/
This commit is contained in:
jiri
parent
ea56e7380d
commit
02a868e8aa
185
nonclass.cc
185
nonclass.cc
@ -103,40 +103,43 @@ void lawritemat(FILE *file,const T *a,int r,int c,const char *form0,
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//////////////////////
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// A will be overwritten, B will contain the solutions, A is nxn, B is rhs x n
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static void linear_solve_do(NRMat<double> &A, double *B, const int nrhs, const int ldb, double *det)
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static void linear_solve_do(NRMat<double> &A, double *B, const int nrhs, const int ldb, double *det, int n)
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{
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int r, *ipiv;
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if (A.nrows() != A.ncols()) laerror("linear_solve() call for non-square matrix");
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if (n==A.nrows() && A.nrows() != A.ncols()) laerror("linear_solve() call for non-square matrix");
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A.copyonwrite();
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ipiv = new int[A.nrows()];
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r = clapack_dgesv(CblasRowMajor, A.nrows(), nrhs, A[0], A.ncols(), ipiv, B , ldb);
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r = clapack_dgesv(CblasRowMajor, n, nrhs, A[0], A.ncols(), ipiv, B , ldb);
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if (r < 0) {
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delete[] ipiv;
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laerror("illegal argument in lapack_gesv");
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}
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if (det && r>=0) {
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*det = A[0][0];
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for (int i=1; i<A.nrows(); ++i) *det *= A[i][i];
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for (int i=1; i<n; ++i) *det *= A[i][i];
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//change sign of det by parity of ipiv permutation
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for (int i=0; i<A.nrows(); ++i) *det = -(*det);
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for (int i=0; i<n; ++i) *det = -(*det);
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}
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delete [] ipiv;
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if (r>0 && B) laerror("singular matrix in lapack_gesv");
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}
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void linear_solve(NRMat<double> &A, NRMat<double> *B, double *det)
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void linear_solve(NRMat<double> &A, NRMat<double> *B, double *det, int n)
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{
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if (B && A.nrows() != B->ncols()) laerror("incompatible matrices in linear_solve()");
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if(n<=0) n=A.nrows(); //default - whole matrix
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if (n==A.nrows() && B && A.nrows() != B->ncols() || B && n>B->ncols() ||n>A.nrows()) laerror("incompatible matrices in linear_solve()");
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if(B) B->copyonwrite();
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linear_solve_do(A,B?(*B)[0]:NULL,B?B->nrows() : 0, B?B->ncols():A.nrows(), det);
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linear_solve_do(A,B?(double *)B:NULL,B?B->nrows() : 0, B?B->ncols():A.nrows(), det,n);
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}
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void linear_solve(NRMat<double> &A, NRVec<double> &B, double *det)
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void linear_solve(NRMat<double> &A, NRVec<double> &B, double *det, int n)
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{
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if(A.nrows() != B.size()) laerror("incompatible matrices in linear_solve()");
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if(n<=0) n=A.nrows(); //default - whole matrix
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if(n==A.nrows() && A.nrows() != B.size() || n>B.size()||n>A.nrows() ) laerror("incompatible matrices in linear_solve()");
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B.copyonwrite();
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linear_solve_do(A,&B[0],1,A.nrows(),det);
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linear_solve_do(A,(double *)B,1,A.nrows(),det,n);
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}
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@ -146,14 +149,13 @@ linear_solve_do(A,&B[0],1,A.nrows(),det);
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extern "C" void FORNAME(dspsv)(const char *UPLO, const int *N, const int *NRHS,
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double *AP, int *IPIV, double *B, const int *LDB, int *INFO);
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static void linear_solve_do(NRSMat<double> &a, double *b, const int nrhs, const int ldb, double *det)
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static void linear_solve_do(NRSMat<double> &a, double *b, const int nrhs, const int ldb, double *det, int n)
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{
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int r, *ipiv;
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if (det) cerr << "@@@ sign of the determinant not implemented correctly yet\n";
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a.copyonwrite();
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ipiv = new int[a.nrows()];
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ipiv = new int[n];
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char U = 'U';
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int n = a.nrows();
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FORNAME(dspsv)(&U, &n, &nrhs, a, ipiv, b, &ldb,&r);
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if (r < 0) {
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delete[] ipiv;
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@ -161,8 +163,8 @@ static void linear_solve_do(NRSMat<double> &a, double *b, const int nrhs, const
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}
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if (det && r >= 0) {
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*det = a(0,0);
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for (int i=1; i<a.nrows(); i++) *det *= a(i,i);
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for (int i=0; i<a.nrows(); i++)
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for (int i=1; i<n; i++) *det *= a(i,i);
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for (int i=0; i<n; i++)
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if (ipiv[i] != i) *det = -(*det);
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}
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delete[] ipiv;
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@ -170,29 +172,36 @@ static void linear_solve_do(NRSMat<double> &a, double *b, const int nrhs, const
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}
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void linear_solve(NRSMat<double> &a, NRMat<double> *B, double *det)
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void linear_solve(NRSMat<double> &a, NRMat<double> *B, double *det, int n)
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{
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if (B && a.nrows() != B->ncols())
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if(n<=0) n=a.nrows();
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if (n==a.nrows() && B && a.nrows() != B->ncols() || B && n>B->ncols() || n>a.nrows())
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laerror("incompatible matrices in symmetric linear_solve()");
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if (B) B->copyonwrite();
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linear_solve_do(a,B?(*B)[0]:NULL,B?B->nrows() : 0, B?B->ncols():a.nrows(),det);
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linear_solve_do(a,B?(*B)[0]:NULL,B?B->nrows() : 0, B?B->ncols():a.nrows(),det,n);
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}
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void linear_solve(NRSMat<double> &a, NRVec<double> &B, double *det)
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void linear_solve(NRSMat<double> &a, NRVec<double> &B, double *det, int n)
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{
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if (a.nrows() != B.size())
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if(n<=0) n=a.nrows();
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if (n==a.nrows() && a.nrows()!= B.size() || n>B.size() || n>a.nrows())
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laerror("incompatible matrices in symmetric linear_solve()");
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B.copyonwrite();
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linear_solve_do(a,&B[0],1,a.nrows(),det);
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linear_solve_do(a,&B[0],1,a.nrows(),det,n);
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}
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extern "C" void FORNAME(dsyev)(const char *JOBZ, const char *UPLO, const int *N,
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double *A, const int *LDA, double *W, double *WORK, const int *LWORK, int *INFO);
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extern "C" void FORNAME(dsygv)(const int *ITYPE, const char *JOBZ, const char *UPLO, const int *N,
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double *A, const int *LDA, double *B, const int *LDB, double *W, double *WORK, const int *LWORK, int *INFO);
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// a will contain eigenvectors (columns if corder==1), w eigenvalues
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void diagonalize(NRMat<double> &a, NRVec<double> &w, const bool eivec,
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const bool corder, int n)
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const bool corder, int n, NRMat<double> *b, const int itype)
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{
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int m = a.nrows();
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if (m != a.ncols()) laerror("diagonalize() call with non-square matrix");
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@ -200,9 +209,11 @@ void diagonalize(NRMat<double> &a, NRVec<double> &w, const bool eivec,
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laerror("inconsistent dimension of eigenvalue vector in diagonalize()");
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if(n==0) n=m;
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if(n<0||n>m) laerror("actual dimension out of range in diagonalize");
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if(b) if(n>b->nrows() || n> b->ncols()) laerror("wrong B matrix dimension in diagonalize");
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a.copyonwrite();
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w.copyonwrite();
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if(b) b->copyonwrite();
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int r = 0;
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char U ='U';
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@ -210,17 +221,20 @@ void diagonalize(NRMat<double> &a, NRVec<double> &w, const bool eivec,
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if (!eivec) vectors = 'N';
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int LWORK = -1;
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double WORKX;
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int ldb=0; if(b) ldb=b->ncols();
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// First call is to determine size of workspace
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FORNAME(dsyev)(&vectors, &U, &n, a, &m, w, (double *)&WORKX, &LWORK, &r );
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if(b) FORNAME(dsygv)(&itype,&vectors, &U, &n, a, &m, *b, &ldb, w, (double *)&WORKX, &LWORK, &r );
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else FORNAME(dsyev)(&vectors, &U, &n, a, &m, w, (double *)&WORKX, &LWORK, &r );
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LWORK = (int)WORKX;
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double *WORK = new double[LWORK];
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FORNAME(dsyev)(&vectors, &U, &n, a, &m, w, WORK, &LWORK, &r );
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if(b) FORNAME(dsygv)(&itype,&vectors, &U, &n, a, &m, *b,&ldb, w, WORK, &LWORK, &r );
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else FORNAME(dsyev)(&vectors, &U, &n, a, &m, w, WORK, &LWORK, &r );
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delete[] WORK;
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if (vectors == 'V' && corder) a.transposeme();
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if (vectors == 'V' && corder) a.transposeme(n);
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if (r < 0) laerror("illegal argument in syev() of diagonalize()");
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if (r > 0) laerror("convergence problem in syev() of diagonalize()");
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if (r < 0) laerror("illegal argument in sygv/syev in diagonalize()");
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if (r > 0) laerror("convergence problem in sygv/syev in diagonalize()");
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}
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@ -228,29 +242,39 @@ void diagonalize(NRMat<double> &a, NRVec<double> &w, const bool eivec,
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extern "C" void FORNAME(dspev)(const char *JOBZ, const char *UPLO, const int *N,
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double *AP, double *W, double *Z, const int *LDZ, double *WORK, int *INFO);
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extern "C" void FORNAME(dspgv)(const int *ITYPE, const char *JOBZ, const char *UPLO, const int *N,
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double *AP, double *BP, double *W, double *Z, const int *LDZ, double *WORK, int *INFO);
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// v will contain eigenvectors, w eigenvalues
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void diagonalize(NRSMat<double> &a, NRVec<double> &w, NRMat<double> *v,
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const bool corder)
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const bool corder, int n, NRSMat<double> *b, const int itype)
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{
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int n = a.nrows();
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if (v) if (v->nrows() != v ->ncols() || n != v->nrows())
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if(n<=0) n = a.nrows();
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if (v) if (v->nrows() != v ->ncols() || n > v->nrows() || n > a.nrows())
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laerror("diagonalize() call with inconsistent dimensions");
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if (n != w.size()) laerror("inconsistent dimension of eigenvalue vector");
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if (n==a.nrows() && n != w.size() || n>w.size()) laerror("inconsistent dimension of eigenvalue vector");
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if(b) if(n>b->nrows() || n> b->ncols()) laerror("wrong B matrix dimension in diagonalize");
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a.copyonwrite();
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w.copyonwrite();
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if(v) v->copyonwrite();
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if(b) b->copyonwrite();
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int r = 0;
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char U = 'U';
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char job = v ? 'v' : 'n';
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double *WORK = new double[3*n];
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FORNAME(dspev)(&job, &U, &n, a, w, v?(*v)[0]:(double *)0, &n, WORK, &r );
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int ldv=v?v->ncols():n;
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if(b) FORNAME(dspgv)(&itype,&job, &U, &n, a, *b, w, v?(*v)[0]:(double *)0, &ldv, WORK, &r );
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else FORNAME(dspev)(&job, &U, &n, a, w, v?(*v)[0]:(double *)0, &ldv, WORK, &r );
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delete[] WORK;
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if (v && corder) v->transposeme();
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if (v && corder) v->transposeme(n);
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if (r < 0) laerror("illegal argument in spev() of diagonalize()");
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if (r > 0) laerror("convergence problem in spev() of diagonalize()");
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if (r < 0) laerror("illegal argument in spgv/spev in diagonalize()");
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if (r > 0) laerror("convergence problem in spgv/spev in diagonalize()");
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}
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@ -259,15 +283,18 @@ extern "C" void FORNAME(dgesvd)(const char *JOBU, const char *JOBVT, const int
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double *VT, const int *LDVT, double *WORK, const int *LWORK, int *INFO );
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void singular_decomposition(NRMat<double> &a, NRMat<double> *u, NRVec<double> &s,
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NRMat<double> *v, const bool corder)
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NRMat<double> *v, const bool corder, int m, int n)
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{
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int m = a.nrows();
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int n = a.ncols();
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if (u) if (m != u->nrows() || m!= u->ncols())
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int m0 = a.nrows();
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int n0 = a.ncols();
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if(m<=0) m=m0;
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if(n<=0) n=n0;
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if(n>n0 || m>m0) laerror("bad dimension in singular_decomposition");
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if (u) if (m > u->nrows() || m> u->ncols())
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laerror("inconsistent dimension of U Mat in singular_decomposition()");
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if (s.size() < m && s.size() < n)
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laerror("inconsistent dimension of S Vec in singular_decomposition()");
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if (v) if (n != v->nrows() || n != v->ncols())
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if (v) if (n > v->nrows() || n > v->ncols())
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laerror("inconsistent dimension of V Mat in singular_decomposition()");
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a.copyonwrite();
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@ -282,14 +309,14 @@ void singular_decomposition(NRMat<double> &a, NRMat<double> *u, NRVec<double> &s
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double work0;
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int lwork = -1;
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int r;
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FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &n, s, v?(*v)[0]:0, &n,
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u?(*u)[0]:0, &m, &work0, &lwork, &r);
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FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &n0, s, v?(*v)[0]:0, &n0,
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u?(*u)[0]:0, &m0, &work0, &lwork, &r);
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lwork = (int) work0;
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double *work = new double[lwork];
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FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &n, s, v?(*v)[0]:0, &n,
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u?(*u)[0]:0, &m, &work0, &lwork, &r);
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FORNAME(dgesvd)(&jobv, &jobu, &n, &m, a, &n0, s, v?(*v)[0]:0, &n0,
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u?(*u)[0]:0, &m0, &work0, &lwork, &r);
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delete[] work;
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if (v && corder) v->transposeme();
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if (v && corder) v->transposeme(n);
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if (r < 0) laerror("illegal argument in gesvd() of singular_decomposition()");
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if (r > 0) laerror("convergence problem in gesvd() of ingular_decomposition()");
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@ -300,58 +327,81 @@ extern "C" void FORNAME(dgeev)(const char *JOBVL, const char *JOBVR, const int *
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double *A, const int *LDA, double *WR, double *WI, double *VL, const int *LDVL,
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double *VR, const int *LDVR, double *WORK, const int *LWORK, int *INFO );
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extern "C" void FORNAME(dggev)(const char *JOBVL, const char *JOBVR, const int *N,
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double *A, const int *LDA, double *B, const int *LDB, double *WR, double *WI, double *WBETA,
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double *VL, const int *LDVL, double *VR, const int *LDVR,
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double *WORK, const int *LWORK, int *INFO );
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void gdiagonalize(NRMat<double> &a, NRVec<double> &wr, NRVec<double> &wi,
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NRMat<double> *vl, NRMat<double> *vr, const bool corder)
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NRMat<double> *vl, NRMat<double> *vr, const bool corder, int n,
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NRMat<double> *b, NRVec<double> *beta)
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{
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int n = a.nrows();
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if (n != a.ncols()) laerror("gdiagonalize() call for a non-square matrix");
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if (n != wr.size())
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if(n<=0) n = a.nrows();
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if (n > a.ncols() || n>a.nrows() ) laerror("gdiagonalize() call for a non-square matrix");
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if (n > wr.size())
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laerror("inconsistent dimension of eigen vector in gdiagonalize()");
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if (vl) if (n != vl->nrows() || n != vl->ncols())
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if (vl) if (n > vl->nrows() || n > vl->ncols())
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laerror("inconsistent dimension of vl in gdiagonalize()");
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if (vr) if (n != vr->nrows() || n != vr->ncols())
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if (vr) if (n > vr->nrows() || n > vr->ncols())
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laerror("inconsistent dimension of vr in gdiagonalize()");
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if (beta) if(n > beta ->size()) laerror("inconsistent dimension of beta in gdiagonalize()");
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if(b) if(n > b->nrows() || n > b->ncols())
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laerror("inconsistent dimension of b in gdiagonalize()");
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if(b && !beta || beta && !b) laerror("missing array for generalized diagonalization");
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a.copyonwrite();
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wr.copyonwrite();
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wi.copyonwrite();
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if (vl) vl->copyonwrite();
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if (vr) vr->copyonwrite();
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if (beta) beta->copyonwrite();
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if (b) b->copyonwrite();
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char jobvl = vl ? 'V' : 'N';
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char jobvr = vr ? 'V' : 'N';
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double work0;
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int lwork = -1;
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int r;
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FORNAME(dgeev)(&jobvr, &jobvl, &n, a, &n, wr, wi, vr?vr[0]:(double *)0,
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&n, vl?vl[0]:(double *)0, &n, &work0, &lwork, &r);
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int lda=a.ncols();
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int ldb=0;
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if(b) ldb=b->ncols();
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int ldvl= vl?vl->ncols():lda;
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int ldvr= vr?vr->ncols():lda;
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if(b) FORNAME(dggev)(&jobvr, &jobvl, &n, a, &lda, *b, &ldb, wr, wi, *beta, vr?vr[0]:(double *)0,
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&ldvr, vl?vl[0]:(double *)0, &ldvl, &work0, &lwork, &r);
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else FORNAME(dgeev)(&jobvr, &jobvl, &n, a, &lda, wr, wi, vr?vr[0]:(double *)0,
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&ldvr, vl?vl[0]:(double *)0, &ldvl, &work0, &lwork, &r);
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lwork = (int) work0;
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double *work = new double[lwork];
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FORNAME(dgeev)(&jobvr, &jobvl, &n, a, &n, wr, wi, vr?vr[0]:(double *)0,
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&n, vl?vl[0]:(double *)0, &n, &work0, &lwork, &r);
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if(b) FORNAME(dggev)(&jobvr, &jobvl, &n, a, &lda, *b, &ldb, wr, wi, *beta, vr?vr[0]:(double *)0,
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&ldvr, vl?vl[0]:(double *)0, &ldvl, &work0, &lwork, &r);
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else FORNAME(dgeev)(&jobvr, &jobvl, &n, a, &lda, wr, wi, vr?vr[0]:(double *)0,
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&ldvr, vl?vl[0]:(double *)0, &ldvl, &work0, &lwork, &r);
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delete[] work;
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if (corder) {
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if (vl) vl->transposeme();
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if (vr) vr->transposeme();
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if (vl) vl->transposeme(n);
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if (vr) vr->transposeme(n);
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}
|
||||
|
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if (r < 0) laerror("illegal argument in geev() of gdiagonalize()");
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if (r > 0) laerror("convergence problem in geev() of gdiagonalize()");
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if (r < 0) laerror("illegal argument in ggev/geev in gdiagonalize()");
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if (r > 0) laerror("convergence problem in ggev/geev in gdiagonalize()");
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||||
}
|
||||
|
||||
void gdiagonalize(NRMat<double> &a, NRVec< complex<double> > &w,
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NRMat< complex<double> >*vl, NRMat< complex<double> > *vr)
|
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NRMat< complex<double> >*vl, NRMat< complex<double> > *vr,
|
||||
const bool corder, int n,NRMat<double> *b, NRVec<double> *beta)
|
||||
{
|
||||
int n = a.nrows();
|
||||
if(n != a.ncols()) laerror("gdiagonalize() call for a non-square matrix");
|
||||
if(!corder) laerror("gdiagonalize() corder 0 not implemented");
|
||||
if(n<=0) n = a.nrows();
|
||||
if(n> a.nrows() || n == a.nrows() && n != a.ncols()) laerror("gdiagonalize() call for a non-square matrix");
|
||||
|
||||
NRVec<double> wr(n), wi(n);
|
||||
NRMat<double> *rvl = 0;
|
||||
NRMat<double> *rvr = 0;
|
||||
if (vl) rvl = new NRMat<double>(n, n);
|
||||
if (vr) rvr = new NRMat<double>(n, n);
|
||||
gdiagonalize(a, wr, wi, rvl, rvr, 0);
|
||||
gdiagonalize(a, wr, wi, rvl, rvr, 0, n, b, beta);
|
||||
|
||||
//process the results into complex matrices
|
||||
int i;
|
||||
@ -534,9 +584,7 @@ double trace2(const NRSMat<double> &a, const NRSMat<double> &b,
|
||||
}
|
||||
|
||||
|
||||
//generalized diagonalization, eivecs will be in columns of a
|
||||
//counts with actual dimension smaller than allocated dimension
|
||||
|
||||
#ifdef obsolete
|
||||
void gendiagonalize(NRMat<double> &a, NRVec<double> &w, NRMat<double> b, int n)
|
||||
{
|
||||
if(a.nrows()!=a.ncols() || a.nrows()!=w.size() || a.nrows()!=b.nrows() || b.nrows()!=b.ncols() ) laerror("incompatible Mats in gendiagonalize");
|
||||
@ -606,8 +654,9 @@ for(int i=n-1; i>=0; --i)//component loop
|
||||
a(i,j) /= dl[i];
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
#endif
|
||||
//obsolete
|
||||
|
||||
//auxiliary routine to adjust eigenvectors to guarantee real logarithm
|
||||
//at the moment not rigorous yet
|
||||
|
||||
26
nonclass.h
26
nonclass.h
@ -51,24 +51,26 @@ extern const NRVec<T> diagofproduct(const NRMat<T> &a, const NRMat<T> &b,\
|
||||
bool trb=0, bool conjb=0); \
|
||||
extern T trace2(const NRMat<T> &a, const NRMat<T> &b, bool trb=0); \
|
||||
extern T trace2(const NRSMat<T> &a, const NRSMat<T> &b, const bool diagscaled=0);\
|
||||
extern void linear_solve(NRMat<T> &a, NRMat<T> *b, double *det=0); \
|
||||
extern void linear_solve(NRSMat<T> &a, NRMat<T> *b, double *det=0); \
|
||||
extern void linear_solve(NRMat<T> &a, NRVec<T> &b, double *det=0); \
|
||||
extern void linear_solve(NRSMat<T> &a, NRVec<T> &b, double *det=0); \
|
||||
extern void diagonalize(NRMat<T> &a, NRVec<T> &w, const bool eivec=1, const bool corder=1, int n=0); \
|
||||
extern void diagonalize(NRSMat<T> &a, NRVec<T> &w, NRMat<T> *v, const bool corder=1);\
|
||||
extern void linear_solve(NRMat<T> &a, NRMat<T> *b, double *det=0,int n=0); \
|
||||
extern void linear_solve(NRSMat<T> &a, NRMat<T> *b, double *det=0, int n=0); \
|
||||
extern void linear_solve(NRMat<T> &a, NRVec<T> &b, double *det=0, int n=0); \
|
||||
extern void linear_solve(NRSMat<T> &a, NRVec<T> &b, double *det=0, int n=0); \
|
||||
extern void diagonalize(NRMat<T> &a, NRVec<T> &w, const bool eivec=1, const bool corder=1, int n=0, NRMat<T> *b=NULL, const int itype=1); \
|
||||
extern void diagonalize(NRSMat<T> &a, NRVec<T> &w, NRMat<T> *v, const bool corder=1, int n=0, NRSMat<T> *b=NULL, const int itype=1);\
|
||||
extern void singular_decomposition(NRMat<T> &a, NRMat<T> *u, NRVec<T> &s,\
|
||||
NRMat<T> *v, const bool corder=1);
|
||||
NRMat<T> *v, const bool corder=1, int m=0, int n=0);
|
||||
|
||||
declare_la(double)
|
||||
declare_la(complex<double>)
|
||||
|
||||
// Separate declarations
|
||||
//general nonsymmetric matrix
|
||||
//general nonsymmetric matrix and generalized diagonalization
|
||||
extern void gdiagonalize(NRMat<double> &a, NRVec<double> &wr, NRVec<double> &wi,
|
||||
NRMat<double> *vl, NRMat<double> *vr, const bool corder=1);
|
||||
NRMat<double> *vl, NRMat<double> *vr, const bool corder=1, int n=0,
|
||||
NRMat<double> *b=NULL, NRVec<double> *beta=NULL);
|
||||
extern void gdiagonalize(NRMat<double> &a, NRVec< complex<double> > &w,
|
||||
NRMat< complex<double> >*vl, NRMat< complex<double> > *vr);
|
||||
NRMat< complex<double> >*vl, NRMat< complex<double> > *vr,
|
||||
const bool corder=1, int n=0, NRMat<double> *b=NULL, NRVec<double> *beta=NULL);
|
||||
extern NRMat<double> matrixfunction(NRSMat<double> a, double (*f) (double));
|
||||
extern NRMat<double> matrixfunction(NRMat<double> a, complex<double> (*f)(const complex<double> &),const bool adjust=0);
|
||||
|
||||
@ -77,10 +79,6 @@ extern NRMat<double> matrixfunction(NRMat<double> a, complex<double> (*f)(const
|
||||
//other than lapack functions/
|
||||
//////////////////////////////
|
||||
|
||||
|
||||
//generalized diagonalization of symmetric matrix with symmetric positive definite metric matrix b
|
||||
extern void gendiagonalize(NRMat<double> &a, NRVec<double> &w, NRMat<double> b, const int n=0);
|
||||
|
||||
//functions on matrices
|
||||
inline NRMat<double> sqrt(const NRSMat<double> &a) { return matrixfunction(a,&sqrt); }
|
||||
inline NRMat<double> log(const NRSMat<double> &a) { return matrixfunction(a,&log); }
|
||||
|
||||
Loading…
Reference in New Issue
Block a user