void Matrix<real>::RemoveRows(int rowStart, int rowEnd)
{
InPlaceTransposeMatrix(m, n, data);
int mBuf = m;
m = n;
n = mBuf;
RemoveColumns(rowStart, rowEnd);
InPlaceTransposeMatrix(m, n, data);
mBuf = m;
m = n;
n = mBuf;
}
Matrix<real> & Matrix<real>::InPlaceTranspose()
{
InPlaceTransposeMatrix(m, n, data);
// swap m,n
int swap = m;
m = n;
n = swap;
return (*this);
}
void Matrix<real>::AppendRows(const Matrix<real> & rows)
{
if (rows.Getn() != n)
{
printf("Error: mismatch in number of columns in AppendRows.\n");
throw 42;
}
InPlaceTransposeMatrix(m, n, data);
int mBuf = m;
m = n;
n = mBuf;
Matrix<real> rowsT = Transpose(rows);
AppendColumns(rowsT);
InPlaceTransposeMatrix(m, n, data);
mBuf = m;
m = n;
n = mBuf;
}
int MatrixPCA(ThresholdingSpecification * thresholdingSpecification,
int m, int n, double * A, int * r, double * weights)
{
if (!A)
{
printf("Error: input matrix is NULL.\n");
return -1;
}
if (weights != NULL)
{
// transform row i of A by sqrt(weights[i])
for(int row=0; row<m; row++)
{
double rowWeight = sqrt(weights[row]);
for(int column=0; column<n; column++)
A[ELT(m, row, column)] *= rowWeight;
}
}
bool transpose = false;
if (m > n)
{
transpose = true;
InPlaceTransposeMatrix(m,n,A);
// swap m,n
int bufferi = m;
m = n;
n = bufferi;
}
// do SVD
char jobu = 'O';//overwrites A with U (left singular vectors)
//char jobu = 'N';
char jobvt = 'S';//all rows returned in VT
//char jobvt = 'N';
int ldA = m;
int ldU = m;
int lwork = 64*MAX(3*MIN( m, n)+MAX(m,n), 5*MIN(m,n)-4);
double * work = (double*) malloc (sizeof(double) * lwork);
if (!work)
{
printf("Error: failed to allocate workspace.\n");
return -2;
}
//printf("Workspace size is: %G Mb .\n",1.0 * lwork * sizeof(int) / 1024 / 1024);
// allocate array for singular vectors
double * S = (double *) malloc (sizeof(double) * MIN(m,n));
if (!S)
{
printf("Error: failed to allocate singular vectors.\n");
return -2;
}
double * dummyU = NULL;
// allocate array for VT
int ldVT = MIN(m,n);
double * VT = (double *) malloc (sizeof(double) * ldVT * n);
if (!VT)
{
printf("Error: failed to allocate VT.\n");
return -2;
}
#ifdef __APPLE__
#define DGESVD dgesvd_
#define INTEGER __CLPK_integer
#else
#define DGESVD dgesvd
#define INTEGER int
#endif
INTEGER M = m;
INTEGER N = n;
INTEGER LDA = ldA;
INTEGER LDU = ldU;
INTEGER LDVT = ldVT;
INTEGER LWORK = lwork;
INTEGER INFO;
//printf("Calling LAPACK dgesvd routine...\n");fflush(NULL);
//SUBROUTINE SGESVD( JOBU, JOBVT, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, LWORK, INFO )
DGESVD (&jobu, &jobvt, &M, &N, A, &LDA,
S, dummyU, &LDU, VT,
&LDVT, work, &LWORK, &INFO);
if (INFO != 0)
{
int code = INFO;
printf("Error: SVD solver returned non-zero exit code: %d.\n", code);
free(VT);
free(S);
free(work);
return code;
}
free(work);
if (transpose)
{
InPlaceTransposeMatrix(m,n,VT);
memcpy(A, VT, sizeof(double) * m * n);
// swap m and n
int bufferii = m;
m = n;
n = bufferii;
}
free(VT);
if (weights != NULL)
{
// transform row i of A by sqrt(weights[i])^{-1}
for(int row=0; row<m; row++)
{
double rowWeight = 1.0 / sqrt(weights[row]);
for(int column=0; column<n; column++)
A[ELT(m, row, column)] *= rowWeight;
}
}
//double totalEnergy = 0;
//printf ("Singular values:\n");fflush(NULL);
//for (int i=0; i< MIN(m,n); i++)
//printf("%f ",S[i]);
//printf ("\n");
// discard unneccesary modes
//printf("Discarding unnecessary components...\n");fflush(NULL);
if (thresholdingSpecification->tresholdingType == ThresholdingSpecification::epsilonBased)
DoTresholding_Epsilon(S,MIN(m,n),r,thresholdingSpecification->epsilon);
else
DoTresholding_NumberOfModes(S,MIN(m,n),r,thresholdingSpecification->rDesired);
// now, variable r has been set to the number of retained modes
free(S);
return 0;
}
void MatrixSVD(int m, int n, real * mtx, real * U, real * Sigma, real * VT)
{
real * A = (real*) malloc (sizeof(real) * m * n);
memcpy(A, mtx, sizeof(real) * m * n);
// must deal with transpose since Intel MKL sometimes crashes on thin matrices
bool transpose = (m > n);
if (transpose)
{
InPlaceTransposeMatrix(m, n, A);
// swap arguments
int buffer = m;
m = n;
n = buffer;
real * bufferr = U;
U = VT;
VT = bufferr;
}
// now, we always have m <= n
char jobu = 'S'; //left singular vectors returned in U
char jobvt = 'S'; //right singular vectors returned in VT
INTEGER NB = 32; // optimal block size; could also call ilaenv
int lwork = NB*MAX(3*MIN( m, n)+MAX(m,n), 5*MIN(m,n)-4);
real * work = (real*) malloc (sizeof(real) * lwork);
if (!work)
{
printf("Error: failed to allocate workspace.\n");
throw 1;
}
//printf("Workspace size is: %G Mb .\n",1.0 * lwork * sizeof(int) / 1024 / 1024);
INTEGER M = m;
INTEGER N = n;
INTEGER LDA = m;
INTEGER LDU = m;
INTEGER LDVT = MIN(m,n);
INTEGER LWORK = lwork;
INTEGER INFO;
//printf("Calling LAPACK dgesvd routine...\n");fflush(NULL);
//SUBROUTINE SGESVD( JOBU, JOBVT, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, LWORK, INFO )
_xgesvd<sizeof(real)==sizeof(float)>::f
(&jobu, &jobvt, &M, &N, A, &LDA,
Sigma, U, &LDU, VT,
&LDVT, work, &LWORK, &INFO);
if (INFO != 0)
{
int code = INFO;
printf("Error: SVD solver returned non-zero exit code: %d.\n", code);
free(work);
free(A);
throw 2;
}
free(work);
free(A);
if (transpose)
{
InPlaceTransposeMatrix(m, MIN(m,n), U);
InPlaceTransposeMatrix(MIN(m,n), n, VT);
}
}
real * PseudoInverseMatrix(int m, int n, real * mtx, real singularValueThreshold, int * rank_, real * output)
{
real * A = (real*) malloc (sizeof(real) * m * n);
memcpy(A, mtx, sizeof(real) * m * n);
bool transpose = (m > n);
if (transpose)
{
// swap m,n
InPlaceTransposeMatrix(m,n, A);
int buffer = m;
m = n;
n = buffer;
}
// now, we always have m <= n
char jobu = 'O';//overwrites A with U (left singular vectors)
char jobvt = 'S';//all rows returned in VT
int ldA = m;
int ldU = m;
INTEGER NB = 32; // optimal block size; could also call ilaenv
int lwork = NB*MAX(3*MIN( m, n)+MAX(m,n), 5*MIN(m,n)-4);
real * work = (real*) malloc (sizeof(real) * lwork);
if (!work)
{
printf("Error: failed to allocate workspace.\n");
throw 1;
}
//printf("Workspace size is: %G Mb .\n",1.0 * lwork * sizeof(int) / 1024 / 1024);
// allocate array for singular vectors
real * S = (real *) malloc (sizeof(real) * MIN(m,n));
if (!S)
{
printf("Error: failed to allocate singular vectors.\n");
free(work);
throw 2;
}
// allocate array for VT
int ldVT = MIN(m,n);
real * VT = (real *) malloc (sizeof(real) * ldVT * n);
if (!VT)
{
printf("Error: failed to allocate VT.\n");
free(S);
free(work);
throw 3;
}
INTEGER M = m;
INTEGER N = n;
INTEGER LDA = ldA;
INTEGER LDU = ldU;
INTEGER LDVT = ldVT;
INTEGER LWORK = lwork;
INTEGER INFO;
//printf("Calling LAPACK dgesvd routine...\n");fflush(NULL);
//SUBROUTINE SGESVD( JOBU, JOBVT, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, LWORK, INFO )
_xgesvd<sizeof(real)==sizeof(float)>::f
(&jobu, &jobvt, &M, &N, A, &LDA,
S, NULL, &LDU, VT,
&LDVT, work, &LWORK, &INFO);
if (INFO != 0)
{
int code = INFO;
printf("Error: SVD solver returned non-zero exit code: %d.\n", code);
free(VT);
free(S);
free(work);
throw 4;
}
free(work);
//printf ("Singular values:\n");fflush(NULL);
//for (int i=0; i< MIN(m,n); i++)
// printf("%f ",S[i]);
//printf ("\n");
// discard small singular values
int rank = MIN(m,n);
for(int i=0; i< MIN(m,n); i++)
{
if (S[i] / S[0] < singularValueThreshold)
{
rank = i;
break;
}
}
for(int i=0; i< rank; i++)
S[i] = ((real)1.0) / S[i];
for(int i=rank; i< MIN(m,n); i++)
S[i] = 0.0;
real * U = A;
memset(&U[ELT(m,0,rank)], 0, sizeof(real) * m * (n-rank));
InPlaceTransposeMatrix(m, m, U);
real * UT = U;
// UT is now m x m
InPlaceTransposeMatrix(m,n,VT);
real * V = VT;
// V is now n x m
// multiply A^{\dagger} = V * Sigma^{-1} * U^T
for(int j=0; j<m; j++) // over all columns
for(int i=0; i<n; i++) // over all rows
V[ELT(n, i, j)] *= S[j];
real * target = output;
if (target == NULL)
target = (real*) malloc (sizeof(real) * n * m);
// V * UT
// (n x m) * (m x m)
// output is n x m
MultiplyMatrices(n, m, m, V, UT, target);
if (transpose)
InPlaceTransposeMatrix(n, m, target);
free(A);
free(S);
free(VT);
if (rank_ != NULL)
*rank_ = rank;
return target;
}
