[SCM] GeoGebra: Dynamic mathematics software for education branch, build, updated. upstream/3.2.40.0+dfsg1-71-g1cc4ec9
Giovanni Mascellani
gio at alioth.debian.org
Sat Jul 10 18:18:45 UTC 2010
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commit 1cc4ec914b17927a97f3a9f8d266a48ca330cba3
Author: Giovanni Mascellani <mascellani at poisson.phc.unipi.it>
Date: Sat Jul 10 20:07:44 2010 +0200
Patches updated
commit 61eb416c617ae05d4c0707a0d2c9ba995528186f
Author: Giovanni Mascellani <mascellani at poisson.phc.unipi.it>
Date: Sat Jul 10 19:38:02 2010 +0200
Patches updated
commit 12b7a224ae73e7b06e9f090b86ad1924650c13ae
Merge: 5f209c5 cfe4e31
Author: Giovanni Mascellani <mascellani at poisson.phc.unipi.it>
Date: Sat Jul 10 19:34:44 2010 +0200
Merge branch 'master' into build
-----------------------------------------------------------------------
Summary of changes:
debian/TODO | 1 -
debian/control | 2 +
debian/copyright | 516 +++++++++-
debian/get_orig_source.sh | 7 +-
debian/patches/patch/build.xml.diff | 25 +-
debian/patches/patch/jama.diff | 184 ++++
debian/patches/series | 1 +
debian/rules | 1 +
geogebra/kernel/jama/CholeskyDecomposition.java | 199 ----
geogebra/kernel/jama/EigenvalueDecomposition.java | 955 ------------------
geogebra/kernel/jama/LUDecomposition.java | 311 ------
geogebra/kernel/jama/Matrix.java | 1049 --------------------
geogebra/kernel/jama/QRDecomposition.java | 218 ----
.../kernel/jama/SingularValueDecomposition.java | 547 ----------
geogebra/kernel/jama/util/Maths.java | 20 -
15 files changed, 694 insertions(+), 3342 deletions(-)
diff --git a/debian/TODO b/debian/TODO
index cc35673..922a5dc 100644
--- a/debian/TODO
+++ b/debian/TODO
@@ -1,3 +1,2 @@
- * Verify hoteqn and jasymca (embedded copies?)
* verify exportable JARs
* add a menu entry
diff --git a/debian/control b/debian/control
index 409a269..a0b704f 100644
--- a/debian/control
+++ b/debian/control
@@ -13,6 +13,7 @@ Build-Depends:
quilt,
mathpiper,
libcommons-math-java,
+ libjama-java,
libfreehep-xml-java,
libfreehep-util-java,
libfreehep-graphics2d-java,
@@ -31,6 +32,7 @@ Depends:
default-jre | java5-runtime,
mathpiper,
libcommons-math-java,
+ libjama-java,
libfreehep-xml-java,
libfreehep-util-java,
libfreehep-graphics2d-java,
diff --git a/debian/copyright b/debian/copyright
index a9629f8..bc9cf7a 100644
--- a/debian/copyright
+++ b/debian/copyright
@@ -1,7 +1,28 @@
+Format-Specification: http://dep.debian.net/deps/dep5/
+Name: GeoGebra
+Source: http://www.geogebra.org/
+
Files: *
-Copyright: 2001-2010, Markus Hohenwarter
- Michael Borcherds
+Copyright:
+ 2001-2010, Markus Hohenwarter
+ 2007-2010, Michael Borcherds
+ 2005-2010, Yves Kreis
+ 2006, Loïc Le Coq
+ 2007, Joan Carles Naranjo
+ 2007, Victor Franco
+ 2007, Eloi Puertas
+ 2007, Philipp Weissenbacher
+ 2007-2009, Cong Liu
+ 2007-2009, Amy Varkey
+ 2007-2009, Quan Yuan
+ 2008, Hans-Petter Ulven
+ 2008, Florian Sonner
+ 2009, George Sturr
License: GPL-2+
+X-Comments: Some files have a GPL-2 only header: this has already been
+ discussed with upstream and fixed in the upstream repository, so they can
+ be considered GPL-2+. The correct headers, of course, will be merged
+ with the next release.
Files: jasymca/*
Copyright: 2006, Helmut Dersch <der at hs-furtwangen.de>
@@ -12,14 +33,120 @@ Copyright: 2006, Stefan Möller
2006, Christian Schmid
License: GPL
-Files: geogebra/gui/PointStyleListRenderer.java
-Copyright: 2009, George Sturr
-License: GPL-2+
+File: geogebra/properties/*
+Copyright:
+ Brahim Boulakbech
+ Haboubi Abdessalem
+ Maha Ah
+ Gonzalo Elcano Vizcay
+ Maja Hrbat
+ Hristo Stoyanov
+ Jaume Bartroli
+ Pep Bujosa
+ Josep Lluis Canadilla
+ Carlos Gimenez
+ Antoni Goma
+ Jorge Sanchez
+ Roser Sebastian (Spain)
+ Fu-Kwun Hwang
+ Chen-Hui Lin
+ Pegasus Roe
+ Joe Chen
+ Chen Xing
+ Sime Suljic
+ Ela Rac
+ Josip Klicinovic
+ Marie Pokorna
+ Pavel Sokol
+ Steen Grode
+ Beatrijs Versichel
+ Ivan De Winne
+ Pedro Tytgat
+ Carel van de Giessen
+ Markus Hohenwarter
+ Judith Hohenwarter
+ Yves Kreis
+ Michael Borcherds
+ Jane Albre
+ Hannu Korhonen
+ Juha Leino
+ Kirsi Malinen
+ Noel Lambert
+ Jesus Garcia Otero
+ Irene Arias Lopez
+ Lasha Kokilashvili
+ Nicholas Mousoulides
+ Constantinos Christou
+ Spiros Mavrogiannis
+ Manolis Koutlis
+ Fergadiotis Athanasios
+ Guy Hed
+ Zsuzsanna Papp-Varga
+ Andras Hrasko
+ Peter Csiba
+ Major Zoltan
+ Freyja Hreinsdottir
+ Aam Sudrajat
+ Alessandra Tomasi
+ Simona Riva
+ Akihito Wachi
+ Kazuhiro Hasegawa
+ Kyeong-Sik Choi
+ Rokas Tamosiunas
+ Linda Fahlberg-Stojanovska
+ OIKT, Faculty of Technical Sciences, UKLO
+ Sigbjorn Hals
+ Saeed Aminorroaya
+ Ali SafarNavadeh
+ Azam Zabihi
+ Ania Borkowska
+ Marzanna Miasko
+ Malgorzata Paliga
+ Ewa Piwek
+ Edyta Pobiega
+ Kasia Winkowska-Nowak
+ Humberto Bortolossi
+ Herminio Borges Neto
+ Alana Paula
+ Luciana de Lima
+ Araujo Freitas
+ Alana Souza de Olivieira
+ Jorge Geraldes
+ Antonio Ribeiro
+ Anatoly Scherbakov
+ Beatrice Versichel
+ Djordje Herceg
+ Dragoslav Herceg
+ Peter Csiba
+ Iveta Kohanova
+ Stanislav Senveter
+ Jonas Enlund
+ Thomas Lingefjard
+ Liliana Saidon
+ Erol Karakirik
+ Mustafa Dogan
+ Suleyman Cengiz
+ Nguyen Thanh Trung
+ Quang Nguyen
+ Uned Gyfieithu Translation Unit, Prifysgol Bangor University
+ Gwyn Jones
+License: CC-BY-SA-3.0+
-Files: geogebra/gui/DecorationAngleListRenderer.java,
- geogebra/gui/DecorationListRenderer.java
-Copyright: 2006, Loïc Le Coq
-License: GPL-2+
+Files: geogebra/export/epsgraphics/*
+Copyright: 2001-2004, Paul James Mutton
+License: GPL
+
+Files: geogebra/euclidian/clipping/*
+Copyright: 2009, Jeremy Wood
+License: BSD
+X-Original-Source: https://javagraphics.dev.java.net/
+
+Files: geogebra/euclidian/clipping/ClipLine.java
+Copyright: 2000, Andreas M. Rammelt <rammi at caff.de>
+License: PD
+ This source code is in the public domain.
+ USE AT YOUR OWN RISK!
+X-Original-Source: http://caff.de/dxfviewer/
Files: geogebra/gui/inputbar/AutoComplete.java
Copyright: 1999-2001, Matt Welsh
@@ -52,25 +179,6 @@ Files: jasymca/MPN.java, jasymca/Random.java
Copyright: 1998, 1999, 2000, 2001, 2002, Free Software Foundation, Inc
License: GPL-2+-link
-Files: geogebra/kernel/AlgoCurvature.java,
- geogebra/kernel/AlgoLengthFunction.java,
- geogebra/kernel/AlgoLengthFunction2Points.java,
- geogebra/kernel/AlgoTangentCurve.java,
- geogebra/kernel/AlgoCurvatureCurve.java,
- geogebra/kernel/AlgoLengthCurve.java,
- geogebra/kernel/AlgoCurvatureVectorCurve.java,
- geogebra/kernel/AlgoLengthCurve2Points.java
-Copyright: 2007, Victor Franco Espino
- Markus Hohenwarter
-License: ??
-
-Files: geogebra/kernel/AlgoListLCM.java,
- geogebra/kernel/AlgoFactor.java,
- geogebra/kernel/AlgoTake.java,
- geogebra/kernel/AlgoBinomial.java
-Copyright: 2008, Michael Borcherds
-License: GPL-2
-
Files: debian/*
Copyright: 2010, Giovanni Mascellani <gio at debian.org>
License: GPL-2+
@@ -81,8 +189,28 @@ Files: debian/geogebra.png,
Copyright: 2010, Gabor Ancsin <gabor at geogebra.org>
License: GPL-2+
+License: GPL-2+
+ This program 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 of the License, or
+ (at your option) any later version.
+ .
+ On Debian systems, the full text of the GPL-2 license can be found in the file
+ `/usr/share/common-licenses/GPL-2'.
+
+License: GPL
+ This program 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.
+ .
+ On Debian systems, the full text of the GPL-2 license can be found in the file
+ `/usr/share/common-licenses/GPL-2'.
+
License: GPL-2+-link
- Usual term of GPL-2+ apply, with the following expection:
+ This program 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 of the License, or
+ (at your option) any later version.
.
Linking this library statically or dynamically with other modules is
making a combined work based on this library. Thus, the terms and
@@ -100,6 +228,9 @@ License: GPL-2+-link
this exception to your version of the library, but you are not
obligated to do so. If you do not wish to do so, delete this
exception statement from your version.
+ .
+ On Debian systems, the full text of the GPL-2 license can be found in the file
+ `/usr/share/common-licenses/GPL-2'.
License: IBM
International Business Machines, Inc. (hereinafter called IBM) grants
@@ -124,3 +255,330 @@ License: IBM
ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS
SOFTWARE, EVEN IF IBM IS APPRISED OF THE POSSIBILITY OF SUCH
DAMAGES.
+
+License: BSD
+ All rights reserved.
+ .
+ Redistribution and use in source and binary forms, with or without
+ modification, are permitted provided that the following conditions are met:
+ .
+ * Redistributions of source code must retain the above copyright notice, this
+ list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+ * Neither the name of the author nor the names of its contributors
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+ 5. Representations, Warranties and Disclaimer
+ UNLESS OTHERWISE MUTUALLY AGREED TO BY THE PARTIES IN WRITING, LICENSOR OFFERS
+ THE WORK AS-IS AND MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND
+ CONCERNING THE WORK, EXPRESS, IMPLIED, STATUTORY OR OTHERWISE, INCLUDING,
+ WITHOUT LIMITATION, WARRANTIES OF TITLE, MERCHANTIBILITY, FITNESS FOR A
+ PARTICULAR PURPOSE, NONINFRINGEMENT, OR THE ABSENCE OF LATENT OR OTHER DEFECTS,
+ ACCURACY, OR THE PRESENCE OF ABSENCE OF ERRORS, WHETHER OR NOT DISCOVERABLE.
+ SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF IMPLIED WARRANTIES, SO SUCH
+ EXCLUSION MAY NOT APPLY TO YOU.
+ .
+ 6. Limitation on Liability. EXCEPT TO THE EXTENT REQUIRED BY APPLICABLE LAW,
+ IN NO EVENT WILL LICENSOR BE LIABLE TO YOU ON ANY LEGAL THEORY FOR ANY SPECIAL,
+ INCIDENTAL, CONSEQUENTIAL, PUNITIVE OR EXEMPLARY DAMAGES ARISING OUT OF THIS
+ LICENSE OR THE USE OF THE WORK, EVEN IF LICENSOR HAS BEEN ADVISED OF THE
+ POSSIBILITY OF SUCH DAMAGES.
+ .
+ 7. Termination
+ a. This License and the rights granted hereunder will terminate automatically
+ upon any breach by You of the terms of this License. Individuals or entities
+ who have received Adaptations or Collections from You under this License,
+ however, will not have their licenses terminated provided such individuals or
+ entities remain in full compliance with those licenses. Sections 1, 2, 5, 6, 7,
+ and 8 will survive any termination of this License.
+ b. Subject to the above terms and conditions, the license granted here is
+ perpetual (for the duration of the applicable copyright in the Work).
+ Notwithstanding the above, Licensor reserves the right to release the Work
+ under different license terms or to stop distributing the Work at any time;
+ provided, however that any such election will not serve to withdraw this
+ License (or any other license that has been, or is required to be, granted
+ under the terms of this License), and this License will continue in full force
+ and effect unless terminated as stated above.
+ .
+ 8. Miscellaneous
+ a. Each time You Distribute or Publicly Perform the Work or a Collection, the
+ Licensor offers to the recipient a license to the Work on the same terms and
+ conditions as the license granted to You under this License.
+ b. Each time You Distribute or Publicly Perform an Adaptation, Licensor
+ offers to the recipient a license to the original Work on the same terms and
+ conditions as the license granted to You under this License.
+ c. If any provision of this License is invalid or unenforceable under
+ applicable law, it shall not affect the validity or enforceability of the
+ remainder of the terms of this License, and without further action by the
+ parties to this agreement, such provision shall be reformed to the minimum
+ extent necessary to make such provision valid and enforceable.
+ d. No term or provision of this License shall be deemed waived and no breach
+ consented to unless such waiver or consent shall be in writing and signed by
+ the party to be charged with such waiver or consent.
+ e. This License constitutes the entire agreement between the parties with
+ respect to the Work licensed here. There are no understandings, agreements or
+ representations with respect to the Work not specified here. Licensor shall not
+ be bound by any additional provisions that may appear in any communication from
+ You. This License may not be modified without the mutual written agreement of
+ the Licensor and You.
+ f. The rights granted under, and the subject matter referenced, in this
+ License were drafted utilizing the terminology of the Berne Convention for the
+ Protection of Literary and Artistic Works (as amended on September 28, 1979),
+ the Rome Convention of 1961, the WIPO Copyright Treaty of 1996, the WIPO
+ Performances and Phonograms Treaty of 1996 and the Universal Copyright
+ Convention (as revised on July 24, 1971). These rights and subject matter take
+ effect in the relevant jurisdiction in which the License terms are sought to be
+ enforced according to the corresponding provisions of the implementation of
+ those treaty provisions in the applicable national law. If the standard suite
+ of rights granted under applicable copyright law includes additional rights not
+ granted under this License, such additional rights are deemed to be included in
+ the License; this License is not intended to restrict the license of any rights
+ under applicable law.
diff --git a/debian/get_orig_source.sh b/debian/get_orig_source.sh
index 1cecb7a..5507aea 100755
--- a/debian/get_orig_source.sh
+++ b/debian/get_orig_source.sh
@@ -6,6 +6,7 @@
DESTDIR="../tarballs/geogebra-$VERSION"
DESTTGZ="../tarballs/geogebra_$VERSION.orig.tar.gz"
+TEMPDIR="$(mktemp -d)"
# Downloads code from SVN repository
test -d ../tarballs/. || mkdir -p ../tarballs
@@ -24,10 +25,14 @@ rm -vf "$DESTDIR/geogebra/kernel/integration/GaussQuadIntegration.java"
# Removes embedded copies of other software
rm -vfr "$DESTDIR/org"
+mv -v "$DESTDIR/geogebra/kernel/jama/GgbMat.java" "$TEMPDIR"
+rm -vfr "$DESTDIR/geogebra/kernel/jama/"*
+mv -v "$TEMPDIR/GgbMat.java" "$DESTDIR/geogebra/kernel/jama"
# Builds tarball
tar czfv "$DESTTGZ" -C `dirname "$DESTDIR"` `basename "$DESTDIR"`
-# Deletes snapshot dir
+# Deletes snapshot and temporary dir
rm -fr "$DESTDIR"
+rm -fr "$TEMPDIR"
diff --git a/debian/patches/patch/build.xml.diff b/debian/patches/patch/build.xml.diff
index 1f8e5d9..cae1aa7 100644
--- a/debian/patches/patch/build.xml.diff
+++ b/debian/patches/patch/build.xml.diff
@@ -6,11 +6,11 @@ Fixes the build.xml for just building GeoGebra.
Signed-off-by: Giovanni Mascellani <mascellani at poisson.phc.unipi.it>
---
- build.xml | 322 ++++++++++---------------------------------------------------
- 1 files changed, 51 insertions(+), 271 deletions(-)
+ build.xml | 323 ++++++++++---------------------------------------------------
+ 1 files changed, 52 insertions(+), 271 deletions(-)
diff --git a/build.xml b/build.xml
-index e67d26f..b821cc2 100644
+index e67d26f..1cff9bc 100644
--- a/build.xml
+++ b/build.xml
@@ -38,22 +38,31 @@ office at geogebra.org
@@ -57,7 +57,7 @@ index e67d26f..b821cc2 100644
<!-- create all jar files -->
<target name="ggb-jar-files"
-@@ -63,11 +72,25 @@ office at geogebra.org
+@@ -63,11 +72,26 @@ office at geogebra.org
<manifest file="../manifest.mf">
<attribute name="Main-Class" value="geogebra.GeoGebra"/>
<attribute name="Class-Path"
@@ -70,6 +70,7 @@ index e67d26f..b821cc2 100644
+ /usr/share/geogebra/geogebra_cas.jar
+ /usr/share/java/mathpiper.jar
+ /usr/share/java/commons-math.jar
++ /usr/share/java/jama.jar
+ /usr/share/java/freehep-xml.jar
+ /usr/share/java/freehep-util.jar
+ /usr/share/java/freehep-graphics2d.jar
@@ -85,7 +86,7 @@ index e67d26f..b821cc2 100644
<mkdir dir="${build.dir}"/>
<mkdir dir="${build.dir}/packed"/>
<mkdir dir="${build.dir}/unpacked"/>
-@@ -79,6 +102,11 @@ office at geogebra.org
+@@ -79,6 +103,11 @@ office at geogebra.org
<fileset dir="${build.dir}" includes="**/geogebra*.jar, **/gluegen-rt.jar, **/jogl.jar, **/jlatexmath.jar ,**/*.jar.pack.gz, **/*.html"/>
</delete>
</target>
@@ -97,7 +98,7 @@ index e67d26f..b821cc2 100644
<target name="finish">
<delete dir="${propertiestemp.dir}"/>
-@@ -109,7 +137,7 @@ office at geogebra.org
+@@ -109,7 +138,7 @@ office at geogebra.org
</target>
<!-- geogebra.jar loads the geogebra_main.jar file and starts up the application/applet -->
@@ -106,7 +107,7 @@ index e67d26f..b821cc2 100644
<jar jarfile="${build.dir}/geogebra.jar" manifest="../manifest.mf" >
<fileset dir="${src.dir}"
includes="geogebra/*"
-@@ -132,7 +160,7 @@ office at geogebra.org
+@@ -132,7 +161,7 @@ office at geogebra.org
<!-- geogebra_main.jar includes all basic classes to run the application and applet -->
@@ -115,7 +116,7 @@ index e67d26f..b821cc2 100644
<jar jarfile="${build.dir}/geogebra_main.jar"
basedir="${src.dir}"
includes="**/*.class,
-@@ -156,7 +184,7 @@ office at geogebra.org
+@@ -156,7 +185,7 @@ office at geogebra.org
/>
</target>
@@ -124,7 +125,7 @@ index e67d26f..b821cc2 100644
<jar jarfile="${build.dir}/geogebra_export.jar"
basedir="${src.dir}"
includes="geogebra/export/**,
-@@ -166,7 +194,7 @@ office at geogebra.org
+@@ -166,7 +195,7 @@ office at geogebra.org
/>
</target>
@@ -133,7 +134,7 @@ index e67d26f..b821cc2 100644
<jar jarfile="${build.dir}/geogebra_cas.jar"
basedir="${src.dir}"
includes="geogebra/cas/**,
-@@ -176,7 +204,7 @@ office at geogebra.org
+@@ -176,7 +205,7 @@ office at geogebra.org
/>
</target>
@@ -142,7 +143,7 @@ index e67d26f..b821cc2 100644
<jar jarfile="${build.dir}/geogebra_gui.jar"
basedir="${src.dir}"
includes="geogebra/gui/**"
-@@ -184,91 +212,13 @@ office at geogebra.org
+@@ -184,91 +213,13 @@ office at geogebra.org
/>
</target>
@@ -236,7 +237,7 @@ index e67d26f..b821cc2 100644
<!-- reads the version/build number from geogebra.GeoGebra.java -->
<target name="readVersion">
<loadfile property="fullversion" srcfile="${src.dir}/geogebra/GeoGebra.java">
-@@ -327,175 +277,5 @@ office at geogebra.org
+@@ -327,175 +278,5 @@ office at geogebra.org
<echo> ${builddate} </echo>
-->
</target>
diff --git a/debian/patches/patch/jama.diff b/debian/patches/patch/jama.diff
new file mode 100644
index 0000000..de0dc4e
--- /dev/null
+++ b/debian/patches/patch/jama.diff
@@ -0,0 +1,184 @@
+From: Giovanni Mascellani <mascellani at poisson.phc.unipi.it>
+Subject: [PATCH] patch/jama
+
+This patch fixes the import used to work with the JAMA library.
+
+Signed-off-by: Giovanni Mascellani <mascellani at poisson.phc.unipi.it>
+
+---
+ geogebra/kernel/AlgoInvert.java | 2 +-
+ geogebra/kernel/AlgoTranspose.java | 2 +-
+ geogebra/kernel/jama/GgbMat.java | 68 ++++++++---------------
+ geogebra/kernel/statistics/RegressionMath.java | 2 +-
+ 4 files changed, 27 insertions(+), 47 deletions(-)
+
+diff --git a/geogebra/kernel/AlgoInvert.java b/geogebra/kernel/AlgoInvert.java
+index 0934f2f..890b8e8 100644
+--- a/geogebra/kernel/AlgoInvert.java
++++ b/geogebra/kernel/AlgoInvert.java
+@@ -81,7 +81,7 @@ public class AlgoInvert extends AlgoElement {
+ return;
+ }*/
+
+- matrix.inverseImmediate();
++ matrix = new GgbMat(matrix.inverse());
+
+ if (matrix.isUndefined()) {
+ //outputList.setUndefined();
+diff --git a/geogebra/kernel/AlgoTranspose.java b/geogebra/kernel/AlgoTranspose.java
+index 282466c..89f7495 100644
+--- a/geogebra/kernel/AlgoTranspose.java
++++ b/geogebra/kernel/AlgoTranspose.java
+@@ -63,7 +63,7 @@ public class AlgoTranspose extends AlgoElement {
+ return;
+ }
+
+- matrix.transposeImmediate();
++ matrix = new GgbMat(matrix.transpose());
+ // Transpose[{{1,2},{3,4}}]
+
+ outputList = matrix.getGeoList(outputList, cons);
+diff --git a/geogebra/kernel/jama/GgbMat.java b/geogebra/kernel/jama/GgbMat.java
+index 80ee214..e8aa175 100644
+--- a/geogebra/kernel/jama/GgbMat.java
++++ b/geogebra/kernel/jama/GgbMat.java
+@@ -1,44 +1,55 @@
+ package geogebra.kernel.jama;
+
++import java.awt.Dimension;
++
+ import geogebra.kernel.Construction;
+ import geogebra.kernel.GeoElement;
+ import geogebra.kernel.GeoList;
+ import geogebra.kernel.GeoNumeric;
+ import geogebra.main.Application;
+
++import Jama.Matrix;
+
+ public class GgbMat extends Matrix{
+
+ private boolean isUndefined = false;
+
+- public GgbMat (GeoList inputList) {
++ public GgbMat (Matrix m) {
++ super(m.getArray());
++ }
++
++ public static Dimension calcDim(GeoList inputList) {
+ int rows = inputList.size();
+ if (!inputList.isDefined() || rows == 0) {
+- setIsUndefined(true);
+- return;
++ return new Dimension(0, 0);
+ }
+
+ GeoElement geo = inputList.get(0);
+
+ if (!geo.isGeoList()) {
+- setIsUndefined(true);
+- return;
++ return new Dimension(0, 0);
+ }
+
+
+ int cols = ((GeoList)geo).size();
+
+ if (cols == 0) {
+- setIsUndefined(true);
+- return;
++ return new Dimension(0, 0);
+ }
+
+- A = new double[rows][cols];
+- m = rows;
+- n = cols;
++ return new Dimension(rows, cols);
++
++ }
++
++ public GgbMat (GeoList inputList) {
++ super(calcDim(inputList).width, calcDim(inputList).height);
++
++ int rows = this.getRowDimension();
++ int cols = this.getColumnDimension();
+
+ GeoList rowList;
+
++ GeoElement geo;
+ for (int r = 0 ; r < rows ; r++) {
+ geo = inputList.get(r);
+ if (!geo.isGeoList()) {
+@@ -62,37 +73,6 @@ public class GgbMat extends Matrix{
+ }
+ }
+
+- public void inverseImmediate() {
+-
+- try {
+- Matrix ret = inverse();
+- A = ret.A;
+- m = ret.m;
+- n = ret.n;
+- }
+- catch (Exception e) { // can't invert
+- setIsUndefined(true);
+- }
+-
+- }
+-
+-
+-
+- public void transposeImmediate() {
+-
+- double[][] C = new double[n][m];
+- for (int i = 0; i < m; i++) {
+- for (int j = 0; j < n; j++) {
+- C[j][i] = A[i][j];
+- }
+- }
+- A = C;
+- int temp = n;
+- n = m;
+- m = temp;
+- //Application.debug(""+A[0][0]);
+- }
+-
+ /*
+ * returns GgbMatrix as a GeoList eg { {1,2}, {3,4} }
+ */
+@@ -106,9 +86,9 @@ public class GgbMat extends Matrix{
+ outputList.clear();
+ outputList.setDefined(true);
+
+- for (int r = 0 ; r < m ; r++) {
++ for (int r = 0 ; r < this.getRowDimension() ; r++) {
+ GeoList columnList = new GeoList(cons);
+- for (int c = 0 ; c < n ; c++) {
++ for (int c = 0 ; c < this.getColumnDimension() ; c++) {
+ //Application.debug(get(r, c)+"");
+ columnList.add(new GeoNumeric(cons, get(r, c)));
+ }
+@@ -131,7 +111,7 @@ public class GgbMat extends Matrix{
+ }
+
+ public boolean isSquare() {
+- return (n == m);
++ return (this.getColumnDimension() == this.getRowDimension());
+ }
+
+
+diff --git a/geogebra/kernel/statistics/RegressionMath.java b/geogebra/kernel/statistics/RegressionMath.java
+index 55ee4fc..8d4ff23 100644
+--- a/geogebra/kernel/statistics/RegressionMath.java
++++ b/geogebra/kernel/statistics/RegressionMath.java
+@@ -2,7 +2,7 @@ package geogebra.kernel.statistics;
+ import geogebra.kernel.GeoList;
+ import geogebra.kernel.GeoPoint;
+ import geogebra.kernel.GeoElement;
+-import geogebra.kernel.jama.*;
++import Jama.*;
+
+ /*
+ GeoGebra - Dynamic Mathematics for Everyone
+--
+tg: (f0cc56c..) patch/jama (depends on: master)
diff --git a/debian/patches/series b/debian/patches/series
index 3b7f55c..9c9d63f 100644
--- a/debian/patches/series
+++ b/debian/patches/series
@@ -1,4 +1,5 @@
patch/ScientificFormat.java.diff -p1
patch/build.xml.diff -p1
patch/flanagan_nonfree.diff -p1
+patch/jama.diff -p1
patch/no_mac.diff -p1
diff --git a/debian/rules b/debian/rules
index 9faabf3..cdd4bbe 100755
--- a/debian/rules
+++ b/debian/rules
@@ -15,6 +15,7 @@ DEB_JARS := /usr/share/java/ant-nodeps.jar
# Dependencies
DEB_JARS += /usr/share/java/mathpiper.jar
DEB_JARS += /usr/share/java/commons-math.jar
+DEB_JARS += /usr/share/java/jama.jar
DEB_JARS += /usr/share/java/freehep-xml.jar
DEB_JARS += /usr/share/java/freehep-util.jar
DEB_JARS += /usr/share/java/freehep-graphics2d.jar
diff --git a/geogebra/kernel/jama/CholeskyDecomposition.java b/geogebra/kernel/jama/CholeskyDecomposition.java
deleted file mode 100644
index c24b073..0000000
--- a/geogebra/kernel/jama/CholeskyDecomposition.java
+++ /dev/null
@@ -1,199 +0,0 @@
-package geogebra.kernel.jama;
-
- /** Cholesky Decomposition.
- <P>
- For a symmetric, positive definite matrix A, the Cholesky decomposition
- is an lower triangular matrix L so that A = L*L'.
- <P>
- If the matrix is not symmetric or positive definite, the constructor
- returns a partial decomposition and sets an internal flag that may
- be queried by the isSPD() method.
- */
-
-public class CholeskyDecomposition implements java.io.Serializable {
-
-/* ------------------------
- Class variables
- * ------------------------ */
-
- /** Array for internal storage of decomposition.
- @serial internal array storage.
- */
- private double[][] L;
-
- /** Row and column dimension (square matrix).
- @serial matrix dimension.
- */
- private int n;
-
- /** Symmetric and positive definite flag.
- @serial is symmetric and positive definite flag.
- */
- private boolean isspd;
-
-/* ------------------------
- Constructor
- * ------------------------ */
-
- /** Cholesky algorithm for symmetric and positive definite matrix.
- @param A Square, symmetric matrix.
- @return Structure to access L and isspd flag.
- */
-
- public CholeskyDecomposition (Matrix Arg) {
-
-
- // Initialize.
- double[][] A = Arg.getArray();
- n = Arg.getRowDimension();
- L = new double[n][n];
- isspd = (Arg.getColumnDimension() == n);
- // Main loop.
- for (int j = 0; j < n; j++) {
- double[] Lrowj = L[j];
- double d = 0.0;
- for (int k = 0; k < j; k++) {
- double[] Lrowk = L[k];
- double s = 0.0;
- for (int i = 0; i < k; i++) {
- s += Lrowk[i]*Lrowj[i];
- }
- Lrowj[k] = s = (A[j][k] - s)/L[k][k];
- d = d + s*s;
- isspd = isspd & (A[k][j] == A[j][k]);
- }
- d = A[j][j] - d;
- isspd = isspd & (d > 0.0);
- L[j][j] = Math.sqrt(Math.max(d,0.0));
- for (int k = j+1; k < n; k++) {
- L[j][k] = 0.0;
- }
- }
- }
-
-/* ------------------------
- Temporary, experimental code.
- * ------------------------ *\
-
- \** Right Triangular Cholesky Decomposition.
- <P>
- For a symmetric, positive definite matrix A, the Right Cholesky
- decomposition is an upper triangular matrix R so that A = R'*R.
- This constructor computes R with the Fortran inspired column oriented
- algorithm used in LINPACK and MATLAB. In Java, we suspect a row oriented,
- lower triangular decomposition is faster. We have temporarily included
- this constructor here until timing experiments confirm this suspicion.
- *\
-
- \** Array for internal storage of right triangular decomposition. **\
- private transient double[][] R;
-
- \** Cholesky algorithm for symmetric and positive definite matrix.
- @param A Square, symmetric matrix.
- @param rightflag Actual value ignored.
- @return Structure to access R and isspd flag.
- *\
-
- public CholeskyDecomposition (Matrix Arg, int rightflag) {
- // Initialize.
- double[][] A = Arg.getArray();
- n = Arg.getColumnDimension();
- R = new double[n][n];
- isspd = (Arg.getColumnDimension() == n);
- // Main loop.
- for (int j = 0; j < n; j++) {
- double d = 0.0;
- for (int k = 0; k < j; k++) {
- double s = A[k][j];
- for (int i = 0; i < k; i++) {
- s = s - R[i][k]*R[i][j];
- }
- R[k][j] = s = s/R[k][k];
- d = d + s*s;
- isspd = isspd & (A[k][j] == A[j][k]);
- }
- d = A[j][j] - d;
- isspd = isspd & (d > 0.0);
- R[j][j] = Math.sqrt(Math.max(d,0.0));
- for (int k = j+1; k < n; k++) {
- R[k][j] = 0.0;
- }
- }
- }
-
- \** Return upper triangular factor.
- @return R
- *\
-
- public Matrix getR () {
- return new Matrix(R,n,n);
- }
-
-\* ------------------------
- End of temporary code.
- * ------------------------ */
-
-/* ------------------------
- Public Methods
- * ------------------------ */
-
- /** Is the matrix symmetric and positive definite?
- @return true if A is symmetric and positive definite.
- */
-
- public boolean isSPD () {
- return isspd;
- }
-
- /** Return triangular factor.
- @return L
- */
-
- public Matrix getL () {
- return new Matrix(L,n,n);
- }
-
- /** Solve A*X = B
- @param B A Matrix with as many rows as A and any number of columns.
- @return X so that L*L'*X = B
- @exception IllegalArgumentException Matrix row dimensions must agree.
- @exception RuntimeException Matrix is not symmetric positive definite.
- */
-
- public Matrix solve (Matrix B) {
- if (B.getRowDimension() != n) {
- throw new IllegalArgumentException("Matrix row dimensions must agree.");
- }
- if (!isspd) {
- throw new RuntimeException("Matrix is not symmetric positive definite.");
- }
-
- // Copy right hand side.
- double[][] X = B.getArrayCopy();
- int nx = B.getColumnDimension();
-
- // Solve L*Y = B;
- for (int k = 0; k < n; k++) {
- for (int j = 0; j < nx; j++) {
- for (int i = 0; i < k ; i++) {
- X[k][j] -= X[i][j]*L[k][i];
- }
- X[k][j] /= L[k][k];
- }
- }
-
- // Solve L'*X = Y;
- for (int k = n-1; k >= 0; k--) {
- for (int j = 0; j < nx; j++) {
- for (int i = k+1; i < n ; i++) {
- X[k][j] -= X[i][j]*L[i][k];
- }
- X[k][j] /= L[k][k];
- }
- }
-
-
- return new Matrix(X,n,nx);
- }
-}
-
diff --git a/geogebra/kernel/jama/EigenvalueDecomposition.java b/geogebra/kernel/jama/EigenvalueDecomposition.java
deleted file mode 100644
index d4dd03c..0000000
--- a/geogebra/kernel/jama/EigenvalueDecomposition.java
+++ /dev/null
@@ -1,955 +0,0 @@
-package geogebra.kernel.jama;
-import geogebra.kernel.jama.util.*;
-
-/** Eigenvalues and eigenvectors of a real matrix.
-<P>
- If A is symmetric, then A = V*D*V' where the eigenvalue matrix D is
- diagonal and the eigenvector matrix V is orthogonal.
- I.e. A = V.times(D.times(V.transpose())) and
- V.times(V.transpose()) equals the identity matrix.
-<P>
- If A is not symmetric, then the eigenvalue matrix D is block diagonal
- with the real eigenvalues in 1-by-1 blocks and any complex eigenvalues,
- lambda + i*mu, in 2-by-2 blocks, [lambda, mu; -mu, lambda]. The
- columns of V represent the eigenvectors in the sense that A*V = V*D,
- i.e. A.times(V) equals V.times(D). The matrix V may be badly
- conditioned, or even singular, so the validity of the equation
- A = V*D*inverse(V) depends upon V.cond().
-**/
-
-public class EigenvalueDecomposition implements java.io.Serializable {
-
-/* ------------------------
- Class variables
- * ------------------------ */
-
- /** Row and column dimension (square matrix).
- @serial matrix dimension.
- */
- private int n;
-
- /** Symmetry flag.
- @serial internal symmetry flag.
- */
- private boolean issymmetric;
-
- /** Arrays for internal storage of eigenvalues.
- @serial internal storage of eigenvalues.
- */
- private double[] d, e;
-
- /** Array for internal storage of eigenvectors.
- @serial internal storage of eigenvectors.
- */
- private double[][] V;
-
- /** Array for internal storage of nonsymmetric Hessenberg form.
- @serial internal storage of nonsymmetric Hessenberg form.
- */
- private double[][] H;
-
- /** Working storage for nonsymmetric algorithm.
- @serial working storage for nonsymmetric algorithm.
- */
- private double[] ort;
-
-/* ------------------------
- Private Methods
- * ------------------------ */
-
- // Symmetric Householder reduction to tridiagonal form.
-
- private void tred2 () {
-
- // This is derived from the Algol procedures tred2 by
- // Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
- // Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
- // Fortran subroutine in EISPACK.
-
- for (int j = 0; j < n; j++) {
- d[j] = V[n-1][j];
- }
-
- // Householder reduction to tridiagonal form.
-
- for (int i = n-1; i > 0; i--) {
-
- // Scale to avoid under/overflow.
-
- double scale = 0.0;
- double h = 0.0;
- for (int k = 0; k < i; k++) {
- scale = scale + Math.abs(d[k]);
- }
- if (scale == 0.0) {
- e[i] = d[i-1];
- for (int j = 0; j < i; j++) {
- d[j] = V[i-1][j];
- V[i][j] = 0.0;
- V[j][i] = 0.0;
- }
- } else {
-
- // Generate Householder vector.
-
- for (int k = 0; k < i; k++) {
- d[k] /= scale;
- h += d[k] * d[k];
- }
- double f = d[i-1];
- double g = Math.sqrt(h);
- if (f > 0) {
- g = -g;
- }
- e[i] = scale * g;
- h = h - f * g;
- d[i-1] = f - g;
- for (int j = 0; j < i; j++) {
- e[j] = 0.0;
- }
-
- // Apply similarity transformation to remaining columns.
-
- for (int j = 0; j < i; j++) {
- f = d[j];
- V[j][i] = f;
- g = e[j] + V[j][j] * f;
- for (int k = j+1; k <= i-1; k++) {
- g += V[k][j] * d[k];
- e[k] += V[k][j] * f;
- }
- e[j] = g;
- }
- f = 0.0;
- for (int j = 0; j < i; j++) {
- e[j] /= h;
- f += e[j] * d[j];
- }
- double hh = f / (h + h);
- for (int j = 0; j < i; j++) {
- e[j] -= hh * d[j];
- }
- for (int j = 0; j < i; j++) {
- f = d[j];
- g = e[j];
- for (int k = j; k <= i-1; k++) {
- V[k][j] -= (f * e[k] + g * d[k]);
- }
- d[j] = V[i-1][j];
- V[i][j] = 0.0;
- }
- }
- d[i] = h;
- }
-
- // Accumulate transformations.
-
- for (int i = 0; i < n-1; i++) {
- V[n-1][i] = V[i][i];
- V[i][i] = 1.0;
- double h = d[i+1];
- if (h != 0.0) {
- for (int k = 0; k <= i; k++) {
- d[k] = V[k][i+1] / h;
- }
- for (int j = 0; j <= i; j++) {
- double g = 0.0;
- for (int k = 0; k <= i; k++) {
- g += V[k][i+1] * V[k][j];
- }
- for (int k = 0; k <= i; k++) {
- V[k][j] -= g * d[k];
- }
- }
- }
- for (int k = 0; k <= i; k++) {
- V[k][i+1] = 0.0;
- }
- }
- for (int j = 0; j < n; j++) {
- d[j] = V[n-1][j];
- V[n-1][j] = 0.0;
- }
- V[n-1][n-1] = 1.0;
- e[0] = 0.0;
- }
-
- // Symmetric tridiagonal QL algorithm.
-
- private void tql2 () {
-
- // This is derived from the Algol procedures tql2, by
- // Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
- // Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
- // Fortran subroutine in EISPACK.
-
- for (int i = 1; i < n; i++) {
- e[i-1] = e[i];
- }
- e[n-1] = 0.0;
-
- double f = 0.0;
- double tst1 = 0.0;
- double eps = Math.pow(2.0,-52.0);
- for (int l = 0; l < n; l++) {
-
- // Find small subdiagonal element
-
- tst1 = Math.max(tst1,Math.abs(d[l]) + Math.abs(e[l]));
- int m = l;
- while (m < n) {
- if (Math.abs(e[m]) <= eps*tst1) {
- break;
- }
- m++;
- }
-
- // If m == l, d[l] is an eigenvalue,
- // otherwise, iterate.
-
- if (m > l) {
- int iter = 0;
- do {
- iter = iter + 1; // (Could check iteration count here.)
-
- // Compute implicit shift
-
- double g = d[l];
- double p = (d[l+1] - g) / (2.0 * e[l]);
- double r = Maths.hypot(p,1.0);
- if (p < 0) {
- r = -r;
- }
- d[l] = e[l] / (p + r);
- d[l+1] = e[l] * (p + r);
- double dl1 = d[l+1];
- double h = g - d[l];
- for (int i = l+2; i < n; i++) {
- d[i] -= h;
- }
- f = f + h;
-
- // Implicit QL transformation.
-
- p = d[m];
- double c = 1.0;
- double c2 = c;
- double c3 = c;
- double el1 = e[l+1];
- double s = 0.0;
- double s2 = 0.0;
- for (int i = m-1; i >= l; i--) {
- c3 = c2;
- c2 = c;
- s2 = s;
- g = c * e[i];
- h = c * p;
- r = Maths.hypot(p,e[i]);
- e[i+1] = s * r;
- s = e[i] / r;
- c = p / r;
- p = c * d[i] - s * g;
- d[i+1] = h + s * (c * g + s * d[i]);
-
- // Accumulate transformation.
-
- for (int k = 0; k < n; k++) {
- h = V[k][i+1];
- V[k][i+1] = s * V[k][i] + c * h;
- V[k][i] = c * V[k][i] - s * h;
- }
- }
- p = -s * s2 * c3 * el1 * e[l] / dl1;
- e[l] = s * p;
- d[l] = c * p;
-
- // Check for convergence.
-
- } while (Math.abs(e[l]) > eps*tst1);
- }
- d[l] = d[l] + f;
- e[l] = 0.0;
- }
-
- // Sort eigenvalues and corresponding vectors.
-
- for (int i = 0; i < n-1; i++) {
- int k = i;
- double p = d[i];
- for (int j = i+1; j < n; j++) {
- if (d[j] < p) {
- k = j;
- p = d[j];
- }
- }
- if (k != i) {
- d[k] = d[i];
- d[i] = p;
- for (int j = 0; j < n; j++) {
- p = V[j][i];
- V[j][i] = V[j][k];
- V[j][k] = p;
- }
- }
- }
- }
-
- // Nonsymmetric reduction to Hessenberg form.
-
- private void orthes () {
-
- // This is derived from the Algol procedures orthes and ortran,
- // by Martin and Wilkinson, Handbook for Auto. Comp.,
- // Vol.ii-Linear Algebra, and the corresponding
- // Fortran subroutines in EISPACK.
-
- int low = 0;
- int high = n-1;
-
- for (int m = low+1; m <= high-1; m++) {
-
- // Scale column.
-
- double scale = 0.0;
- for (int i = m; i <= high; i++) {
- scale = scale + Math.abs(H[i][m-1]);
- }
- if (scale != 0.0) {
-
- // Compute Householder transformation.
-
- double h = 0.0;
- for (int i = high; i >= m; i--) {
- ort[i] = H[i][m-1]/scale;
- h += ort[i] * ort[i];
- }
- double g = Math.sqrt(h);
- if (ort[m] > 0) {
- g = -g;
- }
- h = h - ort[m] * g;
- ort[m] = ort[m] - g;
-
- // Apply Householder similarity transformation
- // H = (I-u*u'/h)*H*(I-u*u')/h)
-
- for (int j = m; j < n; j++) {
- double f = 0.0;
- for (int i = high; i >= m; i--) {
- f += ort[i]*H[i][j];
- }
- f = f/h;
- for (int i = m; i <= high; i++) {
- H[i][j] -= f*ort[i];
- }
- }
-
- for (int i = 0; i <= high; i++) {
- double f = 0.0;
- for (int j = high; j >= m; j--) {
- f += ort[j]*H[i][j];
- }
- f = f/h;
- for (int j = m; j <= high; j++) {
- H[i][j] -= f*ort[j];
- }
- }
- ort[m] = scale*ort[m];
- H[m][m-1] = scale*g;
- }
- }
-
- // Accumulate transformations (Algol's ortran).
-
- for (int i = 0; i < n; i++) {
- for (int j = 0; j < n; j++) {
- V[i][j] = (i == j ? 1.0 : 0.0);
- }
- }
-
- for (int m = high-1; m >= low+1; m--) {
- if (H[m][m-1] != 0.0) {
- for (int i = m+1; i <= high; i++) {
- ort[i] = H[i][m-1];
- }
- for (int j = m; j <= high; j++) {
- double g = 0.0;
- for (int i = m; i <= high; i++) {
- g += ort[i] * V[i][j];
- }
- // Double division avoids possible underflow
- g = (g / ort[m]) / H[m][m-1];
- for (int i = m; i <= high; i++) {
- V[i][j] += g * ort[i];
- }
- }
- }
- }
- }
-
-
- // Complex scalar division.
-
- private transient double cdivr, cdivi;
- private void cdiv(double xr, double xi, double yr, double yi) {
- double r,d;
- if (Math.abs(yr) > Math.abs(yi)) {
- r = yi/yr;
- d = yr + r*yi;
- cdivr = (xr + r*xi)/d;
- cdivi = (xi - r*xr)/d;
- } else {
- r = yr/yi;
- d = yi + r*yr;
- cdivr = (r*xr + xi)/d;
- cdivi = (r*xi - xr)/d;
- }
- }
-
-
- // Nonsymmetric reduction from Hessenberg to real Schur form.
-
- private void hqr2 () {
-
- // This is derived from the Algol procedure hqr2,
- // by Martin and Wilkinson, Handbook for Auto. Comp.,
- // Vol.ii-Linear Algebra, and the corresponding
- // Fortran subroutine in EISPACK.
-
- // Initialize
-
- int nn = this.n;
- int n = nn-1;
- int low = 0;
- int high = nn-1;
- double eps = Math.pow(2.0,-52.0);
- double exshift = 0.0;
- double p=0,q=0,r=0,s=0,z=0,t,w,x,y;
-
- // Store roots isolated by balanc and compute matrix norm
-
- double norm = 0.0;
- for (int i = 0; i < nn; i++) {
- if (i < low | i > high) {
- d[i] = H[i][i];
- e[i] = 0.0;
- }
- for (int j = Math.max(i-1,0); j < nn; j++) {
- norm = norm + Math.abs(H[i][j]);
- }
- }
-
- // Outer loop over eigenvalue index
-
- int iter = 0;
- while (n >= low) {
-
- // Look for single small sub-diagonal element
-
- int l = n;
- while (l > low) {
- s = Math.abs(H[l-1][l-1]) + Math.abs(H[l][l]);
- if (s == 0.0) {
- s = norm;
- }
- if (Math.abs(H[l][l-1]) < eps * s) {
- break;
- }
- l--;
- }
-
- // Check for convergence
- // One root found
-
- if (l == n) {
- H[n][n] = H[n][n] + exshift;
- d[n] = H[n][n];
- e[n] = 0.0;
- n--;
- iter = 0;
-
- // Two roots found
-
- } else if (l == n-1) {
- w = H[n][n-1] * H[n-1][n];
- p = (H[n-1][n-1] - H[n][n]) / 2.0;
- q = p * p + w;
- z = Math.sqrt(Math.abs(q));
- H[n][n] = H[n][n] + exshift;
- H[n-1][n-1] = H[n-1][n-1] + exshift;
- x = H[n][n];
-
- // Real pair
-
- if (q >= 0) {
- if (p >= 0) {
- z = p + z;
- } else {
- z = p - z;
- }
- d[n-1] = x + z;
- d[n] = d[n-1];
- if (z != 0.0) {
- d[n] = x - w / z;
- }
- e[n-1] = 0.0;
- e[n] = 0.0;
- x = H[n][n-1];
- s = Math.abs(x) + Math.abs(z);
- p = x / s;
- q = z / s;
- r = Math.sqrt(p * p+q * q);
- p = p / r;
- q = q / r;
-
- // Row modification
-
- for (int j = n-1; j < nn; j++) {
- z = H[n-1][j];
- H[n-1][j] = q * z + p * H[n][j];
- H[n][j] = q * H[n][j] - p * z;
- }
-
- // Column modification
-
- for (int i = 0; i <= n; i++) {
- z = H[i][n-1];
- H[i][n-1] = q * z + p * H[i][n];
- H[i][n] = q * H[i][n] - p * z;
- }
-
- // Accumulate transformations
-
- for (int i = low; i <= high; i++) {
- z = V[i][n-1];
- V[i][n-1] = q * z + p * V[i][n];
- V[i][n] = q * V[i][n] - p * z;
- }
-
- // Complex pair
-
- } else {
- d[n-1] = x + p;
- d[n] = x + p;
- e[n-1] = z;
- e[n] = -z;
- }
- n = n - 2;
- iter = 0;
-
- // No convergence yet
-
- } else {
-
- // Form shift
-
- x = H[n][n];
- y = 0.0;
- w = 0.0;
- if (l < n) {
- y = H[n-1][n-1];
- w = H[n][n-1] * H[n-1][n];
- }
-
- // Wilkinson's original ad hoc shift
-
- if (iter == 10) {
- exshift += x;
- for (int i = low; i <= n; i++) {
- H[i][i] -= x;
- }
- s = Math.abs(H[n][n-1]) + Math.abs(H[n-1][n-2]);
- x = y = 0.75 * s;
- w = -0.4375 * s * s;
- }
-
- // MATLAB's new ad hoc shift
-
- if (iter == 30) {
- s = (y - x) / 2.0;
- s = s * s + w;
- if (s > 0) {
- s = Math.sqrt(s);
- if (y < x) {
- s = -s;
- }
- s = x - w / ((y - x) / 2.0 + s);
- for (int i = low; i <= n; i++) {
- H[i][i] -= s;
- }
- exshift += s;
- x = y = w = 0.964;
- }
- }
-
- iter = iter + 1; // (Could check iteration count here.)
-
- // Look for two consecutive small sub-diagonal elements
-
- int m = n-2;
- while (m >= l) {
- z = H[m][m];
- r = x - z;
- s = y - z;
- p = (r * s - w) / H[m+1][m] + H[m][m+1];
- q = H[m+1][m+1] - z - r - s;
- r = H[m+2][m+1];
- s = Math.abs(p) + Math.abs(q) + Math.abs(r);
- p = p / s;
- q = q / s;
- r = r / s;
- if (m == l) {
- break;
- }
- if (Math.abs(H[m][m-1]) * (Math.abs(q) + Math.abs(r)) <
- eps * (Math.abs(p) * (Math.abs(H[m-1][m-1]) + Math.abs(z) +
- Math.abs(H[m+1][m+1])))) {
- break;
- }
- m--;
- }
-
- for (int i = m+2; i <= n; i++) {
- H[i][i-2] = 0.0;
- if (i > m+2) {
- H[i][i-3] = 0.0;
- }
- }
-
- // Double QR step involving rows l:n and columns m:n
-
- for (int k = m; k <= n-1; k++) {
- boolean notlast = (k != n-1);
- if (k != m) {
- p = H[k][k-1];
- q = H[k+1][k-1];
- r = (notlast ? H[k+2][k-1] : 0.0);
- x = Math.abs(p) + Math.abs(q) + Math.abs(r);
- if (x != 0.0) {
- p = p / x;
- q = q / x;
- r = r / x;
- }
- }
- if (x == 0.0) {
- break;
- }
- s = Math.sqrt(p * p + q * q + r * r);
- if (p < 0) {
- s = -s;
- }
- if (s != 0) {
- if (k != m) {
- H[k][k-1] = -s * x;
- } else if (l != m) {
- H[k][k-1] = -H[k][k-1];
- }
- p = p + s;
- x = p / s;
- y = q / s;
- z = r / s;
- q = q / p;
- r = r / p;
-
- // Row modification
-
- for (int j = k; j < nn; j++) {
- p = H[k][j] + q * H[k+1][j];
- if (notlast) {
- p = p + r * H[k+2][j];
- H[k+2][j] = H[k+2][j] - p * z;
- }
- H[k][j] = H[k][j] - p * x;
- H[k+1][j] = H[k+1][j] - p * y;
- }
-
- // Column modification
-
- for (int i = 0; i <= Math.min(n,k+3); i++) {
- p = x * H[i][k] + y * H[i][k+1];
- if (notlast) {
- p = p + z * H[i][k+2];
- H[i][k+2] = H[i][k+2] - p * r;
- }
- H[i][k] = H[i][k] - p;
- H[i][k+1] = H[i][k+1] - p * q;
- }
-
- // Accumulate transformations
-
- for (int i = low; i <= high; i++) {
- p = x * V[i][k] + y * V[i][k+1];
- if (notlast) {
- p = p + z * V[i][k+2];
- V[i][k+2] = V[i][k+2] - p * r;
- }
- V[i][k] = V[i][k] - p;
- V[i][k+1] = V[i][k+1] - p * q;
- }
- } // (s != 0)
- } // k loop
- } // check convergence
- } // while (n >= low)
-
- // Backsubstitute to find vectors of upper triangular form
-
- if (norm == 0.0) {
- return;
- }
-
- for (n = nn-1; n >= 0; n--) {
- p = d[n];
- q = e[n];
-
- // Real vector
-
- if (q == 0) {
- int l = n;
- H[n][n] = 1.0;
- for (int i = n-1; i >= 0; i--) {
- w = H[i][i] - p;
- r = 0.0;
- for (int j = l; j <= n; j++) {
- r = r + H[i][j] * H[j][n];
- }
- if (e[i] < 0.0) {
- z = w;
- s = r;
- } else {
- l = i;
- if (e[i] == 0.0) {
- if (w != 0.0) {
- H[i][n] = -r / w;
- } else {
- H[i][n] = -r / (eps * norm);
- }
-
- // Solve real equations
-
- } else {
- x = H[i][i+1];
- y = H[i+1][i];
- q = (d[i] - p) * (d[i] - p) + e[i] * e[i];
- t = (x * s - z * r) / q;
- H[i][n] = t;
- if (Math.abs(x) > Math.abs(z)) {
- H[i+1][n] = (-r - w * t) / x;
- } else {
- H[i+1][n] = (-s - y * t) / z;
- }
- }
-
- // Overflow control
-
- t = Math.abs(H[i][n]);
- if ((eps * t) * t > 1) {
- for (int j = i; j <= n; j++) {
- H[j][n] = H[j][n] / t;
- }
- }
- }
- }
-
- // Complex vector
-
- } else if (q < 0) {
- int l = n-1;
-
- // Last vector component imaginary so matrix is triangular
-
- if (Math.abs(H[n][n-1]) > Math.abs(H[n-1][n])) {
- H[n-1][n-1] = q / H[n][n-1];
- H[n-1][n] = -(H[n][n] - p) / H[n][n-1];
- } else {
- cdiv(0.0,-H[n-1][n],H[n-1][n-1]-p,q);
- H[n-1][n-1] = cdivr;
- H[n-1][n] = cdivi;
- }
- H[n][n-1] = 0.0;
- H[n][n] = 1.0;
- for (int i = n-2; i >= 0; i--) {
- double ra,sa,vr,vi;
- ra = 0.0;
- sa = 0.0;
- for (int j = l; j <= n; j++) {
- ra = ra + H[i][j] * H[j][n-1];
- sa = sa + H[i][j] * H[j][n];
- }
- w = H[i][i] - p;
-
- if (e[i] < 0.0) {
- z = w;
- r = ra;
- s = sa;
- } else {
- l = i;
- if (e[i] == 0) {
- cdiv(-ra,-sa,w,q);
- H[i][n-1] = cdivr;
- H[i][n] = cdivi;
- } else {
-
- // Solve complex equations
-
- x = H[i][i+1];
- y = H[i+1][i];
- vr = (d[i] - p) * (d[i] - p) + e[i] * e[i] - q * q;
- vi = (d[i] - p) * 2.0 * q;
- if (vr == 0.0 & vi == 0.0) {
- vr = eps * norm * (Math.abs(w) + Math.abs(q) +
- Math.abs(x) + Math.abs(y) + Math.abs(z));
- }
- cdiv(x*r-z*ra+q*sa,x*s-z*sa-q*ra,vr,vi);
- H[i][n-1] = cdivr;
- H[i][n] = cdivi;
- if (Math.abs(x) > (Math.abs(z) + Math.abs(q))) {
- H[i+1][n-1] = (-ra - w * H[i][n-1] + q * H[i][n]) / x;
- H[i+1][n] = (-sa - w * H[i][n] - q * H[i][n-1]) / x;
- } else {
- cdiv(-r-y*H[i][n-1],-s-y*H[i][n],z,q);
- H[i+1][n-1] = cdivr;
- H[i+1][n] = cdivi;
- }
- }
-
- // Overflow control
-
- t = Math.max(Math.abs(H[i][n-1]),Math.abs(H[i][n]));
- if ((eps * t) * t > 1) {
- for (int j = i; j <= n; j++) {
- H[j][n-1] = H[j][n-1] / t;
- H[j][n] = H[j][n] / t;
- }
- }
- }
- }
- }
- }
-
- // Vectors of isolated roots
-
- for (int i = 0; i < nn; i++) {
- if (i < low | i > high) {
- for (int j = i; j < nn; j++) {
- V[i][j] = H[i][j];
- }
- }
- }
-
- // Back transformation to get eigenvectors of original matrix
-
- for (int j = nn-1; j >= low; j--) {
- for (int i = low; i <= high; i++) {
- z = 0.0;
- for (int k = low; k <= Math.min(j,high); k++) {
- z = z + V[i][k] * H[k][j];
- }
- V[i][j] = z;
- }
- }
- }
-
-
-/* ------------------------
- Constructor
- * ------------------------ */
-
- /** Check for symmetry, then construct the eigenvalue decomposition
- @param A Square matrix
- @return Structure to access D and V.
- */
-
- public EigenvalueDecomposition (Matrix Arg) {
- double[][] A = Arg.getArray();
- n = Arg.getColumnDimension();
- V = new double[n][n];
- d = new double[n];
- e = new double[n];
-
- issymmetric = true;
- for (int j = 0; (j < n) & issymmetric; j++) {
- for (int i = 0; (i < n) & issymmetric; i++) {
- issymmetric = (A[i][j] == A[j][i]);
- }
- }
-
- if (issymmetric) {
- for (int i = 0; i < n; i++) {
- for (int j = 0; j < n; j++) {
- V[i][j] = A[i][j];
- }
- }
-
- // Tridiagonalize.
- tred2();
-
- // Diagonalize.
- tql2();
-
- } else {
- H = new double[n][n];
- ort = new double[n];
-
- for (int j = 0; j < n; j++) {
- for (int i = 0; i < n; i++) {
- H[i][j] = A[i][j];
- }
- }
-
- // Reduce to Hessenberg form.
- orthes();
-
- // Reduce Hessenberg to real Schur form.
- hqr2();
- }
- }
-
-/* ------------------------
- Public Methods
- * ------------------------ */
-
- /** Return the eigenvector matrix
- @return V
- */
-
- public Matrix getV () {
- return new Matrix(V,n,n);
- }
-
- /** Return the real parts of the eigenvalues
- @return real(diag(D))
- */
-
- public double[] getRealEigenvalues () {
- return d;
- }
-
- /** Return the imaginary parts of the eigenvalues
- @return imag(diag(D))
- */
-
- public double[] getImagEigenvalues () {
- return e;
- }
-
- /** Return the block diagonal eigenvalue matrix
- @return D
- */
-
- public Matrix getD () {
- Matrix X = new Matrix(n,n);
- double[][] D = X.getArray();
- for (int i = 0; i < n; i++) {
- for (int j = 0; j < n; j++) {
- D[i][j] = 0.0;
- }
- D[i][i] = d[i];
- if (e[i] > 0) {
- D[i][i+1] = e[i];
- } else if (e[i] < 0) {
- D[i][i-1] = e[i];
- }
- }
- return X;
- }
-}
diff --git a/geogebra/kernel/jama/LUDecomposition.java b/geogebra/kernel/jama/LUDecomposition.java
deleted file mode 100644
index 1badc15..0000000
--- a/geogebra/kernel/jama/LUDecomposition.java
+++ /dev/null
@@ -1,311 +0,0 @@
-package geogebra.kernel.jama;
-
- /** LU Decomposition.
- <P>
- For an m-by-n matrix A with m >= n, the LU decomposition is an m-by-n
- unit lower triangular matrix L, an n-by-n upper triangular matrix U,
- and a permutation vector piv of length m so that A(piv,:) = L*U.
- If m < n, then L is m-by-m and U is m-by-n.
- <P>
- The LU decompostion with pivoting always exists, even if the matrix is
- singular, so the constructor will never fail. The primary use of the
- LU decomposition is in the solution of square systems of simultaneous
- linear equations. This will fail if isNonsingular() returns false.
- */
-
-public class LUDecomposition implements java.io.Serializable {
-
-/* ------------------------
- Class variables
- * ------------------------ */
-
- /** Array for internal storage of decomposition.
- @serial internal array storage.
- */
- private double[][] LU;
-
- /** Row and column dimensions, and pivot sign.
- @serial column dimension.
- @serial row dimension.
- @serial pivot sign.
- */
- private int m, n, pivsign;
-
- /** Internal storage of pivot vector.
- @serial pivot vector.
- */
- private int[] piv;
-
-/* ------------------------
- Constructor
- * ------------------------ */
-
- /** LU Decomposition
- @param A Rectangular matrix
- @return Structure to access L, U and piv.
- */
-
- public LUDecomposition (Matrix A) {
-
- // Use a "left-looking", dot-product, Crout/Doolittle algorithm.
-
- LU = A.getArrayCopy();
- m = A.getRowDimension();
- n = A.getColumnDimension();
- piv = new int[m];
- for (int i = 0; i < m; i++) {
- piv[i] = i;
- }
- pivsign = 1;
- double[] LUrowi;
- double[] LUcolj = new double[m];
-
- // Outer loop.
-
- for (int j = 0; j < n; j++) {
-
- // Make a copy of the j-th column to localize references.
-
- for (int i = 0; i < m; i++) {
- LUcolj[i] = LU[i][j];
- }
-
- // Apply previous transformations.
-
- for (int i = 0; i < m; i++) {
- LUrowi = LU[i];
-
- // Most of the time is spent in the following dot product.
-
- int kmax = Math.min(i,j);
- double s = 0.0;
- for (int k = 0; k < kmax; k++) {
- s += LUrowi[k]*LUcolj[k];
- }
-
- LUrowi[j] = LUcolj[i] -= s;
- }
-
- // Find pivot and exchange if necessary.
-
- int p = j;
- for (int i = j+1; i < m; i++) {
- if (Math.abs(LUcolj[i]) > Math.abs(LUcolj[p])) {
- p = i;
- }
- }
- if (p != j) {
- for (int k = 0; k < n; k++) {
- double t = LU[p][k]; LU[p][k] = LU[j][k]; LU[j][k] = t;
- }
- int k = piv[p]; piv[p] = piv[j]; piv[j] = k;
- pivsign = -pivsign;
- }
-
- // Compute multipliers.
-
- if (j < m & LU[j][j] != 0.0) {
- for (int i = j+1; i < m; i++) {
- LU[i][j] /= LU[j][j];
- }
- }
- }
- }
-
-/* ------------------------
- Temporary, experimental code.
- ------------------------ *\
-
- \** LU Decomposition, computed by Gaussian elimination.
- <P>
- This constructor computes L and U with the "daxpy"-based elimination
- algorithm used in LINPACK and MATLAB. In Java, we suspect the dot-product,
- Crout algorithm will be faster. We have temporarily included this
- constructor until timing experiments confirm this suspicion.
- <P>
- @param A Rectangular matrix
- @param linpackflag Use Gaussian elimination. Actual value ignored.
- @return Structure to access L, U and piv.
- *\
-
- public LUDecomposition (Matrix A, int linpackflag) {
- // Initialize.
- LU = A.getArrayCopy();
- m = A.getRowDimension();
- n = A.getColumnDimension();
- piv = new int[m];
- for (int i = 0; i < m; i++) {
- piv[i] = i;
- }
- pivsign = 1;
- // Main loop.
- for (int k = 0; k < n; k++) {
- // Find pivot.
- int p = k;
- for (int i = k+1; i < m; i++) {
- if (Math.abs(LU[i][k]) > Math.abs(LU[p][k])) {
- p = i;
- }
- }
- // Exchange if necessary.
- if (p != k) {
- for (int j = 0; j < n; j++) {
- double t = LU[p][j]; LU[p][j] = LU[k][j]; LU[k][j] = t;
- }
- int t = piv[p]; piv[p] = piv[k]; piv[k] = t;
- pivsign = -pivsign;
- }
- // Compute multipliers and eliminate k-th column.
- if (LU[k][k] != 0.0) {
- for (int i = k+1; i < m; i++) {
- LU[i][k] /= LU[k][k];
- for (int j = k+1; j < n; j++) {
- LU[i][j] -= LU[i][k]*LU[k][j];
- }
- }
- }
- }
- }
-
-\* ------------------------
- End of temporary code.
- * ------------------------ */
-
-/* ------------------------
- Public Methods
- * ------------------------ */
-
- /** Is the matrix nonsingular?
- @return true if U, and hence A, is nonsingular.
- */
-
- public boolean isNonsingular () {
- for (int j = 0; j < n; j++) {
- if (LU[j][j] == 0)
- return false;
- }
- return true;
- }
-
- /** Return lower triangular factor
- @return L
- */
-
- public Matrix getL () {
- Matrix X = new Matrix(m,n);
- double[][] L = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- if (i > j) {
- L[i][j] = LU[i][j];
- } else if (i == j) {
- L[i][j] = 1.0;
- } else {
- L[i][j] = 0.0;
- }
- }
- }
- return X;
- }
-
- /** Return upper triangular factor
- @return U
- */
-
- public Matrix getU () {
- Matrix X = new Matrix(n,n);
- double[][] U = X.getArray();
- for (int i = 0; i < n; i++) {
- for (int j = 0; j < n; j++) {
- if (i <= j) {
- U[i][j] = LU[i][j];
- } else {
- U[i][j] = 0.0;
- }
- }
- }
- return X;
- }
-
- /** Return pivot permutation vector
- @return piv
- */
-
- public int[] getPivot () {
- int[] p = new int[m];
- for (int i = 0; i < m; i++) {
- p[i] = piv[i];
- }
- return p;
- }
-
- /** Return pivot permutation vector as a one-dimensional double array
- @return (double) piv
- */
-
- public double[] getDoublePivot () {
- double[] vals = new double[m];
- for (int i = 0; i < m; i++) {
- vals[i] = (double) piv[i];
- }
- return vals;
- }
-
- /** Determinant
- @return det(A)
- @exception IllegalArgumentException Matrix must be square
- */
-
- public double det () {
- if (m != n) {
- throw new IllegalArgumentException("Matrix must be square.");
- }
- double d = (double) pivsign;
- for (int j = 0; j < n; j++) {
- d *= LU[j][j];
- }
- return d;
- }
-
- /** Solve A*X = B
- @param B A Matrix with as many rows as A and any number of columns.
- @return X so that L*U*X = B(piv,:)
- @exception IllegalArgumentException Matrix row dimensions must agree.
- @exception RuntimeException Matrix is singular.
- */
-
- public Matrix solve (Matrix B) {
- if (B.getRowDimension() != m) {
- throw new IllegalArgumentException("Matrix row dimensions must agree.");
- }
- if (!this.isNonsingular()) {
- throw new RuntimeException("Matrix is singular.");
- }
-
- // Copy right hand side with pivoting
- int nx = B.getColumnDimension();
- Matrix Xmat = B.getMatrix(piv,0,nx-1);
- double[][] X = Xmat.getArray();
-
- // Solve L*Y = B(piv,:)
- for (int k = 0; k < n; k++) {
- for (int i = k+1; i < n; i++) {
- for (int j = 0; j < nx; j++) {
- X[i][j] -= X[k][j]*LU[i][k];
- }
- }
- }
- // Solve U*X = Y;
- for (int k = n-1; k >= 0; k--) {
- for (int j = 0; j < nx; j++) {
- X[k][j] /= LU[k][k];
- }
- for (int i = 0; i < k; i++) {
- for (int j = 0; j < nx; j++) {
- X[i][j] -= X[k][j]*LU[i][k];
- }
- }
- }
- return Xmat;
- }
-}
diff --git a/geogebra/kernel/jama/Matrix.java b/geogebra/kernel/jama/Matrix.java
deleted file mode 100644
index a795173..0000000
--- a/geogebra/kernel/jama/Matrix.java
+++ /dev/null
@@ -1,1049 +0,0 @@
-package geogebra.kernel.jama;
-
-import geogebra.kernel.jama.util.*;
-
-import java.text.NumberFormat;
-import java.text.DecimalFormat;
-import java.text.DecimalFormatSymbols;
-import java.util.Locale;
-import java.text.FieldPosition;
-import java.io.PrintWriter;
-import java.io.BufferedReader;
-import java.io.StreamTokenizer;
-
-/**
- Jama = Java Matrix class.
-<P>
- The Java Matrix Class provides the fundamental operations of numerical
- linear algebra. Various constructors create Matrices from two dimensional
- arrays of double precision floating point numbers. Various "gets" and
- "sets" provide access to submatrices and matrix elements. Several methods
- implement basic matrix arithmetic, including matrix addition and
- multiplication, matrix norms, and element-by-element array operations.
- Methods for reading and printing matrices are also included. All the
- operations in this version of the Matrix Class involve real matrices.
- Complex matrices may be handled in a future version.
-<P>
- Five fundamental matrix decompositions, which consist of pairs or triples
- of matrices, permutation vectors, and the like, produce results in five
- decomposition classes. These decompositions are accessed by the Matrix
- class to compute solutions of simultaneous linear equations, determinants,
- inverses and other matrix functions. The five decompositions are:
-<P><UL>
- <LI>Cholesky Decomposition of symmetric, positive definite matrices.
- <LI>LU Decomposition of rectangular matrices.
- <LI>QR Decomposition of rectangular matrices.
- <LI>Singular Value Decomposition of rectangular matrices.
- <LI>Eigenvalue Decomposition of both symmetric and nonsymmetric square matrices.
-</UL>
-<DL>
-<DT><B>Example of use:</B></DT>
-<P>
-<DD>Solve a linear system A x = b and compute the residual norm, ||b - A x||.
-<P><PRE>
- double[][] vals = {{1.,2.,3},{4.,5.,6.},{7.,8.,10.}};
- Matrix A = new Matrix(vals);
- Matrix b = Matrix.random(3,1);
- Matrix x = A.solve(b);
- Matrix r = A.times(x).minus(b);
- double rnorm = r.normInf();
-</PRE></DD>
-</DL>
-
- at author The MathWorks, Inc. and the National Institute of Standards and Technology.
- at version 5 August 1998
-*/
-
-public class Matrix implements Cloneable, java.io.Serializable {
-
-/* ------------------------
- Class variables
- * ------------------------ */
-
- /** Array for internal storage of elements.
- @serial internal array storage.
- */
- protected double[][] A;
-
- /** Row and column dimensions.
- @serial row dimension.
- @serial column dimension.
- */
- protected int m, n;
-
-/* ------------------------
- Constructors
- * ------------------------ */
-
- public Matrix () {
- }
-
- /** Construct an m-by-n matrix of zeros.
- @param m Number of rows.
- @param n Number of colums.
- */
-
- public Matrix (int m, int n) {
- this.m = m;
- this.n = n;
- A = new double[m][n];
- }
-
- /** Construct an m-by-n constant matrix.
- @param m Number of rows.
- @param n Number of colums.
- @param s Fill the matrix with this scalar value.
- */
-
- public Matrix (int m, int n, double s) {
- this.m = m;
- this.n = n;
- A = new double[m][n];
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = s;
- }
- }
- }
-
- /** Construct a matrix from a 2-D array.
- @param A Two-dimensional array of doubles.
- @exception IllegalArgumentException All rows must have the same length
- @see #constructWithCopy
- */
-
- public Matrix (double[][] A) {
- m = A.length;
- n = A[0].length;
- for (int i = 0; i < m; i++) {
- if (A[i].length != n) {
- throw new IllegalArgumentException("All rows must have the same length.");
- }
- }
- this.A = A;
- }
-
- /** Construct a matrix quickly without checking arguments.
- @param A Two-dimensional array of doubles.
- @param m Number of rows.
- @param n Number of colums.
- */
-
- public Matrix (double[][] A, int m, int n) {
- this.A = A;
- this.m = m;
- this.n = n;
- }
-
- /** Construct a matrix from a one-dimensional packed array
- @param vals One-dimensional array of doubles, packed by columns (ala Fortran).
- @param m Number of rows.
- @exception IllegalArgumentException Array length must be a multiple of m.
- */
-
- public Matrix (double vals[], int m) {
- this.m = m;
- n = (m != 0 ? vals.length/m : 0);
- if (m*n != vals.length) {
- throw new IllegalArgumentException("Array length must be a multiple of m.");
- }
- A = new double[m][n];
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = vals[i+j*m];
- }
- }
- }
-
-/* ------------------------
- Public Methods
- * ------------------------ */
-
- /** Construct a matrix from a copy of a 2-D array.
- @param A Two-dimensional array of doubles.
- @exception IllegalArgumentException All rows must have the same length
- */
-
- public static Matrix constructWithCopy(double[][] A) {
- int m = A.length;
- int n = A[0].length;
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- if (A[i].length != n) {
- throw new IllegalArgumentException
- ("All rows must have the same length.");
- }
- for (int j = 0; j < n; j++) {
- C[i][j] = A[i][j];
- }
- }
- return X;
- }
-
- /** Make a deep copy of a matrix
- */
-
- public Matrix copy () {
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = A[i][j];
- }
- }
- return X;
- }
-
- /** Clone the Matrix object.
- */
-
- public Object clone () {
- return this.copy();
- }
-
- /** Access the internal two-dimensional array.
- @return Pointer to the two-dimensional array of matrix elements.
- */
-
- public double[][] getArray () {
- return A;
- }
-
- /** Copy the internal two-dimensional array.
- @return Two-dimensional array copy of matrix elements.
- */
-
- public double[][] getArrayCopy () {
- double[][] C = new double[m][n];
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = A[i][j];
- }
- }
- return C;
- }
-
- /** Make a one-dimensional column packed copy of the internal array.
- @return Matrix elements packed in a one-dimensional array by columns.
- */
-
- public double[] getColumnPackedCopy () {
- double[] vals = new double[m*n];
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- vals[i+j*m] = A[i][j];
- }
- }
- return vals;
- }
-
- /** Make a one-dimensional row packed copy of the internal array.
- @return Matrix elements packed in a one-dimensional array by rows.
- */
-
- public double[] getRowPackedCopy () {
- double[] vals = new double[m*n];
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- vals[i*n+j] = A[i][j];
- }
- }
- return vals;
- }
-
- /** Get row dimension.
- @return m, the number of rows.
- */
-
- public int getRowDimension () {
- return m;
- }
-
- /** Get column dimension.
- @return n, the number of columns.
- */
-
- public int getColumnDimension () {
- return n;
- }
-
- /** Get a single element.
- @param i Row index.
- @param j Column index.
- @return A(i,j)
- @exception ArrayIndexOutOfBoundsException
- */
-
- public double get (int i, int j) {
- return A[i][j];
- }
-
- /** Get a submatrix.
- @param i0 Initial row index
- @param i1 Final row index
- @param j0 Initial column index
- @param j1 Final column index
- @return A(i0:i1,j0:j1)
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public Matrix getMatrix (int i0, int i1, int j0, int j1) {
- Matrix X = new Matrix(i1-i0+1,j1-j0+1);
- double[][] B = X.getArray();
- try {
- for (int i = i0; i <= i1; i++) {
- for (int j = j0; j <= j1; j++) {
- B[i-i0][j-j0] = A[i][j];
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- return X;
- }
-
- /** Get a submatrix.
- @param r Array of row indices.
- @param c Array of column indices.
- @return A(r(:),c(:))
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public Matrix getMatrix (int[] r, int[] c) {
- Matrix X = new Matrix(r.length,c.length);
- double[][] B = X.getArray();
- try {
- for (int i = 0; i < r.length; i++) {
- for (int j = 0; j < c.length; j++) {
- B[i][j] = A[r[i]][c[j]];
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- return X;
- }
-
- /** Get a submatrix.
- @param i0 Initial row index
- @param i1 Final row index
- @param c Array of column indices.
- @return A(i0:i1,c(:))
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public Matrix getMatrix (int i0, int i1, int[] c) {
- Matrix X = new Matrix(i1-i0+1,c.length);
- double[][] B = X.getArray();
- try {
- for (int i = i0; i <= i1; i++) {
- for (int j = 0; j < c.length; j++) {
- B[i-i0][j] = A[i][c[j]];
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- return X;
- }
-
- /** Get a submatrix.
- @param r Array of row indices.
- @param i0 Initial column index
- @param i1 Final column index
- @return A(r(:),j0:j1)
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public Matrix getMatrix (int[] r, int j0, int j1) {
- Matrix X = new Matrix(r.length,j1-j0+1);
- double[][] B = X.getArray();
- try {
- for (int i = 0; i < r.length; i++) {
- for (int j = j0; j <= j1; j++) {
- B[i][j-j0] = A[r[i]][j];
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- return X;
- }
-
- /** Set a single element.
- @param i Row index.
- @param j Column index.
- @param s A(i,j).
- @exception ArrayIndexOutOfBoundsException
- */
-
- public void set (int i, int j, double s) {
- A[i][j] = s;
- }
-
- /** Set a submatrix.
- @param i0 Initial row index
- @param i1 Final row index
- @param j0 Initial column index
- @param j1 Final column index
- @param X A(i0:i1,j0:j1)
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public void setMatrix (int i0, int i1, int j0, int j1, Matrix X) {
- try {
- for (int i = i0; i <= i1; i++) {
- for (int j = j0; j <= j1; j++) {
- A[i][j] = X.get(i-i0,j-j0);
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- }
-
- /** Set a submatrix.
- @param r Array of row indices.
- @param c Array of column indices.
- @param X A(r(:),c(:))
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public void setMatrix (int[] r, int[] c, Matrix X) {
- try {
- for (int i = 0; i < r.length; i++) {
- for (int j = 0; j < c.length; j++) {
- A[r[i]][c[j]] = X.get(i,j);
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- }
-
- /** Set a submatrix.
- @param r Array of row indices.
- @param j0 Initial column index
- @param j1 Final column index
- @param X A(r(:),j0:j1)
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public void setMatrix (int[] r, int j0, int j1, Matrix X) {
- try {
- for (int i = 0; i < r.length; i++) {
- for (int j = j0; j <= j1; j++) {
- A[r[i]][j] = X.get(i,j-j0);
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- }
-
- /** Set a submatrix.
- @param i0 Initial row index
- @param i1 Final row index
- @param c Array of column indices.
- @param X A(i0:i1,c(:))
- @exception ArrayIndexOutOfBoundsException Submatrix indices
- */
-
- public void setMatrix (int i0, int i1, int[] c, Matrix X) {
- try {
- for (int i = i0; i <= i1; i++) {
- for (int j = 0; j < c.length; j++) {
- A[i][c[j]] = X.get(i-i0,j);
- }
- }
- } catch(ArrayIndexOutOfBoundsException e) {
- throw new ArrayIndexOutOfBoundsException("Submatrix indices");
- }
- }
-
- /** Matrix transpose.
- @return A'
- */
-
- public Matrix transpose () {
- Matrix X = new Matrix(n,m);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[j][i] = A[i][j];
- }
- }
- return X;
- }
-
- /** One norm
- @return maximum column sum.
- */
-
- public double norm1 () {
- double f = 0;
- for (int j = 0; j < n; j++) {
- double s = 0;
- for (int i = 0; i < m; i++) {
- s += Math.abs(A[i][j]);
- }
- f = Math.max(f,s);
- }
- return f;
- }
-
- /** Two norm
- @return maximum singular value.
- */
-
- public double norm2 () {
- return (new SingularValueDecomposition(this).norm2());
- }
-
- /** Infinity norm
- @return maximum row sum.
- */
-
- public double normInf () {
- double f = 0;
- for (int i = 0; i < m; i++) {
- double s = 0;
- for (int j = 0; j < n; j++) {
- s += Math.abs(A[i][j]);
- }
- f = Math.max(f,s);
- }
- return f;
- }
-
- /** Frobenius norm
- @return sqrt of sum of squares of all elements.
- */
-
- public double normF () {
- double f = 0;
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- f = Maths.hypot(f,A[i][j]);
- }
- }
- return f;
- }
-
- /** Unary minus
- @return -A
- */
-
- public Matrix uminus () {
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = -A[i][j];
- }
- }
- return X;
- }
-
- /** C = A + B
- @param B another matrix
- @return A + B
- */
-
- public Matrix plus (Matrix B) {
- checkMatrixDimensions(B);
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = A[i][j] + B.A[i][j];
- }
- }
- return X;
- }
-
- /** A = A + B
- @param B another matrix
- @return A + B
- */
-
- public Matrix plusEquals (Matrix B) {
- checkMatrixDimensions(B);
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = A[i][j] + B.A[i][j];
- }
- }
- return this;
- }
-
- /** C = A - B
- @param B another matrix
- @return A - B
- */
-
- public Matrix minus (Matrix B) {
- checkMatrixDimensions(B);
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = A[i][j] - B.A[i][j];
- }
- }
- return X;
- }
-
- /** A = A - B
- @param B another matrix
- @return A - B
- */
-
- public Matrix minusEquals (Matrix B) {
- checkMatrixDimensions(B);
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = A[i][j] - B.A[i][j];
- }
- }
- return this;
- }
-
- /** Element-by-element multiplication, C = A.*B
- @param B another matrix
- @return A.*B
- */
-
- public Matrix arrayTimes (Matrix B) {
- checkMatrixDimensions(B);
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = A[i][j] * B.A[i][j];
- }
- }
- return X;
- }
-
- /** Element-by-element multiplication in place, A = A.*B
- @param B another matrix
- @return A.*B
- */
-
- public Matrix arrayTimesEquals (Matrix B) {
- checkMatrixDimensions(B);
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = A[i][j] * B.A[i][j];
- }
- }
- return this;
- }
-
- /** Element-by-element right division, C = A./B
- @param B another matrix
- @return A./B
- */
-
- public Matrix arrayRightDivide (Matrix B) {
- checkMatrixDimensions(B);
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = A[i][j] / B.A[i][j];
- }
- }
- return X;
- }
-
- /** Element-by-element right division in place, A = A./B
- @param B another matrix
- @return A./B
- */
-
- public Matrix arrayRightDivideEquals (Matrix B) {
- checkMatrixDimensions(B);
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = A[i][j] / B.A[i][j];
- }
- }
- return this;
- }
-
- /** Element-by-element left division, C = A.\B
- @param B another matrix
- @return A.\B
- */
-
- public Matrix arrayLeftDivide (Matrix B) {
- checkMatrixDimensions(B);
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = B.A[i][j] / A[i][j];
- }
- }
- return X;
- }
-
- /** Element-by-element left division in place, A = A.\B
- @param B another matrix
- @return A.\B
- */
-
- public Matrix arrayLeftDivideEquals (Matrix B) {
- checkMatrixDimensions(B);
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = B.A[i][j] / A[i][j];
- }
- }
- return this;
- }
-
- /** Multiply a matrix by a scalar, C = s*A
- @param s scalar
- @return s*A
- */
-
- public Matrix times (double s) {
- Matrix X = new Matrix(m,n);
- double[][] C = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- C[i][j] = s*A[i][j];
- }
- }
- return X;
- }
-
- /** Multiply a matrix by a scalar in place, A = s*A
- @param s scalar
- @return replace A by s*A
- */
-
- public Matrix timesEquals (double s) {
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- A[i][j] = s*A[i][j];
- }
- }
- return this;
- }
-
- /** Linear algebraic matrix multiplication, A * B
- @param B another matrix
- @return Matrix product, A * B
- @exception IllegalArgumentException Matrix inner dimensions must agree.
- */
-
- public Matrix times (Matrix B) {
- if (B.m != n) {
- throw new IllegalArgumentException("Matrix inner dimensions must agree.");
- }
- Matrix X = new Matrix(m,B.n);
- double[][] C = X.getArray();
- double[] Bcolj = new double[n];
- for (int j = 0; j < B.n; j++) {
- for (int k = 0; k < n; k++) {
- Bcolj[k] = B.A[k][j];
- }
- for (int i = 0; i < m; i++) {
- double[] Arowi = A[i];
- double s = 0;
- for (int k = 0; k < n; k++) {
- s += Arowi[k]*Bcolj[k];
- }
- C[i][j] = s;
- }
- }
- return X;
- }
-
- /** LU Decomposition
- @return LUDecomposition
- @see LUDecomposition
- */
-
- public LUDecomposition lu () {
- return new LUDecomposition(this);
- }
-
- /** QR Decomposition
- @return QRDecomposition
- @see QRDecomposition
- */
-
- public QRDecomposition qr () {
- return new QRDecomposition(this);
- }
-
- /** Cholesky Decomposition
- @return CholeskyDecomposition
- @see CholeskyDecomposition
- */
-
- public CholeskyDecomposition chol () {
- return new CholeskyDecomposition(this);
- }
-
- /** Singular Value Decomposition
- @return SingularValueDecomposition
- @see SingularValueDecomposition
- */
-
- public SingularValueDecomposition svd () {
- return new SingularValueDecomposition(this);
- }
-
- /** Eigenvalue Decomposition
- @return EigenvalueDecomposition
- @see EigenvalueDecomposition
- */
-
- public EigenvalueDecomposition eig () {
- return new EigenvalueDecomposition(this);
- }
-
- /** Solve A*X = B
- @param B right hand side
- @return solution if A is square, least squares solution otherwise
- */
-
- public Matrix solve (Matrix B) {
- return (m == n ? (new LUDecomposition(this)).solve(B) :
- (new QRDecomposition(this)).solve(B));
- }
-
- /** Solve X*A = B, which is also A'*X' = B'
- @param B right hand side
- @return solution if A is square, least squares solution otherwise.
- */
-
- public Matrix solveTranspose (Matrix B) {
- return transpose().solve(B.transpose());
- }
-
- /** Matrix inverse or pseudoinverse
- @return inverse(A) if A is square, pseudoinverse otherwise.
- */
-
- public Matrix inverse () {
- return solve(identity(m,m));
- }
-
- /** Matrix determinant
- @return determinant
- */
-
- public double det () {
- return new LUDecomposition(this).det();
- }
-
- /** Matrix rank
- @return effective numerical rank, obtained from SVD.
- */
-
- public int rank () {
- return new SingularValueDecomposition(this).rank();
- }
-
- /** Matrix condition (2 norm)
- @return ratio of largest to smallest singular value.
- */
-
- public double cond () {
- return new SingularValueDecomposition(this).cond();
- }
-
- /** Matrix trace.
- @return sum of the diagonal elements.
- */
-
- public double trace () {
- double t = 0;
- for (int i = 0; i < Math.min(m,n); i++) {
- t += A[i][i];
- }
- return t;
- }
-
- /** Generate matrix with random elements
- @param m Number of rows.
- @param n Number of colums.
- @return An m-by-n matrix with uniformly distributed random elements.
- */
-
- public static Matrix random (int m, int n) {
- Matrix A = new Matrix(m,n);
- double[][] X = A.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- X[i][j] = Math.random();
- }
- }
- return A;
- }
-
- /** Generate identity matrix
- @param m Number of rows.
- @param n Number of colums.
- @return An m-by-n matrix with ones on the diagonal and zeros elsewhere.
- */
-
- public static Matrix identity (int m, int n) {
- Matrix A = new Matrix(m,n);
- double[][] X = A.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- X[i][j] = (i == j ? 1.0 : 0.0);
- }
- }
- return A;
- }
-
-
- /** Print the matrix to stdout. Line the elements up in columns
- * with a Fortran-like 'Fw.d' style format.
- @param w Column width.
- @param d Number of digits after the decimal.
- */
-
- public void print (int w, int d) {
- print(new PrintWriter(System.out,true),w,d); }
-
- /** Print the matrix to the output stream. Line the elements up in
- * columns with a Fortran-like 'Fw.d' style format.
- @param output Output stream.
- @param w Column width.
- @param d Number of digits after the decimal.
- */
-
- public void print (PrintWriter output, int w, int d) {
- DecimalFormat format = new DecimalFormat();
- format.setDecimalFormatSymbols(new DecimalFormatSymbols(Locale.US));
- format.setMinimumIntegerDigits(1);
- format.setMaximumFractionDigits(d);
- format.setMinimumFractionDigits(d);
- format.setGroupingUsed(false);
- print(output,format,w+2);
- }
-
- /** Print the matrix to stdout. Line the elements up in columns.
- * Use the format object, and right justify within columns of width
- * characters.
- * Note that is the matrix is to be read back in, you probably will want
- * to use a NumberFormat that is set to US Locale.
- @param format A Formatting object for individual elements.
- @param width Field width for each column.
- @see java.text.DecimalFormat#setDecimalFormatSymbols
- */
-
- public void print (NumberFormat format, int width) {
- print(new PrintWriter(System.out,true),format,width); }
-
- // DecimalFormat is a little disappointing coming from Fortran or C's printf.
- // Since it doesn't pad on the left, the elements will come out different
- // widths. Consequently, we'll pass the desired column width in as an
- // argument and do the extra padding ourselves.
-
- /** Print the matrix to the output stream. Line the elements up in columns.
- * Use the format object, and right justify within columns of width
- * characters.
- * Note that is the matrix is to be read back in, you probably will want
- * to use a NumberFormat that is set to US Locale.
- @param output the output stream.
- @param format A formatting object to format the matrix elements
- @param width Column width.
- @see java.text.DecimalFormat#setDecimalFormatSymbols
- */
-
- public void print (PrintWriter output, NumberFormat format, int width) {
- output.println(); // start on new line.
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- String s = format.format(A[i][j]); // format the number
- int padding = Math.max(1,width-s.length()); // At _least_ 1 space
- for (int k = 0; k < padding; k++)
- output.print(' ');
- output.print(s);
- }
- output.println();
- }
- output.println(); // end with blank line.
- }
-
- /** Read a matrix from a stream. The format is the same the print method,
- * so printed matrices can be read back in (provided they were printed using
- * US Locale). Elements are separated by
- * whitespace, all the elements for each row appear on a single line,
- * the last row is followed by a blank line.
- @param input the input stream.
- */
-
- public static Matrix read (BufferedReader input) throws java.io.IOException {
- StreamTokenizer tokenizer= new StreamTokenizer(input);
-
- // Although StreamTokenizer will parse numbers, it doesn't recognize
- // scientific notation (E or D); however, Double.valueOf does.
- // The strategy here is to disable StreamTokenizer's number parsing.
- // We'll only get whitespace delimited words, EOL's and EOF's.
- // These words should all be numbers, for Double.valueOf to parse.
-
- tokenizer.resetSyntax();
- tokenizer.wordChars(0,255);
- tokenizer.whitespaceChars(0, ' ');
- tokenizer.eolIsSignificant(true);
- java.util.Vector v = new java.util.Vector();
-
- // Ignore initial empty lines
- while (tokenizer.nextToken() == StreamTokenizer.TT_EOL);
- if (tokenizer.ttype == StreamTokenizer.TT_EOF)
- throw new java.io.IOException("Unexpected EOF on matrix read.");
- do {
- v.addElement(Double.valueOf(tokenizer.sval)); // Read & store 1st row.
- } while (tokenizer.nextToken() == StreamTokenizer.TT_WORD);
-
- int n = v.size(); // Now we've got the number of columns!
- double row[] = new double[n];
- for (int j=0; j<n; j++) // extract the elements of the 1st row.
- row[j]=((Double)v.elementAt(j)).doubleValue();
- v.removeAllElements();
- v.addElement(row); // Start storing rows instead of columns.
- while (tokenizer.nextToken() == StreamTokenizer.TT_WORD) {
- // While non-empty lines
- v.addElement(row = new double[n]);
- int j = 0;
- do {
- if (j >= n) throw new java.io.IOException
- ("Row " + v.size() + " is too long.");
- row[j++] = Double.valueOf(tokenizer.sval).doubleValue();
- } while (tokenizer.nextToken() == StreamTokenizer.TT_WORD);
- if (j < n) throw new java.io.IOException
- ("Row " + v.size() + " is too short.");
- }
- int m = v.size(); // Now we've got the number of rows.
- double[][] A = new double[m][];
- v.copyInto(A); // copy the rows out of the vector
- return new Matrix(A);
- }
-
-
-/* ------------------------
- Private Methods
- * ------------------------ */
-
- /** Check if size(A) == size(B) **/
-
- private void checkMatrixDimensions (Matrix B) {
- if (B.m != m || B.n != n) {
- throw new IllegalArgumentException("Matrix dimensions must agree.");
- }
- }
-
-}
diff --git a/geogebra/kernel/jama/QRDecomposition.java b/geogebra/kernel/jama/QRDecomposition.java
deleted file mode 100644
index 0f71bbc..0000000
--- a/geogebra/kernel/jama/QRDecomposition.java
+++ /dev/null
@@ -1,218 +0,0 @@
-package geogebra.kernel.jama;
-import geogebra.kernel.jama.util.*;
-
-/** QR Decomposition.
-<P>
- For an m-by-n matrix A with m >= n, the QR decomposition is an m-by-n
- orthogonal matrix Q and an n-by-n upper triangular matrix R so that
- A = Q*R.
-<P>
- The QR decompostion always exists, even if the matrix does not have
- full rank, so the constructor will never fail. The primary use of the
- QR decomposition is in the least squares solution of nonsquare systems
- of simultaneous linear equations. This will fail if isFullRank()
- returns false.
-*/
-
-public class QRDecomposition implements java.io.Serializable {
-
-/* ------------------------
- Class variables
- * ------------------------ */
-
- /** Array for internal storage of decomposition.
- @serial internal array storage.
- */
- private double[][] QR;
-
- /** Row and column dimensions.
- @serial column dimension.
- @serial row dimension.
- */
- private int m, n;
-
- /** Array for internal storage of diagonal of R.
- @serial diagonal of R.
- */
- private double[] Rdiag;
-
-/* ------------------------
- Constructor
- * ------------------------ */
-
- /** QR Decomposition, computed by Householder reflections.
- @param A Rectangular matrix
- @return Structure to access R and the Householder vectors and compute Q.
- */
-
- public QRDecomposition (Matrix A) {
- // Initialize.
- QR = A.getArrayCopy();
- m = A.getRowDimension();
- n = A.getColumnDimension();
- Rdiag = new double[n];
-
- // Main loop.
- for (int k = 0; k < n; k++) {
- // Compute 2-norm of k-th column without under/overflow.
- double nrm = 0;
- for (int i = k; i < m; i++) {
- nrm = Maths.hypot(nrm,QR[i][k]);
- }
-
- if (nrm != 0.0) {
- // Form k-th Householder vector.
- if (QR[k][k] < 0) {
- nrm = -nrm;
- }
- for (int i = k; i < m; i++) {
- QR[i][k] /= nrm;
- }
- QR[k][k] += 1.0;
-
- // Apply transformation to remaining columns.
- for (int j = k+1; j < n; j++) {
- double s = 0.0;
- for (int i = k; i < m; i++) {
- s += QR[i][k]*QR[i][j];
- }
- s = -s/QR[k][k];
- for (int i = k; i < m; i++) {
- QR[i][j] += s*QR[i][k];
- }
- }
- }
- Rdiag[k] = -nrm;
- }
- }
-
-/* ------------------------
- Public Methods
- * ------------------------ */
-
- /** Is the matrix full rank?
- @return true if R, and hence A, has full rank.
- */
-
- public boolean isFullRank () {
- for (int j = 0; j < n; j++) {
- if (Rdiag[j] == 0)
- return false;
- }
- return true;
- }
-
- /** Return the Householder vectors
- @return Lower trapezoidal matrix whose columns define the reflections
- */
-
- public Matrix getH () {
- Matrix X = new Matrix(m,n);
- double[][] H = X.getArray();
- for (int i = 0; i < m; i++) {
- for (int j = 0; j < n; j++) {
- if (i >= j) {
- H[i][j] = QR[i][j];
- } else {
- H[i][j] = 0.0;
- }
- }
- }
- return X;
- }
-
- /** Return the upper triangular factor
- @return R
- */
-
- public Matrix getR () {
- Matrix X = new Matrix(n,n);
- double[][] R = X.getArray();
- for (int i = 0; i < n; i++) {
- for (int j = 0; j < n; j++) {
- if (i < j) {
- R[i][j] = QR[i][j];
- } else if (i == j) {
- R[i][j] = Rdiag[i];
- } else {
- R[i][j] = 0.0;
- }
- }
- }
- return X;
- }
-
- /** Generate and return the (economy-sized) orthogonal factor
- @return Q
- */
-
- public Matrix getQ () {
- Matrix X = new Matrix(m,n);
- double[][] Q = X.getArray();
- for (int k = n-1; k >= 0; k--) {
- for (int i = 0; i < m; i++) {
- Q[i][k] = 0.0;
- }
- Q[k][k] = 1.0;
- for (int j = k; j < n; j++) {
- if (QR[k][k] != 0) {
- double s = 0.0;
- for (int i = k; i < m; i++) {
- s += QR[i][k]*Q[i][j];
- }
- s = -s/QR[k][k];
- for (int i = k; i < m; i++) {
- Q[i][j] += s*QR[i][k];
- }
- }
- }
- }
- return X;
- }
-
- /** Least squares solution of A*X = B
- @param B A Matrix with as many rows as A and any number of columns.
- @return X that minimizes the two norm of Q*R*X-B.
- @exception IllegalArgumentException Matrix row dimensions must agree.
- @exception RuntimeException Matrix is rank deficient.
- */
-
- public Matrix solve (Matrix B) {
- if (B.getRowDimension() != m) {
- throw new IllegalArgumentException("Matrix row dimensions must agree.");
- }
- if (!this.isFullRank()) {
- throw new RuntimeException("Matrix is rank deficient.");
- }
-
- // Copy right hand side
- int nx = B.getColumnDimension();
- double[][] X = B.getArrayCopy();
-
- // Compute Y = transpose(Q)*B
- for (int k = 0; k < n; k++) {
- for (int j = 0; j < nx; j++) {
- double s = 0.0;
- for (int i = k; i < m; i++) {
- s += QR[i][k]*X[i][j];
- }
- s = -s/QR[k][k];
- for (int i = k; i < m; i++) {
- X[i][j] += s*QR[i][k];
- }
- }
- }
- // Solve R*X = Y;
- for (int k = n-1; k >= 0; k--) {
- for (int j = 0; j < nx; j++) {
- X[k][j] /= Rdiag[k];
- }
- for (int i = 0; i < k; i++) {
- for (int j = 0; j < nx; j++) {
- X[i][j] -= X[k][j]*QR[i][k];
- }
- }
- }
- return (new Matrix(X,n,nx).getMatrix(0,n-1,0,nx-1));
- }
-}
diff --git a/geogebra/kernel/jama/SingularValueDecomposition.java b/geogebra/kernel/jama/SingularValueDecomposition.java
deleted file mode 100644
index ea7054b..0000000
--- a/geogebra/kernel/jama/SingularValueDecomposition.java
+++ /dev/null
@@ -1,547 +0,0 @@
-package geogebra.kernel.jama;
-import geogebra.kernel.jama.util.*;
-
- /** Singular Value Decomposition.
- <P>
- For an m-by-n matrix A with m >= n, the singular value decomposition is
- an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and
- an n-by-n orthogonal matrix V so that A = U*S*V'.
- <P>
- The singular values, sigma[k] = S[k][k], are ordered so that
- sigma[0] >= sigma[1] >= ... >= sigma[n-1].
- <P>
- The singular value decompostion always exists, so the constructor will
- never fail. The matrix condition number and the effective numerical
- rank can be computed from this decomposition.
- */
-
-public class SingularValueDecomposition implements java.io.Serializable {
-
-/* ------------------------
- Class variables
- * ------------------------ */
-
- /** Arrays for internal storage of U and V.
- @serial internal storage of U.
- @serial internal storage of V.
- */
- private double[][] U, V;
-
- /** Array for internal storage of singular values.
- @serial internal storage of singular values.
- */
- private double[] s;
-
- /** Row and column dimensions.
- @serial row dimension.
- @serial column dimension.
- */
- private int m, n;
-
-/* ------------------------
- Constructor
- * ------------------------ */
-
- /** Construct the singular value decomposition
- @param A Rectangular matrix
- @return Structure to access U, S and V.
- */
-
- public SingularValueDecomposition (Matrix Arg) {
-
- // Derived from LINPACK code.
- // Initialize.
- double[][] A = Arg.getArrayCopy();
- m = Arg.getRowDimension();
- n = Arg.getColumnDimension();
-
- /* Apparently the failing cases are only a proper subset of (m<n),
- so let's not throw error. Correct fix to come later?
- if (m<n) {
- throw new IllegalArgumentException("Jama SVD only works for m >= n"); }
- */
- int nu = Math.min(m,n);
- s = new double [Math.min(m+1,n)];
- U = new double [m][nu];
- V = new double [n][n];
- double[] e = new double [n];
- double[] work = new double [m];
- boolean wantu = true;
- boolean wantv = true;
-
- // Reduce A to bidiagonal form, storing the diagonal elements
- // in s and the super-diagonal elements in e.
-
- int nct = Math.min(m-1,n);
- int nrt = Math.max(0,Math.min(n-2,m));
- for (int k = 0; k < Math.max(nct,nrt); k++) {
- if (k < nct) {
-
- // Compute the transformation for the k-th column and
- // place the k-th diagonal in s[k].
- // Compute 2-norm of k-th column without under/overflow.
- s[k] = 0;
- for (int i = k; i < m; i++) {
- s[k] = Maths.hypot(s[k],A[i][k]);
- }
- if (s[k] != 0.0) {
- if (A[k][k] < 0.0) {
- s[k] = -s[k];
- }
- for (int i = k; i < m; i++) {
- A[i][k] /= s[k];
- }
- A[k][k] += 1.0;
- }
- s[k] = -s[k];
- }
- for (int j = k+1; j < n; j++) {
- if ((k < nct) & (s[k] != 0.0)) {
-
- // Apply the transformation.
-
- double t = 0;
- for (int i = k; i < m; i++) {
- t += A[i][k]*A[i][j];
- }
- t = -t/A[k][k];
- for (int i = k; i < m; i++) {
- A[i][j] += t*A[i][k];
- }
- }
-
- // Place the k-th row of A into e for the
- // subsequent calculation of the row transformation.
-
- e[j] = A[k][j];
- }
- if (wantu & (k < nct)) {
-
- // Place the transformation in U for subsequent back
- // multiplication.
-
- for (int i = k; i < m; i++) {
- U[i][k] = A[i][k];
- }
- }
- if (k < nrt) {
-
- // Compute the k-th row transformation and place the
- // k-th super-diagonal in e[k].
- // Compute 2-norm without under/overflow.
- e[k] = 0;
- for (int i = k+1; i < n; i++) {
- e[k] = Maths.hypot(e[k],e[i]);
- }
- if (e[k] != 0.0) {
- if (e[k+1] < 0.0) {
- e[k] = -e[k];
- }
- for (int i = k+1; i < n; i++) {
- e[i] /= e[k];
- }
- e[k+1] += 1.0;
- }
- e[k] = -e[k];
- if ((k+1 < m) & (e[k] != 0.0)) {
-
- // Apply the transformation.
-
- for (int i = k+1; i < m; i++) {
- work[i] = 0.0;
- }
- for (int j = k+1; j < n; j++) {
- for (int i = k+1; i < m; i++) {
- work[i] += e[j]*A[i][j];
- }
- }
- for (int j = k+1; j < n; j++) {
- double t = -e[j]/e[k+1];
- for (int i = k+1; i < m; i++) {
- A[i][j] += t*work[i];
- }
- }
- }
- if (wantv) {
-
- // Place the transformation in V for subsequent
- // back multiplication.
-
- for (int i = k+1; i < n; i++) {
- V[i][k] = e[i];
- }
- }
- }
- }
-
- // Set up the final bidiagonal matrix or order p.
-
- int p = Math.min(n,m+1);
- if (nct < n) {
- s[nct] = A[nct][nct];
- }
- if (m < p) {
- s[p-1] = 0.0;
- }
- if (nrt+1 < p) {
- e[nrt] = A[nrt][p-1];
- }
- e[p-1] = 0.0;
-
- // If required, generate U.
-
- if (wantu) {
- for (int j = nct; j < nu; j++) {
- for (int i = 0; i < m; i++) {
- U[i][j] = 0.0;
- }
- U[j][j] = 1.0;
- }
- for (int k = nct-1; k >= 0; k--) {
- if (s[k] != 0.0) {
- for (int j = k+1; j < nu; j++) {
- double t = 0;
- for (int i = k; i < m; i++) {
- t += U[i][k]*U[i][j];
- }
- t = -t/U[k][k];
- for (int i = k; i < m; i++) {
- U[i][j] += t*U[i][k];
- }
- }
- for (int i = k; i < m; i++ ) {
- U[i][k] = -U[i][k];
- }
- U[k][k] = 1.0 + U[k][k];
- for (int i = 0; i < k-1; i++) {
- U[i][k] = 0.0;
- }
- } else {
- for (int i = 0; i < m; i++) {
- U[i][k] = 0.0;
- }
- U[k][k] = 1.0;
- }
- }
- }
-
- // If required, generate V.
-
- if (wantv) {
- for (int k = n-1; k >= 0; k--) {
- if ((k < nrt) & (e[k] != 0.0)) {
- for (int j = k+1; j < nu; j++) {
- double t = 0;
- for (int i = k+1; i < n; i++) {
- t += V[i][k]*V[i][j];
- }
- t = -t/V[k+1][k];
- for (int i = k+1; i < n; i++) {
- V[i][j] += t*V[i][k];
- }
- }
- }
- for (int i = 0; i < n; i++) {
- V[i][k] = 0.0;
- }
- V[k][k] = 1.0;
- }
- }
-
- // Main iteration loop for the singular values.
-
- int pp = p-1;
- int iter = 0;
- double eps = Math.pow(2.0,-52.0);
- double tiny = Math.pow(2.0,-966.0);
- while (p > 0) {
- int k,kase;
-
- // Here is where a test for too many iterations would go.
-
- // This section of the program inspects for
- // negligible elements in the s and e arrays. On
- // completion the variables kase and k are set as follows.
-
- // kase = 1 if s(p) and e[k-1] are negligible and k<p
- // kase = 2 if s(k) is negligible and k<p
- // kase = 3 if e[k-1] is negligible, k<p, and
- // s(k), ..., s(p) are not negligible (qr step).
- // kase = 4 if e(p-1) is negligible (convergence).
-
- for (k = p-2; k >= -1; k--) {
- if (k == -1) {
- break;
- }
- if (Math.abs(e[k]) <=
- tiny + eps*(Math.abs(s[k]) + Math.abs(s[k+1]))) {
- e[k] = 0.0;
- break;
- }
- }
- if (k == p-2) {
- kase = 4;
- } else {
- int ks;
- for (ks = p-1; ks >= k; ks--) {
- if (ks == k) {
- break;
- }
- double t = (ks != p ? Math.abs(e[ks]) : 0.) +
- (ks != k+1 ? Math.abs(e[ks-1]) : 0.);
- if (Math.abs(s[ks]) <= tiny + eps*t) {
- s[ks] = 0.0;
- break;
- }
- }
- if (ks == k) {
- kase = 3;
- } else if (ks == p-1) {
- kase = 1;
- } else {
- kase = 2;
- k = ks;
- }
- }
- k++;
-
- // Perform the task indicated by kase.
-
- switch (kase) {
-
- // Deflate negligible s(p).
-
- case 1: {
- double f = e[p-2];
- e[p-2] = 0.0;
- for (int j = p-2; j >= k; j--) {
- double t = Maths.hypot(s[j],f);
- double cs = s[j]/t;
- double sn = f/t;
- s[j] = t;
- if (j != k) {
- f = -sn*e[j-1];
- e[j-1] = cs*e[j-1];
- }
- if (wantv) {
- for (int i = 0; i < n; i++) {
- t = cs*V[i][j] + sn*V[i][p-1];
- V[i][p-1] = -sn*V[i][j] + cs*V[i][p-1];
- V[i][j] = t;
- }
- }
- }
- }
- break;
-
- // Split at negligible s(k).
-
- case 2: {
- double f = e[k-1];
- e[k-1] = 0.0;
- for (int j = k; j < p; j++) {
- double t = Maths.hypot(s[j],f);
- double cs = s[j]/t;
- double sn = f/t;
- s[j] = t;
- f = -sn*e[j];
- e[j] = cs*e[j];
- if (wantu) {
- for (int i = 0; i < m; i++) {
- t = cs*U[i][j] + sn*U[i][k-1];
- U[i][k-1] = -sn*U[i][j] + cs*U[i][k-1];
- U[i][j] = t;
- }
- }
- }
- }
- break;
-
- // Perform one qr step.
-
- case 3: {
-
- // Calculate the shift.
-
- double scale = Math.max(Math.max(Math.max(Math.max(
- Math.abs(s[p-1]),Math.abs(s[p-2])),Math.abs(e[p-2])),
- Math.abs(s[k])),Math.abs(e[k]));
- double sp = s[p-1]/scale;
- double spm1 = s[p-2]/scale;
- double epm1 = e[p-2]/scale;
- double sk = s[k]/scale;
- double ek = e[k]/scale;
- double b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/2.0;
- double c = (sp*epm1)*(sp*epm1);
- double shift = 0.0;
- if ((b != 0.0) | (c != 0.0)) {
- shift = Math.sqrt(b*b + c);
- if (b < 0.0) {
- shift = -shift;
- }
- shift = c/(b + shift);
- }
- double f = (sk + sp)*(sk - sp) + shift;
- double g = sk*ek;
-
- // Chase zeros.
-
- for (int j = k; j < p-1; j++) {
- double t = Maths.hypot(f,g);
- double cs = f/t;
- double sn = g/t;
- if (j != k) {
- e[j-1] = t;
- }
- f = cs*s[j] + sn*e[j];
- e[j] = cs*e[j] - sn*s[j];
- g = sn*s[j+1];
- s[j+1] = cs*s[j+1];
- if (wantv) {
- for (int i = 0; i < n; i++) {
- t = cs*V[i][j] + sn*V[i][j+1];
- V[i][j+1] = -sn*V[i][j] + cs*V[i][j+1];
- V[i][j] = t;
- }
- }
- t = Maths.hypot(f,g);
- cs = f/t;
- sn = g/t;
- s[j] = t;
- f = cs*e[j] + sn*s[j+1];
- s[j+1] = -sn*e[j] + cs*s[j+1];
- g = sn*e[j+1];
- e[j+1] = cs*e[j+1];
- if (wantu && (j < m-1)) {
- for (int i = 0; i < m; i++) {
- t = cs*U[i][j] + sn*U[i][j+1];
- U[i][j+1] = -sn*U[i][j] + cs*U[i][j+1];
- U[i][j] = t;
- }
- }
- }
- e[p-2] = f;
- iter = iter + 1;
- }
- break;
-
- // Convergence.
-
- case 4: {
-
- // Make the singular values positive.
-
- if (s[k] <= 0.0) {
- s[k] = (s[k] < 0.0 ? -s[k] : 0.0);
- if (wantv) {
- for (int i = 0; i <= pp; i++) {
- V[i][k] = -V[i][k];
- }
- }
- }
-
- // Order the singular values.
-
- while (k < pp) {
- if (s[k] >= s[k+1]) {
- break;
- }
- double t = s[k];
- s[k] = s[k+1];
- s[k+1] = t;
- if (wantv && (k < n-1)) {
- for (int i = 0; i < n; i++) {
- t = V[i][k+1]; V[i][k+1] = V[i][k]; V[i][k] = t;
- }
- }
- if (wantu && (k < m-1)) {
- for (int i = 0; i < m; i++) {
- t = U[i][k+1]; U[i][k+1] = U[i][k]; U[i][k] = t;
- }
- }
- k++;
- }
- iter = 0;
- p--;
- }
- break;
- }
- }
- }
-
-/* ------------------------
- Public Methods
- * ------------------------ */
-
- /** Return the left singular vectors
- @return U
- */
-
- public Matrix getU () {
- return new Matrix(U,m,Math.min(m+1,n));
- }
-
- /** Return the right singular vectors
- @return V
- */
-
- public Matrix getV () {
- return new Matrix(V,n,n);
- }
-
- /** Return the one-dimensional array of singular values
- @return diagonal of S.
- */
-
- public double[] getSingularValues () {
- return s;
- }
-
- /** Return the diagonal matrix of singular values
- @return S
- */
-
- public Matrix getS () {
- Matrix X = new Matrix(n,n);
- double[][] S = X.getArray();
- for (int i = 0; i < n; i++) {
- for (int j = 0; j < n; j++) {
- S[i][j] = 0.0;
- }
- S[i][i] = this.s[i];
- }
- return X;
- }
-
- /** Two norm
- @return max(S)
- */
-
- public double norm2 () {
- return s[0];
- }
-
- /** Two norm condition number
- @return max(S)/min(S)
- */
-
- public double cond () {
- return s[0]/s[Math.min(m,n)-1];
- }
-
- /** Effective numerical matrix rank
- @return Number of nonnegligible singular values.
- */
-
- public int rank () {
- double eps = Math.pow(2.0,-52.0);
- double tol = Math.max(m,n)*s[0]*eps;
- int r = 0;
- for (int i = 0; i < s.length; i++) {
- if (s[i] > tol) {
- r++;
- }
- }
- return r;
- }
-}
diff --git a/geogebra/kernel/jama/util/Maths.java b/geogebra/kernel/jama/util/Maths.java
deleted file mode 100644
index 1776a51..0000000
--- a/geogebra/kernel/jama/util/Maths.java
+++ /dev/null
@@ -1,20 +0,0 @@
-package geogebra.kernel.jama.util;
-
-public class Maths {
-
- /** sqrt(a^2 + b^2) without under/overflow. **/
-
- public static double hypot(double a, double b) {
- double r;
- if (Math.abs(a) > Math.abs(b)) {
- r = b/a;
- r = Math.abs(a)*Math.sqrt(1+r*r);
- } else if (b != 0) {
- r = a/b;
- r = Math.abs(b)*Math.sqrt(1+r*r);
- } else {
- r = 0.0;
- }
- return r;
- }
-}
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