Mercurial > hg > octave-nkf
view src/ov-re-sparse.cc @ 5261:90a9058de7e8
[project @ 2005-03-31 02:48:38 by jwe]
author | jwe |
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date | Thu, 31 Mar 2005 02:48:39 +0000 |
parents | 57077d0ddc8e |
children | 23b37da9fd5b |
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/* Copyright (C) 2004 David Bateman Copyright (C) 1998-2004 Andy Adler Octave is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2, or (at your option) any later version. Octave is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; see the file COPYING. If not, write to the Free Software Foundation, 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. */ #ifdef HAVE_CONFIG_H #include <config.h> #endif #include <climits> #include <iostream> #include <vector> #include "ov-base.h" #include "ov-scalar.h" #include "gripes.h" #include "ls-hdf5.h" #include "ov-re-sparse.h" #include "ov-base-sparse.h" #include "ov-base-sparse.cc" #include "ov-bool-sparse.h" template class octave_base_sparse<SparseMatrix>; DEFINE_OCTAVE_ALLOCATOR (octave_sparse_matrix); DEFINE_OV_TYPEID_FUNCTIONS_AND_DATA (octave_sparse_matrix, "sparse matrix", "sparse"); octave_value * octave_sparse_matrix::try_narrowing_conversion (void) { octave_value *retval = 0; // Don't use numel, since it can overflow for very large matrices // Note that for the second test, this means it becomes approximative // since it involves a cast to double to avoid issues of overflow if (matrix.rows () == 1 && matrix.cols () == 1) { // Const copy of the matrix, so the right version of () operator used const SparseMatrix tmp (matrix); retval = new octave_scalar (tmp (0)); } else if (matrix.cols () > 0 && matrix.rows () > 0 && double (matrix.byte_size ()) > double (matrix.rows ()) * double (matrix.cols ()) * sizeof (double)) retval = new octave_matrix (matrix.matrix_value ()); return retval; } bool octave_sparse_matrix::valid_as_scalar_index (void) const { // XXX FIXME XXX return false; } double octave_sparse_matrix::double_value (bool) const { double retval = lo_ieee_nan_value (); if (numel () > 0) { // XXX FIXME XXX -- is warn_fortran_indexing the right variable here? if (Vwarn_fortran_indexing) gripe_implicit_conversion ("real sparse matrix", "real scalar"); retval = matrix (0, 0); } else gripe_invalid_conversion ("real sparse matrix", "real scalar"); return retval; } Complex octave_sparse_matrix::complex_value (bool) const { double tmp = lo_ieee_nan_value (); Complex retval (tmp, tmp); // XXX FIXME XXX -- maybe this should be a function, valid_as_scalar() if (rows () > 0 && columns () > 0) { // XXX FIXME XXX -- is warn_fortran_indexing the right variable here? if (Vwarn_fortran_indexing) gripe_implicit_conversion ("real sparse matrix", "complex scalar"); retval = matrix (0, 0); } else gripe_invalid_conversion ("real sparse matrix", "complex scalar"); return retval; } Matrix octave_sparse_matrix::matrix_value (bool) const { return matrix.matrix_value (); } ComplexMatrix octave_sparse_matrix::complex_matrix_value (bool) const { return ComplexMatrix (matrix.matrix_value ()); } ComplexNDArray octave_sparse_matrix::complex_array_value (bool) const { return ComplexNDArray (ComplexMatrix (matrix.matrix_value ())); } NDArray octave_sparse_matrix::array_value (bool) const { return NDArray (matrix.matrix_value ()); } streamoff_array octave_sparse_matrix::streamoff_array_value (void) const { streamoff_array retval (dims ()); int nc = matrix.cols (); int nr = matrix.rows (); for (int j = 0; j < nc; j++) for (int i = matrix.cidx(i); i < matrix.cidx(i+1); i++) { double d = matrix.data(i); if (D_NINT (d) == d) { retval(matrix.ridx(i) + nr * j) = std::streamoff (static_cast<long> (d)); } else { error ("conversion to streamoff_array value failed"); break; } } return retval; } bool octave_sparse_matrix::save_binary (std::ostream& os, bool&save_as_floats) { dim_vector d = this->dims (); if (d.length() < 1) return false; // Ensure that additional memory is deallocated matrix.maybe_compress (); int nr = d(0); int nc = d(1); int nz = nnz (); FOUR_BYTE_INT itmp; // Use negative value for ndims to be consistent with other formats itmp= -2; os.write (X_CAST (char *, &itmp), 4); itmp= nr; os.write (X_CAST (char *, &itmp), 4); itmp= nc; os.write (X_CAST (char *, &itmp), 4); itmp= nz; os.write (X_CAST (char *, &itmp), 4); save_type st = LS_DOUBLE; if (save_as_floats) { if (matrix.too_large_for_float ()) { warning ("save: some values too large to save as floats --"); warning ("save: saving as doubles instead"); } else st = LS_FLOAT; } else if (matrix.nnz () > 8192) // XXX FIXME XXX -- make this configurable. { double max_val, min_val; if (matrix.all_integers (max_val, min_val)) st = get_save_type (max_val, min_val); } // add one to the printed indices to go from // zero-based to one-based arrays for (int i = 0; i < nc+1; i++) { OCTAVE_QUIT; itmp = matrix.cidx(i); os.write (X_CAST (char *, &itmp), 4); } for (int i = 0; i < nz; i++) { OCTAVE_QUIT; itmp = matrix.ridx(i); os.write (X_CAST (char *, &itmp), 4); } write_doubles (os, matrix.data(), st, nz); return true; } bool octave_sparse_matrix::load_binary (std::istream& is, bool swap, oct_mach_info::float_format fmt) { FOUR_BYTE_INT nz, nc, nr, tmp; if (! is.read (X_CAST (char *, &tmp), 4)) return false; if (swap) swap_bytes<4> (&tmp); if (tmp != -2) { error("load: only 2D sparse matrices are supported"); return false; } if (! is.read (X_CAST (char *, &nr), 4)) return false; if (! is.read (X_CAST (char *, &nc), 4)) return false; if (! is.read (X_CAST (char *, &nz), 4)) return false; if (swap) { swap_bytes<4> (&nr); swap_bytes<4> (&nc); swap_bytes<4> (&nz); } SparseMatrix m (nr, nc, nz); for (int i = 0; i < nc+1; i++) { OCTAVE_QUIT; if (! is.read (X_CAST (char *, &tmp), 4)) return false; if (swap) swap_bytes<4> (&tmp); m.xcidx(i) = tmp; } for (int i = 0; i < nz; i++) { OCTAVE_QUIT; if (! is.read (X_CAST (char *, &tmp), 4)) return false; if (swap) swap_bytes<4> (&tmp); m.xridx(i) = tmp; } if (! is.read (X_CAST (char *, &tmp), 1)) return false; read_doubles (is, m.xdata(), X_CAST (save_type, tmp), nz, swap, fmt); if (error_state || ! is) return false; matrix = m; return true; } #if defined (HAVE_HDF5) bool octave_sparse_matrix::save_hdf5 (hid_t loc_id, const char *name, bool save_as_floats) { dim_vector dv = dims (); int empty = save_hdf5_empty (loc_id, name, dv); if (empty) return (empty > 0); // Ensure that additional memory is deallocated matrix.maybe_compress (); hid_t group_hid = H5Gcreate (loc_id, name, 0); if (group_hid < 0) return false; hid_t space_hid = -1, data_hid = -1; bool retval = true; SparseMatrix m = sparse_matrix_value (); int tmp; hsize_t hdims[2]; space_hid = H5Screate_simple (0, hdims, (hsize_t*) 0); if (space_hid < 0) { H5Gclose (group_hid); return false; } data_hid = H5Dcreate (group_hid, "nr", H5T_NATIVE_INT, space_hid, H5P_DEFAULT); if (data_hid < 0) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } tmp = m.rows (); retval = H5Dwrite (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void*) &tmp) >= 0; H5Dclose (data_hid); if (!retval) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } data_hid = H5Dcreate (group_hid, "nc", H5T_NATIVE_INT, space_hid, H5P_DEFAULT); if (data_hid < 0) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } tmp = m.cols (); retval = H5Dwrite (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void*) &tmp) >= 0; H5Dclose (data_hid); if (!retval) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } data_hid = H5Dcreate (group_hid, "nz", H5T_NATIVE_INT, space_hid, H5P_DEFAULT); if (data_hid < 0) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } tmp = m.nnz (); retval = H5Dwrite (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void*) &tmp) >= 0; H5Dclose (data_hid); if (!retval) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } H5Sclose (space_hid); hdims[0] = m.cols() + 1; hdims[1] = 1; space_hid = H5Screate_simple (2, hdims, 0); if (space_hid < 0) { H5Gclose (group_hid); return false; } data_hid = H5Dcreate (group_hid, "cidx", H5T_NATIVE_INT, space_hid, H5P_DEFAULT); if (data_hid < 0) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } int * itmp = m.xcidx (); retval = H5Dwrite (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void*) itmp) >= 0; H5Dclose (data_hid); if (!retval) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } H5Sclose (space_hid); hdims[0] = m.nnz(); hdims[1] = 1; space_hid = H5Screate_simple (2, hdims, 0); if (space_hid < 0) { H5Gclose (group_hid); return false; } data_hid = H5Dcreate (group_hid, "ridx", H5T_NATIVE_INT, space_hid, H5P_DEFAULT); if (data_hid < 0) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } itmp = m.xridx (); retval = H5Dwrite (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void*) itmp) >= 0; H5Dclose (data_hid); if (!retval) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } hid_t save_type_hid = H5T_NATIVE_DOUBLE; if (save_as_floats) { if (m.too_large_for_float ()) { warning ("save: some values too large to save as floats --"); warning ("save: saving as doubles instead"); } else save_type_hid = H5T_NATIVE_FLOAT; } #if HAVE_HDF5_INT2FLOAT_CONVERSIONS // hdf5 currently doesn't support float/integer conversions else { double max_val, min_val; if (m.all_integers (max_val, min_val)) save_type_hid = save_type_to_hdf5 (get_save_type (max_val, min_val)); } #endif /* HAVE_HDF5_INT2FLOAT_CONVERSIONS */ data_hid = H5Dcreate (group_hid, "data", save_type_hid, space_hid, H5P_DEFAULT); if (data_hid < 0) { H5Sclose (space_hid); H5Gclose (group_hid); return false; } double * dtmp = m.xdata (); retval = H5Dwrite (data_hid, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void*) dtmp) >= 0; H5Dclose (data_hid); H5Sclose (space_hid); H5Gclose (group_hid); return retval; } bool octave_sparse_matrix::load_hdf5 (hid_t loc_id, const char *name, bool /* have_h5giterate_bug */) { int nr, nc, nz; hid_t group_hid, data_hid, space_hid; hsize_t rank; dim_vector dv; int empty = load_hdf5_empty (loc_id, name, dv); if (empty > 0) matrix.resize(dv); if (empty) return (empty > 0); group_hid = H5Gopen (loc_id, name); if (group_hid < 0 ) return false; data_hid = H5Dopen (group_hid, "nr"); space_hid = H5Dget_space (data_hid); rank = H5Sget_simple_extent_ndims (space_hid); if (rank != 0) { H5Dclose (data_hid); H5Gclose (group_hid); return false; } if (H5Dread (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void *) &nr) < 0) { H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Dclose (data_hid); data_hid = H5Dopen (group_hid, "nc"); space_hid = H5Dget_space (data_hid); rank = H5Sget_simple_extent_ndims (space_hid); if (rank != 0) { H5Dclose (data_hid); H5Gclose (group_hid); return false; } if (H5Dread (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void *) &nc) < 0) { H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Dclose (data_hid); data_hid = H5Dopen (group_hid, "nz"); space_hid = H5Dget_space (data_hid); rank = H5Sget_simple_extent_ndims (space_hid); if (rank != 0) { H5Dclose (data_hid); H5Gclose (group_hid); return false; } if (H5Dread (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void *) &nz) < 0) { H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Dclose (data_hid); SparseMatrix m (nr, nc, nz); data_hid = H5Dopen (group_hid, "cidx"); space_hid = H5Dget_space (data_hid); rank = H5Sget_simple_extent_ndims (space_hid); if (rank != 2) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } OCTAVE_LOCAL_BUFFER (hsize_t, hdims, rank); OCTAVE_LOCAL_BUFFER (hsize_t, maxdims, rank); H5Sget_simple_extent_dims (space_hid, hdims, maxdims); if (hdims[0] != nc + 1 || hdims[1] != 1) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } int *itmp = m.xcidx (); if (H5Dread (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void *) itmp) < 0) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Sclose (space_hid); H5Dclose (data_hid); data_hid = H5Dopen (group_hid, "ridx"); space_hid = H5Dget_space (data_hid); rank = H5Sget_simple_extent_ndims (space_hid); if (rank != 2) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Sget_simple_extent_dims (space_hid, hdims, maxdims); if (hdims[0] != nz || hdims[1] != 1) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } itmp = m.xridx (); if (H5Dread (data_hid, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void *) itmp) < 0) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Sclose (space_hid); H5Dclose (data_hid); data_hid = H5Dopen (group_hid, "data"); space_hid = H5Dget_space (data_hid); rank = H5Sget_simple_extent_ndims (space_hid); if (rank != 2) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Sget_simple_extent_dims (space_hid, hdims, maxdims); if (hdims[0] != nz || hdims[1] != 1) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } double *dtmp = m.xdata (); if (H5Dread (data_hid, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, (void *) dtmp) < 0) { H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); return false; } H5Sclose (space_hid); H5Dclose (data_hid); H5Gclose (group_hid); matrix = m; return true; } #endif /* ;;; Local Variables: *** ;;; mode: C++ *** ;;; End: *** */