения Ax <=b следующую величину b + t * A * c (с = [1])
ValueType* vshift = (ValueType *) malloc(inSetDim * sizeof (ValueType));
ValueType* t_C = (ValueType *) malloc((vectorDim - 1) * sizeof (ValueType));
for (IndexType i = 0; i < vectorDim - 1; i++) {
t_C[i] = -lpShift;
}
IndexType maxApprIters = 10;
ValueType *x_s = new_host_array<ValueType > (vectorDim);
ValueType *delta_x = new_host_array<ValueType > (vectorDim);
ValueType* v_t = new_host_array<ValueType > (vectorDim); //- 1); //(ValueType *) malloc((vectorDim -1) * sizeof (ValueType));
IndexType *kvec = new_host_array<IndexType>(2 * inputSet.num_cols + 1 );
IndexType *kvec_old = new_host_array<IndexType>(2 * inputSet.num_cols + 1 );
IndexType *basisVecInx = new_host_array<IndexType>(2 * inputSet.num_cols + 1);
IndexType baselen = 0;
for (IndexType i = 0; i < 2 * inputSet.num_cols + 1; i++) {
kvec[i] = 0;
kvec_old[i] = 0;
}
//Начальный x_s это ноль
cblas_scal(vectorDim, 0.0, x_s, 1);
for (IndexType apprIt = 0; apprIt < maxApprIters; apprIt++) {
//Получаем новое B
cblas_copy(vectorDim - 1, t_C, 1, v_t, 1);
cblas_axpy(vectorDim - 1, -1.0, x_s, 1, v_t, 1);
//std::cout << "Vector V_t\n";
//printMatrixCPU(vectorDim - 1, 1, v_t);
cblas_copy(vectorDim, x_s, 1, delta_x, 1);
inputSet.num_rows--;
spmv_csr_t_serial_host(inputSet, v_t, vshift);
inputSet.num_rows++;
//printMatrixCPU(inSetDim, 1, vshift);
incValsInLstMtxRowVec(inputSet, inputSet.num_rows - 1, vshift);
std::cout << "Input set on iteration\n";
//print_csr_matrix(inputSet);
//getProjectionOnConus(inputSet, minNormVector, inSetDim, vectorDim, tollerance);
csr_matrix<IndexType, ValueType> inSetCopy = getCsrMtxCopy(inputSet);
if(apprIt > 0){
memcpy(kvec_old, kvec, (2 * inputSet.num_cols + 1) * sizeof (IndexType));
}
//print_csr_matrix(inSetCopy);
//projOnFixedSimplex(inSetCopy, minNormVector, kvec, basisVecInx, baselen, tollerance );
getMinNormElemOutRepr(in_a_csc, minNormVector, 0.0001, kvec, basisVecInx, baselen, numberOfEqConstr);
delete_host_matrix(inSetCopy);
IndexType kvec_razn = 0;
if(apprIt > 0){
for (IndexType i = 0; i < 2 * inputSet.num_cols + 1; i++) {
if(kvec[i] == kvec_old[i] && kvec[i] == 1){
kvec_razn++;
}
}
}
std::cout << "KVEC RAZN is = " << kvec_razn <<"\n";
std::cout << "baselen is = " << baselen <<"\n";
cblas_axpy(vectorDim, -1.0, v_t, 1, minNormVector, 1);
//std::cout << "Min norm vector on iteration\n";
//printMatrixCPU(vectorDim, 1, minNormVector);
decValsInLstMtxRowVec(inputSet, inputSet.num_rows - 1, vshift);
cblas_copy(vectorDim, minNormVector, 1, x_s, 1);
cblas_axpy(vectorDim, -1.0, x_s, 1, delta_x, 1);
ValueType z_summ = 0.0;
for (IndexType i = 0; i < vectorDim - 1; i++) {
z_summ += minNormVector[i];
}
std::cout << "Summ of elements " << z_summ << " on "<< apprIt <<" iteration\n";
ValueType dist = cblas_dot(vectorDim - 1, delta_x, 1, delta_x, 1);
if (dist < tollerance * tollerance) {
std::cout << "iterations count :" << apprIt << "\n";
break;
}
}
//cblas_axpy(vectorDim, -1.0, v_t, 1, minNormVector, 1);
ValueType dist = cblas_dot(vectorDim - 1, minNormVector, 1, minNormVector, 1);
std::cout << "Min Vector Lengh = " << sqrt(dist) << "\n";
ValueType z_summ = 0.0;
IndexType nonzer_summ = 0;
for (IndexType i = 0; i < vectorDim - 1; i++) {
z_summ += minNormVector[i];
if (minNormVector[i] != 0.0) {
nonzer_summ++;
}
}
std::cout << "Summ of elements " << z_summ << " \n";
std::cout << "Count of nonzerros " << nonzer_summ << " \n";
//printMatrixToFileForOctave(vectorDim, 1, minNormVector);
ValueType* b_contr = new_host_array<ValueType > (inSetDim);
inputSet.num_rows--;
spmv_csr_t_serial_host(inputSet, minNormVector, b_contr);
inputSet.num_rows++;
//printMatrixCPU(inSetDim, 1, b_contr);
IndexType b_begin = inputSet.Ap[vectorDim - 1];
IndexType b_end = inputSet.Ap[vectorDim];
IndexType inconsCount = 0;
for (IndexType i = b_begin; i < b_end; i++) {
IndexType j = inputSet.Aj[i];
if (b_contr[j] > inputSet.Ax[i] + tollerance * tollerance) {
//std::cout << "b_contr " << b_contr[j] << " Ax " << inputSet.Ax[i] << " \n";
ValueType razn = b_contr[j] - inputSet.Ax[i];
//printf("bcontr[%i] %e Ax %e razn %e\n", j ,b_contr[j], inputSet.Ax[i], razn);
inconsCount++;
}
}
std::cout << "Inconsistent X count: " << inconsCount << " \n";
}
