Mercurial > octave-nkf
annotate src/DLD-FUNCTIONS/matrix_type.cc @ 14846:460a3c6d8bf1
maint: Use Octave coding convention for cuddled parenthis in function calls with empty argument lists.
Example: func() => func ()
* dynamic.txi, func.txi, oop.txi, var.txi, embedded.cc, fortdemo.cc,
funcdemo.cc, paramdemo.cc, stringdemo.cc, unwinddemo.cc, Array.cc, Array.h,
CColVector.cc, CDiagMatrix.h, CMatrix.cc, CNDArray.cc, CRowVector.cc,
CSparse.cc, CmplxGEPBAL.cc, EIG.cc, MSparse.cc, MatrixType.cc,
Sparse-op-defs.h, Sparse-perm-op-defs.h, Sparse.cc, Sparse.h,
SparseCmplxCHOL.cc, SparseCmplxCHOL.h, SparseCmplxLU.cc, SparseCmplxQR.cc,
SparseCmplxQR.h, SparseQR.cc, SparseQR.h, SparsedbleCHOL.cc, SparsedbleCHOL.h,
SparsedbleLU.cc, SparsedbleLU.h, base-lu.cc, cmd-hist.cc, dColVector.cc,
dDiagMatrix.h, dMatrix.cc, dNDArray.cc, dRowVector.cc, dSparse.cc, dbleCHOL.cc,
dbleGEPBAL.cc, dim-vector.cc, eigs-base.cc, f2c-main.c, fCColVector.cc,
fCDiagMatrix.h, fCMatrix.cc, fCNDArray.cc, fCRowVector.cc, fCmplxGEPBAL.cc,
fColVector.cc, fDiagMatrix.h, fEIG.cc, fMatrix.cc, fNDArray.cc, fRowVector.cc,
file-ops.cc, file-stat.cc, floatCHOL.cc, floatGEPBAL.cc, idx-vector.h,
lo-specfun.cc, lo-sysdep.cc, mx-inlines.cc, oct-binmap.h, oct-convn.cc,
oct-md5.cc, oct-mem.h, oct-rand.cc, oct-syscalls.cc, randgamma.c, randmtzig.c,
sparse-base-chol.cc, sparse-base-chol.h, sparse-base-lu.cc, sparse-dmsolve.cc,
tempname.c, curl.m, divergence.m, randi.m, dlmwrite.m, edit.m, getappdata.m,
what.m, getarchdir.m, install.m, installed_packages.m, repackage.m,
unload_packages.m, colorbar.m, figure.m, isosurface.m, legend.m, loglog.m,
plot.m, plot3.m, plotyy.m, polar.m, __errplot__.m, __ghostscript__.m,
__marching_cube__.m, __plt__.m, __scatter__.m, semilogx.m, semilogy.m,
trimesh.m, trisurf.m, demo.m, test.m, datetick.m, __delaunayn__.cc,
__dsearchn__.cc, __fltk_uigetfile__.cc, __glpk__.cc, __init_fltk__.cc,
__lin_interpn__.cc, __magick_read__.cc, __pchip_deriv__.cc, balance.cc,
bsxfun.cc, ccolamd.cc, cellfun.cc, chol.cc, daspk.cc, dasrt.cc, dassl.cc,
dmperm.cc, eig.cc, eigs.cc, fftw.cc, filter.cc, find.cc, kron.cc, lookup.cc,
lsode.cc, matrix_type.cc, md5sum.cc, mgorth.cc, qr.cc, quad.cc, rand.cc,
regexp.cc, symbfact.cc, tril.cc, urlwrite.cc, op-bm-bm.cc, op-cdm-cdm.cc,
op-cell.cc, op-chm.cc, op-cm-cm.cc, op-cm-scm.cc, op-cm-sm.cc, op-cs-scm.cc,
op-cs-sm.cc, op-dm-dm.cc, op-dm-scm.cc, op-dm-sm.cc, op-fcdm-fcdm.cc,
op-fcm-fcm.cc, op-fdm-fdm.cc, op-fm-fm.cc, op-int.h, op-m-m.cc, op-m-scm.cc,
op-m-sm.cc, op-pm-pm.cc, op-pm-scm.cc, op-pm-sm.cc, op-range.cc, op-s-scm.cc,
op-s-sm.cc, op-sbm-sbm.cc, op-scm-cm.cc, op-scm-cs.cc, op-scm-m.cc,
op-scm-s.cc, op-scm-scm.cc, op-scm-sm.cc, op-sm-cm.cc, op-sm-cs.cc, op-sm-m.cc,
op-sm-s.cc, op-sm-scm.cc, op-sm-sm.cc, op-str-str.cc, op-struct.cc, bitfcns.cc,
data.cc, debug.cc, dynamic-ld.cc, error.cc, gl-render.cc, graphics.cc,
graphics.in.h, load-path.cc, ls-hdf5.cc, ls-mat5.cc, ls-mat5.h,
ls-oct-ascii.cc, ls-oct-ascii.h, mex.cc, mk-errno-list, oct-map.cc, oct-obj.h,
oct-parse.yy, octave-config.in.cc, ov-base-int.cc, ov-base-mat.cc, ov-base.cc,
ov-bool-mat.cc, ov-bool-sparse.cc, ov-bool.cc, ov-cell.cc, ov-class.cc,
ov-class.h, ov-cx-mat.cc, ov-cx-sparse.cc, ov-fcn-handle.cc, ov-flt-cx-mat.cc,
ov-flt-re-mat.cc, ov-intx.h, ov-range.h, ov-re-mat.cc, ov-re-sparse.cc,
ov-str-mat.cc, ov-struct.cc, ov-usr-fcn.h, ov.h, pr-output.cc, pt-id.cc,
pt-id.h, pt-mat.cc, pt-select.cc, sparse.cc, symtab.cc, symtab.h, syscalls.cc,
toplev.cc, txt-eng-ft.cc, variables.cc, zfstream.cc, zfstream.h, Dork.m,
getStash.m, myStash.m, Gork.m, Pork.m, myStash.m, getStash.m, myStash.m,
getStash.m, myStash.m, fntests.m: Use Octave coding convention for
cuddled parenthis in function calls with empty argument lists.
author | Rik <octave@nomad.inbox5.com> |
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date | Sun, 08 Jul 2012 11:28:50 -0700 |
parents | 60e5cf354d80 |
children |
rev | line source |
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5323 | 1 /* |
2 | |
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3 Copyright (C) 2005-2012 David Bateman |
5323 | 4 |
5720 | 5 This file is part of Octave. |
6 | |
5323 | 7 Octave is free software; you can redistribute it and/or modify it |
8 under the terms of the GNU General Public License as published by the | |
7016 | 9 Free Software Foundation; either version 3 of the License, or (at your |
10 option) any later version. | |
5323 | 11 |
12 Octave is distributed in the hope that it will be useful, but WITHOUT | |
13 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
15 for more details. | |
16 | |
17 You should have received a copy of the GNU General Public License | |
7016 | 18 along with Octave; see the file COPYING. If not, see |
19 <http://www.gnu.org/licenses/>. | |
5323 | 20 |
21 */ | |
22 | |
23 #ifdef HAVE_CONFIG_H | |
24 #include <config.h> | |
25 #endif | |
26 | |
5403 | 27 #include <algorithm> |
28 | |
5323 | 29 #include "ov.h" |
30 #include "defun-dld.h" | |
31 #include "error.h" | |
5785 | 32 #include "ov-re-mat.h" |
33 #include "ov-cx-mat.h" | |
5323 | 34 #include "ov-re-sparse.h" |
35 #include "ov-cx-sparse.h" | |
5785 | 36 #include "MatrixType.h" |
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37 #include "oct-locbuf.h" |
5323 | 38 |
39 DEFUN_DLD (matrix_type, args, , | |
40 "-*- texinfo -*-\n\ | |
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41 @deftypefn {Loadable Function} {@var{type} =} matrix_type (@var{A})\n\ |
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42 @deftypefnx {Loadable Function} {@var{type} =} matrix_type (@var{A}, \"nocompute\")\n\ |
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43 @deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, @var{type})\n\ |
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44 @deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, \"upper\", @var{perm})\n\ |
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45 @deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, \"lower\", @var{perm})\n\ |
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46 @deftypefnx {Loadable Function} {@var{A} =} matrix_type (@var{A}, \"banded\", @var{nl}, @var{nu})\n\ |
10840 | 47 Identify the matrix type or mark a matrix as a particular type. This allows\n\ |
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48 more rapid solutions of linear equations involving @var{A} to be performed.\n\ |
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49 Called with a single argument, @code{matrix_type} returns the type of the\n\ |
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50 matrix and caches it for future use. Called with more than one argument,\n\ |
10840 | 51 @code{matrix_type} allows the type of the matrix to be defined.\n\ |
5323 | 52 \n\ |
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53 If the option \"nocompute\" is given, the function will not attempt to guess\n\ |
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54 the type if it is still unknown. This is useful for debugging purposes.\n\ |
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55 \n\ |
10840 | 56 The possible matrix types depend on whether the matrix is full or sparse, and\n\ |
57 can be one of the following\n\ | |
5323 | 58 \n\ |
59 @table @asis\n\ | |
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60 @item \"unknown\"\n\ |
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61 Remove any previously cached matrix type, and mark type as unknown.\n\ |
5323 | 62 \n\ |
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63 @item \"full\"\n\ |
5323 | 64 Mark the matrix as full.\n\ |
65 \n\ | |
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66 @item \"positive definite\"\n\ |
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67 Probable full positive definite matrix.\n\ |
5323 | 68 \n\ |
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69 @item \"diagonal\"\n\ |
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70 Diagonal matrix. (Sparse matrices only)\n\ |
5323 | 71 \n\ |
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72 @item \"permuted diagonal\"\n\ |
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73 Permuted Diagonal matrix. The permutation does not need to be specifically\n\ |
10840 | 74 indicated, as the structure of the matrix explicitly gives this. (Sparse\n\ |
75 matrices only)\n\ | |
5323 | 76 \n\ |
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77 @item \"upper\"\n\ |
10840 | 78 Upper triangular. If the optional third argument @var{perm} is given, the\n\ |
79 matrix is assumed to be a permuted upper triangular with the permutations\n\ | |
80 defined by the vector @var{perm}.\n\ | |
5323 | 81 \n\ |
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82 @item \"lower\"\n\ |
10840 | 83 Lower triangular. If the optional third argument @var{perm} is given, the\n\ |
84 matrix is assumed to be a permuted lower triangular with the permutations\n\ | |
85 defined by the vector @var{perm}.\n\ | |
5323 | 86 \n\ |
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87 @item \"banded\"\n\ |
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88 @itemx \"banded positive definite\"\n\ |
10840 | 89 Banded matrix with the band size of @var{nl} below the diagonal and @var{nu}\n\ |
90 above it. If @var{nl} and @var{nu} are 1, then the matrix is tridiagonal and\n\ | |
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91 treated with specialized code. In addition the matrix can be marked as\n\ |
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92 probably a positive definite. (Sparse matrices only)\n\ |
5323 | 93 \n\ |
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94 @item \"singular\"\n\ |
10840 | 95 The matrix is assumed to be singular and will be treated with a minimum norm\n\ |
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96 solution.\n\ |
5323 | 97 \n\ |
98 @end table\n\ | |
99 \n\ | |
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100 Note that the matrix type will be discovered automatically on the first\n\ |
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101 attempt to solve a linear equation involving @var{A}. Therefore\n\ |
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102 @code{matrix_type} is only useful to give Octave hints of the matrix type.\n\ |
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103 Incorrectly defining the matrix type will result in incorrect results from\n\ |
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104 solutions of linear equations; it is entirely @strong{the responsibility of\n\ |
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105 the user} to correctly identify the matrix type.\n\ |
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106 \n\ |
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107 Also, the test for positive definiteness is a low-cost test for a Hermitian\n\ |
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108 matrix with a real positive diagonal. This does not guarantee that the\n\ |
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109 matrix is positive definite, but only that it is a probable candidate. When\n\ |
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110 such a matrix is factorized, a Cholesky@tie{}factorization is first\n\ |
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111 attempted, and if that fails the matrix is then treated with an\n\ |
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112 LU@tie{}factorization. Once the matrix has been factorized,\n\ |
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113 @code{matrix_type} will return the correct classification of the matrix.\n\ |
5323 | 114 @end deftypefn") |
115 { | |
116 int nargin = args.length (); | |
117 octave_value retval; | |
118 | |
119 if (nargin == 0) | |
5823 | 120 print_usage (); |
5323 | 121 else if (nargin > 4) |
122 error ("matrix_type: incorrect number of arguments"); | |
123 else | |
124 { | |
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125 bool autocomp = true; |
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126 if (nargin == 2 && args(1).is_string () && args(1).string_value () == "nocompute") |
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127 { |
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128 nargin = 1; |
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129 autocomp = false; |
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130 } |
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131 |
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132 if (args(0).is_scalar_type ()) |
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133 { |
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134 if (nargin == 1) |
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135 retval = octave_value ("Diagonal"); |
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136 else |
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137 retval = args(0); |
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138 } |
6371 | 139 else if (args(0).is_sparse_type ()) |
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140 { |
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141 if (nargin == 1) |
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142 { |
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143 MatrixType mattyp; |
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145 if (args(0).is_complex_type ()) |
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146 { |
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147 mattyp = args(0).matrix_type (); |
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149 if (mattyp.is_unknown () && autocomp ) |
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150 { |
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151 SparseComplexMatrix m = |
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152 args(0).sparse_complex_matrix_value (); |
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153 if (!error_state) |
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154 { |
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155 mattyp = MatrixType (m); |
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156 args(0).matrix_type (mattyp); |
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157 } |
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158 } |
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159 } |
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160 else |
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161 { |
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162 mattyp = args(0).matrix_type (); |
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164 if (mattyp.is_unknown () && autocomp) |
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165 { |
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166 SparseMatrix m = args(0).sparse_matrix_value (); |
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167 if (!error_state) |
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168 { |
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169 mattyp = MatrixType (m); |
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170 args(0).matrix_type (mattyp); |
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171 } |
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172 } |
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173 } |
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175 int typ = mattyp.type (); |
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177 if (typ == MatrixType::Diagonal) |
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178 retval = octave_value ("Diagonal"); |
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179 else if (typ == MatrixType::Permuted_Diagonal) |
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180 retval = octave_value ("Permuted Diagonal"); |
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181 else if (typ == MatrixType::Upper) |
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182 retval = octave_value ("Upper"); |
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183 else if (typ == MatrixType::Permuted_Upper) |
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184 retval = octave_value ("Permuted Upper"); |
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185 else if (typ == MatrixType::Lower) |
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186 retval = octave_value ("Lower"); |
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187 else if (typ == MatrixType::Permuted_Lower) |
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188 retval = octave_value ("Permuted Lower"); |
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189 else if (typ == MatrixType::Banded) |
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190 retval = octave_value ("Banded"); |
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191 else if (typ == MatrixType::Banded_Hermitian) |
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192 retval = octave_value ("Banded Positive Definite"); |
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193 else if (typ == MatrixType::Tridiagonal) |
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194 retval = octave_value ("Tridiagonal"); |
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195 else if (typ == MatrixType::Tridiagonal_Hermitian) |
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196 retval = octave_value ("Tridiagonal Positive Definite"); |
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197 else if (typ == MatrixType::Hermitian) |
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198 retval = octave_value ("Positive Definite"); |
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199 else if (typ == MatrixType::Rectangular) |
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200 { |
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201 if (args(0).rows () == args(0).columns ()) |
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202 retval = octave_value ("Singular"); |
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203 else |
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204 retval = octave_value ("Rectangular"); |
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205 } |
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206 else if (typ == MatrixType::Full) |
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207 retval = octave_value ("Full"); |
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208 else |
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209 retval = octave_value ("Unknown"); |
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210 } |
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211 else |
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212 { |
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213 // Ok, we're changing the matrix type |
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214 std::string str_typ = args(1).string_value (); |
5323 | 215 |
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216 // FIXME -- why do I have to explicitly call the constructor? |
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217 MatrixType mattyp = MatrixType (); |
5323 | 218 |
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219 octave_idx_type nl = 0; |
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220 octave_idx_type nu = 0; |
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221 |
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222 if (error_state) |
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223 error ("matrix_type: TYPE must be a string"); |
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224 else |
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225 { |
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226 // Use STL function to convert to lower case |
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227 std::transform (str_typ.begin (), str_typ.end (), |
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228 str_typ.begin (), tolower); |
5323 | 229 |
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230 if (str_typ == "diagonal") |
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231 mattyp.mark_as_diagonal (); |
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232 if (str_typ == "permuted diagonal") |
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233 mattyp.mark_as_permuted_diagonal (); |
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234 else if (str_typ == "upper") |
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235 mattyp.mark_as_upper_triangular (); |
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236 else if (str_typ == "lower") |
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237 mattyp.mark_as_lower_triangular (); |
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238 else if (str_typ == "banded" || str_typ == "banded positive definite") |
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239 { |
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|
240 if (nargin != 4) |
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|
241 error ("matrix_type: banded matrix type requires 4 arguments"); |
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|
242 else |
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|
243 { |
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|
244 nl = args(2).nint_value (); |
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|
245 nu = args(3).nint_value (); |
5323 | 246 |
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|
247 if (error_state) |
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|
248 error ("matrix_type: band size NL, NU must be integers"); |
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249 else |
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|
250 { |
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|
251 if (nl == 1 && nu == 1) |
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252 mattyp.mark_as_tridiagonal (); |
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|
253 else |
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|
254 mattyp.mark_as_banded (nu, nl); |
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255 |
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|
256 if (str_typ == "banded positive definite") |
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|
257 mattyp.mark_as_symmetric (); |
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|
258 } |
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|
259 } |
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|
260 } |
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|
261 else if (str_typ == "positive definite") |
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|
262 { |
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|
263 mattyp.mark_as_full (); |
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|
264 mattyp.mark_as_symmetric (); |
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265 } |
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266 else if (str_typ == "singular") |
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267 mattyp.mark_as_rectangular (); |
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268 else if (str_typ == "full") |
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|
269 mattyp.mark_as_full (); |
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270 else if (str_typ == "unknown") |
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271 mattyp.invalidate_type (); |
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272 else |
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273 error ("matrix_type: Unknown matrix type %s", str_typ.c_str ()); |
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275 if (! error_state) |
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276 { |
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277 if (nargin == 3 && (str_typ == "upper" || str_typ == "lower")) |
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278 { |
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279 const ColumnVector perm = |
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280 ColumnVector (args (2).vector_value ()); |
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282 if (error_state) |
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283 error ("matrix_type: Invalid permutation vector PERM"); |
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284 else |
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285 { |
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286 octave_idx_type len = perm.length (); |
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287 dim_vector dv = args(0).dims (); |
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288 |
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289 if (len != dv(0)) |
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290 error ("matrix_type: Invalid permutation vector PERM"); |
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291 else |
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292 { |
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293 OCTAVE_LOCAL_BUFFER (octave_idx_type, p, len); |
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295 for (octave_idx_type i = 0; i < len; i++) |
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296 p[i] = static_cast<octave_idx_type> (perm (i)) - 1; |
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298 if (str_typ == "upper") |
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299 mattyp.mark_as_permuted (len, p); |
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300 else |
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301 mattyp.mark_as_permuted (len, p); |
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302 } |
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303 } |
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304 } |
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305 else if (nargin != 2 && str_typ != "banded positive definite" && |
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306 str_typ != "banded") |
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307 error ("matrix_type: Invalid number of arguments"); |
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309 if (! error_state) |
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310 { |
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311 // Set the matrix type |
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312 if (args(0).is_complex_type ()) |
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313 retval = |
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314 octave_value (args(0).sparse_complex_matrix_value (), |
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315 mattyp); |
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316 else |
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317 retval = octave_value (args(0).sparse_matrix_value (), |
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318 mattyp); |
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319 } |
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320 } |
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321 } |
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322 } |
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323 } |
5323 | 324 else |
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325 { |
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326 if (nargin == 1) |
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327 { |
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328 MatrixType mattyp; |
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330 if (args(0).is_complex_type ()) |
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331 { |
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332 mattyp = args(0).matrix_type (); |
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334 if (mattyp.is_unknown () && autocomp) |
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335 { |
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336 if (args(0).is_single_type ()) |
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337 { |
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338 FloatComplexMatrix m = args(0).float_complex_matrix_value (); |
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339 if (!error_state) |
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340 { |
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341 mattyp = MatrixType (m); |
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342 args(0).matrix_type (mattyp); |
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343 } |
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344 } |
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345 else |
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346 { |
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347 ComplexMatrix m = args(0).complex_matrix_value (); |
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348 if (!error_state) |
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349 { |
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350 mattyp = MatrixType (m); |
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351 args(0).matrix_type (mattyp); |
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352 } |
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353 } |
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354 } |
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355 } |
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356 else |
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357 { |
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358 mattyp = args(0).matrix_type (); |
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360 if (mattyp.is_unknown () && autocomp) |
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361 { |
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362 if (args(0).is_single_type ()) |
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363 { |
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364 FloatMatrix m = args(0).float_matrix_value (); |
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365 if (!error_state) |
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366 { |
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367 mattyp = MatrixType (m); |
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368 args(0).matrix_type (mattyp); |
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369 } |
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370 } |
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|
371 else |
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|
372 { |
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|
373 Matrix m = args(0).matrix_value (); |
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374 if (!error_state) |
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375 { |
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|
376 mattyp = MatrixType (m); |
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377 args(0).matrix_type (mattyp); |
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|
378 } |
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|
379 } |
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|
380 } |
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381 } |
5785 | 382 |
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383 int typ = mattyp.type (); |
5785 | 384 |
10154
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385 if (typ == MatrixType::Upper) |
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386 retval = octave_value ("Upper"); |
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387 else if (typ == MatrixType::Permuted_Upper) |
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388 retval = octave_value ("Permuted Upper"); |
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389 else if (typ == MatrixType::Lower) |
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390 retval = octave_value ("Lower"); |
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391 else if (typ == MatrixType::Permuted_Lower) |
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392 retval = octave_value ("Permuted Lower"); |
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393 else if (typ == MatrixType::Hermitian) |
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394 retval = octave_value ("Positive Definite"); |
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395 else if (typ == MatrixType::Rectangular) |
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396 { |
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|
397 if (args(0).rows () == args(0).columns ()) |
10154
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|
398 retval = octave_value ("Singular"); |
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|
399 else |
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400 retval = octave_value ("Rectangular"); |
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401 } |
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402 else if (typ == MatrixType::Full) |
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403 retval = octave_value ("Full"); |
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404 else |
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405 retval = octave_value ("Unknown"); |
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406 } |
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407 else |
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408 { |
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409 // Ok, we're changing the matrix type |
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410 std::string str_typ = args(1).string_value (); |
5785 | 411 |
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412 // FIXME -- why do I have to explicitly call the constructor? |
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413 MatrixType mattyp = MatrixType (MatrixType::Unknown, true); |
5785 | 414 |
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415 if (error_state) |
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416 error ("matrix_type: TYPE must be a string"); |
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417 else |
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418 { |
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419 // Use STL function to convert to lower case |
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420 std::transform (str_typ.begin (), str_typ.end (), |
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421 str_typ.begin (), tolower); |
5785 | 422 |
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423 if (str_typ == "upper") |
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424 mattyp.mark_as_upper_triangular (); |
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425 else if (str_typ == "lower") |
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426 mattyp.mark_as_lower_triangular (); |
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427 else if (str_typ == "positive definite") |
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428 { |
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429 mattyp.mark_as_full (); |
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430 mattyp.mark_as_symmetric (); |
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431 } |
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432 else if (str_typ == "singular") |
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433 mattyp.mark_as_rectangular (); |
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434 else if (str_typ == "full") |
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435 mattyp.mark_as_full (); |
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436 else if (str_typ == "unknown") |
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437 mattyp.invalidate_type (); |
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438 else |
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439 error ("matrix_type: Unknown matrix type %s", str_typ.c_str ()); |
5785 | 440 |
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441 if (! error_state) |
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442 { |
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443 if (nargin == 3 && (str_typ == "upper" |
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444 || str_typ == "lower")) |
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445 { |
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446 const ColumnVector perm = |
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447 ColumnVector (args (2).vector_value ()); |
5785 | 448 |
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449 if (error_state) |
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450 error ("matrix_type: Invalid permutation vector PERM"); |
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451 else |
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452 { |
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453 octave_idx_type len = perm.length (); |
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454 dim_vector dv = args(0).dims (); |
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455 |
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456 if (len != dv(0)) |
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457 error ("matrix_type: Invalid permutation vector PERM"); |
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458 else |
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459 { |
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460 OCTAVE_LOCAL_BUFFER (octave_idx_type, p, len); |
5785 | 461 |
10154
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462 for (octave_idx_type i = 0; i < len; i++) |
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463 p[i] = static_cast<octave_idx_type> (perm (i)) - 1; |
5785 | 464 |
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465 if (str_typ == "upper") |
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466 mattyp.mark_as_permuted (len, p); |
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|
467 else |
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|
468 mattyp.mark_as_permuted (len, p); |
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|
469 } |
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|
470 } |
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|
471 } |
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472 else if (nargin != 2) |
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473 error ("matrix_type: Invalid number of arguments"); |
5785 | 474 |
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475 if (! error_state) |
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|
476 { |
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|
477 // Set the matrix type |
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478 if (args(0).is_single_type ()) |
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|
479 { |
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|
480 if (args(0).is_complex_type ()) |
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481 retval = octave_value |
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482 (args(0).float_complex_matrix_value (), |
10154
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|
483 mattyp); |
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|
484 else |
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|
485 retval = octave_value |
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|
486 (args(0).float_matrix_value (), |
10154
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|
487 mattyp); |
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|
488 } |
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|
489 else |
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|
490 { |
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|
491 if (args(0).is_complex_type ()) |
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492 retval = octave_value |
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|
493 (args(0).complex_matrix_value (), |
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|
494 mattyp); |
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|
495 else |
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496 retval = octave_value |
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497 (args(0).matrix_value (), |
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498 mattyp); |
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499 } |
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|
500 } |
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|
501 } |
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|
502 } |
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|
503 } |
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504 } |
5323 | 505 } |
506 | |
507 return retval; | |
508 } | |
509 | |
510 /* | |
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511 ## FIXME: |
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512 ## Disable tests for lower under-determined and upper over-determined |
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513 ## matrices as this detection is disabled in MatrixType due to issues |
5681 | 514 ## of non minimum norm solution being found. |
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515 |
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516 %!assert (matrix_type (speye (10,10)), "Diagonal") |
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517 %!assert (matrix_type (speye (10,10)([2:10,1],:)), "Permuted Diagonal") |
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518 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1;sparse(9,1);1]]), "Upper") |
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|
519 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1;sparse(9,1);1]](:,[2,1,3:11])), "Permuted Upper") |
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|
520 %!assert (matrix_type ([speye(10,10),sparse(10,1);1,sparse(1,9),1]), "Lower") |
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|
521 %!assert (matrix_type ([speye(10,10),sparse(10,1);1,sparse(1,9),1]([2,1,3:11],:)), "Permuted Lower") |
5610 | 522 |
523 %!test | |
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|
524 %! bnd = spparms ("bandden"); |
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|
525 %! spparms ("bandden", 0.5); |
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|
526 %! a = spdiags (rand (10,3)-0.5,[-1,0,1],10,10); |
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|
527 %! assert (matrix_type (a), "Tridiagonal"); |
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528 %! assert (matrix_type (a'+a+2*speye (10)), "Tridiagonal Positive Definite"); |
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529 %! spparms ("bandden", bnd); |
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530 %!test |
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531 %! bnd=spparms ("bandden"); |
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532 %! spparms ("bandden", 0.5); |
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533 %! a = spdiags (randn (10,4),[-2:1],10,10); |
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534 %! assert (matrix_type (a), "Banded"); |
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535 %! assert (matrix_type (a'*a), "Banded Positive Definite"); |
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536 %! spparms ("bandden", bnd); |
5610 | 537 %!test |
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538 %! a = [speye(10,10),[sparse(9,1);1];-1,sparse(1,9),1]; |
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539 %! assert (matrix_type (a), "Full"); |
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540 %! assert (matrix_type (a'*a), "Positive Definite"); |
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541 |
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542 %!assert (matrix_type (speye (10,11)), "Diagonal") |
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543 %!assert (matrix_type (speye (10,11)([2:10,1],:)), "Permuted Diagonal") |
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544 %!assert (matrix_type (speye (11,10)), "Diagonal") |
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545 %!assert (matrix_type (speye (11,10)([2:11,1],:)), "Permuted Diagonal") |
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546 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1,1];sparse(9,2);[1,1]]]), "Upper") |
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547 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1,1];sparse(9,2);[1,1]]](:,[2,1,3:12])), "Permuted Upper") |
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548 %!assert (matrix_type ([speye(11,9),[1;sparse(8,1);1;0]]), "Upper") |
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549 %!assert (matrix_type ([speye(11,9),[1;sparse(8,1);1;0]](:,[2,1,3:10])), "Permuted Upper") |
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550 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1;1],sparse(2,9),[1;1]]), "Lower") |
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551 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1;1],sparse(2,9),[1;1]]([2,1,3:12],:)), "Permuted Lower") |
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552 %!assert (matrix_type ([speye(9,11);[1,sparse(1,8),1,0]]), "Lower") |
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553 %!assert (matrix_type ([speye(9,11);[1,sparse(1,8),1,0]]([2,1,3:10],:)), "Permuted Lower") |
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554 %!assert (matrix_type (spdiags (randn (10,4),[-2:1],10,9)), "Rectangular") |
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555 |
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556 %!assert (matrix_type (1i*speye (10,10)), "Diagonal") |
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557 %!assert (matrix_type (1i*speye (10,10)([2:10,1],:)), "Permuted Diagonal") |
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558 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1i;sparse(9,1);1]]), "Upper") |
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559 %!assert (matrix_type ([[speye(10,10);sparse(1,10)],[1i;sparse(9,1);1]](:,[2,1,3:11])), "Permuted Upper") |
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560 %!assert (matrix_type ([speye(10,10),sparse(10,1);1i,sparse(1,9),1]), "Lower") |
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561 %!assert (matrix_type ([speye(10,10),sparse(10,1);1i,sparse(1,9),1]([2,1,3:11],:)), "Permuted Lower") |
5610 | 562 |
563 %!test | |
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564 %! bnd = spparms ("bandden"); |
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565 %! spparms ("bandden", 0.5); |
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566 %! assert (matrix_type (spdiags (1i*randn (10,3),[-1,0,1],10,10)), "Tridiagonal"); |
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567 %! a = 1i*(rand (9,1)-0.5); |
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568 %! a = [[a;0],ones(10,1),[0;-a]]; |
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569 %! assert (matrix_type (spdiags (a,[-1,0,1],10,10)), "Tridiagonal Positive Definite"); |
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570 %! spparms ("bandden", bnd); |
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571 %!test |
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572 %! bnd = spparms ("bandden"); |
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573 %! spparms ("bandden", 0.5); |
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574 %! assert (matrix_type (spdiags (1i*randn (10,4),[-2:1],10,10)), "Banded"); |
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575 %! a = 1i*(rand (9,2)-0.5); |
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576 %! a = [[a;[0,0]],ones(10,1),[[0;-a(:,2)],[0;0;-a(1:8,1)]]]; |
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577 %! assert (matrix_type (spdiags (a,[-2:2],10,10)), "Banded Positive Definite"); |
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578 %! spparms ("bandden", bnd); |
5785 | 579 %!test |
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580 %! a = [speye(10,10),[sparse(9,1);1i];-1,sparse(1,9),1]; |
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581 %! assert (matrix_type (a), "Full"); |
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582 %! assert (matrix_type (a'*a), "Positive Definite"); |
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583 |
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584 %!assert (matrix_type (1i*speye (10,11)), "Diagonal") |
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585 %!assert (matrix_type (1i*speye (10,11)([2:10,1],:)), "Permuted Diagonal") |
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586 %!assert (matrix_type (1i*speye (11,10)), "Diagonal") |
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587 %!assert (matrix_type (1i*speye (11,10)([2:11,1],:)), "Permuted Diagonal") |
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588 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1i,1i];sparse(9,2);[1i,1i]]]), "Upper") |
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589 %#!assert (matrix_type ([[speye(10,10);sparse(1,10)],[[1i,1i];sparse(9,2);[1i,1i]]](:,[2,1,3:12])), "Permuted Upper") |
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590 %!assert (matrix_type ([speye(11,9),[1i;sparse(8,1);1i;0]]), "Upper") |
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591 %!assert (matrix_type ([speye(11,9),[1i;sparse(8,1);1i;0]](:,[2,1,3:10])), "Permuted Upper") |
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592 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1i;1i],sparse(2,9),[1i;1i]]), "Lower") |
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593 %#!assert (matrix_type ([speye(10,10),sparse(10,1);[1i;1i],sparse(2,9),[1i;1i]]([2,1,3:12],:)), "Permuted Lower") |
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594 %!assert (matrix_type ([speye(9,11);[1i,sparse(1,8),1i,0]]), "Lower") |
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595 %!assert (matrix_type ([speye(9,11);[1i,sparse(1,8),1i,0]]([2,1,3:10],:)), "Permuted Lower") |
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596 %!assert (matrix_type (1i*spdiags(randn(10,4),[-2:1],10,9)), "Rectangular") |
5785 | 597 |
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598 %!test |
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599 %! a = matrix_type (spdiags (randn (10,3),[-1,0,1],10,10), "Singular"); |
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600 %! assert (matrix_type (a), "Singular"); |
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601 |
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602 %!assert (matrix_type (triu (ones(10,10))), "Upper") |
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603 %!assert (matrix_type (triu (ones(10,10),-1)), "Full") |
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604 %!assert (matrix_type (tril (ones(10,10))), "Lower") |
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605 %!assert (matrix_type (tril (ones(10,10),1)), "Full") |
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606 %!assert (matrix_type (10*eye (10,10) + ones (10,10)), "Positive Definite") |
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607 %!assert (matrix_type (ones (11,10)), "Rectangular") |
5785 | 608 %!test |
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609 %! a = matrix_type (ones (10,10), "Singular"); |
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610 %! assert (matrix_type (a), "Singular"); |
5785 | 611 |
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612 %!assert (matrix_type (triu (1i*ones (10,10))), "Upper") |
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613 %!assert (matrix_type (triu (1i*ones (10,10),-1)), "Full") |
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614 %!assert (matrix_type (tril (1i*ones (10,10))), "Lower") |
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615 %!assert (matrix_type (tril (1i*ones (10,10),1)), "Full") |
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616 %!assert (matrix_type (10*eye (10,10) + 1i*triu (ones (10,10),1) -1i*tril (ones (10,10),-1)), "Positive Definite") |
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617 %!assert (matrix_type (ones (11,10)), "Rectangular") |
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618 %!test |
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619 %! a = matrix_type (ones (10,10), "Singular"); |
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620 %! assert (matrix_type (a), "Singular"); |
5610 | 621 */ |