Mercurial > hg > octave-nkf
diff liboctave/dSparse.cc @ 10314:07ebe522dac2
untabify liboctave C++ sources
| author | John W. Eaton <jwe@octave.org> |
|---|---|
| date | Thu, 11 Feb 2010 12:23:32 -0500 |
| parents | 4c0cdbe0acca |
| children | 12884915a8e4 |
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--- a/liboctave/dSparse.cc +++ b/liboctave/dSparse.cc @@ -67,66 +67,66 @@ { F77_RET_T F77_FUNC (dgbtrf, DGBTRF) (const octave_idx_type&, const octave_idx_type&, - const octave_idx_type&, const octave_idx_type&, - double*, const octave_idx_type&, - octave_idx_type*, octave_idx_type&); + const octave_idx_type&, const octave_idx_type&, + double*, const octave_idx_type&, + octave_idx_type*, octave_idx_type&); F77_RET_T F77_FUNC (dgbtrs, DGBTRS) (F77_CONST_CHAR_ARG_DECL, const octave_idx_type&, - const octave_idx_type&, const octave_idx_type&, const octave_idx_type&, - const double*, const octave_idx_type&, - const octave_idx_type*, double*, const octave_idx_type&, octave_idx_type& - F77_CHAR_ARG_LEN_DECL); + const octave_idx_type&, const octave_idx_type&, const octave_idx_type&, + const double*, const octave_idx_type&, + const octave_idx_type*, double*, const octave_idx_type&, octave_idx_type& + F77_CHAR_ARG_LEN_DECL); F77_RET_T F77_FUNC (dgbcon, DGBCON) (F77_CONST_CHAR_ARG_DECL, const octave_idx_type&, - const octave_idx_type&, const octave_idx_type&, double*, - const octave_idx_type&, const octave_idx_type*, const double&, - double&, double*, octave_idx_type*, octave_idx_type& - F77_CHAR_ARG_LEN_DECL); + const octave_idx_type&, const octave_idx_type&, double*, + const octave_idx_type&, const octave_idx_type*, const double&, + double&, double*, octave_idx_type*, octave_idx_type& + F77_CHAR_ARG_LEN_DECL); F77_RET_T F77_FUNC (dpbtrf, DPBTRF) (F77_CONST_CHAR_ARG_DECL, const octave_idx_type&, - const octave_idx_type&, double*, const octave_idx_type&, octave_idx_type& - F77_CHAR_ARG_LEN_DECL); + const octave_idx_type&, double*, const octave_idx_type&, octave_idx_type& + F77_CHAR_ARG_LEN_DECL); F77_RET_T F77_FUNC (dpbtrs, DPBTRS) (F77_CONST_CHAR_ARG_DECL, const octave_idx_type&, - const octave_idx_type&, const octave_idx_type&, double*, const octave_idx_type&, - double*, const octave_idx_type&, octave_idx_type& - F77_CHAR_ARG_LEN_DECL); + const octave_idx_type&, const octave_idx_type&, double*, const octave_idx_type&, + double*, const octave_idx_type&, octave_idx_type& + F77_CHAR_ARG_LEN_DECL); F77_RET_T F77_FUNC (dpbcon, DPBCON) (F77_CONST_CHAR_ARG_DECL, const octave_idx_type&, - const octave_idx_type&, double*, const octave_idx_type&, - const double&, double&, double*, octave_idx_type*, octave_idx_type& - F77_CHAR_ARG_LEN_DECL); + const octave_idx_type&, double*, const octave_idx_type&, + const double&, double&, double*, octave_idx_type*, octave_idx_type& + F77_CHAR_ARG_LEN_DECL); F77_RET_T F77_FUNC (dptsv, DPTSV) (const octave_idx_type&, const octave_idx_type&, double*, double*, - double*, const octave_idx_type&, octave_idx_type&); + double*, const octave_idx_type&, octave_idx_type&); F77_RET_T F77_FUNC (dgtsv, DGTSV) (const octave_idx_type&, const octave_idx_type&, double*, double*, - double*, double*, const octave_idx_type&, octave_idx_type&); + double*, double*, const octave_idx_type&, octave_idx_type&); F77_RET_T F77_FUNC (dgttrf, DGTTRF) (const octave_idx_type&, double*, double*, double*, double*, - octave_idx_type*, octave_idx_type&); + octave_idx_type*, octave_idx_type&); F77_RET_T F77_FUNC (dgttrs, DGTTRS) (F77_CONST_CHAR_ARG_DECL, const octave_idx_type&, - const octave_idx_type&, const double*, const double*, - const double*, const double*, const octave_idx_type*, - double *, const octave_idx_type&, octave_idx_type& - F77_CHAR_ARG_LEN_DECL); + const octave_idx_type&, const double*, const double*, + const double*, const double*, const octave_idx_type*, + double *, const octave_idx_type&, octave_idx_type& + F77_CHAR_ARG_LEN_DECL); F77_RET_T F77_FUNC (zptsv, ZPTSV) (const octave_idx_type&, const octave_idx_type&, double*, Complex*, - Complex*, const octave_idx_type&, octave_idx_type&); + Complex*, const octave_idx_type&, octave_idx_type&); F77_RET_T F77_FUNC (zgtsv, ZGTSV) (const octave_idx_type&, const octave_idx_type&, Complex*, Complex*, - Complex*, Complex*, const octave_idx_type&, octave_idx_type&); + Complex*, Complex*, const octave_idx_type&, octave_idx_type&); } @@ -202,7 +202,7 @@ for (octave_idx_type i = 0; i < nc + 1; i++) if (cidx(i) != a.cidx(i)) - return false; + return false; for (octave_idx_type i = 0; i < nz; i++) if (data(i) != a.data(i) || ridx(i) != a.ridx(i)) @@ -226,30 +226,30 @@ if (nr == nc && nr > 0) { for (octave_idx_type j = 0; j < nc; j++) - { - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - octave_idx_type ri = ridx(i); - - if (ri != j) - { - bool found = false; - - for (octave_idx_type k = cidx(ri); k < cidx(ri+1); k++) - { - if (ridx(k) == j) - { - if (data(i) == data(k)) - found = true; - break; - } - } - - if (! found) - return false; - } - } - } + { + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + octave_idx_type ri = ridx(i); + + if (ri != j) + { + bool found = false; + + for (octave_idx_type k = cidx(ri); k < cidx(ri+1); k++) + { + if (ridx(k) == j) + { + if (data(i) == data(k)) + found = true; + break; + } + } + + if (! found) + return false; + } + } + } return true; } @@ -298,99 +298,99 @@ idx_arg.clear (1, nc); octave_idx_type nel = 0; for (octave_idx_type j = 0; j < nc; j++) - { - double tmp_max = octave_NaN; - octave_idx_type idx_j = 0; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) != idx_j) - break; - else - idx_j++; - } - - if (idx_j != nr) - tmp_max = 0.; - - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - double tmp = data (i); - - if (xisnan (tmp)) - continue; - else if (xisnan (tmp_max) || tmp > tmp_max) - { - idx_j = ridx (i); - tmp_max = tmp; - } - - } - - idx_arg.elem (j) = xisnan (tmp_max) ? 0 : idx_j; - if (tmp_max != 0.) - nel++; - } + { + double tmp_max = octave_NaN; + octave_idx_type idx_j = 0; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) != idx_j) + break; + else + idx_j++; + } + + if (idx_j != nr) + tmp_max = 0.; + + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + double tmp = data (i); + + if (xisnan (tmp)) + continue; + else if (xisnan (tmp_max) || tmp > tmp_max) + { + idx_j = ridx (i); + tmp_max = tmp; + } + + } + + idx_arg.elem (j) = xisnan (tmp_max) ? 0 : idx_j; + if (tmp_max != 0.) + nel++; + } result = SparseMatrix (1, nc, nel); octave_idx_type ii = 0; result.xcidx (0) = 0; for (octave_idx_type j = 0; j < nc; j++) - { - double tmp = elem (idx_arg(j), j); - if (tmp != 0.) - { - result.xdata (ii) = tmp; - result.xridx (ii++) = 0; - } - result.xcidx (j+1) = ii; - - } + { + double tmp = elem (idx_arg(j), j); + if (tmp != 0.) + { + result.xdata (ii) = tmp; + result.xridx (ii++) = 0; + } + result.xcidx (j+1) = ii; + + } } else { idx_arg.resize_fill (nr, 1, 0); for (octave_idx_type i = cidx(0); i < cidx(1); i++) - idx_arg.elem(ridx(i)) = -1; + idx_arg.elem(ridx(i)) = -1; for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = 0; i < nr; i++) - { - if (idx_arg.elem(i) != -1) - continue; - bool found = false; - for (octave_idx_type k = cidx(j); k < cidx(j+1); k++) - if (ridx(k) == i) - { - found = true; - break; - } - - if (!found) - idx_arg.elem(i) = j; - - } + for (octave_idx_type i = 0; i < nr; i++) + { + if (idx_arg.elem(i) != -1) + continue; + bool found = false; + for (octave_idx_type k = cidx(j); k < cidx(j+1); k++) + if (ridx(k) == i) + { + found = true; + break; + } + + if (!found) + idx_arg.elem(i) = j; + + } for (octave_idx_type j = 0; j < nc; j++) - { - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - octave_idx_type ir = ridx (i); - octave_idx_type ix = idx_arg.elem (ir); - double tmp = data (i); - - if (xisnan (tmp)) - continue; - else if (ix == -1 || tmp > elem (ir, ix)) - idx_arg.elem (ir) = j; - } - } + { + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + octave_idx_type ir = ridx (i); + octave_idx_type ix = idx_arg.elem (ir); + double tmp = data (i); + + if (xisnan (tmp)) + continue; + else if (ix == -1 || tmp > elem (ir, ix)) + idx_arg.elem (ir) = j; + } + } octave_idx_type nel = 0; for (octave_idx_type j = 0; j < nr; j++) - if (idx_arg.elem(j) == -1 || elem (j, idx_arg.elem (j)) != 0.) - nel++; + if (idx_arg.elem(j) == -1 || elem (j, idx_arg.elem (j)) != 0.) + nel++; result = SparseMatrix (nr, 1, nel); @@ -398,23 +398,23 @@ result.xcidx (0) = 0; result.xcidx (1) = nel; for (octave_idx_type j = 0; j < nr; j++) - { - if (idx_arg(j) == -1) - { - idx_arg(j) = 0; - result.xdata (ii) = octave_NaN; - result.xridx (ii++) = j; - } - else - { - double tmp = elem (j, idx_arg(j)); - if (tmp != 0.) - { - result.xdata (ii) = tmp; - result.xridx (ii++) = j; - } - } - } + { + if (idx_arg(j) == -1) + { + idx_arg(j) = 0; + result.xdata (ii) = octave_NaN; + result.xridx (ii++) = j; + } + else + { + double tmp = elem (j, idx_arg(j)); + if (tmp != 0.) + { + result.xdata (ii) = tmp; + result.xridx (ii++) = j; + } + } + } } return result; @@ -447,99 +447,99 @@ idx_arg.clear (1, nc); octave_idx_type nel = 0; for (octave_idx_type j = 0; j < nc; j++) - { - double tmp_min = octave_NaN; - octave_idx_type idx_j = 0; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) != idx_j) - break; - else - idx_j++; - } - - if (idx_j != nr) - tmp_min = 0.; - - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - double tmp = data (i); - - if (xisnan (tmp)) - continue; - else if (xisnan (tmp_min) || tmp < tmp_min) - { - idx_j = ridx (i); - tmp_min = tmp; - } - - } - - idx_arg.elem (j) = xisnan (tmp_min) ? 0 : idx_j; - if (tmp_min != 0.) - nel++; - } + { + double tmp_min = octave_NaN; + octave_idx_type idx_j = 0; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) != idx_j) + break; + else + idx_j++; + } + + if (idx_j != nr) + tmp_min = 0.; + + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + double tmp = data (i); + + if (xisnan (tmp)) + continue; + else if (xisnan (tmp_min) || tmp < tmp_min) + { + idx_j = ridx (i); + tmp_min = tmp; + } + + } + + idx_arg.elem (j) = xisnan (tmp_min) ? 0 : idx_j; + if (tmp_min != 0.) + nel++; + } result = SparseMatrix (1, nc, nel); octave_idx_type ii = 0; result.xcidx (0) = 0; for (octave_idx_type j = 0; j < nc; j++) - { - double tmp = elem (idx_arg(j), j); - if (tmp != 0.) - { - result.xdata (ii) = tmp; - result.xridx (ii++) = 0; - } - result.xcidx (j+1) = ii; - - } + { + double tmp = elem (idx_arg(j), j); + if (tmp != 0.) + { + result.xdata (ii) = tmp; + result.xridx (ii++) = 0; + } + result.xcidx (j+1) = ii; + + } } else { idx_arg.resize_fill (nr, 1, 0); for (octave_idx_type i = cidx(0); i < cidx(1); i++) - idx_arg.elem(ridx(i)) = -1; + idx_arg.elem(ridx(i)) = -1; for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = 0; i < nr; i++) - { - if (idx_arg.elem(i) != -1) - continue; - bool found = false; - for (octave_idx_type k = cidx(j); k < cidx(j+1); k++) - if (ridx(k) == i) - { - found = true; - break; - } - - if (!found) - idx_arg.elem(i) = j; - - } + for (octave_idx_type i = 0; i < nr; i++) + { + if (idx_arg.elem(i) != -1) + continue; + bool found = false; + for (octave_idx_type k = cidx(j); k < cidx(j+1); k++) + if (ridx(k) == i) + { + found = true; + break; + } + + if (!found) + idx_arg.elem(i) = j; + + } for (octave_idx_type j = 0; j < nc; j++) - { - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - octave_idx_type ir = ridx (i); - octave_idx_type ix = idx_arg.elem (ir); - double tmp = data (i); - - if (xisnan (tmp)) - continue; - else if (ix == -1 || tmp < elem (ir, ix)) - idx_arg.elem (ir) = j; - } - } + { + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + octave_idx_type ir = ridx (i); + octave_idx_type ix = idx_arg.elem (ir); + double tmp = data (i); + + if (xisnan (tmp)) + continue; + else if (ix == -1 || tmp < elem (ir, ix)) + idx_arg.elem (ir) = j; + } + } octave_idx_type nel = 0; for (octave_idx_type j = 0; j < nr; j++) - if (idx_arg.elem(j) == -1 || elem (j, idx_arg.elem (j)) != 0.) - nel++; + if (idx_arg.elem(j) == -1 || elem (j, idx_arg.elem (j)) != 0.) + nel++; result = SparseMatrix (nr, 1, nel); @@ -547,23 +547,23 @@ result.xcidx (0) = 0; result.xcidx (1) = nel; for (octave_idx_type j = 0; j < nr; j++) - { - if (idx_arg(j) == -1) - { - idx_arg(j) = 0; - result.xdata (ii) = octave_NaN; - result.xridx (ii++) = j; - } - else - { - double tmp = elem (j, idx_arg(j)); - if (tmp != 0.) - { - result.xdata (ii) = tmp; - result.xridx (ii++) = j; - } - } - } + { + if (idx_arg(j) == -1) + { + idx_arg(j) = 0; + result.xdata (ii) = octave_NaN; + result.xridx (ii++) = j; + } + else + { + double tmp = elem (j, idx_arg(j)); + if (tmp != 0.) + { + result.xdata (ii) = tmp; + result.xridx (ii++) = j; + } + } + } } return result; @@ -673,8 +673,8 @@ Matrix tmp (nr, nc, atan2 (x, 0.)); for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = y.cidx (j); i < y.cidx (j+1); i++) - tmp.elem (y.ridx(i), j) = atan2 (x, y.data(i)); + for (octave_idx_type i = y.cidx (j); i < y.cidx (j+1); i++) + tmp.elem (y.ridx(i), j) = atan2 (x, y.data(i)); return SparseMatrix (tmp); } @@ -694,14 +694,14 @@ for (octave_idx_type i = 0; i < nc; i++) { for (octave_idx_type j = x.cidx(i); j < x.cidx(i+1); j++) - { - double tmp = atan2 (x.data(j), y); - if (tmp != 0.) - { - retval.xdata (ii) = tmp; - retval.xridx (ii++) = x.ridx (j); - } - } + { + double tmp = atan2 (x.data(j), y); + if (tmp != 0.) + { + retval.xdata (ii) = tmp; + retval.xridx (ii++) = x.ridx (j); + } + } retval.xcidx (i+1) = ii; } @@ -709,12 +709,12 @@ { SparseMatrix retval2 (nr, nc, ii); for (octave_idx_type i = 0; i < nc+1; i++) - retval2.xcidx (i) = retval.cidx (i); + retval2.xcidx (i) = retval.cidx (i); for (octave_idx_type i = 0; i < ii; i++) - { - retval2.xdata (i) = retval.data (i); - retval2.xridx (i) = retval.ridx (i); - } + { + retval2.xdata (i) = retval.data (i); + retval2.xridx (i) = retval.ridx (i); + } return retval2; } else @@ -735,61 +735,61 @@ octave_idx_type y_nc = y.cols (); if (x_nr != y_nr || x_nc != y_nc) - gripe_nonconformant ("atan2", x_nr, x_nc, y_nr, y_nc); + gripe_nonconformant ("atan2", x_nr, x_nc, y_nr, y_nc); else - { - r = SparseMatrix (x_nr, x_nc, (x.nnz () + y.nnz ())); + { + r = SparseMatrix (x_nr, x_nc, (x.nnz () + y.nnz ())); - octave_idx_type jx = 0; - r.cidx (0) = 0; - for (octave_idx_type i = 0 ; i < x_nc ; i++) - { - octave_idx_type ja = x.cidx(i); - octave_idx_type ja_max = x.cidx(i+1); - bool ja_lt_max= ja < ja_max; + octave_idx_type jx = 0; + r.cidx (0) = 0; + for (octave_idx_type i = 0 ; i < x_nc ; i++) + { + octave_idx_type ja = x.cidx(i); + octave_idx_type ja_max = x.cidx(i+1); + bool ja_lt_max= ja < ja_max; - octave_idx_type jb = y.cidx(i); - octave_idx_type jb_max = y.cidx(i+1); - bool jb_lt_max = jb < jb_max; + octave_idx_type jb = y.cidx(i); + octave_idx_type jb_max = y.cidx(i+1); + bool jb_lt_max = jb < jb_max; - while (ja_lt_max || jb_lt_max ) - { - octave_quit (); - if ((! jb_lt_max) || + while (ja_lt_max || jb_lt_max ) + { + octave_quit (); + if ((! jb_lt_max) || (ja_lt_max && (x.ridx(ja) < y.ridx(jb)))) - { - r.ridx(jx) = x.ridx(ja); - r.data(jx) = atan2 (x.data(ja), 0.); - jx++; - ja++; - ja_lt_max= ja < ja_max; - } - else if (( !ja_lt_max ) || - (jb_lt_max && (y.ridx(jb) < x.ridx(ja)) ) ) - { - jb++; - jb_lt_max= jb < jb_max; - } - else - { - double tmp = atan2 (x.data(ja), y.data(jb)); - if (tmp != 0.) - { + { + r.ridx(jx) = x.ridx(ja); + r.data(jx) = atan2 (x.data(ja), 0.); + jx++; + ja++; + ja_lt_max= ja < ja_max; + } + else if (( !ja_lt_max ) || + (jb_lt_max && (y.ridx(jb) < x.ridx(ja)) ) ) + { + jb++; + jb_lt_max= jb < jb_max; + } + else + { + double tmp = atan2 (x.data(ja), y.data(jb)); + if (tmp != 0.) + { r.data(jx) = tmp; r.ridx(jx) = x.ridx(ja); jx++; - } - ja++; - ja_lt_max= ja < ja_max; - jb++; - jb_lt_max= jb < jb_max; - } - } - r.cidx(i+1) = jx; - } - - r.maybe_compress (); - } + } + ja++; + ja_lt_max= ja < ja_max; + jb++; + jb_lt_max= jb < jb_max; + } + } + r.cidx(i+1) = jx; + } + + r.maybe_compress (); + } } else (*current_liboctave_error_handler) ("matrix size mismatch"); @@ -823,8 +823,8 @@ SparseMatrix SparseMatrix::dinverse (MatrixType &mattyp, octave_idx_type& info, - double& rcond, const bool, - const bool calccond) const + double& rcond, const bool, + const bool calccond) const { SparseMatrix retval; @@ -841,35 +841,35 @@ mattyp.info (); if (typ == MatrixType::Diagonal || - typ == MatrixType::Permuted_Diagonal) - { - if (typ == MatrixType::Permuted_Diagonal) - retval = transpose(); - else - retval = *this; - - // Force make_unique to be called - double *v = retval.data(); - - if (calccond) - { - double dmax = 0., dmin = octave_Inf; - for (octave_idx_type i = 0; i < nr; i++) - { - double tmp = fabs(v[i]); - if (tmp > dmax) - dmax = tmp; - if (tmp < dmin) - dmin = tmp; - } - rcond = dmin / dmax; - } - - for (octave_idx_type i = 0; i < nr; i++) - v[i] = 1.0 / v[i]; - } + typ == MatrixType::Permuted_Diagonal) + { + if (typ == MatrixType::Permuted_Diagonal) + retval = transpose(); + else + retval = *this; + + // Force make_unique to be called + double *v = retval.data(); + + if (calccond) + { + double dmax = 0., dmin = octave_Inf; + for (octave_idx_type i = 0; i < nr; i++) + { + double tmp = fabs(v[i]); + if (tmp > dmax) + dmax = tmp; + if (tmp < dmin) + dmin = tmp; + } + rcond = dmin / dmax; + } + + for (octave_idx_type i = 0; i < nr; i++) + v[i] = 1.0 / v[i]; + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -877,8 +877,8 @@ SparseMatrix SparseMatrix::tinverse (MatrixType &mattyp, octave_idx_type& info, - double& rcond, const bool, - const bool calccond) const + double& rcond, const bool, + const bool calccond) const { SparseMatrix retval; @@ -895,255 +895,255 @@ mattyp.info (); if (typ == MatrixType::Upper || typ == MatrixType::Permuted_Upper || - typ == MatrixType::Lower || typ == MatrixType::Permuted_Lower) - { - double anorm = 0.; - double ainvnorm = 0.; - - if (calccond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nr; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - if (typ == MatrixType::Upper || typ == MatrixType::Lower) - { - octave_idx_type nz = nnz (); - octave_idx_type cx = 0; - octave_idx_type nz2 = nz; - retval = SparseMatrix (nr, nc, nz2); - - for (octave_idx_type i = 0; i < nr; i++) - { - octave_quit (); - // place the 1 in the identity position - octave_idx_type cx_colstart = cx; - - if (cx == nz2) - { - nz2 *= 2; - retval.change_capacity (nz2); - } - - retval.xcidx(i) = cx; - retval.xridx(cx) = i; - retval.xdata(cx) = 1.0; - cx++; - - // iterate accross columns of input matrix - for (octave_idx_type j = i+1; j < nr; j++) - { - double v = 0.; - // iterate to calculate sum - octave_idx_type colXp = retval.xcidx(i); - octave_idx_type colUp = cidx(j); - octave_idx_type rpX, rpU; - - if (cidx(j) == cidx(j+1)) - { - (*current_liboctave_error_handler) - ("division by zero"); - goto inverse_singular; - } - - do - { - octave_quit (); - rpX = retval.xridx(colXp); - rpU = ridx(colUp); - - if (rpX < rpU) - colXp++; - else if (rpX > rpU) - colUp++; - else - { - v -= retval.xdata(colXp) * data(colUp); - colXp++; - colUp++; - } - } while ((rpX<j) && (rpU<j) && - (colXp<cx) && (colUp<nz)); - - // get A(m,m) - if (typ == MatrixType::Upper) - colUp = cidx(j+1) - 1; - else - colUp = cidx(j); - double pivot = data(colUp); - if (pivot == 0. || ridx(colUp) != j) - { - (*current_liboctave_error_handler) - ("division by zero"); - goto inverse_singular; - } - - if (v != 0.) - { - if (cx == nz2) - { - nz2 *= 2; - retval.change_capacity (nz2); - } - - retval.xridx(cx) = j; - retval.xdata(cx) = v / pivot; - cx++; - } - } - - // get A(m,m) - octave_idx_type colUp; - if (typ == MatrixType::Upper) - colUp = cidx(i+1) - 1; - else - colUp = cidx(i); - double pivot = data(colUp); - if (pivot == 0. || ridx(colUp) != i) - { - (*current_liboctave_error_handler) ("division by zero"); - goto inverse_singular; - } - - if (pivot != 1.0) - for (octave_idx_type j = cx_colstart; j < cx; j++) - retval.xdata(j) /= pivot; - } - retval.xcidx(nr) = cx; - retval.maybe_compress (); - } - else - { - octave_idx_type nz = nnz (); - octave_idx_type cx = 0; - octave_idx_type nz2 = nz; - retval = SparseMatrix (nr, nc, nz2); - - OCTAVE_LOCAL_BUFFER (double, work, nr); - OCTAVE_LOCAL_BUFFER (octave_idx_type, rperm, nr); - - octave_idx_type *perm = mattyp.triangular_perm(); - if (typ == MatrixType::Permuted_Upper) - { - for (octave_idx_type i = 0; i < nr; i++) - rperm[perm[i]] = i; - } - else - { - for (octave_idx_type i = 0; i < nr; i++) - rperm[i] = perm[i]; - for (octave_idx_type i = 0; i < nr; i++) - perm[rperm[i]] = i; - } - - for (octave_idx_type i = 0; i < nr; i++) - { - octave_quit (); - octave_idx_type iidx = rperm[i]; - - for (octave_idx_type j = 0; j < nr; j++) - work[j] = 0.; - - // place the 1 in the identity position - work[iidx] = 1.0; - - // iterate accross columns of input matrix - for (octave_idx_type j = iidx+1; j < nr; j++) - { - double v = 0.; - octave_idx_type jidx = perm[j]; - // iterate to calculate sum - for (octave_idx_type k = cidx(jidx); - k < cidx(jidx+1); k++) - { - octave_quit (); - v -= work[ridx(k)] * data(k); - } - - // get A(m,m) - double pivot; - if (typ == MatrixType::Permuted_Upper) - pivot = data(cidx(jidx+1) - 1); - else - pivot = data(cidx(jidx)); - if (pivot == 0.) - { - (*current_liboctave_error_handler) - ("division by zero"); - goto inverse_singular; - } - - work[j] = v / pivot; - } - - // get A(m,m) - octave_idx_type colUp; - if (typ == MatrixType::Permuted_Upper) - colUp = cidx(perm[iidx]+1) - 1; - else - colUp = cidx(perm[iidx]); - - double pivot = data(colUp); - if (pivot == 0.) - { - (*current_liboctave_error_handler) - ("division by zero"); - goto inverse_singular; - } - - octave_idx_type new_cx = cx; - for (octave_idx_type j = iidx; j < nr; j++) - if (work[j] != 0.0) - { - new_cx++; - if (pivot != 1.0) - work[j] /= pivot; - } - - if (cx < new_cx) - { - nz2 = (2*nz2 < new_cx ? new_cx : 2*nz2); - retval.change_capacity (nz2); - } - - retval.xcidx(i) = cx; - for (octave_idx_type j = iidx; j < nr; j++) - if (work[j] != 0.) - { - retval.xridx(cx) = j; - retval.xdata(cx++) = work[j]; - } - } - - retval.xcidx(nr) = cx; - retval.maybe_compress (); - } - - if (calccond) - { - // Calculate the 1-norm of inverse matrix for rcond calculation - for (octave_idx_type j = 0; j < nr; j++) - { - double atmp = 0.; - for (octave_idx_type i = retval.cidx(j); - i < retval.cidx(j+1); i++) - atmp += fabs(retval.data(i)); - if (atmp > ainvnorm) - ainvnorm = atmp; - } - - rcond = 1. / ainvnorm / anorm; - } - } + typ == MatrixType::Lower || typ == MatrixType::Permuted_Lower) + { + double anorm = 0.; + double ainvnorm = 0.; + + if (calccond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nr; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + if (typ == MatrixType::Upper || typ == MatrixType::Lower) + { + octave_idx_type nz = nnz (); + octave_idx_type cx = 0; + octave_idx_type nz2 = nz; + retval = SparseMatrix (nr, nc, nz2); + + for (octave_idx_type i = 0; i < nr; i++) + { + octave_quit (); + // place the 1 in the identity position + octave_idx_type cx_colstart = cx; + + if (cx == nz2) + { + nz2 *= 2; + retval.change_capacity (nz2); + } + + retval.xcidx(i) = cx; + retval.xridx(cx) = i; + retval.xdata(cx) = 1.0; + cx++; + + // iterate accross columns of input matrix + for (octave_idx_type j = i+1; j < nr; j++) + { + double v = 0.; + // iterate to calculate sum + octave_idx_type colXp = retval.xcidx(i); + octave_idx_type colUp = cidx(j); + octave_idx_type rpX, rpU; + + if (cidx(j) == cidx(j+1)) + { + (*current_liboctave_error_handler) + ("division by zero"); + goto inverse_singular; + } + + do + { + octave_quit (); + rpX = retval.xridx(colXp); + rpU = ridx(colUp); + + if (rpX < rpU) + colXp++; + else if (rpX > rpU) + colUp++; + else + { + v -= retval.xdata(colXp) * data(colUp); + colXp++; + colUp++; + } + } while ((rpX<j) && (rpU<j) && + (colXp<cx) && (colUp<nz)); + + // get A(m,m) + if (typ == MatrixType::Upper) + colUp = cidx(j+1) - 1; + else + colUp = cidx(j); + double pivot = data(colUp); + if (pivot == 0. || ridx(colUp) != j) + { + (*current_liboctave_error_handler) + ("division by zero"); + goto inverse_singular; + } + + if (v != 0.) + { + if (cx == nz2) + { + nz2 *= 2; + retval.change_capacity (nz2); + } + + retval.xridx(cx) = j; + retval.xdata(cx) = v / pivot; + cx++; + } + } + + // get A(m,m) + octave_idx_type colUp; + if (typ == MatrixType::Upper) + colUp = cidx(i+1) - 1; + else + colUp = cidx(i); + double pivot = data(colUp); + if (pivot == 0. || ridx(colUp) != i) + { + (*current_liboctave_error_handler) ("division by zero"); + goto inverse_singular; + } + + if (pivot != 1.0) + for (octave_idx_type j = cx_colstart; j < cx; j++) + retval.xdata(j) /= pivot; + } + retval.xcidx(nr) = cx; + retval.maybe_compress (); + } + else + { + octave_idx_type nz = nnz (); + octave_idx_type cx = 0; + octave_idx_type nz2 = nz; + retval = SparseMatrix (nr, nc, nz2); + + OCTAVE_LOCAL_BUFFER (double, work, nr); + OCTAVE_LOCAL_BUFFER (octave_idx_type, rperm, nr); + + octave_idx_type *perm = mattyp.triangular_perm(); + if (typ == MatrixType::Permuted_Upper) + { + for (octave_idx_type i = 0; i < nr; i++) + rperm[perm[i]] = i; + } + else + { + for (octave_idx_type i = 0; i < nr; i++) + rperm[i] = perm[i]; + for (octave_idx_type i = 0; i < nr; i++) + perm[rperm[i]] = i; + } + + for (octave_idx_type i = 0; i < nr; i++) + { + octave_quit (); + octave_idx_type iidx = rperm[i]; + + for (octave_idx_type j = 0; j < nr; j++) + work[j] = 0.; + + // place the 1 in the identity position + work[iidx] = 1.0; + + // iterate accross columns of input matrix + for (octave_idx_type j = iidx+1; j < nr; j++) + { + double v = 0.; + octave_idx_type jidx = perm[j]; + // iterate to calculate sum + for (octave_idx_type k = cidx(jidx); + k < cidx(jidx+1); k++) + { + octave_quit (); + v -= work[ridx(k)] * data(k); + } + + // get A(m,m) + double pivot; + if (typ == MatrixType::Permuted_Upper) + pivot = data(cidx(jidx+1) - 1); + else + pivot = data(cidx(jidx)); + if (pivot == 0.) + { + (*current_liboctave_error_handler) + ("division by zero"); + goto inverse_singular; + } + + work[j] = v / pivot; + } + + // get A(m,m) + octave_idx_type colUp; + if (typ == MatrixType::Permuted_Upper) + colUp = cidx(perm[iidx]+1) - 1; + else + colUp = cidx(perm[iidx]); + + double pivot = data(colUp); + if (pivot == 0.) + { + (*current_liboctave_error_handler) + ("division by zero"); + goto inverse_singular; + } + + octave_idx_type new_cx = cx; + for (octave_idx_type j = iidx; j < nr; j++) + if (work[j] != 0.0) + { + new_cx++; + if (pivot != 1.0) + work[j] /= pivot; + } + + if (cx < new_cx) + { + nz2 = (2*nz2 < new_cx ? new_cx : 2*nz2); + retval.change_capacity (nz2); + } + + retval.xcidx(i) = cx; + for (octave_idx_type j = iidx; j < nr; j++) + if (work[j] != 0.) + { + retval.xridx(cx) = j; + retval.xdata(cx++) = work[j]; + } + } + + retval.xcidx(nr) = cx; + retval.maybe_compress (); + } + + if (calccond) + { + // Calculate the 1-norm of inverse matrix for rcond calculation + for (octave_idx_type j = 0; j < nr; j++) + { + double atmp = 0.; + for (octave_idx_type i = retval.cidx(j); + i < retval.cidx(j+1); i++) + atmp += fabs(retval.data(i)); + if (atmp > ainvnorm) + ainvnorm = atmp; + } + + rcond = 1. / ainvnorm / anorm; + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -1154,7 +1154,7 @@ SparseMatrix SparseMatrix::inverse (MatrixType &mattype, octave_idx_type& info, - double& rcond, int, int calc_cond) const + double& rcond, int, int calc_cond) const { int typ = mattype.type (false); SparseMatrix ret; @@ -1174,43 +1174,43 @@ else { if (mattype.is_hermitian()) - { - MatrixType tmp_typ (MatrixType::Upper); - SparseCHOL fact (*this, info, false); - rcond = fact.rcond(); - if (info == 0) - { - double rcond2; - SparseMatrix Q = fact.Q(); - SparseMatrix InvL = fact.L().transpose().tinverse(tmp_typ, - info, rcond2, true, false); - ret = Q * InvL.transpose() * InvL * Q.transpose(); - } - else - { - // Matrix is either singular or not positive definite - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; - } - } + { + MatrixType tmp_typ (MatrixType::Upper); + SparseCHOL fact (*this, info, false); + rcond = fact.rcond(); + if (info == 0) + { + double rcond2; + SparseMatrix Q = fact.Q(); + SparseMatrix InvL = fact.L().transpose().tinverse(tmp_typ, + info, rcond2, true, false); + ret = Q * InvL.transpose() * InvL * Q.transpose(); + } + else + { + // Matrix is either singular or not positive definite + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; + } + } if (!mattype.is_hermitian()) - { - octave_idx_type n = rows(); - ColumnVector Qinit(n); - for (octave_idx_type i = 0; i < n; i++) - Qinit(i) = i; - - MatrixType tmp_typ (MatrixType::Upper); - SparseLU fact (*this, Qinit, Matrix(), false, false); - rcond = fact.rcond(); - double rcond2; - SparseMatrix InvL = fact.L().transpose().tinverse(tmp_typ, - info, rcond2, true, false); - SparseMatrix InvU = fact.U().tinverse(tmp_typ, info, rcond2, - true, false).transpose(); - ret = fact.Pc().transpose() * InvU * InvL * fact.Pr(); - } + { + octave_idx_type n = rows(); + ColumnVector Qinit(n); + for (octave_idx_type i = 0; i < n; i++) + Qinit(i) = i; + + MatrixType tmp_typ (MatrixType::Upper); + SparseLU fact (*this, Qinit, Matrix(), false, false); + rcond = fact.rcond(); + double rcond2; + SparseMatrix InvL = fact.L().transpose().tinverse(tmp_typ, + info, rcond2, true, false); + SparseMatrix InvU = fact.U().tinverse(tmp_typ, info, rcond2, + true, false).transpose(); + ret = fact.Pc().transpose() * InvU * InvL * fact.Pr(); + } } return ret; @@ -1255,19 +1255,19 @@ double tmp = octave_sparse_params::get_key ("spumoni"); if (!xisnan (tmp)) - Control (UMFPACK_PRL) = tmp; + Control (UMFPACK_PRL) = tmp; tmp = octave_sparse_params::get_key ("piv_tol"); if (!xisnan (tmp)) - { - Control (UMFPACK_SYM_PIVOT_TOLERANCE) = tmp; - Control (UMFPACK_PIVOT_TOLERANCE) = tmp; - } + { + Control (UMFPACK_SYM_PIVOT_TOLERANCE) = tmp; + Control (UMFPACK_PIVOT_TOLERANCE) = tmp; + } // Set whether we are allowed to modify Q or not tmp = octave_sparse_params::get_key ("autoamd"); if (!xisnan (tmp)) - Control (UMFPACK_FIXQ) = tmp; + Control (UMFPACK_FIXQ) = tmp; // Turn-off UMFPACK scaling for LU Control (UMFPACK_SCALE) = UMFPACK_SCALE_NONE; @@ -1284,61 +1284,61 @@ Matrix Info (1, UMFPACK_INFO); double *info = Info.fortran_vec (); int status = UMFPACK_DNAME (qsymbolic) (nr, nc, Ap, Ai, - Ax, 0, &Symbolic, control, info); + Ax, 0, &Symbolic, control, info); if (status < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::determinant symbolic factorization failed"); - - UMFPACK_DNAME (report_status) (control, status); - UMFPACK_DNAME (report_info) (control, info); - - UMFPACK_DNAME (free_symbolic) (&Symbolic) ; - } + { + (*current_liboctave_error_handler) + ("SparseMatrix::determinant symbolic factorization failed"); + + UMFPACK_DNAME (report_status) (control, status); + UMFPACK_DNAME (report_info) (control, info); + + UMFPACK_DNAME (free_symbolic) (&Symbolic) ; + } else - { - UMFPACK_DNAME (report_symbolic) (Symbolic, control); - - void *Numeric; - status = UMFPACK_DNAME (numeric) (Ap, Ai, Ax, Symbolic, - &Numeric, control, info) ; - UMFPACK_DNAME (free_symbolic) (&Symbolic) ; - - rcond = Info (UMFPACK_RCOND); - - if (status < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::determinant numeric factorization failed"); - - UMFPACK_DNAME (report_status) (control, status); - UMFPACK_DNAME (report_info) (control, info); - - UMFPACK_DNAME (free_numeric) (&Numeric); - } - else - { - UMFPACK_DNAME (report_numeric) (Numeric, control); - - double c10, e10; - - status = UMFPACK_DNAME (get_determinant) (&c10, &e10, Numeric, info); - - if (status < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::determinant error calculating determinant"); - - UMFPACK_DNAME (report_status) (control, status); - UMFPACK_DNAME (report_info) (control, info); - } - else - retval = DET (c10, e10, 10); - - UMFPACK_DNAME (free_numeric) (&Numeric); - } - } + { + UMFPACK_DNAME (report_symbolic) (Symbolic, control); + + void *Numeric; + status = UMFPACK_DNAME (numeric) (Ap, Ai, Ax, Symbolic, + &Numeric, control, info) ; + UMFPACK_DNAME (free_symbolic) (&Symbolic) ; + + rcond = Info (UMFPACK_RCOND); + + if (status < 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::determinant numeric factorization failed"); + + UMFPACK_DNAME (report_status) (control, status); + UMFPACK_DNAME (report_info) (control, info); + + UMFPACK_DNAME (free_numeric) (&Numeric); + } + else + { + UMFPACK_DNAME (report_numeric) (Numeric, control); + + double c10, e10; + + status = UMFPACK_DNAME (get_determinant) (&c10, &e10, Numeric, info); + + if (status < 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::determinant error calculating determinant"); + + UMFPACK_DNAME (report_status) (control, status); + UMFPACK_DNAME (report_info) (control, info); + } + else + retval = DET (c10, e10, 10); + + UMFPACK_DNAME (free_numeric) (&Numeric); + } + } } #else (*current_liboctave_error_handler) ("UMFPACK not installed"); @@ -1349,8 +1349,8 @@ Matrix SparseMatrix::dsolve (MatrixType &mattype, const Matrix& b, octave_idx_type& err, - double& rcond, solve_singularity_handler, - bool calc_cond) const + double& rcond, solve_singularity_handler, + bool calc_cond) const { Matrix retval; @@ -1371,37 +1371,37 @@ mattype.info (); if (typ == MatrixType::Diagonal || - typ == MatrixType::Permuted_Diagonal) - { - retval.resize (nc, b.cols(), 0.); - if (typ == MatrixType::Diagonal) - for (octave_idx_type j = 0; j < b.cols(); j++) - for (octave_idx_type i = 0; i < nm; i++) - retval(i,j) = b(i,j) / data (i); - else - for (octave_idx_type j = 0; j < b.cols(); j++) - for (octave_idx_type k = 0; k < nc; k++) - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - retval(k,j) = b(ridx(i),j) / data (i); - - if (calc_cond) - { - double dmax = 0., dmin = octave_Inf; - for (octave_idx_type i = 0; i < nm; i++) - { - double tmp = fabs(data(i)); - if (tmp > dmax) - dmax = tmp; - if (tmp < dmin) - dmin = tmp; - } - rcond = dmin / dmax; - } - else - rcond = 1.; - } + typ == MatrixType::Permuted_Diagonal) + { + retval.resize (nc, b.cols(), 0.); + if (typ == MatrixType::Diagonal) + for (octave_idx_type j = 0; j < b.cols(); j++) + for (octave_idx_type i = 0; i < nm; i++) + retval(i,j) = b(i,j) / data (i); + else + for (octave_idx_type j = 0; j < b.cols(); j++) + for (octave_idx_type k = 0; k < nc; k++) + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + retval(k,j) = b(ridx(i),j) / data (i); + + if (calc_cond) + { + double dmax = 0., dmin = octave_Inf; + for (octave_idx_type i = 0; i < nm; i++) + { + double tmp = fabs(data(i)); + if (tmp > dmax) + dmax = tmp; + if (tmp < dmin) + dmin = tmp; + } + rcond = dmin / dmax; + } + else + rcond = 1.; + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -1409,8 +1409,8 @@ SparseMatrix SparseMatrix::dsolve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler, bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler, bool calc_cond) const { SparseMatrix retval; @@ -1431,67 +1431,67 @@ mattype.info (); if (typ == MatrixType::Diagonal || - typ == MatrixType::Permuted_Diagonal) - { - octave_idx_type b_nc = b.cols (); - octave_idx_type b_nz = b.nnz (); - retval = SparseMatrix (nc, b_nc, b_nz); - - retval.xcidx(0) = 0; - octave_idx_type ii = 0; - if (typ == MatrixType::Diagonal) - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - { - if (b.ridx(i) >= nm) - break; - retval.xridx (ii) = b.ridx(i); - retval.xdata (ii++) = b.data(i) / data (b.ridx (i)); - } - retval.xcidx(j+1) = ii; - } - else - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type l = 0; l < nc; l++) - for (octave_idx_type i = cidx(l); i < cidx(l+1); i++) - { - bool found = false; - octave_idx_type k; - for (k = b.cidx(j); k < b.cidx(j+1); k++) - if (ridx(i) == b.ridx(k)) - { - found = true; - break; - } - if (found) - { - retval.xridx (ii) = l; - retval.xdata (ii++) = b.data(k) / data (i); - } - } - retval.xcidx(j+1) = ii; - } - - if (calc_cond) - { - double dmax = 0., dmin = octave_Inf; - for (octave_idx_type i = 0; i < nm; i++) - { - double tmp = fabs(data(i)); - if (tmp > dmax) - dmax = tmp; - if (tmp < dmin) - dmin = tmp; - } - rcond = dmin / dmax; - } - else - rcond = 1.; - } + typ == MatrixType::Permuted_Diagonal) + { + octave_idx_type b_nc = b.cols (); + octave_idx_type b_nz = b.nnz (); + retval = SparseMatrix (nc, b_nc, b_nz); + + retval.xcidx(0) = 0; + octave_idx_type ii = 0; + if (typ == MatrixType::Diagonal) + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + { + if (b.ridx(i) >= nm) + break; + retval.xridx (ii) = b.ridx(i); + retval.xdata (ii++) = b.data(i) / data (b.ridx (i)); + } + retval.xcidx(j+1) = ii; + } + else + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type l = 0; l < nc; l++) + for (octave_idx_type i = cidx(l); i < cidx(l+1); i++) + { + bool found = false; + octave_idx_type k; + for (k = b.cidx(j); k < b.cidx(j+1); k++) + if (ridx(i) == b.ridx(k)) + { + found = true; + break; + } + if (found) + { + retval.xridx (ii) = l; + retval.xdata (ii++) = b.data(k) / data (i); + } + } + retval.xcidx(j+1) = ii; + } + + if (calc_cond) + { + double dmax = 0., dmin = octave_Inf; + for (octave_idx_type i = 0; i < nm; i++) + { + double tmp = fabs(data(i)); + if (tmp > dmax) + dmax = tmp; + if (tmp < dmin) + dmin = tmp; + } + rcond = dmin / dmax; + } + else + rcond = 1.; + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -1499,8 +1499,8 @@ ComplexMatrix SparseMatrix::dsolve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler, bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler, bool calc_cond) const { ComplexMatrix retval; @@ -1521,37 +1521,37 @@ mattype.info (); if (typ == MatrixType::Diagonal || - typ == MatrixType::Permuted_Diagonal) - { - retval.resize (nc, b.cols(), 0); - if (typ == MatrixType::Diagonal) - for (octave_idx_type j = 0; j < b.cols(); j++) - for (octave_idx_type i = 0; i < nm; i++) - retval(i,j) = b(i,j) / data (i); - else - for (octave_idx_type j = 0; j < b.cols(); j++) - for (octave_idx_type k = 0; k < nc; k++) - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - retval(k,j) = b(ridx(i),j) / data (i); - - if (calc_cond) - { - double dmax = 0., dmin = octave_Inf; - for (octave_idx_type i = 0; i < nm; i++) - { - double tmp = fabs(data(i)); - if (tmp > dmax) - dmax = tmp; - if (tmp < dmin) - dmin = tmp; - } - rcond = dmin / dmax; - } - else - rcond = 1.; - } + typ == MatrixType::Permuted_Diagonal) + { + retval.resize (nc, b.cols(), 0); + if (typ == MatrixType::Diagonal) + for (octave_idx_type j = 0; j < b.cols(); j++) + for (octave_idx_type i = 0; i < nm; i++) + retval(i,j) = b(i,j) / data (i); + else + for (octave_idx_type j = 0; j < b.cols(); j++) + for (octave_idx_type k = 0; k < nc; k++) + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + retval(k,j) = b(ridx(i),j) / data (i); + + if (calc_cond) + { + double dmax = 0., dmin = octave_Inf; + for (octave_idx_type i = 0; i < nm; i++) + { + double tmp = fabs(data(i)); + if (tmp > dmax) + dmax = tmp; + if (tmp < dmin) + dmin = tmp; + } + rcond = dmin / dmax; + } + else + rcond = 1.; + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -1559,8 +1559,8 @@ SparseComplexMatrix SparseMatrix::dsolve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler, bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler, bool calc_cond) const { SparseComplexMatrix retval; @@ -1581,67 +1581,67 @@ mattype.info (); if (typ == MatrixType::Diagonal || - typ == MatrixType::Permuted_Diagonal) - { - octave_idx_type b_nc = b.cols (); - octave_idx_type b_nz = b.nnz (); - retval = SparseComplexMatrix (nc, b_nc, b_nz); - - retval.xcidx(0) = 0; - octave_idx_type ii = 0; - if (typ == MatrixType::Diagonal) - for (octave_idx_type j = 0; j < b.cols(); j++) - { - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - { - if (b.ridx(i) >= nm) - break; - retval.xridx (ii) = b.ridx(i); - retval.xdata (ii++) = b.data(i) / data (b.ridx (i)); - } - retval.xcidx(j+1) = ii; - } - else - for (octave_idx_type j = 0; j < b.cols(); j++) - { - for (octave_idx_type l = 0; l < nc; l++) - for (octave_idx_type i = cidx(l); i < cidx(l+1); i++) - { - bool found = false; - octave_idx_type k; - for (k = b.cidx(j); k < b.cidx(j+1); k++) - if (ridx(i) == b.ridx(k)) - { - found = true; - break; - } - if (found) - { - retval.xridx (ii) = l; - retval.xdata (ii++) = b.data(k) / data (i); - } - } - retval.xcidx(j+1) = ii; - } - - if (calc_cond) - { - double dmax = 0., dmin = octave_Inf; - for (octave_idx_type i = 0; i < nm; i++) - { - double tmp = fabs(data(i)); - if (tmp > dmax) - dmax = tmp; - if (tmp < dmin) - dmin = tmp; - } - rcond = dmin / dmax; - } - else - rcond = 1.; - } + typ == MatrixType::Permuted_Diagonal) + { + octave_idx_type b_nc = b.cols (); + octave_idx_type b_nz = b.nnz (); + retval = SparseComplexMatrix (nc, b_nc, b_nz); + + retval.xcidx(0) = 0; + octave_idx_type ii = 0; + if (typ == MatrixType::Diagonal) + for (octave_idx_type j = 0; j < b.cols(); j++) + { + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + { + if (b.ridx(i) >= nm) + break; + retval.xridx (ii) = b.ridx(i); + retval.xdata (ii++) = b.data(i) / data (b.ridx (i)); + } + retval.xcidx(j+1) = ii; + } + else + for (octave_idx_type j = 0; j < b.cols(); j++) + { + for (octave_idx_type l = 0; l < nc; l++) + for (octave_idx_type i = cidx(l); i < cidx(l+1); i++) + { + bool found = false; + octave_idx_type k; + for (k = b.cidx(j); k < b.cidx(j+1); k++) + if (ridx(i) == b.ridx(k)) + { + found = true; + break; + } + if (found) + { + retval.xridx (ii) = l; + retval.xdata (ii++) = b.data(k) / data (i); + } + } + retval.xcidx(j+1) = ii; + } + + if (calc_cond) + { + double dmax = 0., dmin = octave_Inf; + for (octave_idx_type i = 0; i < nm; i++) + { + double tmp = fabs(data(i)); + if (tmp > dmax) + dmax = tmp; + if (tmp < dmin) + dmin = tmp; + } + rcond = dmin / dmax; + } + else + rcond = 1.; + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -1649,9 +1649,9 @@ Matrix SparseMatrix::utsolve (MatrixType &mattype, const Matrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { Matrix retval; @@ -1672,211 +1672,211 @@ mattype.info (); if (typ == MatrixType::Permuted_Upper || - typ == MatrixType::Upper) - { - double anorm = 0.; - double ainvnorm = 0.; - octave_idx_type b_nc = b.cols (); - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - if (typ == MatrixType::Permuted_Upper) - { - retval.resize (nc, b_nc); - octave_idx_type *perm = mattype.triangular_perm (); - OCTAVE_LOCAL_BUFFER (double, work, nm); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - work[i] = b(i,j); - for (octave_idx_type i = nr; i < nc; i++) - work[i] = 0.; - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - octave_idx_type kidx = perm[k]; - - if (work[k] != 0.) - { - if (ridx(cidx(kidx+1)-1) != k || - data(cidx(kidx+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(cidx(kidx+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(kidx); - i < cidx(kidx+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval.xelem (perm[i], j) = work[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - octave_idx_type iidx = perm[k]; - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(iidx+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(iidx); - i < cidx(iidx+1)-1; i++) - { - octave_idx_type idx2 = ridx(i); - work[idx2] = work[idx2] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (double, work, nm); - retval.resize (nc, b_nc); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - work[i] = b(i,j); - for (octave_idx_type i = nr; i < nc; i++) - work[i] = 0.; - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - if (work[k] != 0.) - { - if (ridx(cidx(k+1)-1) != k || - data(cidx(k+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(cidx(k+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval.xelem (i, j) = work[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Upper) + { + double anorm = 0.; + double ainvnorm = 0.; + octave_idx_type b_nc = b.cols (); + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + if (typ == MatrixType::Permuted_Upper) + { + retval.resize (nc, b_nc); + octave_idx_type *perm = mattype.triangular_perm (); + OCTAVE_LOCAL_BUFFER (double, work, nm); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + work[i] = b(i,j); + for (octave_idx_type i = nr; i < nc; i++) + work[i] = 0.; + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + octave_idx_type kidx = perm[k]; + + if (work[k] != 0.) + { + if (ridx(cidx(kidx+1)-1) != k || + data(cidx(kidx+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(cidx(kidx+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(kidx); + i < cidx(kidx+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval.xelem (perm[i], j) = work[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + octave_idx_type iidx = perm[k]; + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(iidx+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(iidx); + i < cidx(iidx+1)-1; i++) + { + octave_idx_type idx2 = ridx(i); + work[idx2] = work[idx2] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (double, work, nm); + retval.resize (nc, b_nc); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + work[i] = b(i,j); + for (octave_idx_type i = nr; i < nc; i++) + work[i] = 0.; + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + if (work[k] != 0.) + { + if (ridx(cidx(k+1)-1) != k || + data(cidx(k+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(cidx(k+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval.xelem (i, j) = work[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -1884,9 +1884,9 @@ SparseMatrix SparseMatrix::utsolve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseMatrix retval; @@ -1907,273 +1907,273 @@ mattype.info (); if (typ == MatrixType::Permuted_Upper || - typ == MatrixType::Upper) - { - double anorm = 0.; - double ainvnorm = 0.; - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - octave_idx_type b_nc = b.cols (); - octave_idx_type b_nz = b.nnz (); - retval = SparseMatrix (nc, b_nc, b_nz); - retval.xcidx(0) = 0; - octave_idx_type ii = 0; - octave_idx_type x_nz = b_nz; - - if (typ == MatrixType::Permuted_Upper) - { - octave_idx_type *perm = mattype.triangular_perm (); - OCTAVE_LOCAL_BUFFER (double, work, nm); - - OCTAVE_LOCAL_BUFFER (octave_idx_type, rperm, nc); - for (octave_idx_type i = 0; i < nc; i++) - rperm[perm[i]] = i; - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - work[b.ridx(i)] = b.data(i); - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - octave_idx_type kidx = perm[k]; - - if (work[k] != 0.) - { - if (ridx(cidx(kidx+1)-1) != k || - data(cidx(kidx+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(cidx(kidx+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(kidx); - i < cidx(kidx+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (work[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (work[rperm[i]] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = work[rperm[i]]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - octave_idx_type iidx = perm[k]; - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(iidx+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(iidx); - i < cidx(iidx+1)-1; i++) - { - octave_idx_type idx2 = ridx(i); - work[idx2] = work[idx2] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (double, work, nm); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - work[b.ridx(i)] = b.data(i); - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - if (work[k] != 0.) - { - if (ridx(cidx(k+1)-1) != k || - data(cidx(k+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(cidx(k+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (work[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (work[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = work[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(k); - i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Upper) + { + double anorm = 0.; + double ainvnorm = 0.; + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + octave_idx_type b_nc = b.cols (); + octave_idx_type b_nz = b.nnz (); + retval = SparseMatrix (nc, b_nc, b_nz); + retval.xcidx(0) = 0; + octave_idx_type ii = 0; + octave_idx_type x_nz = b_nz; + + if (typ == MatrixType::Permuted_Upper) + { + octave_idx_type *perm = mattype.triangular_perm (); + OCTAVE_LOCAL_BUFFER (double, work, nm); + + OCTAVE_LOCAL_BUFFER (octave_idx_type, rperm, nc); + for (octave_idx_type i = 0; i < nc; i++) + rperm[perm[i]] = i; + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + work[b.ridx(i)] = b.data(i); + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + octave_idx_type kidx = perm[k]; + + if (work[k] != 0.) + { + if (ridx(cidx(kidx+1)-1) != k || + data(cidx(kidx+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(cidx(kidx+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(kidx); + i < cidx(kidx+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (work[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (work[rperm[i]] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = work[rperm[i]]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + octave_idx_type iidx = perm[k]; + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(iidx+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(iidx); + i < cidx(iidx+1)-1; i++) + { + octave_idx_type idx2 = ridx(i); + work[idx2] = work[idx2] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (double, work, nm); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + work[b.ridx(i)] = b.data(i); + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + if (work[k] != 0.) + { + if (ridx(cidx(k+1)-1) != k || + data(cidx(k+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(cidx(k+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (work[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (work[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = work[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(k); + i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; } ComplexMatrix SparseMatrix::utsolve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { ComplexMatrix retval; @@ -2194,214 +2194,214 @@ mattype.info (); if (typ == MatrixType::Permuted_Upper || - typ == MatrixType::Upper) - { - double anorm = 0.; - double ainvnorm = 0.; - octave_idx_type b_nc = b.cols (); - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - if (typ == MatrixType::Permuted_Upper) - { - retval.resize (nc, b_nc); - octave_idx_type *perm = mattype.triangular_perm (); - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - cwork[i] = b(i,j); - for (octave_idx_type i = nr; i < nc; i++) - cwork[i] = 0.; - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - octave_idx_type kidx = perm[k]; - - if (cwork[k] != 0.) - { - if (ridx(cidx(kidx+1)-1) != k || - data(cidx(kidx+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(cidx(kidx+1)-1); - cwork[k] = tmp; - for (octave_idx_type i = cidx(kidx); - i < cidx(kidx+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval.xelem (perm[i], j) = cwork[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - octave_idx_type iidx = perm[k]; - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(iidx+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(iidx); - i < cidx(iidx+1)-1; i++) - { - octave_idx_type idx2 = ridx(i); - work[idx2] = work[idx2] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - retval.resize (nc, b_nc); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - cwork[i] = b(i,j); - for (octave_idx_type i = nr; i < nc; i++) - cwork[i] = 0.; - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - if (cwork[k] != 0.) - { - if (ridx(cidx(k+1)-1) != k || - data(cidx(k+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(cidx(k+1)-1); - cwork[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval.xelem (i, j) = cwork[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(k); - i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Upper) + { + double anorm = 0.; + double ainvnorm = 0.; + octave_idx_type b_nc = b.cols (); + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + if (typ == MatrixType::Permuted_Upper) + { + retval.resize (nc, b_nc); + octave_idx_type *perm = mattype.triangular_perm (); + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + cwork[i] = b(i,j); + for (octave_idx_type i = nr; i < nc; i++) + cwork[i] = 0.; + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + octave_idx_type kidx = perm[k]; + + if (cwork[k] != 0.) + { + if (ridx(cidx(kidx+1)-1) != k || + data(cidx(kidx+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(cidx(kidx+1)-1); + cwork[k] = tmp; + for (octave_idx_type i = cidx(kidx); + i < cidx(kidx+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval.xelem (perm[i], j) = cwork[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + octave_idx_type iidx = perm[k]; + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(iidx+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(iidx); + i < cidx(iidx+1)-1; i++) + { + octave_idx_type idx2 = ridx(i); + work[idx2] = work[idx2] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + retval.resize (nc, b_nc); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + cwork[i] = b(i,j); + for (octave_idx_type i = nr; i < nc; i++) + cwork[i] = 0.; + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + if (cwork[k] != 0.) + { + if (ridx(cidx(k+1)-1) != k || + data(cidx(k+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(cidx(k+1)-1); + cwork[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval.xelem (i, j) = cwork[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(k); + i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -2409,9 +2409,9 @@ SparseComplexMatrix SparseMatrix::utsolve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseComplexMatrix retval; @@ -2432,266 +2432,266 @@ mattype.info (); if (typ == MatrixType::Permuted_Upper || - typ == MatrixType::Upper) - { - double anorm = 0.; - double ainvnorm = 0.; - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - octave_idx_type b_nc = b.cols (); - octave_idx_type b_nz = b.nnz (); - retval = SparseComplexMatrix (nc, b_nc, b_nz); - retval.xcidx(0) = 0; - octave_idx_type ii = 0; - octave_idx_type x_nz = b_nz; - - if (typ == MatrixType::Permuted_Upper) - { - octave_idx_type *perm = mattype.triangular_perm (); - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - - OCTAVE_LOCAL_BUFFER (octave_idx_type, rperm, nc); - for (octave_idx_type i = 0; i < nc; i++) - rperm[perm[i]] = i; - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - cwork[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - cwork[b.ridx(i)] = b.data(i); - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - octave_idx_type kidx = perm[k]; - - if (cwork[k] != 0.) - { - if (ridx(cidx(kidx+1)-1) != k || - data(cidx(kidx+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(cidx(kidx+1)-1); - cwork[k] = tmp; - for (octave_idx_type i = cidx(kidx); - i < cidx(kidx+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[rperm[i]] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = cwork[rperm[i]]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - octave_idx_type iidx = perm[k]; - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(iidx+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(iidx); - i < cidx(iidx+1)-1; i++) - { - octave_idx_type idx2 = ridx(i); - work[idx2] = work[idx2] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - cwork[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - cwork[b.ridx(i)] = b.data(i); - - for (octave_idx_type k = nc-1; k >= 0; k--) - { - if (cwork[k] != 0.) - { - if (ridx(cidx(k+1)-1) != k || - data(cidx(k+1)-1) == 0.) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(cidx(k+1)-1); - cwork[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = cwork[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k >= 0; k--) - { - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k+1)-1); - work[k] = tmp; - for (octave_idx_type i = cidx(k); - i < cidx(k+1)-1; i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = 0; i < j+1; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Upper) + { + double anorm = 0.; + double ainvnorm = 0.; + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + octave_idx_type b_nc = b.cols (); + octave_idx_type b_nz = b.nnz (); + retval = SparseComplexMatrix (nc, b_nc, b_nz); + retval.xcidx(0) = 0; + octave_idx_type ii = 0; + octave_idx_type x_nz = b_nz; + + if (typ == MatrixType::Permuted_Upper) + { + octave_idx_type *perm = mattype.triangular_perm (); + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + + OCTAVE_LOCAL_BUFFER (octave_idx_type, rperm, nc); + for (octave_idx_type i = 0; i < nc; i++) + rperm[perm[i]] = i; + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + cwork[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + cwork[b.ridx(i)] = b.data(i); + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + octave_idx_type kidx = perm[k]; + + if (cwork[k] != 0.) + { + if (ridx(cidx(kidx+1)-1) != k || + data(cidx(kidx+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(cidx(kidx+1)-1); + cwork[k] = tmp; + for (octave_idx_type i = cidx(kidx); + i < cidx(kidx+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[rperm[i]] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = cwork[rperm[i]]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + octave_idx_type iidx = perm[k]; + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(iidx+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(iidx); + i < cidx(iidx+1)-1; i++) + { + octave_idx_type idx2 = ridx(i); + work[idx2] = work[idx2] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + cwork[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + cwork[b.ridx(i)] = b.data(i); + + for (octave_idx_type k = nc-1; k >= 0; k--) + { + if (cwork[k] != 0.) + { + if (ridx(cidx(k+1)-1) != k || + data(cidx(k+1)-1) == 0.) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(cidx(k+1)-1); + cwork[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = cwork[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k >= 0; k--) + { + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k+1)-1); + work[k] = tmp; + for (octave_idx_type i = cidx(k); + i < cidx(k+1)-1; i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = 0; i < j+1; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -2699,9 +2699,9 @@ Matrix SparseMatrix::ltsolve (MatrixType &mattype, const Matrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { Matrix retval; @@ -2722,236 +2722,236 @@ mattype.info (); if (typ == MatrixType::Permuted_Lower || - typ == MatrixType::Lower) - { - double anorm = 0.; - double ainvnorm = 0.; - octave_idx_type b_nc = b.cols (); - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - if (typ == MatrixType::Permuted_Lower) - { - retval.resize (nc, b_nc); - OCTAVE_LOCAL_BUFFER (double, work, nm); - octave_idx_type *perm = mattype.triangular_perm (); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - if (nc > nr) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - for (octave_idx_type i = 0; i < nr; i++) - work[perm[i]] = b(i,j); - - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - if (minr != k || data(mini) == 0) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(mini); - work[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval (i, j) = work[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - double tmp = work[k] / data(mini); - work[k] = tmp; - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - double atmp = 0; - for (octave_idx_type i = j; i < nc; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (double, work, nm); - retval.resize (nc, b_nc, 0.); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - work[i] = b(i,j); - for (octave_idx_type i = nr; i < nc; i++) - work[i] = 0.; - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - if (ridx(cidx(k)) != k || - data(cidx(k)) == 0.) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(cidx(k)); - work[k] = tmp; - for (octave_idx_type i = cidx(k)+1; - i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval.xelem (i, j) = work[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k < nc; k++) - { - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k)); - work[k] = tmp; - for (octave_idx_type i = cidx(k)+1; - i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = j; i < nc; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Lower) + { + double anorm = 0.; + double ainvnorm = 0.; + octave_idx_type b_nc = b.cols (); + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + if (typ == MatrixType::Permuted_Lower) + { + retval.resize (nc, b_nc); + OCTAVE_LOCAL_BUFFER (double, work, nm); + octave_idx_type *perm = mattype.triangular_perm (); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + if (nc > nr) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + for (octave_idx_type i = 0; i < nr; i++) + work[perm[i]] = b(i,j); + + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + if (minr != k || data(mini) == 0) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(mini); + work[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval (i, j) = work[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + double tmp = work[k] / data(mini); + work[k] = tmp; + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + double atmp = 0; + for (octave_idx_type i = j; i < nc; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (double, work, nm); + retval.resize (nc, b_nc, 0.); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + work[i] = b(i,j); + for (octave_idx_type i = nr; i < nc; i++) + work[i] = 0.; + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + if (ridx(cidx(k)) != k || + data(cidx(k)) == 0.) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(cidx(k)); + work[k] = tmp; + for (octave_idx_type i = cidx(k)+1; + i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval.xelem (i, j) = work[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k < nc; k++) + { + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k)); + work[k] = tmp; + for (octave_idx_type i = cidx(k)+1; + i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = j; i < nc; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -2959,9 +2959,9 @@ SparseMatrix SparseMatrix::ltsolve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseMatrix retval; @@ -2982,283 +2982,283 @@ mattype.info (); if (typ == MatrixType::Permuted_Lower || - typ == MatrixType::Lower) - { - double anorm = 0.; - double ainvnorm = 0.; - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - octave_idx_type b_nc = b.cols (); - octave_idx_type b_nz = b.nnz (); - retval = SparseMatrix (nc, b_nc, b_nz); - retval.xcidx(0) = 0; - octave_idx_type ii = 0; - octave_idx_type x_nz = b_nz; - - if (typ == MatrixType::Permuted_Lower) - { - OCTAVE_LOCAL_BUFFER (double, work, nm); - octave_idx_type *perm = mattype.triangular_perm (); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - work[perm[b.ridx(i)]] = b.data(i); - - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - if (minr != k || data(mini) == 0) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(mini); - work[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (work[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (work[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = work[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - double tmp = work[k] / data(mini); - work[k] = tmp; - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - double atmp = 0; - for (octave_idx_type i = j; i < nr; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (double, work, nm); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - work[b.ridx(i)] = b.data(i); - - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - if (ridx(cidx(k)) != k || - data(cidx(k)) == 0.) - { - err = -2; - goto triangular_error; - } - - double tmp = work[k] / data(cidx(k)); - work[k] = tmp; - for (octave_idx_type i = cidx(k)+1; i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (work[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (work[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = work[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k < nc; k++) - { - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k)); - work[k] = tmp; - for (octave_idx_type i = cidx(k)+1; - i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = j; i < nc; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Lower) + { + double anorm = 0.; + double ainvnorm = 0.; + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + octave_idx_type b_nc = b.cols (); + octave_idx_type b_nz = b.nnz (); + retval = SparseMatrix (nc, b_nc, b_nz); + retval.xcidx(0) = 0; + octave_idx_type ii = 0; + octave_idx_type x_nz = b_nz; + + if (typ == MatrixType::Permuted_Lower) + { + OCTAVE_LOCAL_BUFFER (double, work, nm); + octave_idx_type *perm = mattype.triangular_perm (); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + work[perm[b.ridx(i)]] = b.data(i); + + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + if (minr != k || data(mini) == 0) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(mini); + work[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (work[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (work[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = work[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + double tmp = work[k] / data(mini); + work[k] = tmp; + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + double atmp = 0; + for (octave_idx_type i = j; i < nr; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (double, work, nm); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + work[b.ridx(i)] = b.data(i); + + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + if (ridx(cidx(k)) != k || + data(cidx(k)) == 0.) + { + err = -2; + goto triangular_error; + } + + double tmp = work[k] / data(cidx(k)); + work[k] = tmp; + for (octave_idx_type i = cidx(k)+1; i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (work[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (work[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = work[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k < nc; k++) + { + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k)); + work[k] = tmp; + for (octave_idx_type i = cidx(k)+1; + i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = j; i < nc; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -3266,9 +3266,9 @@ ComplexMatrix SparseMatrix::ltsolve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { ComplexMatrix retval; @@ -3289,237 +3289,237 @@ mattype.info (); if (typ == MatrixType::Permuted_Lower || - typ == MatrixType::Lower) - { - double anorm = 0.; - double ainvnorm = 0.; - octave_idx_type b_nc = b.cols (); - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - if (typ == MatrixType::Permuted_Lower) - { - retval.resize (nc, b_nc); - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - octave_idx_type *perm = mattype.triangular_perm (); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - cwork[i] = 0.; - for (octave_idx_type i = 0; i < nr; i++) - cwork[perm[i]] = b(i,j); - - for (octave_idx_type k = 0; k < nc; k++) - { - if (cwork[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - if (minr != k || data(mini) == 0) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(mini); - cwork[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval (i, j) = cwork[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - double tmp = work[k] / data(mini); - work[k] = tmp; - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - double atmp = 0; - for (octave_idx_type i = j; i < nc; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - retval.resize (nc, b_nc, 0.); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - cwork[i] = b(i,j); - for (octave_idx_type i = nr; i < nc; i++) - cwork[i] = 0.; - - for (octave_idx_type k = 0; k < nc; k++) - { - if (cwork[k] != 0.) - { - if (ridx(cidx(k)) != k || - data(cidx(k)) == 0.) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(cidx(k)); - cwork[k] = tmp; - for (octave_idx_type i = cidx(k)+1; i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - for (octave_idx_type i = 0; i < nc; i++) - retval.xelem (i, j) = cwork[i]; - } - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k < nc; k++) - { - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k)); - work[k] = tmp; - for (octave_idx_type i = cidx(k)+1; - i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = j; i < nc; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Lower) + { + double anorm = 0.; + double ainvnorm = 0.; + octave_idx_type b_nc = b.cols (); + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + if (typ == MatrixType::Permuted_Lower) + { + retval.resize (nc, b_nc); + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + octave_idx_type *perm = mattype.triangular_perm (); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + cwork[i] = 0.; + for (octave_idx_type i = 0; i < nr; i++) + cwork[perm[i]] = b(i,j); + + for (octave_idx_type k = 0; k < nc; k++) + { + if (cwork[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + if (minr != k || data(mini) == 0) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(mini); + cwork[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval (i, j) = cwork[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + double tmp = work[k] / data(mini); + work[k] = tmp; + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + double atmp = 0; + for (octave_idx_type i = j; i < nc; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + retval.resize (nc, b_nc, 0.); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + cwork[i] = b(i,j); + for (octave_idx_type i = nr; i < nc; i++) + cwork[i] = 0.; + + for (octave_idx_type k = 0; k < nc; k++) + { + if (cwork[k] != 0.) + { + if (ridx(cidx(k)) != k || + data(cidx(k)) == 0.) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(cidx(k)); + cwork[k] = tmp; + for (octave_idx_type i = cidx(k)+1; i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + for (octave_idx_type i = 0; i < nc; i++) + retval.xelem (i, j) = cwork[i]; + } + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k < nc; k++) + { + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k)); + work[k] = tmp; + for (octave_idx_type i = cidx(k)+1; + i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = j; i < nc; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -3527,9 +3527,9 @@ SparseComplexMatrix SparseMatrix::ltsolve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseComplexMatrix retval; @@ -3550,285 +3550,285 @@ mattype.info (); if (typ == MatrixType::Permuted_Lower || - typ == MatrixType::Lower) - { - double anorm = 0.; - double ainvnorm = 0.; - rcond = 1.; - - if (calc_cond) - { - // Calculate the 1-norm of matrix for rcond calculation - for (octave_idx_type j = 0; j < nc; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - octave_idx_type b_nc = b.cols (); - octave_idx_type b_nz = b.nnz (); - retval = SparseComplexMatrix (nc, b_nc, b_nz); - retval.xcidx(0) = 0; - octave_idx_type ii = 0; - octave_idx_type x_nz = b_nz; - - if (typ == MatrixType::Permuted_Lower) - { - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - octave_idx_type *perm = mattype.triangular_perm (); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - cwork[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - cwork[perm[b.ridx(i)]] = b.data(i); - - for (octave_idx_type k = 0; k < nc; k++) - { - if (cwork[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - if (minr != k || data(mini) == 0) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(mini); - cwork[k] = tmp; - for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = cwork[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = 0; k < nc; k++) - { - if (work[k] != 0.) - { - octave_idx_type minr = nr; - octave_idx_type mini = 0; - - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - if (perm[ridx(i)] < minr) - { - minr = perm[ridx(i)]; - mini = i; - } - - double tmp = work[k] / data(mini); - work[k] = tmp; - for (octave_idx_type i = cidx(k); - i < cidx(k+1); i++) - { - if (i == mini) - continue; - - octave_idx_type iidx = perm[ridx(i)]; - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - - double atmp = 0; - for (octave_idx_type i = j; i < nc; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - else - { - OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nm; i++) - cwork[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - cwork[b.ridx(i)] = b.data(i); - - for (octave_idx_type k = 0; k < nc; k++) - { - if (cwork[k] != 0.) - { - if (ridx(cidx(k)) != k || - data(cidx(k)) == 0.) - { - err = -2; - goto triangular_error; - } - - Complex tmp = cwork[k] / data(cidx(k)); - cwork[k] = tmp; - for (octave_idx_type i = cidx(k)+1; i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - cwork[iidx] = cwork[iidx] - tmp * data(i); - } - } - } - - // Count non-zeros in work vector and adjust space in - // retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nc; i++) - if (cwork[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = cwork[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - if (calc_cond) - { - // Calculation of 1-norm of inv(*this) - OCTAVE_LOCAL_BUFFER (double, work, nm); - for (octave_idx_type i = 0; i < nm; i++) - work[i] = 0.; - - for (octave_idx_type j = 0; j < nr; j++) - { - work[j] = 1.; - - for (octave_idx_type k = j; k < nc; k++) - { - - if (work[k] != 0.) - { - double tmp = work[k] / data(cidx(k)); - work[k] = tmp; - for (octave_idx_type i = cidx(k)+1; - i < cidx(k+1); i++) - { - octave_idx_type iidx = ridx(i); - work[iidx] = work[iidx] - tmp * data(i); - } - } - } - double atmp = 0; - for (octave_idx_type i = j; i < nc; i++) - { - atmp += fabs(work[i]); - work[i] = 0.; - } - if (atmp > ainvnorm) - ainvnorm = atmp; - } - rcond = 1. / ainvnorm / anorm; - } - } - - triangular_error: - if (err != 0) - { - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - } - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } + typ == MatrixType::Lower) + { + double anorm = 0.; + double ainvnorm = 0.; + rcond = 1.; + + if (calc_cond) + { + // Calculate the 1-norm of matrix for rcond calculation + for (octave_idx_type j = 0; j < nc; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + octave_idx_type b_nc = b.cols (); + octave_idx_type b_nz = b.nnz (); + retval = SparseComplexMatrix (nc, b_nc, b_nz); + retval.xcidx(0) = 0; + octave_idx_type ii = 0; + octave_idx_type x_nz = b_nz; + + if (typ == MatrixType::Permuted_Lower) + { + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + octave_idx_type *perm = mattype.triangular_perm (); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + cwork[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + cwork[perm[b.ridx(i)]] = b.data(i); + + for (octave_idx_type k = 0; k < nc; k++) + { + if (cwork[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + if (minr != k || data(mini) == 0) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(mini); + cwork[k] = tmp; + for (octave_idx_type i = cidx(k); i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = cwork[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = 0; k < nc; k++) + { + if (work[k] != 0.) + { + octave_idx_type minr = nr; + octave_idx_type mini = 0; + + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + if (perm[ridx(i)] < minr) + { + minr = perm[ridx(i)]; + mini = i; + } + + double tmp = work[k] / data(mini); + work[k] = tmp; + for (octave_idx_type i = cidx(k); + i < cidx(k+1); i++) + { + if (i == mini) + continue; + + octave_idx_type iidx = perm[ridx(i)]; + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + + double atmp = 0; + for (octave_idx_type i = j; i < nc; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + else + { + OCTAVE_LOCAL_BUFFER (Complex, cwork, nm); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nm; i++) + cwork[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + cwork[b.ridx(i)] = b.data(i); + + for (octave_idx_type k = 0; k < nc; k++) + { + if (cwork[k] != 0.) + { + if (ridx(cidx(k)) != k || + data(cidx(k)) == 0.) + { + err = -2; + goto triangular_error; + } + + Complex tmp = cwork[k] / data(cidx(k)); + cwork[k] = tmp; + for (octave_idx_type i = cidx(k)+1; i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + cwork[iidx] = cwork[iidx] - tmp * data(i); + } + } + } + + // Count non-zeros in work vector and adjust space in + // retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nc; i++) + if (cwork[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = cwork[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + if (calc_cond) + { + // Calculation of 1-norm of inv(*this) + OCTAVE_LOCAL_BUFFER (double, work, nm); + for (octave_idx_type i = 0; i < nm; i++) + work[i] = 0.; + + for (octave_idx_type j = 0; j < nr; j++) + { + work[j] = 1.; + + for (octave_idx_type k = j; k < nc; k++) + { + + if (work[k] != 0.) + { + double tmp = work[k] / data(cidx(k)); + work[k] = tmp; + for (octave_idx_type i = cidx(k)+1; + i < cidx(k+1); i++) + { + octave_idx_type iidx = ridx(i); + work[iidx] = work[iidx] - tmp * data(i); + } + } + } + double atmp = 0; + for (octave_idx_type i = j; i < nc; i++) + { + atmp += fabs(work[i]); + work[i] = 0.; + } + if (atmp > ainvnorm) + ainvnorm = atmp; + } + rcond = 1. / ainvnorm / anorm; + } + } + + triangular_error: + if (err != 0) + { + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + } + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } else - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -3836,9 +3836,9 @@ Matrix SparseMatrix::trisolve (MatrixType &mattype, const Matrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { Matrix retval; @@ -3861,125 +3861,125 @@ mattype.info (); if (typ == MatrixType::Tridiagonal_Hermitian) - { - OCTAVE_LOCAL_BUFFER (double, D, nr); - OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); - - if (mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < nc-1; j++) - { - D[j] = data(ii++); - DL[j] = data(ii); - ii += 2; - } - D[nc-1] = data(ii); - } - else - { - D[0] = 0.; - for (octave_idx_type i = 0; i < nr - 1; i++) - { - D[i+1] = 0.; - DL[i] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) == j) - D[j] = data(i); - else if (ridx(i) == j + 1) - DL[j] = data(i); - } - } - - octave_idx_type b_nc = b.cols(); - retval = b; - double *result = retval.fortran_vec (); - - F77_XFCN (dptsv, DPTSV, (nr, b_nc, D, DL, result, - b.rows(), err)); - - if (err != 0) - { - err = 0; - mattype.mark_as_unsymmetric (); - typ = MatrixType::Tridiagonal; - } - else - rcond = 1.; - } + { + OCTAVE_LOCAL_BUFFER (double, D, nr); + OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); + + if (mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < nc-1; j++) + { + D[j] = data(ii++); + DL[j] = data(ii); + ii += 2; + } + D[nc-1] = data(ii); + } + else + { + D[0] = 0.; + for (octave_idx_type i = 0; i < nr - 1; i++) + { + D[i+1] = 0.; + DL[i] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) == j) + D[j] = data(i); + else if (ridx(i) == j + 1) + DL[j] = data(i); + } + } + + octave_idx_type b_nc = b.cols(); + retval = b; + double *result = retval.fortran_vec (); + + F77_XFCN (dptsv, DPTSV, (nr, b_nc, D, DL, result, + b.rows(), err)); + + if (err != 0) + { + err = 0; + mattype.mark_as_unsymmetric (); + typ = MatrixType::Tridiagonal; + } + else + rcond = 1.; + } if (typ == MatrixType::Tridiagonal) - { - OCTAVE_LOCAL_BUFFER (double, DU, nr - 1); - OCTAVE_LOCAL_BUFFER (double, D, nr); - OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); - - if (mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < nc-1; j++) - { - D[j] = data(ii++); - DL[j] = data(ii++); - DU[j] = data(ii++); - } - D[nc-1] = data(ii); - } - else - { - D[0] = 0.; - for (octave_idx_type i = 0; i < nr - 1; i++) - { - D[i+1] = 0.; - DL[i] = 0.; - DU[i] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) == j) - D[j] = data(i); - else if (ridx(i) == j + 1) - DL[j] = data(i); - else if (ridx(i) == j - 1) - DU[j-1] = data(i); - } - } - - octave_idx_type b_nc = b.cols(); - retval = b; - double *result = retval.fortran_vec (); - - F77_XFCN (dgtsv, DGTSV, (nr, b_nc, DL, D, DU, result, - b.rows(), err)); - - if (err != 0) - { - rcond = 0.; - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - - } - else - rcond = 1.; - } + { + OCTAVE_LOCAL_BUFFER (double, DU, nr - 1); + OCTAVE_LOCAL_BUFFER (double, D, nr); + OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); + + if (mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < nc-1; j++) + { + D[j] = data(ii++); + DL[j] = data(ii++); + DU[j] = data(ii++); + } + D[nc-1] = data(ii); + } + else + { + D[0] = 0.; + for (octave_idx_type i = 0; i < nr - 1; i++) + { + D[i+1] = 0.; + DL[i] = 0.; + DU[i] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) == j) + D[j] = data(i); + else if (ridx(i) == j + 1) + DL[j] = data(i); + else if (ridx(i) == j - 1) + DU[j-1] = data(i); + } + } + + octave_idx_type b_nc = b.cols(); + retval = b; + double *result = retval.fortran_vec (); + + F77_XFCN (dgtsv, DGTSV, (nr, b_nc, DL, D, DU, result, + b.rows(), err)); + + if (err != 0) + { + rcond = 0.; + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + + } + else + rcond = 1.; + } else if (typ != MatrixType::Tridiagonal_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -3987,9 +3987,9 @@ SparseMatrix SparseMatrix::trisolve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseMatrix retval; @@ -4013,120 +4013,120 @@ // Note can't treat symmetric case as there is no dpttrf function if (typ == MatrixType::Tridiagonal || - typ == MatrixType::Tridiagonal_Hermitian) - { - OCTAVE_LOCAL_BUFFER (double, DU2, nr - 2); - OCTAVE_LOCAL_BUFFER (double, DU, nr - 1); - OCTAVE_LOCAL_BUFFER (double, D, nr); - OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); - Array<octave_idx_type> ipvt (nr); - octave_idx_type *pipvt = ipvt.fortran_vec (); - - if (mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < nc-1; j++) - { - D[j] = data(ii++); - DL[j] = data(ii++); - DU[j] = data(ii++); - } - D[nc-1] = data(ii); - } - else - { - D[0] = 0.; - for (octave_idx_type i = 0; i < nr - 1; i++) - { - D[i+1] = 0.; - DL[i] = 0.; - DU[i] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) == j) - D[j] = data(i); - else if (ridx(i) == j + 1) - DL[j] = data(i); - else if (ridx(i) == j - 1) - DU[j-1] = data(i); - } - } - - F77_XFCN (dgttrf, DGTTRF, (nr, DL, D, DU, DU2, pipvt, err)); - - if (err != 0) - { - rcond = 0.0; - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - - } - else - { - rcond = 1.0; - char job = 'N'; - volatile octave_idx_type x_nz = b.nnz (); - octave_idx_type b_nc = b.cols (); - retval = SparseMatrix (nr, b_nc, x_nz); - retval.xcidx(0) = 0; - volatile octave_idx_type ii = 0; - - OCTAVE_LOCAL_BUFFER (double, work, nr); - - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - work[i] = 0.; - for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) - work[b.ridx(i)] = b.data(i); - - F77_XFCN (dgttrs, DGTTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, 1, DL, D, DU, DU2, pipvt, - work, b.rows (), err - F77_CHAR_ARG_LEN (1))); - - // Count non-zeros in work vector and adjust - // space in retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nr; i++) - if (work[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nr; i++) - if (work[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = work[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - } - } + typ == MatrixType::Tridiagonal_Hermitian) + { + OCTAVE_LOCAL_BUFFER (double, DU2, nr - 2); + OCTAVE_LOCAL_BUFFER (double, DU, nr - 1); + OCTAVE_LOCAL_BUFFER (double, D, nr); + OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); + Array<octave_idx_type> ipvt (nr); + octave_idx_type *pipvt = ipvt.fortran_vec (); + + if (mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < nc-1; j++) + { + D[j] = data(ii++); + DL[j] = data(ii++); + DU[j] = data(ii++); + } + D[nc-1] = data(ii); + } + else + { + D[0] = 0.; + for (octave_idx_type i = 0; i < nr - 1; i++) + { + D[i+1] = 0.; + DL[i] = 0.; + DU[i] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) == j) + D[j] = data(i); + else if (ridx(i) == j + 1) + DL[j] = data(i); + else if (ridx(i) == j - 1) + DU[j-1] = data(i); + } + } + + F77_XFCN (dgttrf, DGTTRF, (nr, DL, D, DU, DU2, pipvt, err)); + + if (err != 0) + { + rcond = 0.0; + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + + } + else + { + rcond = 1.0; + char job = 'N'; + volatile octave_idx_type x_nz = b.nnz (); + octave_idx_type b_nc = b.cols (); + retval = SparseMatrix (nr, b_nc, x_nz); + retval.xcidx(0) = 0; + volatile octave_idx_type ii = 0; + + OCTAVE_LOCAL_BUFFER (double, work, nr); + + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + work[i] = 0.; + for (octave_idx_type i = b.cidx(j); i < b.cidx(j+1); i++) + work[b.ridx(i)] = b.data(i); + + F77_XFCN (dgttrs, DGTTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, 1, DL, D, DU, DU2, pipvt, + work, b.rows (), err + F77_CHAR_ARG_LEN (1))); + + // Count non-zeros in work vector and adjust + // space in retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nr; i++) + if (work[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nr; i++) + if (work[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = work[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + } + } else if (typ != MatrixType::Tridiagonal_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -4134,9 +4134,9 @@ ComplexMatrix SparseMatrix::trisolve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { ComplexMatrix retval; @@ -4159,126 +4159,126 @@ mattype.info (); if (typ == MatrixType::Tridiagonal_Hermitian) - { - OCTAVE_LOCAL_BUFFER (double, D, nr); - OCTAVE_LOCAL_BUFFER (Complex, DL, nr - 1); - - if (mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < nc-1; j++) - { - D[j] = data(ii++); - DL[j] = data(ii); - ii += 2; - } - D[nc-1] = data(ii); - } - else - { - D[0] = 0.; - for (octave_idx_type i = 0; i < nr - 1; i++) - { - D[i+1] = 0.; - DL[i] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) == j) - D[j] = data(i); - else if (ridx(i) == j + 1) - DL[j] = data(i); - } - } - - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols(); - rcond = 1.; - - retval = b; - Complex *result = retval.fortran_vec (); - - F77_XFCN (zptsv, ZPTSV, (nr, b_nc, D, DL, result, - b_nr, err)); - - if (err != 0) - { - err = 0; - mattype.mark_as_unsymmetric (); - typ = MatrixType::Tridiagonal; - } - } + { + OCTAVE_LOCAL_BUFFER (double, D, nr); + OCTAVE_LOCAL_BUFFER (Complex, DL, nr - 1); + + if (mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < nc-1; j++) + { + D[j] = data(ii++); + DL[j] = data(ii); + ii += 2; + } + D[nc-1] = data(ii); + } + else + { + D[0] = 0.; + for (octave_idx_type i = 0; i < nr - 1; i++) + { + D[i+1] = 0.; + DL[i] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) == j) + D[j] = data(i); + else if (ridx(i) == j + 1) + DL[j] = data(i); + } + } + + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols(); + rcond = 1.; + + retval = b; + Complex *result = retval.fortran_vec (); + + F77_XFCN (zptsv, ZPTSV, (nr, b_nc, D, DL, result, + b_nr, err)); + + if (err != 0) + { + err = 0; + mattype.mark_as_unsymmetric (); + typ = MatrixType::Tridiagonal; + } + } if (typ == MatrixType::Tridiagonal) - { - OCTAVE_LOCAL_BUFFER (Complex, DU, nr - 1); - OCTAVE_LOCAL_BUFFER (Complex, D, nr); - OCTAVE_LOCAL_BUFFER (Complex, DL, nr - 1); - - if (mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < nc-1; j++) - { - D[j] = data(ii++); - DL[j] = data(ii++); - DU[j] = data(ii++); - } - D[nc-1] = data(ii); - } - else - { - D[0] = 0.; - for (octave_idx_type i = 0; i < nr - 1; i++) - { - D[i+1] = 0.; - DL[i] = 0.; - DU[i] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) == j) - D[j] = data(i); - else if (ridx(i) == j + 1) - DL[j] = data(i); - else if (ridx(i) == j - 1) - DU[j-1] = data(i); - } - } - - octave_idx_type b_nr = b.rows(); - octave_idx_type b_nc = b.cols(); - rcond = 1.; - - retval = b; - Complex *result = retval.fortran_vec (); - - F77_XFCN (zgtsv, ZGTSV, (nr, b_nc, DL, D, DU, result, - b_nr, err)); - - if (err != 0) - { - rcond = 0.; - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - } - } + { + OCTAVE_LOCAL_BUFFER (Complex, DU, nr - 1); + OCTAVE_LOCAL_BUFFER (Complex, D, nr); + OCTAVE_LOCAL_BUFFER (Complex, DL, nr - 1); + + if (mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < nc-1; j++) + { + D[j] = data(ii++); + DL[j] = data(ii++); + DU[j] = data(ii++); + } + D[nc-1] = data(ii); + } + else + { + D[0] = 0.; + for (octave_idx_type i = 0; i < nr - 1; i++) + { + D[i+1] = 0.; + DL[i] = 0.; + DU[i] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) == j) + D[j] = data(i); + else if (ridx(i) == j + 1) + DL[j] = data(i); + else if (ridx(i) == j - 1) + DU[j-1] = data(i); + } + } + + octave_idx_type b_nr = b.rows(); + octave_idx_type b_nc = b.cols(); + rcond = 1.; + + retval = b; + Complex *result = retval.fortran_vec (); + + F77_XFCN (zgtsv, ZGTSV, (nr, b_nc, DL, D, DU, result, + b_nr, err)); + + if (err != 0) + { + rcond = 0.; + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + } + } else if (typ != MatrixType::Tridiagonal_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -4286,9 +4286,9 @@ SparseComplexMatrix SparseMatrix::trisolve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseComplexMatrix retval; @@ -4312,152 +4312,152 @@ // Note can't treat symmetric case as there is no dpttrf function if (typ == MatrixType::Tridiagonal || - typ == MatrixType::Tridiagonal_Hermitian) - { - OCTAVE_LOCAL_BUFFER (double, DU2, nr - 2); - OCTAVE_LOCAL_BUFFER (double, DU, nr - 1); - OCTAVE_LOCAL_BUFFER (double, D, nr); - OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); - Array<octave_idx_type> ipvt (nr); - octave_idx_type *pipvt = ipvt.fortran_vec (); - - if (mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < nc-1; j++) - { - D[j] = data(ii++); - DL[j] = data(ii++); - DU[j] = data(ii++); - } - D[nc-1] = data(ii); - } - else - { - D[0] = 0.; - for (octave_idx_type i = 0; i < nr - 1; i++) - { - D[i+1] = 0.; - DL[i] = 0.; - DU[i] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - if (ridx(i) == j) - D[j] = data(i); - else if (ridx(i) == j + 1) - DL[j] = data(i); - else if (ridx(i) == j - 1) - DU[j-1] = data(i); - } - } - - F77_XFCN (dgttrf, DGTTRF, (nr, DL, D, DU, DU2, pipvt, err)); - - if (err != 0) - { - rcond = 0.0; - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - } - else - { - rcond = 1.; - char job = 'N'; - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); - - // Take a first guess that the number of non-zero terms - // will be as many as in b - volatile octave_idx_type x_nz = b.nnz (); - volatile octave_idx_type ii = 0; - retval = SparseComplexMatrix (b_nr, b_nc, x_nz); - - retval.xcidx(0) = 0; - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - - for (octave_idx_type i = 0; i < b_nr; i++) - { - Complex c = b (i,j); - Bx[i] = std::real (c); - Bz[i] = std::imag (c); - } - - F77_XFCN (dgttrs, DGTTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, 1, DL, D, DU, DU2, pipvt, - Bx, b_nr, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - - err = -1; - break; - } - - F77_XFCN (dgttrs, DGTTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, 1, DL, D, DU, DU2, pipvt, - Bz, b_nr, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - - err = -1; - break; - } - - // Count non-zeros in work vector and adjust - // space in retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nr; i++) - if (Bx[i] != 0. || Bz[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nr; i++) - if (Bx[i] != 0. || Bz[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = - Complex (Bx[i], Bz[i]); - } - - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - } - } + typ == MatrixType::Tridiagonal_Hermitian) + { + OCTAVE_LOCAL_BUFFER (double, DU2, nr - 2); + OCTAVE_LOCAL_BUFFER (double, DU, nr - 1); + OCTAVE_LOCAL_BUFFER (double, D, nr); + OCTAVE_LOCAL_BUFFER (double, DL, nr - 1); + Array<octave_idx_type> ipvt (nr); + octave_idx_type *pipvt = ipvt.fortran_vec (); + + if (mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < nc-1; j++) + { + D[j] = data(ii++); + DL[j] = data(ii++); + DU[j] = data(ii++); + } + D[nc-1] = data(ii); + } + else + { + D[0] = 0.; + for (octave_idx_type i = 0; i < nr - 1; i++) + { + D[i+1] = 0.; + DL[i] = 0.; + DU[i] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + if (ridx(i) == j) + D[j] = data(i); + else if (ridx(i) == j + 1) + DL[j] = data(i); + else if (ridx(i) == j - 1) + DU[j-1] = data(i); + } + } + + F77_XFCN (dgttrf, DGTTRF, (nr, DL, D, DU, DU2, pipvt, err)); + + if (err != 0) + { + rcond = 0.0; + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + } + else + { + rcond = 1.; + char job = 'N'; + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); + + // Take a first guess that the number of non-zero terms + // will be as many as in b + volatile octave_idx_type x_nz = b.nnz (); + volatile octave_idx_type ii = 0; + retval = SparseComplexMatrix (b_nr, b_nc, x_nz); + + retval.xcidx(0) = 0; + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + + for (octave_idx_type i = 0; i < b_nr; i++) + { + Complex c = b (i,j); + Bx[i] = std::real (c); + Bz[i] = std::imag (c); + } + + F77_XFCN (dgttrs, DGTTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, 1, DL, D, DU, DU2, pipvt, + Bx, b_nr, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + + err = -1; + break; + } + + F77_XFCN (dgttrs, DGTTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, 1, DL, D, DU, DU2, pipvt, + Bz, b_nr, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + + err = -1; + break; + } + + // Count non-zeros in work vector and adjust + // space in retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nr; i++) + if (Bx[i] != 0. || Bz[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nr; i++) + if (Bx[i] != 0. || Bz[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = + Complex (Bx[i], Bz[i]); + } + + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + } + } else if (typ != MatrixType::Tridiagonal_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -4465,9 +4465,9 @@ Matrix SparseMatrix::bsolve (MatrixType &mattype, const Matrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { Matrix retval; @@ -4487,226 +4487,226 @@ mattype.info (); if (typ == MatrixType::Banded_Hermitian) - { - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_lower + 1; - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - octave_idx_type ri = ridx (i); - if (ri >= j) - m_band(ri - j, j) = data(i); - } - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - anorm = m_band.abs().sum().row(0).max(); - - char job = 'L'; - F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - // Matrix is not positive definite!! Fall through to - // unsymmetric banded solver. - mattype.mark_as_unsymmetric (); - typ = MatrixType::Banded; - rcond = 0.0; - err = 0; - } - else - { - if (calc_cond) - { - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dpbcon, DPBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - retval = b; - double *result = retval.fortran_vec (); - - octave_idx_type b_nc = b.cols (); - - F77_XFCN (dpbtrs, DPBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, b_nc, tmp_data, - ldm, result, b.rows(), err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - err = -1; - } - } - } - } + { + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_lower + 1; + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + octave_idx_type ri = ridx (i); + if (ri >= j) + m_band(ri - j, j) = data(i); + } + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + anorm = m_band.abs().sum().row(0).max(); + + char job = 'L'; + F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + // Matrix is not positive definite!! Fall through to + // unsymmetric banded solver. + mattype.mark_as_unsymmetric (); + typ = MatrixType::Banded; + rcond = 0.0; + err = 0; + } + else + { + if (calc_cond) + { + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dpbcon, DPBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + retval = b; + double *result = retval.fortran_vec (); + + octave_idx_type b_nc = b.cols (); + + F77_XFCN (dpbtrs, DPBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, b_nc, tmp_data, + ldm, result, b.rows(), err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + err = -1; + } + } + } + } if (typ == MatrixType::Banded) - { - // Create the storage for the banded form of the sparse matrix - octave_idx_type n_upper = mattype.nupper (); - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_upper + 2 * n_lower + 1; - - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - { - for (octave_idx_type j = 0; j < nr; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - Array<octave_idx_type> ipvt (nr); - octave_idx_type *pipvt = ipvt.fortran_vec (); - - F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, - ldm, pipvt, err)); - - // Throw-away extra info LAPACK gives so as to not - // change output. - if (err != 0) - { - err = -2; - rcond = 0.0; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - - } - else - { - if (calc_cond) - { - char job = '1'; - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dgbcon, DGBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nc, n_lower, n_upper, tmp_data, ldm, pipvt, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - retval = b; - double *result = retval.fortran_vec (); - - octave_idx_type b_nc = b.cols (); - - char job = 'N'; - F77_XFCN (dgbtrs, DGBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, n_upper, b_nc, tmp_data, - ldm, pipvt, result, b.rows(), err - F77_CHAR_ARG_LEN (1))); - } - } - } + { + // Create the storage for the banded form of the sparse matrix + octave_idx_type n_upper = mattype.nupper (); + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_upper + 2 * n_lower + 1; + + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + { + for (octave_idx_type j = 0; j < nr; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + Array<octave_idx_type> ipvt (nr); + octave_idx_type *pipvt = ipvt.fortran_vec (); + + F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, + ldm, pipvt, err)); + + // Throw-away extra info LAPACK gives so as to not + // change output. + if (err != 0) + { + err = -2; + rcond = 0.0; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + + } + else + { + if (calc_cond) + { + char job = '1'; + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dgbcon, DGBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nc, n_lower, n_upper, tmp_data, ldm, pipvt, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + retval = b; + double *result = retval.fortran_vec (); + + octave_idx_type b_nc = b.cols (); + + char job = 'N'; + F77_XFCN (dgbtrs, DGBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, n_upper, b_nc, tmp_data, + ldm, pipvt, result, b.rows(), err + F77_CHAR_ARG_LEN (1))); + } + } + } else if (typ != MatrixType::Banded_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -4714,9 +4714,9 @@ SparseMatrix SparseMatrix::bsolve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseMatrix retval; @@ -4736,295 +4736,295 @@ mattype.info (); if (typ == MatrixType::Banded_Hermitian) - { - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_lower + 1; - - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - octave_idx_type ri = ridx (i); - if (ri >= j) - m_band(ri - j, j) = data(i); - } - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - anorm = m_band.abs().sum().row(0).max(); - - char job = 'L'; - F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - mattype.mark_as_unsymmetric (); - typ = MatrixType::Banded; - rcond = 0.0; - err = 0; - } - else - { - if (calc_cond) - { - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dpbcon, DPBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); - - // Take a first guess that the number of non-zero terms - // will be as many as in b - volatile octave_idx_type x_nz = b.nnz (); - volatile octave_idx_type ii = 0; - retval = SparseMatrix (b_nr, b_nc, x_nz); - - retval.xcidx(0) = 0; - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < b_nr; i++) - Bx[i] = b.elem (i, j); - - F77_XFCN (dpbtrs, DPBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, 1, tmp_data, - ldm, Bx, b_nr, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - err = -1; - break; - } - - for (octave_idx_type i = 0; i < b_nr; i++) - { - double tmp = Bx[i]; - if (tmp != 0.0) - { - if (ii == x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = x_nz * - (b_nc - j) / b_nc; - sz = (sz > 10 ? sz : 10) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - retval.xdata(ii) = tmp; - retval.xridx(ii++) = i; - } - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - } - } - } + { + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_lower + 1; + + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + octave_idx_type ri = ridx (i); + if (ri >= j) + m_band(ri - j, j) = data(i); + } + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + anorm = m_band.abs().sum().row(0).max(); + + char job = 'L'; + F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + mattype.mark_as_unsymmetric (); + typ = MatrixType::Banded; + rcond = 0.0; + err = 0; + } + else + { + if (calc_cond) + { + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dpbcon, DPBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); + + // Take a first guess that the number of non-zero terms + // will be as many as in b + volatile octave_idx_type x_nz = b.nnz (); + volatile octave_idx_type ii = 0; + retval = SparseMatrix (b_nr, b_nc, x_nz); + + retval.xcidx(0) = 0; + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < b_nr; i++) + Bx[i] = b.elem (i, j); + + F77_XFCN (dpbtrs, DPBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, 1, tmp_data, + ldm, Bx, b_nr, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + err = -1; + break; + } + + for (octave_idx_type i = 0; i < b_nr; i++) + { + double tmp = Bx[i]; + if (tmp != 0.0) + { + if (ii == x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = x_nz * + (b_nc - j) / b_nc; + sz = (sz > 10 ? sz : 10) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + retval.xdata(ii) = tmp; + retval.xridx(ii++) = i; + } + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + } + } + } if (typ == MatrixType::Banded) - { - // Create the storage for the banded form of the sparse matrix - octave_idx_type n_upper = mattype.nupper (); - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_upper + 2 * n_lower + 1; - - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - { - for (octave_idx_type j = 0; j < nr; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - Array<octave_idx_type> ipvt (nr); - octave_idx_type *pipvt = ipvt.fortran_vec (); - - F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, - ldm, pipvt, err)); - - if (err != 0) - { - err = -2; - rcond = 0.0; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - - } - else - { - if (calc_cond) - { - char job = '1'; - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dgbcon, DGBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nc, n_lower, n_upper, tmp_data, ldm, pipvt, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - char job = 'N'; - volatile octave_idx_type x_nz = b.nnz (); - octave_idx_type b_nc = b.cols (); - retval = SparseMatrix (nr, b_nc, x_nz); - retval.xcidx(0) = 0; - volatile octave_idx_type ii = 0; - - OCTAVE_LOCAL_BUFFER (double, work, nr); - - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - work[i] = 0.; - for (octave_idx_type i = b.cidx(j); - i < b.cidx(j+1); i++) - work[b.ridx(i)] = b.data(i); - - F77_XFCN (dgbtrs, DGBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, n_upper, 1, tmp_data, - ldm, pipvt, work, b.rows (), err - F77_CHAR_ARG_LEN (1))); - - // Count non-zeros in work vector and adjust - // space in retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nr; i++) - if (work[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nr; i++) - if (work[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = work[i]; - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - } - } - } + { + // Create the storage for the banded form of the sparse matrix + octave_idx_type n_upper = mattype.nupper (); + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_upper + 2 * n_lower + 1; + + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + { + for (octave_idx_type j = 0; j < nr; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + Array<octave_idx_type> ipvt (nr); + octave_idx_type *pipvt = ipvt.fortran_vec (); + + F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, + ldm, pipvt, err)); + + if (err != 0) + { + err = -2; + rcond = 0.0; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + + } + else + { + if (calc_cond) + { + char job = '1'; + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dgbcon, DGBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nc, n_lower, n_upper, tmp_data, ldm, pipvt, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + char job = 'N'; + volatile octave_idx_type x_nz = b.nnz (); + octave_idx_type b_nc = b.cols (); + retval = SparseMatrix (nr, b_nc, x_nz); + retval.xcidx(0) = 0; + volatile octave_idx_type ii = 0; + + OCTAVE_LOCAL_BUFFER (double, work, nr); + + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + work[i] = 0.; + for (octave_idx_type i = b.cidx(j); + i < b.cidx(j+1); i++) + work[b.ridx(i)] = b.data(i); + + F77_XFCN (dgbtrs, DGBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, n_upper, 1, tmp_data, + ldm, pipvt, work, b.rows (), err + F77_CHAR_ARG_LEN (1))); + + // Count non-zeros in work vector and adjust + // space in retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nr; i++) + if (work[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nr; i++) + if (work[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = work[i]; + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + } + } + } else if (typ != MatrixType::Banded_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -5032,9 +5032,9 @@ ComplexMatrix SparseMatrix::bsolve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { ComplexMatrix retval; @@ -5054,276 +5054,276 @@ mattype.info (); if (typ == MatrixType::Banded_Hermitian) - { - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_lower + 1; - - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - octave_idx_type ri = ridx (i); - if (ri >= j) - m_band(ri - j, j) = data(i); - } - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - anorm = m_band.abs().sum().row(0).max(); - - char job = 'L'; - F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - // Matrix is not positive definite!! Fall through to - // unsymmetric banded solver. - mattype.mark_as_unsymmetric (); - typ = MatrixType::Banded; - rcond = 0.0; - err = 0; - } - else - { - if (calc_cond) - { - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dpbcon, DPBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - - OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); - - retval.resize (b_nr, b_nc); - - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < b_nr; i++) - { - Complex c = b (i,j); - Bx[i] = std::real (c); - Bz[i] = std::imag (c); - } - - F77_XFCN (dpbtrs, DPBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, 1, tmp_data, - ldm, Bx, b_nr, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - err = -1; - break; - } - - F77_XFCN (dpbtrs, DPBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, 1, tmp_data, - ldm, Bz, b.rows(), err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - err = -1; - break; - } - - for (octave_idx_type i = 0; i < b_nr; i++) - retval (i, j) = Complex (Bx[i], Bz[i]); - } - } - } - } + { + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_lower + 1; + + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + octave_idx_type ri = ridx (i); + if (ri >= j) + m_band(ri - j, j) = data(i); + } + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + anorm = m_band.abs().sum().row(0).max(); + + char job = 'L'; + F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + // Matrix is not positive definite!! Fall through to + // unsymmetric banded solver. + mattype.mark_as_unsymmetric (); + typ = MatrixType::Banded; + rcond = 0.0; + err = 0; + } + else + { + if (calc_cond) + { + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dpbcon, DPBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + + OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); + + retval.resize (b_nr, b_nc); + + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < b_nr; i++) + { + Complex c = b (i,j); + Bx[i] = std::real (c); + Bz[i] = std::imag (c); + } + + F77_XFCN (dpbtrs, DPBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, 1, tmp_data, + ldm, Bx, b_nr, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + err = -1; + break; + } + + F77_XFCN (dpbtrs, DPBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, 1, tmp_data, + ldm, Bz, b.rows(), err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + err = -1; + break; + } + + for (octave_idx_type i = 0; i < b_nr; i++) + retval (i, j) = Complex (Bx[i], Bz[i]); + } + } + } + } if (typ == MatrixType::Banded) - { - // Create the storage for the banded form of the sparse matrix - octave_idx_type n_upper = mattype.nupper (); - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_upper + 2 * n_lower + 1; - - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - { - for (octave_idx_type j = 0; j < nr; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - Array<octave_idx_type> ipvt (nr); - octave_idx_type *pipvt = ipvt.fortran_vec (); - - F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, - ldm, pipvt, err)); - - if (err != 0) - { - err = -2; - rcond = 0.0; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - - } - else - { - if (calc_cond) - { - char job = '1'; - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dpbcon, DPBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - char job = 'N'; - octave_idx_type b_nc = b.cols (); - retval.resize (nr,b_nc); - - OCTAVE_LOCAL_BUFFER (double, Bz, nr); - OCTAVE_LOCAL_BUFFER (double, Bx, nr); - - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - { - Complex c = b (i, j); - Bx[i] = std::real (c); - Bz[i] = std::imag (c); - } - - F77_XFCN (dgbtrs, DGBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, n_upper, 1, tmp_data, - ldm, pipvt, Bx, b.rows (), err - F77_CHAR_ARG_LEN (1))); - - F77_XFCN (dgbtrs, DGBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, n_upper, 1, tmp_data, - ldm, pipvt, Bz, b.rows (), err - F77_CHAR_ARG_LEN (1))); - - for (octave_idx_type i = 0; i < nr; i++) - retval (i, j) = Complex (Bx[i], Bz[i]); - } - } - } - } + { + // Create the storage for the banded form of the sparse matrix + octave_idx_type n_upper = mattype.nupper (); + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_upper + 2 * n_lower + 1; + + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + { + for (octave_idx_type j = 0; j < nr; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + Array<octave_idx_type> ipvt (nr); + octave_idx_type *pipvt = ipvt.fortran_vec (); + + F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, + ldm, pipvt, err)); + + if (err != 0) + { + err = -2; + rcond = 0.0; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + + } + else + { + if (calc_cond) + { + char job = '1'; + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dpbcon, DPBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + char job = 'N'; + octave_idx_type b_nc = b.cols (); + retval.resize (nr,b_nc); + + OCTAVE_LOCAL_BUFFER (double, Bz, nr); + OCTAVE_LOCAL_BUFFER (double, Bx, nr); + + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + { + Complex c = b (i, j); + Bx[i] = std::real (c); + Bz[i] = std::imag (c); + } + + F77_XFCN (dgbtrs, DGBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, n_upper, 1, tmp_data, + ldm, pipvt, Bx, b.rows (), err + F77_CHAR_ARG_LEN (1))); + + F77_XFCN (dgbtrs, DGBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, n_upper, 1, tmp_data, + ldm, pipvt, Bz, b.rows (), err + F77_CHAR_ARG_LEN (1))); + + for (octave_idx_type i = 0; i < nr; i++) + retval (i, j) = Complex (Bx[i], Bz[i]); + } + } + } + } else if (typ != MatrixType::Banded_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -5331,9 +5331,9 @@ SparseComplexMatrix SparseMatrix::bsolve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseComplexMatrix retval; @@ -5353,339 +5353,339 @@ mattype.info (); if (typ == MatrixType::Banded_Hermitian) - { - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_lower + 1; - - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - { - octave_idx_type ri = ridx (i); - if (ri >= j) - m_band(ri - j, j) = data(i); - } - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - anorm = m_band.abs().sum().row(0).max(); - - char job = 'L'; - F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - // Matrix is not positive definite!! Fall through to - // unsymmetric banded solver. - mattype.mark_as_unsymmetric (); - typ = MatrixType::Banded; - - rcond = 0.0; - err = 0; - } - else - { - if (calc_cond) - { - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dpbcon, DPBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, tmp_data, ldm, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); - - // Take a first guess that the number of non-zero terms - // will be as many as in b - volatile octave_idx_type x_nz = b.nnz (); - volatile octave_idx_type ii = 0; - retval = SparseComplexMatrix (b_nr, b_nc, x_nz); - - retval.xcidx(0) = 0; - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - - for (octave_idx_type i = 0; i < b_nr; i++) - { - Complex c = b (i,j); - Bx[i] = std::real (c); - Bz[i] = std::imag (c); - } - - F77_XFCN (dpbtrs, DPBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, 1, tmp_data, - ldm, Bx, b_nr, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - err = -1; - break; - } - - F77_XFCN (dpbtrs, DPBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, 1, tmp_data, - ldm, Bz, b_nr, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - - err = -1; - break; - } - - // Count non-zeros in work vector and adjust - // space in retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nr; i++) - if (Bx[i] != 0. || Bz[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nr; i++) - if (Bx[i] != 0. || Bz[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = - Complex (Bx[i], Bz[i]); - } - - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - } - } - } + { + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_lower + 1; + + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + { + octave_idx_type ri = ridx (i); + if (ri >= j) + m_band(ri - j, j) = data(i); + } + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + anorm = m_band.abs().sum().row(0).max(); + + char job = 'L'; + F77_XFCN (dpbtrf, DPBTRF, (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + // Matrix is not positive definite!! Fall through to + // unsymmetric banded solver. + mattype.mark_as_unsymmetric (); + typ = MatrixType::Banded; + + rcond = 0.0; + err = 0; + } + else + { + if (calc_cond) + { + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dpbcon, DPBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, tmp_data, ldm, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); + + // Take a first guess that the number of non-zero terms + // will be as many as in b + volatile octave_idx_type x_nz = b.nnz (); + volatile octave_idx_type ii = 0; + retval = SparseComplexMatrix (b_nr, b_nc, x_nz); + + retval.xcidx(0) = 0; + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + + for (octave_idx_type i = 0; i < b_nr; i++) + { + Complex c = b (i,j); + Bx[i] = std::real (c); + Bz[i] = std::imag (c); + } + + F77_XFCN (dpbtrs, DPBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, 1, tmp_data, + ldm, Bx, b_nr, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + err = -1; + break; + } + + F77_XFCN (dpbtrs, DPBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, 1, tmp_data, + ldm, Bz, b_nr, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + + err = -1; + break; + } + + // Count non-zeros in work vector and adjust + // space in retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nr; i++) + if (Bx[i] != 0. || Bz[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nr; i++) + if (Bx[i] != 0. || Bz[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = + Complex (Bx[i], Bz[i]); + } + + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + } + } + } if (typ == MatrixType::Banded) - { - // Create the storage for the banded form of the sparse matrix - octave_idx_type n_upper = mattype.nupper (); - octave_idx_type n_lower = mattype.nlower (); - octave_idx_type ldm = n_upper + 2 * n_lower + 1; - - Matrix m_band (ldm, nc); - double *tmp_data = m_band.fortran_vec (); - - if (! mattype.is_dense ()) - { - octave_idx_type ii = 0; - - for (octave_idx_type j = 0; j < ldm; j++) - for (octave_idx_type i = 0; i < nc; i++) - tmp_data[ii++] = 0.; - } - - for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); - - // Calculate the norm of the matrix, for later use. - double anorm; - if (calc_cond) - { - for (octave_idx_type j = 0; j < nr; j++) - { - double atmp = 0.; - for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) - atmp += fabs(data(i)); - if (atmp > anorm) - anorm = atmp; - } - } - - Array<octave_idx_type> ipvt (nr); - octave_idx_type *pipvt = ipvt.fortran_vec (); - - F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, - ldm, pipvt, err)); - - if (err != 0) - { - err = -2; - rcond = 0.0; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision"); - - } - else - { - if (calc_cond) - { - char job = '1'; - Array<double> z (3 * nr); - double *pz = z.fortran_vec (); - Array<octave_idx_type> iz (nr); - octave_idx_type *piz = iz.fortran_vec (); - - F77_XFCN (dgbcon, DGBCON, - (F77_CONST_CHAR_ARG2 (&job, 1), - nc, n_lower, n_upper, tmp_data, ldm, pipvt, - anorm, rcond, pz, piz, err - F77_CHAR_ARG_LEN (1))); - - if (err != 0) - err = -2; - - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("matrix singular to machine precision, rcond = %g", - rcond); - } - } - else - rcond = 1.; - - if (err == 0) - { - char job = 'N'; - volatile octave_idx_type x_nz = b.nnz (); - octave_idx_type b_nc = b.cols (); - retval = SparseComplexMatrix (nr, b_nc, x_nz); - retval.xcidx(0) = 0; - volatile octave_idx_type ii = 0; - - OCTAVE_LOCAL_BUFFER (double, Bx, nr); - OCTAVE_LOCAL_BUFFER (double, Bz, nr); - - for (volatile octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < nr; i++) - { - Bx[i] = 0.; - Bz[i] = 0.; - } - for (octave_idx_type i = b.cidx(j); - i < b.cidx(j+1); i++) - { - Complex c = b.data(i); - Bx[b.ridx(i)] = std::real (c); - Bz[b.ridx(i)] = std::imag (c); - } - - F77_XFCN (dgbtrs, DGBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, n_upper, 1, tmp_data, - ldm, pipvt, Bx, b.rows (), err - F77_CHAR_ARG_LEN (1))); - - F77_XFCN (dgbtrs, DGBTRS, - (F77_CONST_CHAR_ARG2 (&job, 1), - nr, n_lower, n_upper, 1, tmp_data, - ldm, pipvt, Bz, b.rows (), err - F77_CHAR_ARG_LEN (1))); - - // Count non-zeros in work vector and adjust - // space in retval if needed - octave_idx_type new_nnz = 0; - for (octave_idx_type i = 0; i < nr; i++) - if (Bx[i] != 0. || Bz[i] != 0.) - new_nnz++; - - if (ii + new_nnz > x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - - for (octave_idx_type i = 0; i < nr; i++) - if (Bx[i] != 0. || Bz[i] != 0.) - { - retval.xridx(ii) = i; - retval.xdata(ii++) = - Complex (Bx[i], Bz[i]); - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - } - } - } + { + // Create the storage for the banded form of the sparse matrix + octave_idx_type n_upper = mattype.nupper (); + octave_idx_type n_lower = mattype.nlower (); + octave_idx_type ldm = n_upper + 2 * n_lower + 1; + + Matrix m_band (ldm, nc); + double *tmp_data = m_band.fortran_vec (); + + if (! mattype.is_dense ()) + { + octave_idx_type ii = 0; + + for (octave_idx_type j = 0; j < ldm; j++) + for (octave_idx_type i = 0; i < nc; i++) + tmp_data[ii++] = 0.; + } + + for (octave_idx_type j = 0; j < nc; j++) + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + m_band(ridx(i) - j + n_lower + n_upper, j) = data(i); + + // Calculate the norm of the matrix, for later use. + double anorm; + if (calc_cond) + { + for (octave_idx_type j = 0; j < nr; j++) + { + double atmp = 0.; + for (octave_idx_type i = cidx(j); i < cidx(j+1); i++) + atmp += fabs(data(i)); + if (atmp > anorm) + anorm = atmp; + } + } + + Array<octave_idx_type> ipvt (nr); + octave_idx_type *pipvt = ipvt.fortran_vec (); + + F77_XFCN (dgbtrf, DGBTRF, (nr, nr, n_lower, n_upper, tmp_data, + ldm, pipvt, err)); + + if (err != 0) + { + err = -2; + rcond = 0.0; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision"); + + } + else + { + if (calc_cond) + { + char job = '1'; + Array<double> z (3 * nr); + double *pz = z.fortran_vec (); + Array<octave_idx_type> iz (nr); + octave_idx_type *piz = iz.fortran_vec (); + + F77_XFCN (dgbcon, DGBCON, + (F77_CONST_CHAR_ARG2 (&job, 1), + nc, n_lower, n_upper, tmp_data, ldm, pipvt, + anorm, rcond, pz, piz, err + F77_CHAR_ARG_LEN (1))); + + if (err != 0) + err = -2; + + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("matrix singular to machine precision, rcond = %g", + rcond); + } + } + else + rcond = 1.; + + if (err == 0) + { + char job = 'N'; + volatile octave_idx_type x_nz = b.nnz (); + octave_idx_type b_nc = b.cols (); + retval = SparseComplexMatrix (nr, b_nc, x_nz); + retval.xcidx(0) = 0; + volatile octave_idx_type ii = 0; + + OCTAVE_LOCAL_BUFFER (double, Bx, nr); + OCTAVE_LOCAL_BUFFER (double, Bz, nr); + + for (volatile octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < nr; i++) + { + Bx[i] = 0.; + Bz[i] = 0.; + } + for (octave_idx_type i = b.cidx(j); + i < b.cidx(j+1); i++) + { + Complex c = b.data(i); + Bx[b.ridx(i)] = std::real (c); + Bz[b.ridx(i)] = std::imag (c); + } + + F77_XFCN (dgbtrs, DGBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, n_upper, 1, tmp_data, + ldm, pipvt, Bx, b.rows (), err + F77_CHAR_ARG_LEN (1))); + + F77_XFCN (dgbtrs, DGBTRS, + (F77_CONST_CHAR_ARG2 (&job, 1), + nr, n_lower, n_upper, 1, tmp_data, + ldm, pipvt, Bz, b.rows (), err + F77_CHAR_ARG_LEN (1))); + + // Count non-zeros in work vector and adjust + // space in retval if needed + octave_idx_type new_nnz = 0; + for (octave_idx_type i = 0; i < nr; i++) + if (Bx[i] != 0. || Bz[i] != 0.) + new_nnz++; + + if (ii + new_nnz > x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = new_nnz * (b_nc - j) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + + for (octave_idx_type i = 0; i < nr; i++) + if (Bx[i] != 0. || Bz[i] != 0.) + { + retval.xridx(ii) = i; + retval.xdata(ii++) = + Complex (Bx[i], Bz[i]); + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + } + } + } else if (typ != MatrixType::Banded_Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -5693,8 +5693,8 @@ void * SparseMatrix::factorize (octave_idx_type& err, double &rcond, Matrix &Control, - Matrix &Info, solve_singularity_handler sing_handler, - bool calc_cond) const + Matrix &Info, solve_singularity_handler sing_handler, + bool calc_cond) const { // The return values void *Numeric = 0; @@ -5735,12 +5735,12 @@ Info = Matrix (1, UMFPACK_INFO); double *info = Info.fortran_vec (); int status = UMFPACK_DNAME (qsymbolic) (nr, nc, Ap, Ai, Ax, 0, - &Symbolic, control, info); + &Symbolic, control, info); if (status < 0) { (*current_liboctave_error_handler) - ("SparseMatrix::solve symbolic factorization failed"); + ("SparseMatrix::solve symbolic factorization failed"); err = -1; UMFPACK_DNAME (report_status) (control, status); @@ -5753,44 +5753,44 @@ UMFPACK_DNAME (report_symbolic) (Symbolic, control); status = UMFPACK_DNAME (numeric) (Ap, Ai, Ax, Symbolic, - &Numeric, control, info) ; + &Numeric, control, info) ; UMFPACK_DNAME (free_symbolic) (&Symbolic) ; if (calc_cond) - rcond = Info (UMFPACK_RCOND); + rcond = Info (UMFPACK_RCOND); else - rcond = 1.; + rcond = 1.; volatile double rcond_plus_one = rcond + 1.0; if (status == UMFPACK_WARNING_singular_matrix || - rcond_plus_one == 1.0 || xisnan (rcond)) - { - UMFPACK_DNAME (report_numeric) (Numeric, control); - - err = -2; - - if (sing_handler) - sing_handler (rcond); - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - - } + rcond_plus_one == 1.0 || xisnan (rcond)) + { + UMFPACK_DNAME (report_numeric) (Numeric, control); + + err = -2; + + if (sing_handler) + sing_handler (rcond); + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + + } else if (status < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve numeric factorization failed"); - - UMFPACK_DNAME (report_status) (control, status); - UMFPACK_DNAME (report_info) (control, info); - - err = -1; - } - else - { - UMFPACK_DNAME (report_numeric) (Numeric, control); - } + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve numeric factorization failed"); + + UMFPACK_DNAME (report_status) (control, status); + UMFPACK_DNAME (report_info) (control, info); + + err = -1; + } + else + { + UMFPACK_DNAME (report_numeric) (Numeric, control); + } } if (err != 0) @@ -5805,9 +5805,9 @@ Matrix SparseMatrix::fsolve (MatrixType &mattype, const Matrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { Matrix retval; @@ -5827,193 +5827,193 @@ mattype.info (); if (typ == MatrixType::Hermitian) - { + { #ifdef HAVE_CHOLMOD - cholmod_common Common; - cholmod_common *cm = &Common; - - // Setup initial parameters - CHOLMOD_NAME(start) (cm); - cm->prefer_zomplex = false; - - double spu = octave_sparse_params::get_key ("spumoni"); - if (spu == 0.) - { - cm->print = -1; - cm->print_function = 0; - } - else - { - cm->print = static_cast<int> (spu) + 2; - cm->print_function =&SparseCholPrint; - } - - cm->error_handler = &SparseCholError; - cm->complex_divide = CHOLMOD_NAME(divcomplex); - cm->hypotenuse = CHOLMOD_NAME(hypot); - - cm->final_ll = true; - - cholmod_sparse Astore; - cholmod_sparse *A = &Astore; - double dummy; - A->nrow = nr; - A->ncol = nc; - - A->p = cidx(); - A->i = ridx(); - A->nzmax = nnz(); - A->packed = true; - A->sorted = true; - A->nz = 0; + cholmod_common Common; + cholmod_common *cm = &Common; + + // Setup initial parameters + CHOLMOD_NAME(start) (cm); + cm->prefer_zomplex = false; + + double spu = octave_sparse_params::get_key ("spumoni"); + if (spu == 0.) + { + cm->print = -1; + cm->print_function = 0; + } + else + { + cm->print = static_cast<int> (spu) + 2; + cm->print_function =&SparseCholPrint; + } + + cm->error_handler = &SparseCholError; + cm->complex_divide = CHOLMOD_NAME(divcomplex); + cm->hypotenuse = CHOLMOD_NAME(hypot); + + cm->final_ll = true; + + cholmod_sparse Astore; + cholmod_sparse *A = &Astore; + double dummy; + A->nrow = nr; + A->ncol = nc; + + A->p = cidx(); + A->i = ridx(); + A->nzmax = nnz(); + A->packed = true; + A->sorted = true; + A->nz = 0; #ifdef IDX_TYPE_LONG - A->itype = CHOLMOD_LONG; + A->itype = CHOLMOD_LONG; #else - A->itype = CHOLMOD_INT; + A->itype = CHOLMOD_INT; #endif - A->dtype = CHOLMOD_DOUBLE; - A->stype = 1; - A->xtype = CHOLMOD_REAL; - - if (nr < 1) - A->x = &dummy; - else - A->x = data(); - - cholmod_dense Bstore; - cholmod_dense *B = &Bstore; - B->nrow = b.rows(); - B->ncol = b.cols(); - B->d = B->nrow; - B->nzmax = B->nrow * B->ncol; - B->dtype = CHOLMOD_DOUBLE; - B->xtype = CHOLMOD_REAL; - if (nc < 1 || b.cols() < 1) - B->x = &dummy; - else - // We won't alter it, honest :-) - B->x = const_cast<double *>(b.fortran_vec()); - - cholmod_factor *L; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - L = CHOLMOD_NAME(analyze) (A, cm); - CHOLMOD_NAME(factorize) (A, L, cm); - if (calc_cond) - rcond = CHOLMOD_NAME(rcond)(L, cm); - else - rcond = 1.0; - - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - if (rcond == 0.0) - { - // Either its indefinite or singular. Try UMFPACK - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; - } - else - { - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - - return retval; - } - - cholmod_dense *X; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - X = CHOLMOD_NAME(solve) (CHOLMOD_A, L, B, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - retval.resize (b.rows (), b.cols()); - for (octave_idx_type j = 0; j < b.cols(); j++) - { - octave_idx_type jr = j * b.rows(); - for (octave_idx_type i = 0; i < b.rows(); i++) - retval.xelem(i,j) = static_cast<double *>(X->x)[jr + i]; - } - - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - CHOLMOD_NAME(free_dense) (&X, cm); - CHOLMOD_NAME(free_factor) (&L, cm); - CHOLMOD_NAME(finish) (cm); - static char tmp[] = " "; - CHOLMOD_NAME(print_common) (tmp, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - } + A->dtype = CHOLMOD_DOUBLE; + A->stype = 1; + A->xtype = CHOLMOD_REAL; + + if (nr < 1) + A->x = &dummy; + else + A->x = data(); + + cholmod_dense Bstore; + cholmod_dense *B = &Bstore; + B->nrow = b.rows(); + B->ncol = b.cols(); + B->d = B->nrow; + B->nzmax = B->nrow * B->ncol; + B->dtype = CHOLMOD_DOUBLE; + B->xtype = CHOLMOD_REAL; + if (nc < 1 || b.cols() < 1) + B->x = &dummy; + else + // We won't alter it, honest :-) + B->x = const_cast<double *>(b.fortran_vec()); + + cholmod_factor *L; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + L = CHOLMOD_NAME(analyze) (A, cm); + CHOLMOD_NAME(factorize) (A, L, cm); + if (calc_cond) + rcond = CHOLMOD_NAME(rcond)(L, cm); + else + rcond = 1.0; + + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + if (rcond == 0.0) + { + // Either its indefinite or singular. Try UMFPACK + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; + } + else + { + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + + return retval; + } + + cholmod_dense *X; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + X = CHOLMOD_NAME(solve) (CHOLMOD_A, L, B, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + retval.resize (b.rows (), b.cols()); + for (octave_idx_type j = 0; j < b.cols(); j++) + { + octave_idx_type jr = j * b.rows(); + for (octave_idx_type i = 0; i < b.rows(); i++) + retval.xelem(i,j) = static_cast<double *>(X->x)[jr + i]; + } + + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + CHOLMOD_NAME(free_dense) (&X, cm); + CHOLMOD_NAME(free_factor) (&L, cm); + CHOLMOD_NAME(finish) (cm); + static char tmp[] = " "; + CHOLMOD_NAME(print_common) (tmp, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + } #else - (*current_liboctave_warning_handler) - ("CHOLMOD not installed"); - - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; + (*current_liboctave_warning_handler) + ("CHOLMOD not installed"); + + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; #endif - } + } if (typ == MatrixType::Full) - { + { #ifdef HAVE_UMFPACK - Matrix Control, Info; - void *Numeric = - factorize (err, rcond, Control, Info, sing_handler, calc_cond); - - if (err == 0) - { - const double *Bx = b.fortran_vec (); - retval.resize (b.rows (), b.cols()); - double *result = retval.fortran_vec (); - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - int status = 0; - double *control = Control.fortran_vec (); - double *info = Info.fortran_vec (); - const octave_idx_type *Ap = cidx (); - const octave_idx_type *Ai = ridx (); - const double *Ax = data (); - - for (octave_idx_type j = 0, iidx = 0; j < b_nc; j++, iidx += b_nr) - { - status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, - Ai, Ax, &result[iidx], &Bx[iidx], - Numeric, control, info); - if (status < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - - UMFPACK_DNAME (report_status) (control, status); - - err = -1; - - break; - } - } - - UMFPACK_DNAME (report_info) (control, info); - - UMFPACK_DNAME (free_numeric) (&Numeric); - } - else - mattype.mark_as_rectangular (); + Matrix Control, Info; + void *Numeric = + factorize (err, rcond, Control, Info, sing_handler, calc_cond); + + if (err == 0) + { + const double *Bx = b.fortran_vec (); + retval.resize (b.rows (), b.cols()); + double *result = retval.fortran_vec (); + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + int status = 0; + double *control = Control.fortran_vec (); + double *info = Info.fortran_vec (); + const octave_idx_type *Ap = cidx (); + const octave_idx_type *Ai = ridx (); + const double *Ax = data (); + + for (octave_idx_type j = 0, iidx = 0; j < b_nc; j++, iidx += b_nr) + { + status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, + Ai, Ax, &result[iidx], &Bx[iidx], + Numeric, control, info); + if (status < 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + + UMFPACK_DNAME (report_status) (control, status); + + err = -1; + + break; + } + } + + UMFPACK_DNAME (report_info) (control, info); + + UMFPACK_DNAME (free_numeric) (&Numeric); + } + else + mattype.mark_as_rectangular (); #else - (*current_liboctave_error_handler) ("UMFPACK not installed"); + (*current_liboctave_error_handler) ("UMFPACK not installed"); #endif - } + } else if (typ != MatrixType::Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -6021,9 +6021,9 @@ SparseMatrix SparseMatrix::fsolve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseMatrix retval; @@ -6043,239 +6043,239 @@ mattype.info (); if (typ == MatrixType::Hermitian) - { + { #ifdef HAVE_CHOLMOD - cholmod_common Common; - cholmod_common *cm = &Common; - - // Setup initial parameters - CHOLMOD_NAME(start) (cm); - cm->prefer_zomplex = false; - - double spu = octave_sparse_params::get_key ("spumoni"); - if (spu == 0.) - { - cm->print = -1; - cm->print_function = 0; - } - else - { - cm->print = static_cast<int> (spu) + 2; - cm->print_function =&SparseCholPrint; - } - - cm->error_handler = &SparseCholError; - cm->complex_divide = CHOLMOD_NAME(divcomplex); - cm->hypotenuse = CHOLMOD_NAME(hypot); - - cm->final_ll = true; - - cholmod_sparse Astore; - cholmod_sparse *A = &Astore; - double dummy; - A->nrow = nr; - A->ncol = nc; - - A->p = cidx(); - A->i = ridx(); - A->nzmax = nnz(); - A->packed = true; - A->sorted = true; - A->nz = 0; + cholmod_common Common; + cholmod_common *cm = &Common; + + // Setup initial parameters + CHOLMOD_NAME(start) (cm); + cm->prefer_zomplex = false; + + double spu = octave_sparse_params::get_key ("spumoni"); + if (spu == 0.) + { + cm->print = -1; + cm->print_function = 0; + } + else + { + cm->print = static_cast<int> (spu) + 2; + cm->print_function =&SparseCholPrint; + } + + cm->error_handler = &SparseCholError; + cm->complex_divide = CHOLMOD_NAME(divcomplex); + cm->hypotenuse = CHOLMOD_NAME(hypot); + + cm->final_ll = true; + + cholmod_sparse Astore; + cholmod_sparse *A = &Astore; + double dummy; + A->nrow = nr; + A->ncol = nc; + + A->p = cidx(); + A->i = ridx(); + A->nzmax = nnz(); + A->packed = true; + A->sorted = true; + A->nz = 0; #ifdef IDX_TYPE_LONG - A->itype = CHOLMOD_LONG; + A->itype = CHOLMOD_LONG; #else - A->itype = CHOLMOD_INT; + A->itype = CHOLMOD_INT; #endif - A->dtype = CHOLMOD_DOUBLE; - A->stype = 1; - A->xtype = CHOLMOD_REAL; - - if (nr < 1) - A->x = &dummy; - else - A->x = data(); - - cholmod_sparse Bstore; - cholmod_sparse *B = &Bstore; - B->nrow = b.rows(); - B->ncol = b.cols(); - B->p = b.cidx(); - B->i = b.ridx(); - B->nzmax = b.nnz(); - B->packed = true; - B->sorted = true; - B->nz = 0; + A->dtype = CHOLMOD_DOUBLE; + A->stype = 1; + A->xtype = CHOLMOD_REAL; + + if (nr < 1) + A->x = &dummy; + else + A->x = data(); + + cholmod_sparse Bstore; + cholmod_sparse *B = &Bstore; + B->nrow = b.rows(); + B->ncol = b.cols(); + B->p = b.cidx(); + B->i = b.ridx(); + B->nzmax = b.nnz(); + B->packed = true; + B->sorted = true; + B->nz = 0; #ifdef IDX_TYPE_LONG - B->itype = CHOLMOD_LONG; + B->itype = CHOLMOD_LONG; #else - B->itype = CHOLMOD_INT; + B->itype = CHOLMOD_INT; #endif - B->dtype = CHOLMOD_DOUBLE; - B->stype = 0; - B->xtype = CHOLMOD_REAL; - - if (b.rows() < 1 || b.cols() < 1) - B->x = &dummy; - else - B->x = b.data(); - - cholmod_factor *L; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - L = CHOLMOD_NAME(analyze) (A, cm); - CHOLMOD_NAME(factorize) (A, L, cm); - if (calc_cond) - rcond = CHOLMOD_NAME(rcond)(L, cm); - else - rcond = 1.; - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - if (rcond == 0.0) - { - // Either its indefinite or singular. Try UMFPACK - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; - } - else - { - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - - return retval; - } - - cholmod_sparse *X; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - X = CHOLMOD_NAME(spsolve) (CHOLMOD_A, L, B, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - retval = SparseMatrix (static_cast<octave_idx_type>(X->nrow), - static_cast<octave_idx_type>(X->ncol), - static_cast<octave_idx_type>(X->nzmax)); - for (octave_idx_type j = 0; - j <= static_cast<octave_idx_type>(X->ncol); j++) - retval.xcidx(j) = static_cast<octave_idx_type *>(X->p)[j]; - for (octave_idx_type j = 0; - j < static_cast<octave_idx_type>(X->nzmax); j++) - { - retval.xridx(j) = static_cast<octave_idx_type *>(X->i)[j]; - retval.xdata(j) = static_cast<double *>(X->x)[j]; - } - - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - CHOLMOD_NAME(free_sparse) (&X, cm); - CHOLMOD_NAME(free_factor) (&L, cm); - CHOLMOD_NAME(finish) (cm); - static char tmp[] = " "; - CHOLMOD_NAME(print_common) (tmp, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - } + B->dtype = CHOLMOD_DOUBLE; + B->stype = 0; + B->xtype = CHOLMOD_REAL; + + if (b.rows() < 1 || b.cols() < 1) + B->x = &dummy; + else + B->x = b.data(); + + cholmod_factor *L; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + L = CHOLMOD_NAME(analyze) (A, cm); + CHOLMOD_NAME(factorize) (A, L, cm); + if (calc_cond) + rcond = CHOLMOD_NAME(rcond)(L, cm); + else + rcond = 1.; + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + if (rcond == 0.0) + { + // Either its indefinite or singular. Try UMFPACK + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; + } + else + { + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + + return retval; + } + + cholmod_sparse *X; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + X = CHOLMOD_NAME(spsolve) (CHOLMOD_A, L, B, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + retval = SparseMatrix (static_cast<octave_idx_type>(X->nrow), + static_cast<octave_idx_type>(X->ncol), + static_cast<octave_idx_type>(X->nzmax)); + for (octave_idx_type j = 0; + j <= static_cast<octave_idx_type>(X->ncol); j++) + retval.xcidx(j) = static_cast<octave_idx_type *>(X->p)[j]; + for (octave_idx_type j = 0; + j < static_cast<octave_idx_type>(X->nzmax); j++) + { + retval.xridx(j) = static_cast<octave_idx_type *>(X->i)[j]; + retval.xdata(j) = static_cast<double *>(X->x)[j]; + } + + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + CHOLMOD_NAME(free_sparse) (&X, cm); + CHOLMOD_NAME(free_factor) (&L, cm); + CHOLMOD_NAME(finish) (cm); + static char tmp[] = " "; + CHOLMOD_NAME(print_common) (tmp, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + } #else - (*current_liboctave_warning_handler) - ("CHOLMOD not installed"); - - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; + (*current_liboctave_warning_handler) + ("CHOLMOD not installed"); + + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; #endif - } + } if (typ == MatrixType::Full) - { + { #ifdef HAVE_UMFPACK - Matrix Control, Info; - void *Numeric = factorize (err, rcond, Control, Info, - sing_handler, calc_cond); - - if (err == 0) - { - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - int status = 0; - double *control = Control.fortran_vec (); - double *info = Info.fortran_vec (); - const octave_idx_type *Ap = cidx (); - const octave_idx_type *Ai = ridx (); - const double *Ax = data (); - - OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Xx, b_nr); - - // Take a first guess that the number of non-zero terms - // will be as many as in b - octave_idx_type x_nz = b.nnz (); - octave_idx_type ii = 0; - retval = SparseMatrix (b_nr, b_nc, x_nz); - - retval.xcidx(0) = 0; - for (octave_idx_type j = 0; j < b_nc; j++) - { - - for (octave_idx_type i = 0; i < b_nr; i++) - Bx[i] = b.elem (i, j); - - status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, - Ai, Ax, Xx, Bx, Numeric, control, - info); - if (status < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - - UMFPACK_DNAME (report_status) (control, status); - - err = -1; - - break; - } - - for (octave_idx_type i = 0; i < b_nr; i++) - { - double tmp = Xx[i]; - if (tmp != 0.0) - { - if (ii == x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = x_nz * (b_nc - j) / b_nc; - sz = (sz > 10 ? sz : 10) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - retval.xdata(ii) = tmp; - retval.xridx(ii++) = i; - } - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - UMFPACK_DNAME (report_info) (control, info); - - UMFPACK_DNAME (free_numeric) (&Numeric); - } - else - mattype.mark_as_rectangular (); + Matrix Control, Info; + void *Numeric = factorize (err, rcond, Control, Info, + sing_handler, calc_cond); + + if (err == 0) + { + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + int status = 0; + double *control = Control.fortran_vec (); + double *info = Info.fortran_vec (); + const octave_idx_type *Ap = cidx (); + const octave_idx_type *Ai = ridx (); + const double *Ax = data (); + + OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Xx, b_nr); + + // Take a first guess that the number of non-zero terms + // will be as many as in b + octave_idx_type x_nz = b.nnz (); + octave_idx_type ii = 0; + retval = SparseMatrix (b_nr, b_nc, x_nz); + + retval.xcidx(0) = 0; + for (octave_idx_type j = 0; j < b_nc; j++) + { + + for (octave_idx_type i = 0; i < b_nr; i++) + Bx[i] = b.elem (i, j); + + status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, + Ai, Ax, Xx, Bx, Numeric, control, + info); + if (status < 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + + UMFPACK_DNAME (report_status) (control, status); + + err = -1; + + break; + } + + for (octave_idx_type i = 0; i < b_nr; i++) + { + double tmp = Xx[i]; + if (tmp != 0.0) + { + if (ii == x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = x_nz * (b_nc - j) / b_nc; + sz = (sz > 10 ? sz : 10) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + retval.xdata(ii) = tmp; + retval.xridx(ii++) = i; + } + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + UMFPACK_DNAME (report_info) (control, info); + + UMFPACK_DNAME (free_numeric) (&Numeric); + } + else + mattype.mark_as_rectangular (); #else - (*current_liboctave_error_handler) ("UMFPACK not installed"); + (*current_liboctave_error_handler) ("UMFPACK not installed"); #endif - } + } else if (typ != MatrixType::Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -6283,9 +6283,9 @@ ComplexMatrix SparseMatrix::fsolve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { ComplexMatrix retval; @@ -6305,211 +6305,211 @@ mattype.info (); if (typ == MatrixType::Hermitian) - { + { #ifdef HAVE_CHOLMOD - cholmod_common Common; - cholmod_common *cm = &Common; - - // Setup initial parameters - CHOLMOD_NAME(start) (cm); - cm->prefer_zomplex = false; - - double spu = octave_sparse_params::get_key ("spumoni"); - if (spu == 0.) - { - cm->print = -1; - cm->print_function = 0; - } - else - { - cm->print = static_cast<int> (spu) + 2; - cm->print_function =&SparseCholPrint; - } - - cm->error_handler = &SparseCholError; - cm->complex_divide = CHOLMOD_NAME(divcomplex); - cm->hypotenuse = CHOLMOD_NAME(hypot); - - cm->final_ll = true; - - cholmod_sparse Astore; - cholmod_sparse *A = &Astore; - double dummy; - A->nrow = nr; - A->ncol = nc; - - A->p = cidx(); - A->i = ridx(); - A->nzmax = nnz(); - A->packed = true; - A->sorted = true; - A->nz = 0; + cholmod_common Common; + cholmod_common *cm = &Common; + + // Setup initial parameters + CHOLMOD_NAME(start) (cm); + cm->prefer_zomplex = false; + + double spu = octave_sparse_params::get_key ("spumoni"); + if (spu == 0.) + { + cm->print = -1; + cm->print_function = 0; + } + else + { + cm->print = static_cast<int> (spu) + 2; + cm->print_function =&SparseCholPrint; + } + + cm->error_handler = &SparseCholError; + cm->complex_divide = CHOLMOD_NAME(divcomplex); + cm->hypotenuse = CHOLMOD_NAME(hypot); + + cm->final_ll = true; + + cholmod_sparse Astore; + cholmod_sparse *A = &Astore; + double dummy; + A->nrow = nr; + A->ncol = nc; + + A->p = cidx(); + A->i = ridx(); + A->nzmax = nnz(); + A->packed = true; + A->sorted = true; + A->nz = 0; #ifdef IDX_TYPE_LONG - A->itype = CHOLMOD_LONG; + A->itype = CHOLMOD_LONG; #else - A->itype = CHOLMOD_INT; + A->itype = CHOLMOD_INT; #endif - A->dtype = CHOLMOD_DOUBLE; - A->stype = 1; - A->xtype = CHOLMOD_REAL; - - if (nr < 1) - A->x = &dummy; - else - A->x = data(); - - cholmod_dense Bstore; - cholmod_dense *B = &Bstore; - B->nrow = b.rows(); - B->ncol = b.cols(); - B->d = B->nrow; - B->nzmax = B->nrow * B->ncol; - B->dtype = CHOLMOD_DOUBLE; - B->xtype = CHOLMOD_COMPLEX; - if (nc < 1 || b.cols() < 1) - B->x = &dummy; - else - // We won't alter it, honest :-) - B->x = const_cast<Complex *>(b.fortran_vec()); - - cholmod_factor *L; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - L = CHOLMOD_NAME(analyze) (A, cm); - CHOLMOD_NAME(factorize) (A, L, cm); - if (calc_cond) - rcond = CHOLMOD_NAME(rcond)(L, cm); - else - rcond = 1.0; - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - if (rcond == 0.0) - { - // Either its indefinite or singular. Try UMFPACK - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; - } - else - { - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - - return retval; - } - - cholmod_dense *X; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - X = CHOLMOD_NAME(solve) (CHOLMOD_A, L, B, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - retval.resize (b.rows (), b.cols()); - for (octave_idx_type j = 0; j < b.cols(); j++) - { - octave_idx_type jr = j * b.rows(); - for (octave_idx_type i = 0; i < b.rows(); i++) - retval.xelem(i,j) = static_cast<Complex *>(X->x)[jr + i]; - } - - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - CHOLMOD_NAME(free_dense) (&X, cm); - CHOLMOD_NAME(free_factor) (&L, cm); - CHOLMOD_NAME(finish) (cm); - static char tmp[] = " "; - CHOLMOD_NAME(print_common) (tmp, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - } + A->dtype = CHOLMOD_DOUBLE; + A->stype = 1; + A->xtype = CHOLMOD_REAL; + + if (nr < 1) + A->x = &dummy; + else + A->x = data(); + + cholmod_dense Bstore; + cholmod_dense *B = &Bstore; + B->nrow = b.rows(); + B->ncol = b.cols(); + B->d = B->nrow; + B->nzmax = B->nrow * B->ncol; + B->dtype = CHOLMOD_DOUBLE; + B->xtype = CHOLMOD_COMPLEX; + if (nc < 1 || b.cols() < 1) + B->x = &dummy; + else + // We won't alter it, honest :-) + B->x = const_cast<Complex *>(b.fortran_vec()); + + cholmod_factor *L; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + L = CHOLMOD_NAME(analyze) (A, cm); + CHOLMOD_NAME(factorize) (A, L, cm); + if (calc_cond) + rcond = CHOLMOD_NAME(rcond)(L, cm); + else + rcond = 1.0; + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + if (rcond == 0.0) + { + // Either its indefinite or singular. Try UMFPACK + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; + } + else + { + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + + return retval; + } + + cholmod_dense *X; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + X = CHOLMOD_NAME(solve) (CHOLMOD_A, L, B, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + retval.resize (b.rows (), b.cols()); + for (octave_idx_type j = 0; j < b.cols(); j++) + { + octave_idx_type jr = j * b.rows(); + for (octave_idx_type i = 0; i < b.rows(); i++) + retval.xelem(i,j) = static_cast<Complex *>(X->x)[jr + i]; + } + + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + CHOLMOD_NAME(free_dense) (&X, cm); + CHOLMOD_NAME(free_factor) (&L, cm); + CHOLMOD_NAME(finish) (cm); + static char tmp[] = " "; + CHOLMOD_NAME(print_common) (tmp, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + } #else - (*current_liboctave_warning_handler) - ("CHOLMOD not installed"); - - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; + (*current_liboctave_warning_handler) + ("CHOLMOD not installed"); + + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; #endif - } + } if (typ == MatrixType::Full) - { + { #ifdef HAVE_UMFPACK - Matrix Control, Info; - void *Numeric = factorize (err, rcond, Control, Info, - sing_handler, calc_cond); - - if (err == 0) - { - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - int status = 0; - double *control = Control.fortran_vec (); - double *info = Info.fortran_vec (); - const octave_idx_type *Ap = cidx (); - const octave_idx_type *Ai = ridx (); - const double *Ax = data (); - - OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); - - retval.resize (b_nr, b_nc); - - OCTAVE_LOCAL_BUFFER (double, Xx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Xz, b_nr); - - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < b_nr; i++) - { - Complex c = b (i,j); - Bx[i] = std::real (c); - Bz[i] = std::imag (c); - } - - status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, - Ai, Ax, Xx, Bx, Numeric, control, - info); - int status2 = UMFPACK_DNAME (solve) (UMFPACK_A, - Ap, Ai, Ax, Xz, Bz, Numeric, - control, info) ; - - if (status < 0 || status2 < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - - UMFPACK_DNAME (report_status) (control, status); - - err = -1; - - break; - } - - for (octave_idx_type i = 0; i < b_nr; i++) - retval (i, j) = Complex (Xx[i], Xz[i]); - } - - UMFPACK_DNAME (report_info) (control, info); - - UMFPACK_DNAME (free_numeric) (&Numeric); - } - else - mattype.mark_as_rectangular (); + Matrix Control, Info; + void *Numeric = factorize (err, rcond, Control, Info, + sing_handler, calc_cond); + + if (err == 0) + { + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + int status = 0; + double *control = Control.fortran_vec (); + double *info = Info.fortran_vec (); + const octave_idx_type *Ap = cidx (); + const octave_idx_type *Ai = ridx (); + const double *Ax = data (); + + OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); + + retval.resize (b_nr, b_nc); + + OCTAVE_LOCAL_BUFFER (double, Xx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Xz, b_nr); + + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < b_nr; i++) + { + Complex c = b (i,j); + Bx[i] = std::real (c); + Bz[i] = std::imag (c); + } + + status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, + Ai, Ax, Xx, Bx, Numeric, control, + info); + int status2 = UMFPACK_DNAME (solve) (UMFPACK_A, + Ap, Ai, Ax, Xz, Bz, Numeric, + control, info) ; + + if (status < 0 || status2 < 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + + UMFPACK_DNAME (report_status) (control, status); + + err = -1; + + break; + } + + for (octave_idx_type i = 0; i < b_nr; i++) + retval (i, j) = Complex (Xx[i], Xz[i]); + } + + UMFPACK_DNAME (report_info) (control, info); + + UMFPACK_DNAME (free_numeric) (&Numeric); + } + else + mattype.mark_as_rectangular (); #else - (*current_liboctave_error_handler) ("UMFPACK not installed"); + (*current_liboctave_error_handler) ("UMFPACK not installed"); #endif - } + } else if (typ != MatrixType::Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -6517,9 +6517,9 @@ SparseComplexMatrix SparseMatrix::fsolve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool calc_cond) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool calc_cond) const { SparseComplexMatrix retval; @@ -6539,249 +6539,249 @@ mattype.info (); if (typ == MatrixType::Hermitian) - { + { #ifdef HAVE_CHOLMOD - cholmod_common Common; - cholmod_common *cm = &Common; - - // Setup initial parameters - CHOLMOD_NAME(start) (cm); - cm->prefer_zomplex = false; - - double spu = octave_sparse_params::get_key ("spumoni"); - if (spu == 0.) - { - cm->print = -1; - cm->print_function = 0; - } - else - { - cm->print = static_cast<int> (spu) + 2; - cm->print_function =&SparseCholPrint; - } - - cm->error_handler = &SparseCholError; - cm->complex_divide = CHOLMOD_NAME(divcomplex); - cm->hypotenuse = CHOLMOD_NAME(hypot); - - cm->final_ll = true; - - cholmod_sparse Astore; - cholmod_sparse *A = &Astore; - double dummy; - A->nrow = nr; - A->ncol = nc; - - A->p = cidx(); - A->i = ridx(); - A->nzmax = nnz(); - A->packed = true; - A->sorted = true; - A->nz = 0; + cholmod_common Common; + cholmod_common *cm = &Common; + + // Setup initial parameters + CHOLMOD_NAME(start) (cm); + cm->prefer_zomplex = false; + + double spu = octave_sparse_params::get_key ("spumoni"); + if (spu == 0.) + { + cm->print = -1; + cm->print_function = 0; + } + else + { + cm->print = static_cast<int> (spu) + 2; + cm->print_function =&SparseCholPrint; + } + + cm->error_handler = &SparseCholError; + cm->complex_divide = CHOLMOD_NAME(divcomplex); + cm->hypotenuse = CHOLMOD_NAME(hypot); + + cm->final_ll = true; + + cholmod_sparse Astore; + cholmod_sparse *A = &Astore; + double dummy; + A->nrow = nr; + A->ncol = nc; + + A->p = cidx(); + A->i = ridx(); + A->nzmax = nnz(); + A->packed = true; + A->sorted = true; + A->nz = 0; #ifdef IDX_TYPE_LONG - A->itype = CHOLMOD_LONG; + A->itype = CHOLMOD_LONG; #else - A->itype = CHOLMOD_INT; + A->itype = CHOLMOD_INT; #endif - A->dtype = CHOLMOD_DOUBLE; - A->stype = 1; - A->xtype = CHOLMOD_REAL; - - if (nr < 1) - A->x = &dummy; - else - A->x = data(); - - cholmod_sparse Bstore; - cholmod_sparse *B = &Bstore; - B->nrow = b.rows(); - B->ncol = b.cols(); - B->p = b.cidx(); - B->i = b.ridx(); - B->nzmax = b.nnz(); - B->packed = true; - B->sorted = true; - B->nz = 0; + A->dtype = CHOLMOD_DOUBLE; + A->stype = 1; + A->xtype = CHOLMOD_REAL; + + if (nr < 1) + A->x = &dummy; + else + A->x = data(); + + cholmod_sparse Bstore; + cholmod_sparse *B = &Bstore; + B->nrow = b.rows(); + B->ncol = b.cols(); + B->p = b.cidx(); + B->i = b.ridx(); + B->nzmax = b.nnz(); + B->packed = true; + B->sorted = true; + B->nz = 0; #ifdef IDX_TYPE_LONG - B->itype = CHOLMOD_LONG; + B->itype = CHOLMOD_LONG; #else - B->itype = CHOLMOD_INT; + B->itype = CHOLMOD_INT; #endif - B->dtype = CHOLMOD_DOUBLE; - B->stype = 0; - B->xtype = CHOLMOD_COMPLEX; - - if (b.rows() < 1 || b.cols() < 1) - B->x = &dummy; - else - B->x = b.data(); - - cholmod_factor *L; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - L = CHOLMOD_NAME(analyze) (A, cm); - CHOLMOD_NAME(factorize) (A, L, cm); - if (calc_cond) - rcond = CHOLMOD_NAME(rcond)(L, cm); - else - rcond = 1.0; - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - if (rcond == 0.0) - { - // Either its indefinite or singular. Try UMFPACK - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; - } - else - { - volatile double rcond_plus_one = rcond + 1.0; - - if (rcond_plus_one == 1.0 || xisnan (rcond)) - { - err = -2; - - if (sing_handler) - { - sing_handler (rcond); - mattype.mark_as_rectangular (); - } - else - (*current_liboctave_error_handler) - ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", - rcond); - - return retval; - } - - cholmod_sparse *X; - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - X = CHOLMOD_NAME(spsolve) (CHOLMOD_A, L, B, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - - retval = SparseComplexMatrix - (static_cast<octave_idx_type>(X->nrow), - static_cast<octave_idx_type>(X->ncol), - static_cast<octave_idx_type>(X->nzmax)); - for (octave_idx_type j = 0; - j <= static_cast<octave_idx_type>(X->ncol); j++) - retval.xcidx(j) = static_cast<octave_idx_type *>(X->p)[j]; - for (octave_idx_type j = 0; - j < static_cast<octave_idx_type>(X->nzmax); j++) - { - retval.xridx(j) = static_cast<octave_idx_type *>(X->i)[j]; - retval.xdata(j) = static_cast<Complex *>(X->x)[j]; - } - - BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - CHOLMOD_NAME(free_sparse) (&X, cm); - CHOLMOD_NAME(free_factor) (&L, cm); - CHOLMOD_NAME(finish) (cm); - static char tmp[] = " "; - CHOLMOD_NAME(print_common) (tmp, cm); - END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; - } + B->dtype = CHOLMOD_DOUBLE; + B->stype = 0; + B->xtype = CHOLMOD_COMPLEX; + + if (b.rows() < 1 || b.cols() < 1) + B->x = &dummy; + else + B->x = b.data(); + + cholmod_factor *L; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + L = CHOLMOD_NAME(analyze) (A, cm); + CHOLMOD_NAME(factorize) (A, L, cm); + if (calc_cond) + rcond = CHOLMOD_NAME(rcond)(L, cm); + else + rcond = 1.0; + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + if (rcond == 0.0) + { + // Either its indefinite or singular. Try UMFPACK + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; + } + else + { + volatile double rcond_plus_one = rcond + 1.0; + + if (rcond_plus_one == 1.0 || xisnan (rcond)) + { + err = -2; + + if (sing_handler) + { + sing_handler (rcond); + mattype.mark_as_rectangular (); + } + else + (*current_liboctave_error_handler) + ("SparseMatrix::solve matrix singular to machine precision, rcond = %g", + rcond); + + return retval; + } + + cholmod_sparse *X; + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + X = CHOLMOD_NAME(spsolve) (CHOLMOD_A, L, B, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + + retval = SparseComplexMatrix + (static_cast<octave_idx_type>(X->nrow), + static_cast<octave_idx_type>(X->ncol), + static_cast<octave_idx_type>(X->nzmax)); + for (octave_idx_type j = 0; + j <= static_cast<octave_idx_type>(X->ncol); j++) + retval.xcidx(j) = static_cast<octave_idx_type *>(X->p)[j]; + for (octave_idx_type j = 0; + j < static_cast<octave_idx_type>(X->nzmax); j++) + { + retval.xridx(j) = static_cast<octave_idx_type *>(X->i)[j]; + retval.xdata(j) = static_cast<Complex *>(X->x)[j]; + } + + BEGIN_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + CHOLMOD_NAME(free_sparse) (&X, cm); + CHOLMOD_NAME(free_factor) (&L, cm); + CHOLMOD_NAME(finish) (cm); + static char tmp[] = " "; + CHOLMOD_NAME(print_common) (tmp, cm); + END_INTERRUPT_IMMEDIATELY_IN_FOREIGN_CODE; + } #else - (*current_liboctave_warning_handler) - ("CHOLMOD not installed"); - - mattype.mark_as_unsymmetric (); - typ = MatrixType::Full; + (*current_liboctave_warning_handler) + ("CHOLMOD not installed"); + + mattype.mark_as_unsymmetric (); + typ = MatrixType::Full; #endif - } + } if (typ == MatrixType::Full) - { + { #ifdef HAVE_UMFPACK - Matrix Control, Info; - void *Numeric = factorize (err, rcond, Control, Info, - sing_handler, calc_cond); - - if (err == 0) - { - octave_idx_type b_nr = b.rows (); - octave_idx_type b_nc = b.cols (); - int status = 0; - double *control = Control.fortran_vec (); - double *info = Info.fortran_vec (); - const octave_idx_type *Ap = cidx (); - const octave_idx_type *Ai = ridx (); - const double *Ax = data (); - - OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); - - // Take a first guess that the number of non-zero terms - // will be as many as in b - octave_idx_type x_nz = b.nnz (); - octave_idx_type ii = 0; - retval = SparseComplexMatrix (b_nr, b_nc, x_nz); - - OCTAVE_LOCAL_BUFFER (double, Xx, b_nr); - OCTAVE_LOCAL_BUFFER (double, Xz, b_nr); - - retval.xcidx(0) = 0; - for (octave_idx_type j = 0; j < b_nc; j++) - { - for (octave_idx_type i = 0; i < b_nr; i++) - { - Complex c = b (i,j); - Bx[i] = std::real (c); - Bz[i] = std::imag (c); - } - - status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, - Ai, Ax, Xx, Bx, Numeric, control, - info); - int status2 = UMFPACK_DNAME (solve) (UMFPACK_A, - Ap, Ai, Ax, Xz, Bz, Numeric, - control, info) ; - - if (status < 0 || status2 < 0) - { - (*current_liboctave_error_handler) - ("SparseMatrix::solve solve failed"); - - UMFPACK_DNAME (report_status) (control, status); - - err = -1; - - break; - } - - for (octave_idx_type i = 0; i < b_nr; i++) - { - Complex tmp = Complex (Xx[i], Xz[i]); - if (tmp != 0.0) - { - if (ii == x_nz) - { - // Resize the sparse matrix - octave_idx_type sz = x_nz * (b_nc - j) / b_nc; - sz = (sz > 10 ? sz : 10) + x_nz; - retval.change_capacity (sz); - x_nz = sz; - } - retval.xdata(ii) = tmp; - retval.xridx(ii++) = i; - } - } - retval.xcidx(j+1) = ii; - } - - retval.maybe_compress (); - - UMFPACK_DNAME (report_info) (control, info); - - UMFPACK_DNAME (free_numeric) (&Numeric); - } - else - mattype.mark_as_rectangular (); + Matrix Control, Info; + void *Numeric = factorize (err, rcond, Control, Info, + sing_handler, calc_cond); + + if (err == 0) + { + octave_idx_type b_nr = b.rows (); + octave_idx_type b_nc = b.cols (); + int status = 0; + double *control = Control.fortran_vec (); + double *info = Info.fortran_vec (); + const octave_idx_type *Ap = cidx (); + const octave_idx_type *Ai = ridx (); + const double *Ax = data (); + + OCTAVE_LOCAL_BUFFER (double, Bx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Bz, b_nr); + + // Take a first guess that the number of non-zero terms + // will be as many as in b + octave_idx_type x_nz = b.nnz (); + octave_idx_type ii = 0; + retval = SparseComplexMatrix (b_nr, b_nc, x_nz); + + OCTAVE_LOCAL_BUFFER (double, Xx, b_nr); + OCTAVE_LOCAL_BUFFER (double, Xz, b_nr); + + retval.xcidx(0) = 0; + for (octave_idx_type j = 0; j < b_nc; j++) + { + for (octave_idx_type i = 0; i < b_nr; i++) + { + Complex c = b (i,j); + Bx[i] = std::real (c); + Bz[i] = std::imag (c); + } + + status = UMFPACK_DNAME (solve) (UMFPACK_A, Ap, + Ai, Ax, Xx, Bx, Numeric, control, + info); + int status2 = UMFPACK_DNAME (solve) (UMFPACK_A, + Ap, Ai, Ax, Xz, Bz, Numeric, + control, info) ; + + if (status < 0 || status2 < 0) + { + (*current_liboctave_error_handler) + ("SparseMatrix::solve solve failed"); + + UMFPACK_DNAME (report_status) (control, status); + + err = -1; + + break; + } + + for (octave_idx_type i = 0; i < b_nr; i++) + { + Complex tmp = Complex (Xx[i], Xz[i]); + if (tmp != 0.0) + { + if (ii == x_nz) + { + // Resize the sparse matrix + octave_idx_type sz = x_nz * (b_nc - j) / b_nc; + sz = (sz > 10 ? sz : 10) + x_nz; + retval.change_capacity (sz); + x_nz = sz; + } + retval.xdata(ii) = tmp; + retval.xridx(ii++) = i; + } + } + retval.xcidx(j+1) = ii; + } + + retval.maybe_compress (); + + UMFPACK_DNAME (report_info) (control, info); + + UMFPACK_DNAME (free_numeric) (&Numeric); + } + else + mattype.mark_as_rectangular (); #else - (*current_liboctave_error_handler) ("UMFPACK not installed"); + (*current_liboctave_error_handler) ("UMFPACK not installed"); #endif - } + } else if (typ != MatrixType::Hermitian) - (*current_liboctave_error_handler) ("incorrect matrix type"); + (*current_liboctave_error_handler) ("incorrect matrix type"); } return retval; @@ -6797,7 +6797,7 @@ Matrix SparseMatrix::solve (MatrixType &mattype, const Matrix& b, - octave_idx_type& info) const + octave_idx_type& info) const { double rcond; return solve (mattype, b, info, rcond, 0); @@ -6805,15 +6805,15 @@ Matrix SparseMatrix::solve (MatrixType &mattype, const Matrix& b, octave_idx_type& info, - double& rcond) const + double& rcond) const { return solve (mattype, b, info, rcond, 0); } Matrix SparseMatrix::solve (MatrixType &mattype, const Matrix& b, octave_idx_type& err, - double& rcond, solve_singularity_handler sing_handler, - bool singular_fallback) const + double& rcond, solve_singularity_handler sing_handler, + bool singular_fallback) const { Matrix retval; int typ = mattype.type (false); @@ -6831,7 +6831,7 @@ else if (typ == MatrixType::Banded || typ == MatrixType::Banded_Hermitian) retval = bsolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Tridiagonal || - typ == MatrixType::Tridiagonal_Hermitian) + typ == MatrixType::Tridiagonal_Hermitian) retval = trisolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Full || typ == MatrixType::Hermitian) retval = fsolve (mattype, b, err, rcond, sing_handler, true); @@ -6865,7 +6865,7 @@ SparseMatrix SparseMatrix::solve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& info) const + octave_idx_type& info) const { double rcond; return solve (mattype, b, info, rcond, 0); @@ -6873,16 +6873,16 @@ SparseMatrix SparseMatrix::solve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& info, double& rcond) const + octave_idx_type& info, double& rcond) const { return solve (mattype, b, info, rcond, 0); } SparseMatrix SparseMatrix::solve (MatrixType &mattype, const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool singular_fallback) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool singular_fallback) const { SparseMatrix retval; int typ = mattype.type (false); @@ -6899,7 +6899,7 @@ else if (typ == MatrixType::Banded || typ == MatrixType::Banded_Hermitian) retval = bsolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Tridiagonal || - typ == MatrixType::Tridiagonal_Hermitian) + typ == MatrixType::Tridiagonal_Hermitian) retval = trisolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Full || typ == MatrixType::Hermitian) retval = fsolve (mattype, b, err, rcond, sing_handler, true); @@ -6916,7 +6916,7 @@ retval = qrsolve (*this, b, err); #else retval = dmsolve<SparseMatrix, SparseMatrix, - SparseMatrix> (*this, b, err); + SparseMatrix> (*this, b, err); #endif } @@ -6933,7 +6933,7 @@ ComplexMatrix SparseMatrix::solve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& info) const + octave_idx_type& info) const { double rcond; return solve (mattype, b, info, rcond, 0); @@ -6941,16 +6941,16 @@ ComplexMatrix SparseMatrix::solve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& info, double& rcond) const + octave_idx_type& info, double& rcond) const { return solve (mattype, b, info, rcond, 0); } ComplexMatrix SparseMatrix::solve (MatrixType &mattype, const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool singular_fallback) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool singular_fallback) const { ComplexMatrix retval; int typ = mattype.type (false); @@ -6967,7 +6967,7 @@ else if (typ == MatrixType::Banded || typ == MatrixType::Banded_Hermitian) retval = bsolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Tridiagonal || - typ == MatrixType::Tridiagonal_Hermitian) + typ == MatrixType::Tridiagonal_Hermitian) retval = trisolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Full || typ == MatrixType::Hermitian) retval = fsolve (mattype, b, err, rcond, sing_handler, true); @@ -6984,7 +6984,7 @@ retval = qrsolve (*this, b, err); #else retval = dmsolve<ComplexMatrix, SparseMatrix, - ComplexMatrix> (*this, b, err); + ComplexMatrix> (*this, b, err); #endif } @@ -7001,7 +7001,7 @@ SparseComplexMatrix SparseMatrix::solve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& info) const + octave_idx_type& info) const { double rcond; return solve (mattype, b, info, rcond, 0); @@ -7009,16 +7009,16 @@ SparseComplexMatrix SparseMatrix::solve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& info, double& rcond) const + octave_idx_type& info, double& rcond) const { return solve (mattype, b, info, rcond, 0); } SparseComplexMatrix SparseMatrix::solve (MatrixType &mattype, const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler, - bool singular_fallback) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler, + bool singular_fallback) const { SparseComplexMatrix retval; int typ = mattype.type (false); @@ -7035,7 +7035,7 @@ else if (typ == MatrixType::Banded || typ == MatrixType::Banded_Hermitian) retval = bsolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Tridiagonal || - typ == MatrixType::Tridiagonal_Hermitian) + typ == MatrixType::Tridiagonal_Hermitian) retval = trisolve (mattype, b, err, rcond, sing_handler, false); else if (typ == MatrixType::Full || typ == MatrixType::Hermitian) retval = fsolve (mattype, b, err, rcond, sing_handler, true); @@ -7052,7 +7052,7 @@ retval = qrsolve (*this, b, err); #else retval = dmsolve<SparseComplexMatrix, SparseMatrix, - SparseComplexMatrix> (*this, b, err); + SparseComplexMatrix> (*this, b, err); #endif } @@ -7081,7 +7081,7 @@ ColumnVector SparseMatrix::solve (MatrixType &mattype, const ColumnVector& b, octave_idx_type& info, double& rcond, - solve_singularity_handler sing_handler) const + solve_singularity_handler sing_handler) const { Matrix tmp (b); return solve (mattype, tmp, info, rcond, sing_handler).column (static_cast<octave_idx_type> (0)); @@ -7104,14 +7104,14 @@ ComplexColumnVector SparseMatrix::solve (MatrixType &mattype, const ComplexColumnVector& b, octave_idx_type& info, - double& rcond) const + double& rcond) const { return solve (mattype, b, info, rcond, 0); } ComplexColumnVector SparseMatrix::solve (MatrixType &mattype, const ComplexColumnVector& b, octave_idx_type& info, double& rcond, - solve_singularity_handler sing_handler) const + solve_singularity_handler sing_handler) const { ComplexMatrix tmp (b); return solve (mattype, tmp, info, rcond, sing_handler).column (static_cast<octave_idx_type> (0)); @@ -7134,15 +7134,15 @@ Matrix SparseMatrix::solve (const Matrix& b, octave_idx_type& info, - double& rcond) const + double& rcond) const { return solve (b, info, rcond, 0); } Matrix SparseMatrix::solve (const Matrix& b, octave_idx_type& err, - double& rcond, - solve_singularity_handler sing_handler) const + double& rcond, + solve_singularity_handler sing_handler) const { MatrixType mattype (*this); return solve (mattype, b, err, rcond, sing_handler); @@ -7158,7 +7158,7 @@ SparseMatrix SparseMatrix::solve (const SparseMatrix& b, - octave_idx_type& info) const + octave_idx_type& info) const { double rcond; return solve (b, info, rcond, 0); @@ -7166,15 +7166,15 @@ SparseMatrix SparseMatrix::solve (const SparseMatrix& b, - octave_idx_type& info, double& rcond) const + octave_idx_type& info, double& rcond) const { return solve (b, info, rcond, 0); } SparseMatrix SparseMatrix::solve (const SparseMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler) const { MatrixType mattype (*this); return solve (mattype, b, err, rcond, sing_handler); @@ -7182,7 +7182,7 @@ ComplexMatrix SparseMatrix::solve (const ComplexMatrix& b, - octave_idx_type& info) const + octave_idx_type& info) const { double rcond; return solve (b, info, rcond, 0); @@ -7190,15 +7190,15 @@ ComplexMatrix SparseMatrix::solve (const ComplexMatrix& b, - octave_idx_type& info, double& rcond) const + octave_idx_type& info, double& rcond) const { return solve (b, info, rcond, 0); } ComplexMatrix SparseMatrix::solve (const ComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler) const { MatrixType mattype (*this); return solve (mattype, b, err, rcond, sing_handler); @@ -7214,7 +7214,7 @@ SparseComplexMatrix SparseMatrix::solve (const SparseComplexMatrix& b, - octave_idx_type& info) const + octave_idx_type& info) const { double rcond; return solve (b, info, rcond, 0); @@ -7222,15 +7222,15 @@ SparseComplexMatrix SparseMatrix::solve (const SparseComplexMatrix& b, - octave_idx_type& info, double& rcond) const + octave_idx_type& info, double& rcond) const { return solve (b, info, rcond, 0); } SparseComplexMatrix SparseMatrix::solve (const SparseComplexMatrix& b, - octave_idx_type& err, double& rcond, - solve_singularity_handler sing_handler) const + octave_idx_type& err, double& rcond, + solve_singularity_handler sing_handler) const { MatrixType mattype (*this); return solve (mattype, b, err, rcond, sing_handler); @@ -7258,7 +7258,7 @@ ColumnVector SparseMatrix::solve (const ColumnVector& b, octave_idx_type& info, double& rcond, - solve_singularity_handler sing_handler) const + solve_singularity_handler sing_handler) const { Matrix tmp (b); return solve (tmp, info, rcond, sing_handler).column (static_cast<octave_idx_type> (0)); @@ -7281,14 +7281,14 @@ ComplexColumnVector SparseMatrix::solve (const ComplexColumnVector& b, octave_idx_type& info, - double& rcond) const + double& rcond) const { return solve (b, info, rcond, 0); } ComplexColumnVector SparseMatrix::solve (const ComplexColumnVector& b, octave_idx_type& info, double& rcond, - solve_singularity_handler sing_handler) const + solve_singularity_handler sing_handler) const { ComplexMatrix tmp (b); return solve (tmp, info, rcond, sing_handler).column (static_cast<octave_idx_type> (0)); @@ -7304,14 +7304,14 @@ if (neg_zero) { for (octave_idx_type i = 0; i < nel; i++) - if (lo_ieee_signbit (data (i))) - return true; + if (lo_ieee_signbit (data (i))) + return true; } else { for (octave_idx_type i = 0; i < nel; i++) - if (data (i) < 0) - return true; + if (data (i) < 0) + return true; } return false; @@ -7326,7 +7326,7 @@ { double val = data (i); if (xisnan (val)) - return true; + return true; } return false; @@ -7341,7 +7341,7 @@ { double val = data (i); if (xisinf (val) || xisnan (val)) - return true; + return true; } return false; @@ -7356,7 +7356,7 @@ { double val = data (i); if (val != 0.0 && val != 1.0) - return true; + return true; } return false; @@ -7383,9 +7383,9 @@ { double val = data (i); if (xisnan (val) || D_NINT (val) == val) - continue; + continue; else - return false; + return false; } return true; @@ -7410,13 +7410,13 @@ double val = data (i); if (val > max_val) - max_val = val; + max_val = val; if (val < min_val) - min_val = val; + min_val = val; if (D_NINT (val) != val) - return false; + return false; } return true; @@ -7432,7 +7432,7 @@ double val = data (i); if (val > FLT_MAX || val < FLT_MIN) - return true; + return true; } return false; @@ -7454,15 +7454,15 @@ for (octave_idx_type i = 0; i < nc; i++) { for (octave_idx_type j = 0; j < nr; j++) - { - if (jj < cidx(i+1) && ridx(jj) == j) - jj++; - else - { - r.data(ii) = true; - r.ridx(ii++) = j; - } - } + { + if (jj < cidx(i+1) && ridx(jj) == j) + jj++; + else + { + r.data(ii) = true; + r.ridx(ii++) = j; + } + } r.cidx (i+1) = ii; } @@ -7504,7 +7504,7 @@ else { SPARSE_REDUCTION_OP (SparseMatrix, double, *=, - (cidx(j+1) - cidx(j) < nr ? 0.0 : 1.0), 1.0); + (cidx(j+1) - cidx(j) < nr ? 0.0 : 1.0), 1.0); } } @@ -7526,7 +7526,7 @@ tmp[j] += d * d SPARSE_BASE_REDUCTION_OP (SparseMatrix, double, ROW_EXPR, COL_EXPR, - 0.0, 0.0); + 0.0, 0.0); #undef ROW_EXPR #undef COL_EXPR @@ -7575,9 +7575,9 @@ for (octave_idx_type j = 0; j < nc; j++) { octave_quit (); for (octave_idx_type i = a.cidx(j); i < a.cidx(j+1); i++) { - os << a.ridx(i) + 1 << " " << j + 1 << " "; - octave_write_double (os, a.data(i)); - os << "\n"; + os << a.ridx(i) + 1 << " " << j + 1 << " "; + octave_write_double (os, a.data(i)); + os << "\n"; } } @@ -7740,43 +7740,43 @@ { result = SparseMatrix (nr, nc, d); for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) - { - double tmp = xmin (d, m.data (i)); - if (tmp != 0.) - { - octave_idx_type idx = m.ridx(i) + j * nr; - result.xdata(idx) = tmp; - result.xridx(idx) = m.ridx(i); - } - } + for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) + { + double tmp = xmin (d, m.data (i)); + if (tmp != 0.) + { + octave_idx_type idx = m.ridx(i) + j * nr; + result.xdata(idx) = tmp; + result.xridx(idx) = m.ridx(i); + } + } } else { octave_idx_type nel = 0; for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) - if (xmin (d, m.data (i)) != 0.) - nel++; + for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) + if (xmin (d, m.data (i)) != 0.) + nel++; result = SparseMatrix (nr, nc, nel); octave_idx_type ii = 0; result.xcidx(0) = 0; for (octave_idx_type j = 0; j < nc; j++) - { - for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) - { - double tmp = xmin (d, m.data (i)); - - if (tmp != 0.) - { - result.xdata(ii) = tmp; - result.xridx(ii++) = m.ridx(i); - } - } - result.xcidx(j+1) = ii; - } + { + for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) + { + double tmp = xmin (d, m.data (i)); + + if (tmp != 0.) + { + result.xdata(ii) = tmp; + result.xridx(ii++) = m.ridx(i); + } + } + result.xcidx(j+1) = ii; + } } return result; @@ -7802,72 +7802,72 @@ octave_idx_type b_nc = b.cols (); if (a_nr != b_nr || a_nc != b_nc) - gripe_nonconformant ("min", a_nr, a_nc, b_nr, b_nc); + gripe_nonconformant ("min", a_nr, a_nc, b_nr, b_nc); else - { - r = SparseMatrix (a_nr, a_nc, (a.nnz () + b.nnz ())); + { + r = SparseMatrix (a_nr, a_nc, (a.nnz () + b.nnz ())); - octave_idx_type jx = 0; - r.cidx (0) = 0; - for (octave_idx_type i = 0 ; i < a_nc ; i++) - { - octave_idx_type ja = a.cidx(i); - octave_idx_type ja_max = a.cidx(i+1); - bool ja_lt_max= ja < ja_max; + octave_idx_type jx = 0; + r.cidx (0) = 0; + for (octave_idx_type i = 0 ; i < a_nc ; i++) + { + octave_idx_type ja = a.cidx(i); + octave_idx_type ja_max = a.cidx(i+1); + bool ja_lt_max= ja < ja_max; - octave_idx_type jb = b.cidx(i); - octave_idx_type jb_max = b.cidx(i+1); - bool jb_lt_max = jb < jb_max; + octave_idx_type jb = b.cidx(i); + octave_idx_type jb_max = b.cidx(i+1); + bool jb_lt_max = jb < jb_max; - while (ja_lt_max || jb_lt_max ) - { - octave_quit (); - if ((! jb_lt_max) || + while (ja_lt_max || jb_lt_max ) + { + octave_quit (); + if ((! jb_lt_max) || (ja_lt_max && (a.ridx(ja) < b.ridx(jb)))) - { - double tmp = xmin (a.data(ja), 0.); - if (tmp != 0.) - { - r.ridx(jx) = a.ridx(ja); - r.data(jx) = tmp; - jx++; - } - ja++; - ja_lt_max= ja < ja_max; - } - else if (( !ja_lt_max ) || - (jb_lt_max && (b.ridx(jb) < a.ridx(ja)) ) ) - { - double tmp = xmin (0., b.data(jb)); - if (tmp != 0.) - { - r.ridx(jx) = b.ridx(jb); - r.data(jx) = tmp; - jx++; - } - jb++; - jb_lt_max= jb < jb_max; - } - else - { - double tmp = xmin (a.data(ja), b.data(jb)); - if (tmp != 0.) - { + { + double tmp = xmin (a.data(ja), 0.); + if (tmp != 0.) + { + r.ridx(jx) = a.ridx(ja); + r.data(jx) = tmp; + jx++; + } + ja++; + ja_lt_max= ja < ja_max; + } + else if (( !ja_lt_max ) || + (jb_lt_max && (b.ridx(jb) < a.ridx(ja)) ) ) + { + double tmp = xmin (0., b.data(jb)); + if (tmp != 0.) + { + r.ridx(jx) = b.ridx(jb); + r.data(jx) = tmp; + jx++; + } + jb++; + jb_lt_max= jb < jb_max; + } + else + { + double tmp = xmin (a.data(ja), b.data(jb)); + if (tmp != 0.) + { r.data(jx) = tmp; r.ridx(jx) = a.ridx(ja); jx++; - } - ja++; - ja_lt_max= ja < ja_max; - jb++; - jb_lt_max= jb < jb_max; - } - } - r.cidx(i+1) = jx; - } - - r.maybe_compress (); - } + } + ja++; + ja_lt_max= ja < ja_max; + jb++; + jb_lt_max= jb < jb_max; + } + } + r.cidx(i+1) = jx; + } + + r.maybe_compress (); + } } else (*current_liboctave_error_handler) ("matrix size mismatch"); @@ -7890,43 +7890,43 @@ { result = SparseMatrix (nr, nc, d); for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) - { - double tmp = xmax (d, m.data (i)); - - if (tmp != 0.) - { - octave_idx_type idx = m.ridx(i) + j * nr; - result.xdata(idx) = tmp; - result.xridx(idx) = m.ridx(i); - } - } + for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) + { + double tmp = xmax (d, m.data (i)); + + if (tmp != 0.) + { + octave_idx_type idx = m.ridx(i) + j * nr; + result.xdata(idx) = tmp; + result.xridx(idx) = m.ridx(i); + } + } } else { octave_idx_type nel = 0; for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) - if (xmax (d, m.data (i)) != 0.) - nel++; + for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) + if (xmax (d, m.data (i)) != 0.) + nel++; result = SparseMatrix (nr, nc, nel); octave_idx_type ii = 0; result.xcidx(0) = 0; for (octave_idx_type j = 0; j < nc; j++) - { - for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) - { - double tmp = xmax (d, m.data (i)); - if (tmp != 0.) - { - result.xdata(ii) = tmp; - result.xridx(ii++) = m.ridx(i); - } - } - result.xcidx(j+1) = ii; - } + { + for (octave_idx_type i = m.cidx(j); i < m.cidx(j+1); i++) + { + double tmp = xmax (d, m.data (i)); + if (tmp != 0.) + { + result.xdata(ii) = tmp; + result.xridx(ii++) = m.ridx(i); + } + } + result.xcidx(j+1) = ii; + } } return result; @@ -7952,72 +7952,72 @@ octave_idx_type b_nc = b.cols (); if (a_nr != b_nr || a_nc != b_nc) - gripe_nonconformant ("min", a_nr, a_nc, b_nr, b_nc); + gripe_nonconformant ("min", a_nr, a_nc, b_nr, b_nc); else - { - r = SparseMatrix (a_nr, a_nc, (a.nnz () + b.nnz ())); + { + r = SparseMatrix (a_nr, a_nc, (a.nnz () + b.nnz ())); - octave_idx_type jx = 0; - r.cidx (0) = 0; - for (octave_idx_type i = 0 ; i < a_nc ; i++) - { - octave_idx_type ja = a.cidx(i); - octave_idx_type ja_max = a.cidx(i+1); - bool ja_lt_max= ja < ja_max; + octave_idx_type jx = 0; + r.cidx (0) = 0; + for (octave_idx_type i = 0 ; i < a_nc ; i++) + { + octave_idx_type ja = a.cidx(i); + octave_idx_type ja_max = a.cidx(i+1); + bool ja_lt_max= ja < ja_max; - octave_idx_type jb = b.cidx(i); - octave_idx_type jb_max = b.cidx(i+1); - bool jb_lt_max = jb < jb_max; + octave_idx_type jb = b.cidx(i); + octave_idx_type jb_max = b.cidx(i+1); + bool jb_lt_max = jb < jb_max; - while (ja_lt_max || jb_lt_max ) - { - octave_quit (); - if ((! jb_lt_max) || + while (ja_lt_max || jb_lt_max ) + { + octave_quit (); + if ((! jb_lt_max) || (ja_lt_max && (a.ridx(ja) < b.ridx(jb)))) - { - double tmp = xmax (a.data(ja), 0.); - if (tmp != 0.) - { - r.ridx(jx) = a.ridx(ja); - r.data(jx) = tmp; - jx++; - } - ja++; - ja_lt_max= ja < ja_max; - } - else if (( !ja_lt_max ) || - (jb_lt_max && (b.ridx(jb) < a.ridx(ja)) ) ) - { - double tmp = xmax (0., b.data(jb)); - if (tmp != 0.) - { - r.ridx(jx) = b.ridx(jb); - r.data(jx) = tmp; - jx++; - } - jb++; - jb_lt_max= jb < jb_max; - } - else - { - double tmp = xmax (a.data(ja), b.data(jb)); - if (tmp != 0.) - { + { + double tmp = xmax (a.data(ja), 0.); + if (tmp != 0.) + { + r.ridx(jx) = a.ridx(ja); + r.data(jx) = tmp; + jx++; + } + ja++; + ja_lt_max= ja < ja_max; + } + else if (( !ja_lt_max ) || + (jb_lt_max && (b.ridx(jb) < a.ridx(ja)) ) ) + { + double tmp = xmax (0., b.data(jb)); + if (tmp != 0.) + { + r.ridx(jx) = b.ridx(jb); + r.data(jx) = tmp; + jx++; + } + jb++; + jb_lt_max= jb < jb_max; + } + else + { + double tmp = xmax (a.data(ja), b.data(jb)); + if (tmp != 0.) + { r.data(jx) = tmp; r.ridx(jx) = a.ridx(ja); jx++; - } - ja++; - ja_lt_max= ja < ja_max; - jb++; - jb_lt_max= jb < jb_max; - } - } - r.cidx(i+1) = jx; - } - - r.maybe_compress (); - } + } + ja++; + ja_lt_max= ja < ja_max; + jb++; + jb_lt_max= jb < jb_max; + } + } + r.cidx(i+1) = jx; + } + + r.maybe_compress (); + } } else (*current_liboctave_error_handler) ("matrix size mismatch");