Mercurial > hg > octave-nkf
view src/ov-bool-mat.cc @ 11951:9cfbc1a1bf0b release-3-0-x
this branch is no longer maintained and is closed for further development
author | John W. Eaton <jwe@octave.org> |
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date | Sat, 22 Jan 2011 00:59:43 -0500 |
parents | a1dbe9d80eee |
children | 82be108cc558 |
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/* Copyright (C) 1996, 1997, 1998, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007 John W. Eaton This file is part of Octave. 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 3 of the License, 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 Octave; see the file COPYING. If not, see <http://www.gnu.org/licenses/>. */ #ifdef HAVE_CONFIG_H #include <config.h> #endif #include <iostream> #include <vector> #include "lo-ieee.h" #include "mx-base.h" #include "gripes.h" #include "oct-obj.h" #include "ops.h" #include "ov-base.h" #include "ov-base-mat.h" #include "ov-base-mat.cc" #include "ov-bool.h" #include "ov-bool-mat.h" #include "ov-re-mat.h" #include "pr-output.h" #include "byte-swap.h" #include "ls-oct-ascii.h" #include "ls-hdf5.h" #include "ls-utils.h" template class octave_base_matrix<boolNDArray>; DEFINE_OCTAVE_ALLOCATOR (octave_bool_matrix); DEFINE_OV_TYPEID_FUNCTIONS_AND_DATA (octave_bool_matrix, "bool matrix", "logical"); static octave_base_value * default_numeric_conversion_function (const octave_base_value& a) { CAST_CONV_ARG (const octave_bool_matrix&); return new octave_matrix (NDArray (v.bool_array_value ())); } octave_base_value::type_conv_fcn octave_bool_matrix::numeric_conversion_function (void) const { return default_numeric_conversion_function; } octave_base_value * octave_bool_matrix::try_narrowing_conversion (void) { octave_base_value *retval = 0; if (matrix.ndims () == 2) { boolMatrix bm = matrix.matrix_value (); octave_idx_type nr = bm.rows (); octave_idx_type nc = bm.cols (); if (nr == 1 && nc == 1) retval = new octave_bool (bm (0, 0)); } return retval; } bool octave_bool_matrix::valid_as_scalar_index (void) const { // FIXME return false; } double octave_bool_matrix::double_value (bool) const { double retval = lo_ieee_nan_value (); if (rows () > 0 && columns () > 0) { gripe_implicit_conversion ("Octave:array-as-scalar", "bool matrix", "real scalar"); retval = matrix (0, 0); } else gripe_invalid_conversion ("bool matrix", "real scalar"); return retval; } Complex octave_bool_matrix::complex_value (bool) const { double tmp = lo_ieee_nan_value (); Complex retval (tmp, tmp); if (rows () > 0 && columns () > 0) { gripe_implicit_conversion ("Octave:array-as-scalar", "bool matrix", "complex scalar"); retval = matrix (0, 0); } else gripe_invalid_conversion ("bool matrix", "complex scalar"); return retval; } octave_value octave_bool_matrix::convert_to_str_internal (bool pad, bool force, char type) const { octave_value tmp = octave_value (array_value ()); return tmp.convert_to_str (pad, force, type); } void octave_bool_matrix::print_raw (std::ostream& os, bool pr_as_read_syntax) const { octave_print_internal (os, matrix, pr_as_read_syntax, current_print_indent_level ()); } bool octave_bool_matrix::save_ascii (std::ostream& os) { dim_vector d = dims (); if (d.length () > 2) { NDArray tmp = array_value (); os << "# ndims: " << d.length () << "\n"; for (int i = 0; i < d.length (); i++) os << " " << d (i); os << "\n" << tmp; } else { // Keep this case, rather than use generic code above for backward // compatiability. Makes load_ascii much more complex!! os << "# rows: " << rows () << "\n" << "# columns: " << columns () << "\n"; Matrix tmp = matrix_value (); os << tmp; } return true; } bool octave_bool_matrix::load_ascii (std::istream& is) { bool success = true; string_vector keywords (2); keywords[0] = "ndims"; keywords[1] = "rows"; std::string kw; octave_idx_type val = 0; if (extract_keyword (is, keywords, kw, val, true)) { if (kw == "ndims") { int mdims = static_cast<int> (val); if (mdims >= 0) { dim_vector dv; dv.resize (mdims); for (int i = 0; i < mdims; i++) is >> dv(i); if (is) { boolNDArray btmp (dv); if (btmp.is_empty ()) matrix = btmp; else { NDArray tmp(dv); is >> tmp; if (is) { for (octave_idx_type i = 0; i < btmp.nelem (); i++) btmp.elem (i) = (tmp.elem (i) != 0.); matrix = btmp; } else { error ("load: failed to load matrix constant"); success = false; } } } else { error ("load: failed to extract dimensions"); success = false; } } else { error ("load: failed to extract number of dimensions"); success = false; } } else if (kw == "rows") { octave_idx_type nr = val; octave_idx_type nc = 0; if (nr >= 0 && extract_keyword (is, "columns", nc) && nc >= 0) { if (nr > 0 && nc > 0) { Matrix tmp (nr, nc); is >> tmp; if (is) { boolMatrix btmp (nr, nc); for (octave_idx_type j = 0; j < nc; j++) for (octave_idx_type i = 0; i < nr; i++) btmp.elem (i,j) = (tmp.elem (i, j) != 0.); matrix = btmp; } else { error ("load: failed to load matrix constant"); success = false; } } else if (nr == 0 || nc == 0) matrix = boolMatrix (nr, nc); else panic_impossible (); } else { error ("load: failed to extract number of rows and columns"); success = false; } } else panic_impossible (); } else { error ("load: failed to extract number of rows and columns"); success = false; } return success; } bool octave_bool_matrix::save_binary (std::ostream& os, bool& /* save_as_floats */) { dim_vector d = dims (); if (d.length() < 1) return false; // Use negative value for ndims to differentiate with old format!! int32_t tmp = - d.length(); os.write (reinterpret_cast<char *> (&tmp), 4); for (int i = 0; i < d.length (); i++) { tmp = d(i); os.write (reinterpret_cast<char *> (&tmp), 4); } boolNDArray m = bool_array_value (); bool *mtmp = m.fortran_vec (); octave_idx_type nel = m.nelem (); OCTAVE_LOCAL_BUFFER (char, htmp, nel); for (octave_idx_type i = 0; i < nel; i++) htmp[i] = (mtmp[i] ? 1 : 0); os.write (htmp, nel); return true; } bool octave_bool_matrix::load_binary (std::istream& is, bool swap, oct_mach_info::float_format /* fmt */) { int32_t mdims; if (! is.read (reinterpret_cast<char *> (&mdims), 4)) return false; if (swap) swap_bytes<4> (&mdims); if (mdims >= 0) return false; // mdims is negative for consistency with other matrices, where it is // negative to allow the positive value to be used for rows/cols for // backward compatibility mdims = - mdims; int32_t di; dim_vector dv; dv.resize (mdims); for (int i = 0; i < mdims; i++) { if (! is.read (reinterpret_cast<char *> (&di), 4)) return false; if (swap) swap_bytes<4> (&di); dv(i) = di; } // Convert an array with a single dimension to be a row vector. // Octave should never write files like this, other software // might. if (mdims == 1) { mdims = 2; dv.resize (mdims); dv(1) = dv(0); dv(0) = 1; } octave_idx_type nel = dv.numel (); OCTAVE_LOCAL_BUFFER (char, htmp, nel); if (! is.read (htmp, nel)) return false; boolNDArray m(dv); bool *mtmp = m.fortran_vec (); for (octave_idx_type i = 0; i < nel; i++) mtmp[i] = (htmp[i] ? 1 : 0); matrix = m; return true; } #if defined (HAVE_HDF5) bool octave_bool_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); int rank = dv.length (); hid_t space_hid = -1, data_hid = -1; bool retval = true; boolNDArray m = bool_array_value (); OCTAVE_LOCAL_BUFFER (hsize_t, hdims, rank); // Octave uses column-major, while HDF5 uses row-major ordering for (int i = 0; i < rank; i++) hdims[i] = dv (rank-i-1); space_hid = H5Screate_simple (rank, hdims, 0); if (space_hid < 0) return false; data_hid = H5Dcreate (loc_id, name, H5T_NATIVE_HBOOL, space_hid, H5P_DEFAULT); if (data_hid < 0) { H5Sclose (space_hid); return false; } octave_idx_type nel = m.nelem (); bool *mtmp = m.fortran_vec (); OCTAVE_LOCAL_BUFFER (hbool_t, htmp, nel); for (octave_idx_type i = 0; i < nel; i++) htmp[i] = mtmp[i]; retval = H5Dwrite (data_hid, H5T_NATIVE_HBOOL, H5S_ALL, H5S_ALL, H5P_DEFAULT, htmp) >= 0; H5Dclose (data_hid); H5Sclose (space_hid); return retval; } bool octave_bool_matrix::load_hdf5 (hid_t loc_id, const char *name, bool /* have_h5giterate_bug */) { bool retval = false; dim_vector dv; int empty = load_hdf5_empty (loc_id, name, dv); if (empty > 0) matrix.resize(dv); if (empty) return (empty > 0); hid_t data_hid = H5Dopen (loc_id, name); hid_t space_id = H5Dget_space (data_hid); hsize_t rank = H5Sget_simple_extent_ndims (space_id); if (rank < 1) { H5Dclose (data_hid); return false; } OCTAVE_LOCAL_BUFFER (hsize_t, hdims, rank); OCTAVE_LOCAL_BUFFER (hsize_t, maxdims, rank); H5Sget_simple_extent_dims (space_id, hdims, maxdims); // Octave uses column-major, while HDF5 uses row-major ordering if (rank == 1) { dv.resize (2); dv(0) = 1; dv(1) = hdims[0]; } else { dv.resize (rank); for (hsize_t i = 0, j = rank - 1; i < rank; i++, j--) dv(j) = hdims[i]; } octave_idx_type nel = dv.numel (); OCTAVE_LOCAL_BUFFER (hbool_t, htmp, nel); if (H5Dread (data_hid, H5T_NATIVE_HBOOL, H5S_ALL, H5S_ALL, H5P_DEFAULT, htmp) >= 0) { retval = true; boolNDArray btmp (dv); for (octave_idx_type i = 0; i < nel; i++) btmp.elem (i) = htmp[i]; matrix = btmp; } H5Dclose (data_hid); return retval; } #endif mxArray * octave_bool_matrix::as_mxArray (void) const { mxArray *retval = new mxArray (mxLOGICAL_CLASS, dims (), mxREAL); bool *pr = static_cast<bool *> (retval->get_data ()); mwSize nel = numel (); const bool *p = matrix.data (); for (mwIndex i = 0; i < nel; i++) pr[i] = p[i]; return retval; } /* ;;; Local Variables: *** ;;; mode: C++ *** ;;; End: *** */