Compare commits

..

10 Commits

Author SHA1 Message Date
Mark Liversedge
d800d8b9fd Undo accidental edit in src.pro
.. that removed VideoWindow for non-Mac.
2016-12-25 13:13:21 +00:00
Mark Liversedge
b08dee941f VERSION 3.4 MAC FIX GOOGLE DRIVE
.. update build id
2016-12-25 13:11:01 +00:00
Mark Liversedge
537da048a5 Deprecate Mac Native Buttons
.. they were removed from code recently but still
   lingered harmlessly in the codebase.

.. now moving into the deprecated folder to stop
   them from being used again in the future.
2016-12-25 12:49:38 +00:00
Mark Liversedge
72226ef3c3 MainWindow showhideToolbar always on Mac now
.. #ifdef should have been removed when the Mac specific
   UI elements in MainWindow were removed.
2016-12-25 12:49:25 +00:00
Mark Liversedge
d20c4e1f29 VERSION 3.4 SIERRA BUILD
.. fixup build id and version strings for Sierra build.
2016-12-25 12:49:07 +00:00
Mark Liversedge
9b8dbc1d6f Splash screen size
.. on hdpi the fonts get squished by spacing
2016-12-25 12:48:56 +00:00
Mark Liversedge
7d64068fe2 Fixup to enable build on QT 5.8 and Xcode 8.1
.. remove all custom widgets and prepare for next commit that
   replaces use of QTKit with AV Foundation on MacOS
2016-12-25 12:48:45 +00:00
Mark Liversedge
3d496d2b28 Ignore SSL errors during reply processing
.. in OAuth dialog
2016-12-24 14:29:36 +00:00
Mark Liversedge
73cc723049 OAUTH ignore handshake "errors"
.. when authorising via SSL we may get handshake "errors" as
   the protocol is established, this seems to occur with
   openssl on Sierra and Mavericks.

.. since the request is completed then some form of protocol was
   established so we ignore it in this instance.

.. even if there is a problem its likely the tokens will be blank
   and that will trigger another error, so fairly safe to ignore
2016-12-24 14:29:23 +00:00
Mark Liversedge
ad3346df35 Google Drive Auth - more diags
.. auth sometimes fails, give better reasons
2016-12-24 14:29:11 +00:00
746 changed files with 105648 additions and 781223 deletions

5
.gitattributes vendored
View File

@@ -1,5 +0,0 @@
# Added this line to .gitattributes
*.pbxproj -crlf -diff -merge
src/translations/* linguist-documentation
src/Resources/translations/* linguist-documentation
test/* linguist-vendored

4
.gitignore vendored
View File

@@ -13,7 +13,6 @@ Makefile
*.prl
*.swp
*.user
*.AppImage
# osx noise
.DS_Store
@@ -50,6 +49,3 @@ qwt/src/Makefile.Debug
qwt/textengines/mathml/debug/
qwt/textengines/mathml/release/
build.pro.user
build.pro.user.*
doc/contrib/WASP Packet Protocol.pdf

View File

@@ -1,60 +1,124 @@
branches:
only:
- master
- /^[vV]\d+\.\d+(\.\d+)?(-\S*)?$/
os:
- osx
- linux
dist: xenial
language: c++
- master
language:
- objective-c
compiler:
- clang
- gcc
env:
matrix:
- BRANCH=master QT=qt4 QT_PATH=qt
- BRANCH=master QT=qt5 QT_PATH=qt5 QT_VER=5.5.1
global:
- BRANCH=master
- secure: iqYW7f3//ZkMVzeCEarYn0S0DqKjFU9juBh0KF6WTlUsKX902Jtsk7dFoJlNDYBf63HLgV+wW2Hc6MxI9sGiUkom0gY9/To/aeGIJFGEX2sLm/e0Ok3qN521FA0Q/OiCFsD0RC6J+yrHxzI+rf8Z1rujceUsz2KgsrfAjYYv+BY=
- secure: C6f58PXwvvHeVOjCLbyDRjgyF0tk+bXjCNUDur8VJLhJEGNdnrt+rH+d3azYaX0n348ZnQZ14as4M4rHjN1A/3DRbdUdOS7PQZrkj/n363ck1tvYOG/tzYqkEcVoQyjIJ7ZoTuBXDQry/VJmLxQjM0glTa2upNFHMOMwqZNkF+I=
- secure: mgf181ok4rJTHxAdSaeIb/OzUx7PQc6UjJYfhJQcZDjN1Nou+Um6OHpnooMHeEq0CdGuLSiv2xVmuQnRjI5MfG5re/a3l39hSzi9tPLWi1y7uOLCtQFooJw3H+LhiKZcgAtEnkTmEhUCEu5uZ7cp4lWhrQZWCR5mCDNtJrGHjiw=
- secure: UkW6SpgeACb6enGZADTAtPPRe23Tffne/SRQoBsZ3kGbKzgv8kTCLY0G5N71B1xEGdLB/36piOa0yji2SMW1jbflxR7tdOsiNpfd9R5qYqWVZRulY0qite8ZCwU5dqgy87pp4ECC1hNSOTq17aa4Sc4G4egg9AOy8cntLBTtxJA=
- secure: rb/MKPHEK8yOK5uYpXq2o+MQ7h65ft+c/xE9XmLFk1jLnK0oxe6+KeoSFlQ0n5UwLSsHrytMXVaUHex6EEt0TheXFlohi7BcNFWRWXr+wLucuaPjMnU49VErrSigjJ5VW/rcR7fORmnDwn5y06r3Rer9SC1hImCxf/pqF8hFZps=
- secure: FXJzm98lwbc1R2eh9/CvVReVRHEPLDm+sCRjiV9HJgeCveIUauLasp9Skamz0c6OKLmkjLY8JERPT491ZgCG8YcQ9x1bM8HGbmRqnn9xSUxINIRzVmyTiLMBoT/ibHHeFjFpyiGfukOAkHwMNNsrSrbaekhiJuekaXo7iTwYQB0=
- secure: K9+6ufffQ2a6dCTwVSI5ZtrGE+JSsj2ZeQwJ8Xk/y1yhSlbnW6Uptfs5oZ4XJ/BAQbuKbctnczP/jwDtGBG/Y0WOxn8m1DYBrkeLeToc0JZ8dn2lF6H6BEcB3VI3iPUtxAXWHNeSCk2qaC83z80Ydjc5GCxoAOwlw5/BEsRYI/s=
- secure: n6khzr3bPnvh2lTE1NmcaPWRWkqLBUcXZL20EO0Q0HyhH2O22fwsKfnODCDtP1UEQxW+E0G3DkedSz/RmpMWbv1KpWKNNKl74wIdUE53nRIBLTULRoypCq1tDZzQqkoogbXu3pWrb23YoUuM2p5zxM9l3TiNbcrdZeQ+PInVL6o=
- secure: mJEJUwt1jhx5qx5h5C8gnYJyaUb5fItSJGU/Tgp0IMCPCUSXtjHf9QTKITAKvg/hY8zggSwo+Vg2VzdMypdxDKqAeH/xAjq/o1+4linWphSjWpUGTqF/B8sR37WtduXtetamX+ctsbG4I77Xw+7y8OPPoCPxDct9hWxfCw6eBrI=
- secure: BX7lVlMs6c6qOCMc7Eu0s3G7/es+3h/EGElS/4wjw4/nxp91bd0RbkOmGmgEKOFw5XRFl8gV0kEzmFhrJTdGfTnWHmdsGjSo2VzwePgW/PbDdQrTVD2rYBmmPoeTXf3S3v0P7d3pBrpuxAqkmj7bFkpnvviCN9erC4bUhSg6jEI=
- secure: AC6pelym0R1Pq6GgcAy7E/BmlNWrni+41P8V8PMtjBKEtiyJ3tQa+KCn5g0UfGzktRHk+0l+szz3Wdy+bzl+ifiJVhXXs95B9F9El03p33UQLFPi+wFlivddP5DLc+4vIsDUiaNX97p89vo1/R96OLjpF1mUzfOMKYmAiMGP/Co=
- secure: QXyyyutxesRVae/WFi75dxlNw2qTyWc6WQ3vmRER9BFhlrNtt8lmE+M6ghMDOhxigzSXWxHcG9r66BLOw4DML7AXg4f3NIAIYuYQrpfsWQ1TKGC/vVvIPDlNBKL62zSOoNowjup1HfZpB575wl4JkmHjoMPDfQ4yM/JVR+MKmIM=
- secure: lefpL3SB8yN0Vn1R2e0hAFpJgFnu4rJ/vn7DucSKQvJ61K7t3LrUHFXElDQGFZMbytx4OJDeYsJtrccrIHjcsSAEIyW8TTcwn5/JopnyeQ3ukV5AYpEoQusym09XKru9E7awqvnZrXz6mdoIum5JP7+H116mPN4vsvz5nkNWxeg=
- secure: RAGPq/thN9x6STNueDbeJWGUN75OLNcUVUkLHI/eZwPrkMaiQPfxIaJ+8eO2PszDcBojw3eYVhzbRvLnLiXmHL3buwD6oXMTyYnxGzCZ61DeDQ2cQa8ynKmRim5JL3viKMqtdyasXVoGf/u0GqMsgaLcqN6e/vXuXMGu6kkUPEQ=
- secure: Lydms45scczE9gZvkWze2fXVbEInKW48DOCIRJWziEzxKkvXUE7WPy74fLvfvL+0JW0LH/ZLZ9EbgHcJAYYs8CBrfAeOOtnyo2DZ0ouEO13RmomSZneEKSpJxRtErcPIu+B0LzcEGyAgf7bxPVevEte50CK0pZJ7z7bHMhU23pY=
- secure: cc0pAJjkmFNw2bO3zVACmtyHTwINAHALrtUxi+nRD+FhOO9KxuxuuwvcKCZKfp9EUOjz5PrYWKV1ZH/zt/jMix8A4Gyue2mWX8WYih7aTmJBcJWsFNTCybnClreKBCh18kHdWWhkmhk8EMINDvlqxzJZGpcNO04gxhL9wuLLrNQ=
- secure: em0xXIm69rMHsHXYQiizeJB7dEFBkX33PsWDHwBNrX6lFBued23eL96KJC4RVbk6A+AHFtXFATrreZ14D5JH/E/37CXhe3X2R93WqiPUSH0s7NI4fFA1BroKUNAlqO4bMqDBidtNmwMPaLTXjaOnOZyvbAG7z+QV3TKC8tOeZDU=
- secure: VFaSERlgsjzjiDQhKw8XFvQrjdvFzHHL7V3NQg+RfELHoT6I1pAGFdl/+lRBIVOiVkbQ6XnpBA28nlf0QydPHElRZdqmh0azQV/bkUXD4ffPE8q0iSqeqhAZ+5L05K5K+Gby/y8TZE4FX6e/7trFL7oq+h9x0gq5RQO8rAcTV84=
matrix:
include:
- os: osx
osx_image: xcode10.1
compiler: clang
- os: linux
compiler: gcc
before_install:
- travis/$TRAVIS_OS_NAME/before_install.sh
## try early just to check, can delete later
- date
- brew update
- sh travis/install-qt.sh
##- brew install $QT
- brew install libical
- brew install libusb libusb-compat
- brew install srmio
- brew install libsamplerate
- brew tap homebrew/science
- brew install r
## Disable KML for now
##- brew install --HEAD travis/libkml.rb
- sudo chmod -R +w /usr/local
- curl -O http://www.ftdichip.com/Drivers/D2XX/MacOSX/D2XX1.2.2.dmg
- git clone --depth 1 https://github.com/sintegrial/qwtplot3d.git qwtplot3d
- cd qwtplot3d
- CC=clang CXX=clang++ /usr/local/opt/$QT_PATH/bin/qmake -makefile -recursive QMAKE_CXXFLAGS_WARN_ON+="-Wno-unused-private-field -Wno-c++11-narrowing"
- CC=clang CXX=clang++ make -j2
- cd ..
- git clone --branch 0.98 https://github.com/kypeli/kQOAuth.git kQOAuth-0.98
- cd kQOAuth-0.98
- CC=clang CXX=clang++ /usr/local/opt/$QT_PATH/bin/qmake -makefile -recursive QMAKE_CXXFLAGS_WARN_ON+="-Wno-unused-private-field -Wno-c++11-narrowing"
- CC=clang CXX=clang++ make -j2 qmake_all
- CC=clang CXX=clang++ sudo make install
- cd ..
- hdiutil mount D2XX1.2.2.dmg
before_script:
- travis/$TRAVIS_OS_NAME/before_script.sh
- mkdir D2XX
- cp /Volumes/release/D2XX/Object/10.5-10.7/x86_64/libftd2xx.1.2.2.dylib D2XX
- sudo cp /Volumes/release/D2XX/Object/10.5-10.7/x86_64/libftd2xx.1.2.2.dylib /usr/local/lib
- cp /Volumes/release/D2XX/bin/*.h D2XX
- sed -i "" "s|libftd2xx.dylib|@executable_path/../Frameworks/libftd2xx.1.2.2.dylib|"
src/FileIO/D2XX.cpp
- cp qwt/qwtconfig.pri.in qwt/qwtconfig.pri
- cp src/gcconfig.pri.in src/gcconfig.pri
- /usr/local/opt/$QT_PATH/bin/lupdate src/src.pro
- sed -i "" "s|#\(CONFIG += release.*\)|\1 static |" src/gcconfig.pri
- sed -i "" "s|#\(QMAKE_LRELEASE\).*|\1 += /usr/local/opt/$QT_PATH/bin/lrelease|"
src/gcconfig.pri
- sed -i "" "s|#\(QMAKE_CXXFLAGS\).*|\1_RELEASE += -mmacosx-version-min=10.7 -arch
x86_64|" src/gcconfig.pri
- sed -i "" "s|^#CloudDB|CloudDB|" src/gcconfig.pri
- sed -i "" "s|^#LIBZ|LIBZ|" src/gcconfig.pri
- sed -i "" "s|#\(SRMIO_INSTALL =.*\)|\1 /usr/local|" src/gcconfig.pri
- sed -i "" "s|#\(D2XX_INCLUDE =.*\)|\1 ../D2XX|" src/gcconfig.pri
- sed -i "" "s|#\(D2XX_LIBS =.*\)|\1 -L../D2XX -lftd2xx.1.2.2|" src/gcconfig.pri
- sed -i "" "s|#\(KQOAUTH_INSTALL =.*\)|\1 /usr/local|" src/gcconfig.pri
- sed -i "" "s|#\(KQOAUTH_INCLUDE =.*\)|\1 \$\$[QT_INSTALL_LIBS]/kqoauth.framework/Headers|"
src/gcconfig.pri
- sed -i "" "s|#\(KQOAUTH_LIBS =.*\)|\1 -F\$\$[QT_INSTALL_LIBS] -framework kqoauth|"
src/gcconfig.pri
- sed -i "" "s|#\(QWT3D_INSTALL =.*\)|\1 ../qwtplot3d|" src/gcconfig.pri
## Disable KML for now
##- sed -i "" "s|#\(KML_INSTALL =\).*|\1 /usr/local|" src/gcconfig.pri
##- sed -i "" "s|#\(KML_LIBS =.*\)|\1 -L/usr/local/lib -lkmlxsd -lkmlregionator -lkmldom
## -lkmlconvenience -lkmlengine -lkmlbase|" src/gcconfig.pri
- sed -i "" "s|#\(ICAL_INSTALL =.*\)|\1 /usr/local|" src/gcconfig.pri
- sed -i "" "s|#\(ICAL_LIBS =.*\)|\1 -L/usr/local/lib -lical|" src/gcconfig.pri
- sed -i "" "s|#\(LIBUSB_INSTALL =\).*|\1 /usr/local|" src/gcconfig.pri
- sed -i "" "s|#\(LIBUSB_LIBS =.*\)|\1 -L/usr/local/lib -lusb -lusb-1.0|" src/gcconfig.pri
- sed -i "" "s|#\(SAMPLERATE_INSTALL =\).*|\1 /usr/local|" src/gcconfig.pri
- sed -i "" "s|#\(SAMPLERATE_LIBS =\).*|\1 -L/usr/local/lib -lsamplerate|" src/gcconfig.pri
- sed -i "" "s|#\(DEFINES += GC_HAVE_LION*\)|\1|" src/gcconfig.pri
- sed -i "" "s|#\(HTPATH = ../httpserver.*\)|\1 |" src/gcconfig.pri
- sed -i "" "s|#\(DEFINES += GC_WANT_ROBOT.*\)|\1 |" src/gcconfig.pri
- sed -i "" "s|\(DEFINES += GC_VIDEO_NONE.*\)|#\1 |" src/gcconfig.pri
- sed -i "" "s|#\(DEFINES += GC_VIDEO_QUICKTIME.*\)|\1 |" src/gcconfig.pri
##Issues with c++11 and stdlib on travis and dependencies (e.g. plot3d)
- sed -i "" "s|#\(DEFINES += GC_WANT_R.*\)|\1 |" src/gcconfig.pri
- echo "QMAKE_CFLAGS_RELEASE += -mmacosx-version-min=10.7 -arch x86_64" >> src/gcconfig.pri
- sed -i "" "s/__GC_GOOGLE_CALENDAR_CLIENT_SECRET__/"$GC_GOOGLE_CALENDAR_CLIENT_SECRET"/" src/Core/Secrets.h
- sed -i "" "s/__GC_STRAVA_CLIENT_SECRET__/"$GC_STRAVA_CLIENT_SECRET"/" src/Core/Secrets.h
- sed -i "" "s/__GC_DROPBOX_CLIENT_SECRET__/"$GC_DROPBOX_CLIENT_SECRET"/" src/Core/Secrets.h
- sed -i "" "s/__GC_CYCLINGANALYTICS_CLIENT_SECRET__/"$GC_CYCLINGANALYTICS_CLIENT_SECRET"/" src/Core/Secrets.h
- sed -i "" "s/__GC_TWITTER_CONSUMER_SECRET__/"$GC_TWITTER_CONSUMER_SECRET"/" src/Core/Secrets.h
- cat src/gcconfig.pri
script:
- travis/$TRAVIS_OS_NAME/script.sh
- CC=clang CXX=clang++ /usr/local/opt/$QT_PATH/bin/qmake -makefile -recursive QMAKE_CXXFLAGS_WARN_ON+="-Wno-unused-private-field -Wno-c++11-narrowing"
- CC=clang CXX=clang++ make qmake_all
- CC=clang CXX=clang++ make -j4 sub-qwt --silent
- CC=clang CXX=clang++ make -j4 sub-src
after_success:
- if [[ $TRAVIS_OS_NAME == "osx" ]]; then
export FINAL_NAME=dev-prerelease-branch-master-build-${TRAVIS_BUILD_NUMBER}.dmg;
else
export FINAL_NAME=dev-prerelease-branch-master-build-${TRAVIS_BUILD_NUMBER}.AppImage;
fi
- travis/$TRAVIS_OS_NAME/after_success.sh
deploy:
provider: releases
api_key:
secure: KlfkRM8oGP02y5LhbdxetnhqUG3YzVylvyhT8BTYjdoJtkJr7YXYpdhj9byZ9aiy1gSWI/g7A1X6/P8/McqRtgt4dEYr4Zg8QO7Y7QdTpgNQEwu8ZrkyyG/7b/rSkfFHDjrOAHslLVXuBNwWgi8YW1aTn0rY2AqDbOri7u6tt9Q=
file: src/$FINAL_NAME
skip_cleanup: true
on:
tags: true
repo: GoldenCheetah/GoldenCheetah
- cd src
- ls -laR GoldenCheetah.app
- GoldenCheetah.app/Contents/MacOS/GoldenCheetah --help
- /usr/local/opt/$QT_PATH/bin/macdeployqt GoldenCheetah.app -verbose=2 -dmg
## fix up the bundle with macdeployqtfix
- python ../travis/macdeployqtfix.py GoldenCheetah.app /usr/local/opt/$QT_PATH
- brew remove $QT
- mv GoldenCheetah.dmg GoldenCheetah_$QT.dmg
- hdiutil mount GoldenCheetah_$QT.dmg
- cd /Volumes/GoldenCheetah
- ls -laR GoldenCheetah.app
- GoldenCheetah.app/Contents/MacOS/GoldenCheetah --help
##deploy broken in travis, read-only filesystem error
##before_deploy:
##- gem install mime-types -v 2.6.2
##deploy:
## provider: releases
## api_key: $GH_OAUTH_TOKEN
## file: GoldenCheetah_$QT.dmg
## skip_cleanup: true
## on:
## tags: true

View File

@@ -1,49 +0,0 @@
## How to get help
#### **Do you have questions about how to use GoldenCheetah?**
* Ask any question about how to use GoldenCheetah on [golden-cheetah-users mailing list](https://groups.google.com/forum/#!forum/golden-cheetah-users), ideally after watching the corresponding [tutorials](https://www.goldencheetah.org/#section-tutorials) and/or reading the relevant parts of the [documentation](https://github.com/GoldenCheetah/GoldenCheetah/wiki).
#### **Do you have questions about the source code?**
* Ask any question about how to build GoldenCheetah or anything related to the source code in the [golden-cheetah-developers mailing list](https://groups.google.com/forum/#!forum/golden-cheetah-developers), please see the [GoldenCheetah Developers Guide](https://github.com/GoldenCheetah/GoldenCheetah/wiki/Developers-guide) for addtional information.
## How to contribute to GoldenCheetah
#### **Did you find a bug?**
* **Ensure the bug was not already reported** by searching on GitHub under [Issues](https://github.com/GoldenCheetah/GoldenCheetah/issues).
* If you're unable to find an open issue addressing the problem, [open a new one](https://github.com/GoldenCheetah/GoldenCheetah/issues/new). Be sure to include a **title and clear description**, as much relevant information as possible, and **steps to reproduce the problem** or a **test file** demonstrating the expected behavior that is not occurring.
#### **Did you write a patch that fixes a bug?**
* Open a new GitHub pull request with the patch.
* Ensure the PR description clearly describes the problem and solution. Include the relevant issue number if applicable.
* See [GoldenCheetah Guidelines for submitting a patch](https://github.com/GoldenCheetah/GoldenCheetah/wiki/Guidelines-for-submitting-a-patch) for additional information.
#### **Did you fix whitespace, format code, or make a purely cosmetic patch?**
Changes that are cosmetic in nature and do not add anything substantial to the stability or functionality of GoldenCheetah will generally not be accepted.
#### **Do you intend to add a new feature or change an existing one?**
* Suggest your change in the [golden-cheetah-developers mailing list](https://groups.google.com/forum/#!forum/golden-cheetah-developers) and start writing code.
* Do not open an issue on GitHub until you have collected positive feedback about the change. GitHub issues are primarily intended for bug reports and fixes.
#### **Do you want to contribute to GoldenCheetah translations?**
* Translators are very welcome, please see [GoldenCheetah Guidelines for translators](https://github.com/GoldenCheetah/GoldenCheetah/wiki/Guidelines-for-translators)
#### **Do you want to contribute to GoldenCheetah documentation?**
* The [GoldenCheetah wiki](https://github.com/GoldenCheetah/GoldenCheetah/wiki) is open to user's contributions. feel free to add what you consider relevant to make other's users experience smoother.
GoldenCheetah is a volunteer effort. Contributions are welcome!
Thanks!
GoldenCheetah Team

833
COPYING
View File

@@ -1,281 +1,622 @@
GNU GENERAL PUBLIC LICENSE
Version 2, June 1991
Version 3, 29 June 2007
Copyright (C) 1989, 1991 Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The licenses for most software are designed to take away your
freedom to share and change it. By contrast, the GNU General Public
License is intended to guarantee your freedom to share and change free
software--to make sure the software is free for all its users. This
General Public License applies to most of the Free Software
Foundation's software and to any other program whose authors commit to
using it. (Some other Free Software Foundation software is covered by
the GNU Lesser General Public License instead.) You can apply it to
The GNU General Public License is a free, copyleft license for
software and other kinds of works.
The licenses for most software and other practical works are designed
to take away your freedom to share and change the works. By contrast,
the GNU General Public License is intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free
software for all its users. We, the Free Software Foundation, use the
GNU General Public License for most of our software; it applies also to
any other work released this way by its authors. You can apply it to
your programs, too.
When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
this service if you wish), that you receive source code or can get it
if you want it, that you can change the software or use pieces of it
in new free programs; and that you know you can do these things.
them if you wish), that you receive source code or can get it if you
want it, that you can change the software or use pieces of it in new
free programs, and that you know you can do these things.
To protect your rights, we need to make restrictions that forbid
anyone to deny you these rights or to ask you to surrender the rights.
These restrictions translate to certain responsibilities for you if you
distribute copies of the software, or if you modify it.
To protect your rights, we need to prevent others from denying you
these rights or asking you to surrender the rights. Therefore, you have
certain responsibilities if you distribute copies of the software, or if
you modify it: responsibilities to respect the freedom of others.
For example, if you distribute copies of such a program, whether
gratis or for a fee, you must give the recipients all the rights that
you have. You must make sure that they, too, receive or can get the
source code. And you must show them these terms so they know their
rights.
gratis or for a fee, you must pass on to the recipients the same
freedoms that you received. You must make sure that they, too, receive
or can get the source code. And you must show them these terms so they
know their rights.
We protect your rights with two steps: (1) copyright the software, and
(2) offer you this license which gives you legal permission to copy,
distribute and/or modify the software.
Developers that use the GNU GPL protect your rights with two steps:
(1) assert copyright on the software, and (2) offer you this License
giving you legal permission to copy, distribute and/or modify it.
Also, for each author's protection and ours, we want to make certain
that everyone understands that there is no warranty for this free
software. If the software is modified by someone else and passed on, we
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Finally, any free program is threatened constantly by software
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GNU GENERAL PUBLIC LICENSE
TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
TERMS AND CONDITIONS
0. This License applies to any program or other work which contains
a notice placed by the copyright holder saying it may be distributed
under the terms of this General Public License. The "Program", below,
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means either the Program or any derivative work under copyright law:
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Activities other than copying, distribution and modification are not
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is covered only if its contents constitute a work based on the
Program (independent of having been made by running the Program).
Whether that is true depends on what the Program does.
"This License" refers to version 3 of the GNU General Public License.
1. You may copy and distribute verbatim copies of the Program's
source code as you receive it, in any medium, provided that you
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"Copyright" also means copyright-like laws that apply to other kinds of
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You may charge a fee for the physical act of transferring a copy, and
you may at your option offer warranty protection in exchange for a fee.
"The Program" refers to any copyrightable work licensed under this
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2. You may modify your copy or copies of the Program or any portion
of it, thus forming a work based on the Program, and copy and
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To "modify" a work means to copy from or adapt all or part of the work
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You may convey verbatim copies of the Program's source code as you
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You may convey a covered work in object code form under the terms
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Additional permissions that are applicable to the entire Program shall
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You may not propagate or modify a covered work except as expressly
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However, if you cease all violation of this License, then your
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Termination of your rights under this section does not terminate the
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9. Acceptance Not Required for Having Copies.
You are not required to accept this License in order to receive or
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occurring solely as a consequence of using peer-to-peer transmission
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10. Automatic Licensing of Downstream Recipients.
Each time you convey a covered work, the recipient automatically
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You may not impose any further restrictions on the exercise of the
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11. Patents.
A "contributor" is a copyright holder who authorizes use under this
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but do not include claims that would be infringed only as a
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infringement or for any other reason (not limited to patent issues),
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Each contributor grants you a non-exclusive, worldwide, royalty-free
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In the following three paragraphs, a "patent license" is any express
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If you convey a covered work, knowingly relying on a patent license,
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If, pursuant to or in connection with a single transaction or
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A patent license is "discriminatory" if it does not include within
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or that patent license was granted, prior to 28 March 2007.
Nothing in this License shall be construed as excluding or limiting
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otherwise be available to you under applicable patent law.
12. No Surrender of Others' Freedom.
If conditions are imposed on you (whether by court order, agreement or
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excuse you from the conditions of this License. If you cannot convey a
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If any portion of this section is held invalid or unenforceable under
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13. Use with the GNU Affero General Public License.
It is not the purpose of this section to induce you to infringe any
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system; it is up to the author/donor to decide if he or she is willing
to distribute software through any other system and a licensee cannot
impose that choice.
Notwithstanding any other provision of this License, you have
permission to link or combine any covered work with a work licensed
under version 3 of the GNU Affero General Public License into a single
combined work, and to convey the resulting work. The terms of this
License will continue to apply to the part which is the covered work,
but the special requirements of the GNU Affero General Public License,
section 13, concerning interaction through a network will apply to the
combination as such.
This section is intended to make thoroughly clear what is believed to
be a consequence of the rest of this License.
14. Revised Versions of this License.
8. If the distribution and/or use of the Program is restricted in
certain countries either by patents or by copyrighted interfaces, the
original copyright holder who places the Program under this License
may add an explicit geographical distribution limitation excluding
those countries, so that distribution is permitted only in or among
countries not thus excluded. In such case, this License incorporates
the limitation as if written in the body of this License.
9. The Free Software Foundation may publish revised and/or new versions
of the General Public License from time to time. Such new versions will
The Free Software Foundation may publish revised and/or new versions of
the GNU General Public License from time to time. Such new versions will
be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the Program
specifies a version number of this License which applies to it and "any
later version", you have the option of following the terms and conditions
either of that version or of any later version published by the Free
Software Foundation. If the Program does not specify a version number of
this License, you may choose any version ever published by the Free Software
Foundation.
Each version is given a distinguishing version number. If the
Program specifies that a certain numbered version of the GNU General
Public License "or any later version" applies to it, you have the
option of following the terms and conditions either of that numbered
version or of any later version published by the Free Software
Foundation. If the Program does not specify a version number of the
GNU General Public License, you may choose any version ever published
by the Free Software Foundation.
10. If you wish to incorporate parts of the Program into other free
programs whose distribution conditions are different, write to the author
to ask for permission. For software which is copyrighted by the Free
Software Foundation, write to the Free Software Foundation; we sometimes
make exceptions for this. Our decision will be guided by the two goals
of preserving the free status of all derivatives of our free software and
of promoting the sharing and reuse of software generally.
If the Program specifies that a proxy can decide which future
versions of the GNU General Public License can be used, that proxy's
public statement of acceptance of a version permanently authorizes you
to choose that version for the Program.
NO WARRANTY
Later license versions may give you additional or different
permissions. However, no additional obligations are imposed on any
author or copyright holder as a result of your choosing to follow a
later version.
11. BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN
OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES
PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED
OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS
TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE
PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING,
REPAIR OR CORRECTION.
15. Disclaimer of Warranty.
12. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
REDISTRIBUTE THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING
OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED
TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER
PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
POSSIBILITY OF SUCH DAMAGES.
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
@@ -287,15 +628,15 @@ free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
convey the exclusion of warranty; and each file should have at least
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software; you can redistribute it and/or modify
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
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
@@ -303,38 +644,32 @@ the "copyright" line and a pointer to where the full notice is found.
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If the program is interactive, make it output a short notice like this
when it starts in an interactive mode:
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
Gnomovision version 69, Copyright (C) year name of author
Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
<program> Copyright (C) <year> <name of author>
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, the commands you use may
be called something other than `show w' and `show c'; they could even be
mouse-clicks or menu items--whatever suits your program.
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or your
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. Here is a sample; alter the names:
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
<http://www.gnu.org/licenses/>.
Yoyodyne, Inc., hereby disclaims all copyright interest in the program
`Gnomovision' (which makes passes at compilers) written by James Hacker.
<signature of Ty Coon>, 1 April 1989
Ty Coon, President of Vice
This General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may
consider it more useful to permit linking proprietary applications with the
library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<http://www.gnu.org/philosophy/why-not-lgpl.html>.

View File

@@ -21,6 +21,7 @@ CONTENTS
- FTDI D2XX
- SRMIO
- liboauth
- QwtPlot3d
- libkml
3. ADDING OPTIONAL DEPENDENCIES WHEN BUILDING VERSION 3
@@ -33,7 +34,7 @@ CONTENTS
1. BASIC INSTALLATION WITH MANDATORY DEPENDENCIES
=================================================
Installed Linux distribution of choice on platforms i386 or amd-64 (currently Debian-based distributions and Arch-based distributions are covered). You will not need to do this if you
Installed Ubuntu 11.04 from CD image amd-64.iso. You will not need to do this if you
already have a Linux distribution installed. Left this step in to highlight the
Linux distribution the commands below were executed on.
@@ -41,12 +42,8 @@ login and open a terminal to get a shell prompt
Download MANDATORY DEPENDENCIES (browser)
-----------------------------------------
Download and install the Qt SDK from http://qt-project.org/
Once that is completed test qmake is ok with: qmake --version (should report 4.9.8 or higher)
DEBIAN-BASED DISTRIBUTION INSTRUCTIONS
--------------------------------------
Download and install the Qt 4.8 SDK from http://qt-project.org/
Once that is completed test qmake is ok with: qmake --version (should report 4.7.0 or higher)
Install git with:
$ sudo apt-get install git
@@ -58,20 +55,6 @@ Install FLEX and BISON
You will need flex v2.5.9 or later
$ sudo apt-get install bison
$ sudo apt-get install flex
-----------------------------------
ARCH-BASED DISTRIBUTION INSTRUCTIONS
------------------------------------
Install git:
$ sudo pacman -S git
INSTALL FLEX and BISON
----------------------
$ sudo pacman -S flex bison
NEXT STEPS
----------
$ vi gcconfig.pri
Ensure you have the following lines (which are now also in gcconfig.pri.in which has
@@ -91,20 +74,6 @@ $ make clean
$ qmake
$ make
To compile translation you need QT tool - lrelease
If it is not found using he defaults in src/src.pro then set the full path and filename in gcconfig.pri
QMAKE_LRELEASE = /usr/bin/lrelease
When build first time you get number of error messages on .qm files missing:
"RCC: Error in 'Resources/application.qrc': Cannot find file 'translations/gc_fr.qm'"
You can ignore these messages for your build. The .qm files will be created during the
build at a later point in time via the "lrelease" command you configured in gcconfig.pri)
If your QT build includes its own local compress libs then you should comment the line below in gcconfig.pri,
otherwise you will need to have the compress libraries installed separately.
#LIBZ_INCLUDE =
#LIBZ_LIBS = -lz
You will now have a release3 binary but with none of the release3 dependencies compiled in.
Get latest GOLDEN CHEETAH source files
--------------------------------------
@@ -206,6 +175,96 @@ $ make
You now have SRM support built in.
OAUTH/CRYPT - For Tweet my ride (twitter) support
-------------------------------------------------
You should be able to install liboauth and dependencies
directly with:
$ sudo apt-get install liboauth-dev
If this does not work then:
Download the source from: http://sourceforge.net/projects/liboauth/files/liboauth-0.9.4.tar.gz/download and
unpack it into ~/Projects/liboauth-0.9.4 using archive manager
$ cd ~/Projects/liboauth-0.9.4
You may find that libcurl is not installed (which liboauth depends upon) so download it
from http://curl.haxx.se/download/curl-7.21.6.tar.gz and unpack it into ~/Projects/curl-7.21.6
using archive manager to drag and drop into your Projects folder
$ cd ~/Projects/curl-7.21.6
$ ./configure
$ make
$ sudo make install
You should now have libcurl and friends installed in /usr/local
You may find that liboauth also requires the openssl libs installed, these are available
pre-packaged thankfully so:
$ sudo apt-get install libssl-dev
This will also install zlibg which liboauth also desires.
$ cd ~/Projects/liboauth-0.9.4
$ ./configure
$ make
$ sudo make install
Now we have liboauth and libcurl in /usr/local and libssl in /usr/lib, so we can go back to
GoldenCheetah and update the gcconfig.pri to point at the right places:
$ cd ~/Projects/Live/GoldenCheetah/src
$ vi gcconfig.pri
Make sure the following are set:
LIBOAUTH_INSTALL = /usr/local
LIBCRYPTO_INSTALL = -lcrypto
LIBCURL_INSTALL=-lcurl
Make clean is needed if you have previously built, since source files examine #defines before
including this feature. You can skip it if you know why ;)
$ make clean
$ qmake
$ make
You can now tweet your rides and amaze your friends, or alternatively tweet your rides but
omit to mention average power to hide your weaknesses.
LIBQWTPLOT3D - For 3D plot
--------------------------
Download the tarball from http://qwtplot3d.svn.sourceforge.net/viewvc/qwtplot3d/branches/maintain_0_2_x/qwtplot3d/?view=tar
and unarchive it into your Projects directory using archive manager. There is no version number it just creates a
subdirectory called qwtplot3d
You will need to install libgl and extensions, this can be done with;
$ sudo apt-get install libgl1-mesa-dev
$ sudo apt-get install libglu-dev
On Ubuntu 12.10 I also ran
$ sudo apt-get install freeglut3 freeglut3-dev
$ cd ~/Projects/qwtplot3d
Edit the qwtplot3d.pri and add
CONFIG += staticlib
You will find that on modern Linuxes you also need to fix include/qwt3d_global.h by adding the line:
#include <GL/glu.h>
then build
$ qmake
$ make
Then to let gc know where the qwtplot3d libs are you need to edit gcconfig.pri;
$ cd ~/Projects/Live/GoldenCheetah/src
$ vi gcconfig.pri
And uncomment the following line and set the install directory to where you build
QWT3D_INSTALL = ~/Projects/qwtplot3d
LIBKML - For export to Google Earth
-----------------------------------

View File

@@ -20,6 +20,8 @@ CONTENTS
2. ADDING OPTIONAL DEPENDENCIES
- FTDI D2XX
- SRMIO
- kQOAuth
- QwtPlot3d
- libkml
- libusb
- libical
@@ -208,11 +210,6 @@ $ cd .. #this should put you in the top level dir containing this file
$ qmake -recursive
$ make
When build first time you get number of error messages on .qm files missing:
"RCC: Error in 'Resources/application.qrc': Cannot find file 'translations/gc_fr.qm'"
You can ignore these messages for your build. The .qm files will be created during the
build at a later point in time via the "lrelease" command you configured in gcconfig.pri)
If make fails to find a Makefile then qmake is configured, by default, to create
an xcode project file. You will need to change the qmake command above to tell it
to create a makefile with the following:
@@ -226,21 +223,12 @@ $ open src/GoldenCheetah.app
And you're up and running.
Now, if you would like to use XCode to debug the project, you can generate
the necessary project file.
$ qmake --recursive -spec macx-xcode
This will create a project as: build.xcodeproj Please be sure to build via
the standard method before checkin to prevent build errors. If the build
fails to launch with "couldn't be opened because you don't have permission
to view it" Then a work around would be to open the project and attach
the debugger.
$ open src/GoldenCheetah.app
2. ADDING OPTIONAL DEPENDENCIES
===============================
- SRMIO
- kQOAuth
- QwtPlot3d
- libkml
- libusb
- libical
@@ -256,7 +244,24 @@ should be taken into account.
SRMIO (git)
./configure CFLAGS="-isysroot /Developer/SDKs/MacOSX10.7.sdk -arch x86_64" CPPFLAGS=-I/usr/local/D2XX/ --disable-dependency-tracking
2.2 libkml - For export to Google Earth
2.2 kQOAuth - For OAuth Authentication
--------------------------------------
kQOauth (0.98)
qmake
2.3 QwtPlot3d - For 3d plot support
-----------------------------------
qwtplot3d (maintain_0_2_x)
Add the following to qwtplot3d.pro:
CONFIG += x86_64 static
QMAKE_MAC_SDK=/Developer/SDKs/MacOSX10.7.sdk
2.4 libkml - For export to Google Earth
---------------------------------------
expat (2.0.1)
@@ -268,7 +273,7 @@ libkml (pulled down from the svn repo)
note: the added CXXFLAGS helped clear the -Werror flag that stopped compilation.
2.3 libusb - For Garmin USB2 stick support
2.5 libusb - For Garmin USB2 stick support
------------------------------------------
libusb (0.1.12)
@@ -285,7 +290,7 @@ make install
note: that the sed line updates some commands in libtool. not sure why the arch clags are not getting passed.
2.4 libical
2.6 libical
-----------
libical (0.46)

View File

@@ -1,207 +1,117 @@
Please note: This is an old build instruction set for Version 2.x.
Most of it is still fairly valid for version 3.x.
Minimum build requirements are: Qt 4.8 with Qt.4.8.4 recommended.
All other libs are find the best that you can except for libusb which requires 0.1.12.
I have found that the cross compiler at http://mxe.cc/ to be great for building GC and SRMIO.
+++++++++++++++++++++++
WIN32 BUILD WALKTHROUGH
+++++++++++++++++++++++
Joern Rischmueller
Gareth Coco
February 2017
May 2011
This instruction will guide you through a standard build of GoldenCheetah (without external
dependencies or API based services included).
For my install, I am installing all my files into the directory: d:\coding.
You can use any directory structure you like, youll just have to change paths.
Just ensure that any folder path you use does not have a space in it.
Prerequisites:
Download the NSI installer application. I use the Portable Apps version from:
http://portableapps.com/apps/development/nsis_portable
- Install in D:\Coding\NSISPortable\
To build on Windows you need the necessary toolchain to be installed. Since 2017
GoldenCheetah is enabled to be build with the Microsoft Visual C++ 2015 toolchain,
which is also the recommended toolchain to be used. Building with the "mingw" toolchain
might still be possible, but may conflict with features needed from the Qt library
which are no longer supported by the "mingw" version of Qt.
Download Qt SDK from:
http://qt.nokia.com/downloads/sdk-windows-cpp
(File I am using is qt-sdk-win-opensource-2010.02.1.exe)
- Install in D:\Coding\Qt
Disclaimer:
Download the D2XX drivers:
http://www.ftdichip.com/Drivers/D2XX.htm
(File I am using is: CDM 202.06.00 WHQL Certified.zip)
- Install in D:\Coding\D2XX
For any of the downloads and tools the document refers to, please check if you comply
with the license agreements. I cannot any responsibility for any of the downloads you
are doing.
Download qwt-plot3d from:
http://sourceforge.net/projects/qwtplot3d/files/
(File I am using is qwtplot3d-0.2.7.zip)
- Install in D:\Coding\qwtplot3d
You need:
Edit D:\coding\qwtplot3d\src\qwt3d_function.cpp
- Add at top of file: #include <cstdio>
Edit D:\coding\qwtplot3d\qwtplot3d.pro
- Comment out: #win32:TEMPLATE = vclib
- Microsoft Visual C++ 2015 - which is part of Visual Studio 2015
-- Download from Microsoft - they offer a "Community Edition" which is sufficient
to build GoldenCheetah
- Microsoft Windows SDK - which needs to be installed separately
-- Download from here: https://developer.microsoft.com/de-de/windows/downloads/windows-10-sdk
-- I am using the Windows 10 SDK - version 10.0.14393.795(since I build on Windows 10) -
Note: building on other Windows Version(s) may require other SDK Version to be installed
but was not tested
-- When installing the SDK you have several options - for GoldenCheetah you need the "SDK" itself and
in case you want to Debug also the "Debugging Tools" to be installed. All other parts (to my experience)
are not required.
- Flex and Bison (below the version working for me)
-- Download from here: https://sourceforge.net/projects/winflexbison/
-- Use the "win_flex_bison-latest.zip" version
-- Unzip whereever you like and make sure that the location "win_bison.exe" and "win_flex.exe
are added to your "Path" environment variable
- Qt C++ Framework
-- As of today, please use Qt 5.8.0 (which is the most recent official release) for Microsoft VC2015
-- Download is available here: https://www.qt.io/download/ - the OpenSource version is sufficient
to build GoldenCheetah
You need to decide if you go for the 32Bit or the 64Bit version, all further descriptions will refer
to the 64Bit version of Qt and the 64Bit Version of the Visual C++ Toolchain.
32 Bit follows the same concepts, you just need to download and/or configure the tools for 32 bit.
The
-- Install Qt and make sure that the \bin directory of Qt is added to your "Path" environment variable
(default path of Qt is C:\Qt\Qt5.8.0\5.8\msvc2015_64\bin)
-- To build GoldenCheetah we recommend to use "jom.exe" which is an "nmake" clone - see https://wiki.qt.io/Jom
With your Qt installation you also get QtCreator installed which is the free IDE for Qt. Jom is
part of the QtCreator installation. For the later build process, make sure that the path to "jom.exe"
is added to your "Path" environment variable.
(default path of QtCreator/Jom is C:\Qt\Qt5.8.0\Tools\QtCreator\bin)
Note: Building a 32bit version / Building for Windows XP
-- 32bit follows the same concepts, you just need to download and/or configure the tools for 32 bit.
-- The Visual Studio standard toolchain as well as the SDK do not support Windows XP any more.
Then I start the “Qt Command Prompt” from the Qt SDK folder.
Building from command line without additional dependencies:
d:
cd d:\coding\qwtplot3d\
qmake -win32
mingw32-make release
For this build, I am installing all source code,... into the directory: c:\coding
Now check out your favourite web sites until the code is built.
- Download GoldenCheetah source (either using Git or downloading the ZIP file)
-- Download from here: https://github.com/GoldenCheetah/GoldenCheetah
-- Install in c:\coding\GoldenCheetah
- Setup the configuration of GoldenCheetah for the Qt windows build
-- Copy C:\coding\GoldenCheetah\qwt\qwtconfig.pri.in to C:\coding\GoldenCheetah\qwt\qwtconfig.pri
-- Copy C:\coding\GoldenCheetah\src\gccconfig.pri.in to C:\coding\GoldenCheetah\src\gccconfig.pri
-- Edit the "gcconfig.pri" file (see also instructions in the file itself)
Lines to be changed (from Default to New - or Add(ed):
Default New
#CONFIG += release CONFIG += release
#DEFINES += NOWEBKIT DEFINES += NOWEBKIT
#QMAKE_LRELEASE = /usr/bin/lrelease QMAKE_LRELEASE = lrelease
Default
#WINKIT_INSTALL= "C:/Program Files (x86)/Windows Kits/8.1/Lib/winv6.3/um/x64"
New
WINKIT_INSTALL= "C:/Program Files (x86)/Windows Kits/10/Lib/10.0.14393.0/um/x64"
Note: This is the default path for the SDK - depending on how you installed the
SDK the path my deviate from the example.
Add Lines
CONFIG += lex
CONFIG += yacc
Default New
#QMAKE_LEX = win_flex QMAKE_LEX = win_flex --wincompat
#QMAKE_YACC = win_bison QMAKE_YACC = win_bison --file-prefix=y -t
Add Lines
# Make sure that LEX/YACC is executed first (to allow multi-core compilation via Jom)
lex.CONFIG += target_predeps
yacc_impl.CONFIG += target_predeps
yacc_decl.CONFIG += target_predeps
Leave the Qt Command Prompt window open as we use it later.
- Open the console tool of your choice in folder c:\coding\GoldenCheetah to run the build process
(I assume cmd.com with prompt ">")
-- Initialize the Visual C++ compile for 64 Bit Builds
>CALL "C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\vcvarsall.bat" amd64
-- Run "qmake" to prepare the build for Qt
>qmake build.pro -spec win32-msvc2015
-- Run "jom" to prepare and run the GoldenCheetah build
>jom qmake_all && jom
Note: When build first time you get number of error messages on .qm files missing.
"RCC: Error in 'Resources\application.qrc': Cannot find file 'translations/gc_fr.qm'"
You can ignore these messages for your build. The .qm files will be created during
the build at a later point in time via the "lrelease.exe" command you configured in
gcconfig.pri)
Hint: In some (still inpredictable cases) the build stops during compilation of the "qwt"
library. Just re-start it by running "jom" again, without any other action. Your
build will continue without problems.
- Wait - the compile with "jom" just uses 1 core. If you want to use more of your machine,
you may use "jom" with option "-j <no_of_cores>" e.g. "jom -j 4".
- Since your are doing an "in-source" build you will find a release version of "GoldenCheetah.exe"
in folder: "C:\coding\GoldenCheetah\src\release". You can run the .exe from that location as long
as the Qt libraries are on your "Path".
- To run GoldenCheetah.exe on a different machine (withoug Qt being installed), you need to collect
the Qt libraries. Easiest way is the "windeployqt" tool provided with Qt.
Details can be found here: http://doc.qt.io/qt-5/windows-deployment.html
Download GoldenCheetah source
(Either use GIT git://github.com/GoldenCheetah/GoldenCheetah.git
or download the zip file:
http://github.com/GoldenCheetah/GoldenCheetah/zipball/master)
- Install in D:\Coding\GoldenCheetah
Copy D:\Coding\GoldenCheetah\src\gccconfig.pri.in
to D:\Coding\GoldenCheetah\src\gccconfig.pri and edit
- Set: D2XX_INCLUDE = d:/coding/D2XX
- Comment out #SRMIO_INSTALL
- Comment out: CONFIG += debug
- Uncomment: CONFIG += static
Building with additional dependencies:
We use a number of libraries for specific functions of GoldenCheetah. You find the list of dependencies
and their sources documented in "gccconfig.pri.in". Here just a short summary which of those libraries
are available in the official GoldenCheetah builds and some hints how to build them to be usable.
Copy D:\Coding\GoldenCheetah\qwt\qwtconfig.pri.in
to D:\Coding\GoldenCheetah\qwt\qwtconfig.pri and edit
- Set win32 { INSTALLBASE = D:/Coding/Qt }
- In #Qt4 win32 { section
Comment out: #CONFIG += debug # release/debug/debug_and_release
Add in: CONFIG += release
Info: I plan to provide a pre-compiled set of the dependencies for the Windows version of GoldenCheetah,
so that not everybody has to invest the efforts to build the .dll's for the different tools.
- SRM download support via SRMIO
-- Is NOT part of the official Windows builds since I was not able to create a .DLL which works
with an MSVC2015 based build of GoldenCheetah. If anybody finds a solution to add this dependency
again - highly welcome.
- D2XX device download support
-- Is part of the official Windows builds - we use the libs and do static linking.
The version currently used is: "CDM v2.10.00 WHQL Certified" - while there are more recent
version available for download.
- Google Earth .kml files (export)
-- Is part of the official build as a static lib - build is done with MSVC2015 - the build uses Release 1.2
(path of source code has changed to https://github.com/google/libkml)
Using the “Qt Command Prompt” window from before:
- iCal Calendar support (prerequisite for the "Diary" view)
-- Is part of the official build as a static lib - the build uses Release 1.0.1
- USB1 support via USBExpress
-- Is part of the official build as .dll - the build uses Release 3.5.1
- USB2 support via libusb
-- Is part of the official build - the build uses the pre-compiled release 1.2.6.0
- Video Playback via VLC
-- Is part of the official build as .dll - the build uses the pre-compiled release 2.2.1
- Resampling via libsamplerate
-- Is part of the official build as .dll - the build uses
cd d:\coding\GoldenCheetah
qmake -win32 -recursive
mingw32-make release
Building with integration to external services (via APIs)
Go back to checking your email or favourite web sites while this builds.
As of today a number of integrations with external services like Strava, Cyclinganalytics,
Google Calendar, Dropbox, Today's Plan, Google Drive, CloudDB) exist in the official GoldenCheetah
builds. The permission to use API's of such services requires a dedicated registration (in this case
for "GoldenCheetah" as the consumer of the services) where in return the GoldenCheetah team get's
specific credentials to access the services.
When all is finished, you should have a release version in:
All of the services request that the access credentials are kept private and are under responsibility
of the team/company/individual who has registered for the API use with the company providing the services.
D:\Coding\GoldenCheetah\src\release\
You can always start your personal registration process with the services to get your own credentials
to build GoldenCheetah version which can use the service APIs. But you are doing that on your own full
responsibility.
*****************************************************************************************************
Have fun to build your own version. Feedback/Contributions to this guide are welcome. The easiest way
to contribute is to provide a pull-request.
Cheers.
Joern
Next , move required build files into the d:\coding\GoldenCheetah\src\release directory.
cd d:\coding\GoldenCheetah
copy /y ..\Qt\qt\bin\mingwm10.dll src\release\
copy /y ..\Qt\qt\bin\QtCore4.dll src\release\
copy /y ..\Qt\qt\bin\QtGui4.dll src\release\
copy /y ..\Qt\qt\bin\QtSql4.dll src\release\
copy /y ..\Qt\qt\bin\QtXml4.dll src\release\
copy /y ..\Qt\qt\bin\QtNetwork4.dll src\release\
copy /y ..\Qt\qt\bin\QtOpenGL4.dll src\release\
copy /y ..\Qt\qt\bin\QtWebKit4.dll src\release\
copy /y ..\Qt\qt\bin\QtXmlPatterns4.dll src\release\
copy /y ..\Qt\qt\bin\phonon4.dll src\release\
copy /y ..\Qt\qt\bin\libgcc_s_dw2-1.dll src\release\
copy /y ..\qwtplot3d\lib\qwtplot3d.dll src\release\
mkdir src\release\sqldrivers
copy /y ..\Qt\qt\plugins\sqldrivers\qsqlite4.dll src\release\sqldrivers\
mkdir src\release\imageformats
copy /y ..\Qt\qt\plugins\imageformats\qjpeg4.dll src\release\imageformats\
To build the self installer:
cd d:\coding\GoldenCheetah\src\win32
d:\coding\NSISPortable\App\NSIS\makensis.exe GoldenCheetahInstall.nsi
You should find the installer file in the directory you are in.
Install and enjoy.

View File

@@ -1 +0,0 @@
Issue tracker is **only** for Bugs and Features, before to open a new issue please read the Contributing document (link at the right) and use the forums if you need help.

View File

@@ -1,30 +1,9 @@
<img src="src/Resources/images/gc.png" height="25%" width="25%">
# GoldenCheetah
## About
GoldenCheetah is an open-source data analysis tool primarily written in C++
with Qt for cyclists and triathletes
with support for training as well.
GoldenCheetah can connect with indoor trainers and cycling equipment such
as cycling computers and power meters to import data.
In addition, GoldenCheetah can connect to cloud services.
It can then manipulate and view the data, as well as analyze it.
## Installing
Golden Cheetah install and build instructions are documented
for each platform;
INSTALL-WIN32 For building on Microsoft Windows
INSTALL-LINUX For building on Linux
INSTALL-LINUX For building on Ubuntu Linux
INSTALL-MAC For building on Apple OS X
@@ -35,6 +14,6 @@ Windows: [![Build status](https://ci.appveyor.com/api/projects/status/i6dwn4m8oy
[![Coverity Status](https://scan.coverity.com/projects/7503/badge.svg)](https://scan.coverity.com/projects/goldencheetah-goldencheetah)
Alternatively, official builds are available from http://www.goldencheetah.org
Alternatively official builds are available from http://www.goldencheetah.org
whilst the latest developer builds are available from https://github.com/GoldenCheetah/GoldenCheetah/releases
whilst latest developer builds are available from https://github.com/GoldenCheetah/GoldenCheetah/releases

View File

@@ -2,9 +2,9 @@ version: ci.{build}
image: Visual Studio 2015
clone_depth: 1
init:
# Setup QT 5.9 - 64Bit
# Setup QT 5.6.0 - 64Bit
- set QTDIR=C:\Qt\5.9\msvc2015_64
- set QTDIR=C:\Qt\5.6\msvc2015_64
- set PATH=%QTDIR%\bin;%PATH%
# Setup MSVC - VS 2015
@@ -22,7 +22,7 @@ install:
- copy c:\libs\gcconfig64-Release.appveyor.pri src\gcconfig.pri
build_script:
- qmake.exe build.pro -r -spec win32-msvc
- qmake.exe build.pro -r -spec win32-msvc2015
- nmake
#notifications:

View File

@@ -1,4 +1,7 @@
TEMPLATE = subdirs
SUBDIRS = qwt
unix:!macx {
SUBDIRS += kqoauth
}
SUBDIRS += src
CONFIG += ordered

View File

@@ -1,707 +0,0 @@
/*
* Copyright (c) 2010 Justin Knotzke (jknotzke@shampoo.ca)
* Copyright (c) 2017 Mark Liversedge (liversedge@gmail.com)
*
* 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.
*
* This program is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
* more details.
*
* You should have received a copy of the GNU General Public License along
* with this program; if not, write to the Free Software Foundation, Inc., 51
* Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
#include "Secrets.h"
#include "OAuthManager.h"
#include "OAuthDialog.h"
#include "Athlete.h"
#include "Context.h"
#include "Settings.h"
#include "Colors.h"
#include "TimeUtils.h"
#if QT_VERSION > 0x050000
#include "GoogleDrive.h"
#include "PolarFlow.h"
#include <QJsonParseError>
#endif
OAuthManager::OAuthManager(Context *context, OAuthSite site, CloudService *service, QString baseURL, QString clientsecret) :
context(context), site(site), service(service), baseURL(baseURL), clientsecret(clientsecret)
{
if (service) { // ultimately this will be the only way this works
if (service->id() == "Strava") site = this->site = STRAVA;
if (service->id() == "Dropbox") site = this->site = DROPBOX;
if (service->id() == "Cycling Analytics") site = this->site = CYCLING_ANALYTICS;
if (service->id() == "Google Drive") site = this->site = GOOGLE_DRIVE;
if (service->id() == "University of Kent") site = this->site = KENTUNI;
if (service->id() == "Today's Plan") site = this->site = TODAYSPLAN;
if (service->id() == "Withings") site = this->site = WITHINGS;
if (service->id() == "PolarFlow") site = this->site = POLAR;
if (service->id() == "SportTracks.mobi") site = this->site = SPORTTRACKS;
if (service->id() == "Xert") site = this->site = XERT;
}
// check if SSL is available - if not - message and end
if (!QSslSocket::supportsSsl()) {
QString text = QString(tr("SSL Security Libraries required for 'Authorise' are missing in this installation."));
QMessageBox sslMissing(QMessageBox::Critical, tr("Authorization Error"), text);
sslMissing.exec();
noSSLlib = true;
return;
}
// ignore responses to false, used by POLARFLOW when binding the user
ignore = false;
// SSL is available - so authorisation can take place
noSSLlib = false;
}
void
OAuthManager::authorize()
{
//
// All services have some kind of initial authorisation URL where the user needs
// to login and confirm they are willing to authorise the particular app and
// provide a temporary token to get the real token with
//
QString urlstr = "";
if (site == STRAVA) {
urlstr = QString("https://www.strava.com/oauth/authorize?");
urlstr.append("client_id=").append(GC_STRAVA_CLIENT_ID).append("&");
urlstr.append("scope=view_private,write&");
urlstr.append("redirect_uri=http://www.goldencheetah.org/&");
urlstr.append("response_type=code&");
urlstr.append("approval_prompt=force");
} else if (site == DROPBOX) {
urlstr = QString("https://www.dropbox.com/oauth2/authorize?");
#ifdef GC_DROPBOX_CLIENT_ID
urlstr.append("client_id=").append(GC_DROPBOX_CLIENT_ID).append("&");
#endif
urlstr.append("redirect_uri=https://goldencheetah.github.io/blank.html&");
urlstr.append("response_type=code&");
urlstr.append("force_reapprove=true");
} else if (site == CYCLING_ANALYTICS) {
urlstr = QString("https://www.cyclinganalytics.com/api/auth?");
urlstr.append("client_id=").append(GC_CYCLINGANALYTICS_CLIENT_ID).append("&");
urlstr.append("scope=modify_rides&");
urlstr.append("redirect_uri=http://www.goldencheetah.org/&");
urlstr.append("response_type=code&");
urlstr.append("approval_prompt=force");
#if QT_VERSION >= 0x050000
} else if (site == GOOGLE_DRIVE) {
const QString scope = service->getSetting(GC_GOOGLE_DRIVE_AUTH_SCOPE, "drive.appdata").toString();
// OAUTH 2.0 - Google flow for installed applications
urlstr = QString("https://accounts.google.com/o/oauth2/auth?");
// We only request access to the application data folder, not all files.
urlstr.append("scope=https://www.googleapis.com/auth/" + scope + "&");
urlstr.append("redirect_uri=urn:ietf:wg:oauth:2.0:oob&");
urlstr.append("response_type=code&");
urlstr.append("client_id=").append(GC_GOOGLE_DRIVE_CLIENT_ID);
} else if (site == KENTUNI) {
const QString scope = service->getSetting(GC_UOK_GOOGLE_DRIVE_AUTH_SCOPE, "drive.appdata").toString();
// OAUTH 2.0 - Google flow for installed applications
urlstr = QString("https://accounts.google.com/o/oauth2/auth?");
// We only request access to the application data folder, not all files.
urlstr.append("scope=https://www.googleapis.com/auth/" + scope + "&");
urlstr.append("redirect_uri=urn:ietf:wg:oauth:2.0:oob&");
urlstr.append("response_type=code&");
urlstr.append("client_id=").append(GC_GOOGLE_DRIVE_CLIENT_ID);
#endif
} else if (site == TODAYSPLAN) {
//urlstr = QString("https://whats.todaysplan.com.au/en/authorize/"); //XXX fixup below when pages.cpp goes
if (baseURL=="") baseURL=service->getSetting(GC_TODAYSPLAN_URL, "https://whats.todaysplan.com.au").toString();
urlstr = QString("%1/authorize/").arg(baseURL);
urlstr.append(GC_TODAYSPLAN_CLIENT_ID);
} else if (site == POLAR) {
// OAUTH 2.0 - Google flow for installed applications
urlstr = QString("%1?").arg(GC_POLARFLOW_OAUTH_URL);
// We only request access to the application data folder, not all files.
urlstr.append("response_type=code&");
urlstr.append("client_id=").append(GC_POLARFLOW_CLIENT_ID);
} else if (site == SPORTTRACKS) {
// We only request access to the application data folder, not all files.
urlstr = QString("https://api.sporttracks.mobi/oauth2/authorize?");
urlstr.append("redirect_uri=http://www.goldencheetah.org&");
urlstr.append("state=xyzzy&");
urlstr.append("response_type=code&");
urlstr.append("client_id=").append(GC_SPORTTRACKS_CLIENT_ID);
} else if (site == WITHINGS) {
// Withings is the only service that uses KQOauth for now.
#ifdef GC_HAVE_KQOAUTH
oauthRequest = new KQOAuthRequest;
oauthManager = new KQOAuthManager(this);
connect(oauthManager, SIGNAL(temporaryTokenReceived(QString,QString)), this, SLOT(onTemporaryTokenReceived(QString, QString)));
connect(oauthManager, SIGNAL(authorizationReceived(QString,QString)), this, SLOT( onAuthorizationReceived(QString, QString)));
connect(oauthManager, SIGNAL(accessTokenReceived(QString,QString)), this, SLOT(onAccessTokenReceived(QString,QString)));
connect(oauthManager, SIGNAL(requestReady(QByteArray)), this, SLOT(onRequestReady(QByteArray)));
connect(oauthManager, SIGNAL(authorizationPageRequested(QUrl)), this, SLOT(onAuthorizationPageRequested(QUrl)));
oauthRequest->initRequest(KQOAuthRequest::TemporaryCredentials, QUrl("https://oauth.withings.com/account/request_token"));
//oauthRequest->setEnableDebugOutput(true);
oauthRequest->setHttpMethod(KQOAuthRequest::GET);
oauthRequest->setConsumerKey(GC_WITHINGS_CONSUMER_KEY);
oauthRequest->setConsumerSecretKey(GC_WITHINGS_CONSUMER_SECRET);
//oauthRequest->setCallbackUrl(QUrl("http://www.goldencheetah.org"));
oauthManager->setHandleUserAuthorization(true); // false to use callback
oauthManager->setHandleAuthorizationPageOpening(false);
oauthManager->executeRequest(oauthRequest);
#endif
} else if (site == XERT) {
getTokenWithCode("");
}
//
// STEP 1: LOGIN AND AUTHORISE THE APPLICATION
//
/*if (site == DROPBOX || site == STRAVA || site == CYCLING_ANALYTICS || site == POLAR || site == SPORTTRACKS || site == GOOGLE_DRIVE || site == KENTUNI || site == TODAYSPLAN) {
url = QUrl(urlstr);
view->setUrl(url);
// connects
connect(view, SIGNAL(urlChanged(const QUrl&)), this, SLOT(urlChanged(const QUrl&)));
connect(view, SIGNAL(loadFinished(bool)), this, SLOT(loadFinished(bool)));
}*/
}
// just ignore SSL handshake errors at all times
void
OAuthManager::onSslErrors(QNetworkReply *reply, const QList<QSslError>&)
{
reply->ignoreSslErrors();
}
#ifdef GC_HAVE_KQOAUTH
//
// KQOauth call backs
//
void
OAuthManager::onTemporaryTokenReceived(QString, QString)
{
//qDebug() << "onTemporaryTokenReceived";
QUrl userAuthURL;
if (site == WITHINGS) {
userAuthURL = "https://oauth.withings.com/account/authorize";
}
if(oauthManager->lastError() == KQOAuthManager::NoError) {
oauthManager->getUserAuthorization(userAuthURL);
} else
qDebug() << "error" << oauthManager->lastError();
}
void
OAuthManager::onAuthorizationReceived(QString, QString)
{
//qDebug() << "Authorization token received: " << token << verifier;
if (site == WITHINGS) {
oauthManager->getUserAccessTokens(QUrl("https://oauth.withings.com/account/access_token"));
}
if(oauthManager->lastError() != KQOAuthManager::NoError) {
QString error = QString(tr("Error fetching OAuth credentials - Endpoint: /oauth/access_token"));
QMessageBox oautherr(QMessageBox::Critical, tr("Authorization Error"), error);
oautherr.exec();
//accept();
}
}
void
OAuthManager::onAccessTokenReceived(QString token, QString tokenSecret)
{
//qDebug() << "Access token received: " << token << tokenSecret;
QString info;
if (site == WITHINGS) {
service->setSetting(GC_WITHINGS_TOKEN, token);
service->setSetting(GC_WITHINGS_SECRET, tokenSecret);
appsettings->setCValue(context->athlete->cyclist, GC_NOKIA_REFRESH_TOKEN, "");
info = QString(tr("Nokia Health (Withings) authorization was successful."));
}
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
//accept();
}
void
OAuthManager::onAuthorizedRequestDone() {} // request sent - do nothing
void
OAuthManager::onRequestReady(QByteArray response)
{
//qDebug() << "Response received: " << response;
QString r = response;
if (r.contains("\"errors\"", Qt::CaseInsensitive)) {
QMessageBox oautherr(QMessageBox::Critical, tr("Error in authorization"),
tr("There was an error during authorization. Please check the error description."));
oautherr.setDetailedText(r); // probably blank
oautherr.exec();
} else {
if (site == WITHINGS) {
QString userid;
#if QT_VERSION > 0x050000
QUrlQuery params;
params.setQuery(response);
#else
QUrl params;
params.setEncodedQuery(response);
#endif
userid = params.queryItemValue("userid");
if (userid.isEmpty() == false) {
service->setSetting(GC_WIUSER, userid);
}
}
}
}
void OAuthManager::onAuthorizationPageRequested(QUrl url) {
// open Authorization page in view
view->setUrl(url);
}
#endif // KQOAuth callbacks used by Withings only
//
// STEP 2: AUTHORISATION REDIRECT WITH TEMPORARY CODE
//
// When the URL changes, it will be the redirect with the temporary token after
// the initial authorisation. The URL will have some parameters to indicate this
// if they exist we should intercept the redirect to get the permanent token.
// If they don't get passed then we don't need to do anything.
//
void
OAuthManager::getTokenWithCode(QString code)
{
QString authheader;
// sites that use this scheme
if (site == DROPBOX || site == STRAVA || site == CYCLING_ANALYTICS || site == TODAYSPLAN || site == POLAR || site == SPORTTRACKS || site == XERT) {
// sporttracks insists on passing state
if (code.endsWith("&state=xyzzy")) code = code.mid(0,code.length()-12);
QByteArray data;
#if QT_VERSION > 0x050000
QUrlQuery params;
#else
QUrl params;
#endif
QString urlstr = "";
// now get the final token to store
if (site == DROPBOX) {
urlstr = QString("https://api.dropboxapi.com/oauth2/token?");
urlstr.append("redirect_uri=https://goldencheetah.github.io/blank.html&");
params.addQueryItem("grant_type", "authorization_code");
#ifdef GC_DROPBOX_CLIENT_ID
params.addQueryItem("client_id", GC_DROPBOX_CLIENT_ID);
#endif
#ifdef GC_DROPBOX_CLIENT_SECRET
params.addQueryItem("client_secret", GC_DROPBOX_CLIENT_SECRET);
#endif
} else if (site == POLAR) {
urlstr = QString("%1?").arg(GC_POLARFLOW_TOKEN_URL);
urlstr.append("redirect_uri=http://www.goldencheetah.org");
params.addQueryItem("grant_type", "authorization_code");
#if (defined GC_POLARFLOW_CLIENT_ID) && (defined GC_POLARFLOW_CLIENT_SECRET)
authheader = QString("%1:%2").arg(GC_POLARFLOW_CLIENT_ID).arg(GC_POLARFLOW_CLIENT_SECRET);
#endif
} else if (site == SPORTTRACKS) {
urlstr = QString("https://api.sporttracks.mobi/oauth2/token?");
params.addQueryItem("client_id", GC_SPORTTRACKS_CLIENT_ID);
params.addQueryItem("client_secret", GC_SPORTTRACKS_CLIENT_SECRET);
params.addQueryItem("redirect_uri","http://www.goldencheetah.org");
params.addQueryItem("grant_type", "authorization_code");
} else if (site == STRAVA) {
urlstr = QString("https://www.strava.com/oauth/token?");
params.addQueryItem("client_id", GC_STRAVA_CLIENT_ID);
#ifdef GC_STRAVA_CLIENT_SECRET
params.addQueryItem("client_secret", GC_STRAVA_CLIENT_SECRET);
#endif
} else if (site == CYCLING_ANALYTICS) {
urlstr = QString("https://www.cyclinganalytics.com/api/token?");
params.addQueryItem("client_id", GC_CYCLINGANALYTICS_CLIENT_ID);
#ifdef GC_CYCLINGANALYTICS_CLIENT_SECRET
params.addQueryItem("client_secret", GC_CYCLINGANALYTICS_CLIENT_SECRET);
#endif
params.addQueryItem("grant_type", "authorization_code");
} else if (site == TODAYSPLAN) {
if (baseURL=="") baseURL=service->getSetting(GC_TODAYSPLAN_URL, "https://whats.todaysplan.com.au").toString();
urlstr = QString("%1/rest/oauth/access_token?").arg(baseURL);
params.addQueryItem("client_id", GC_TODAYSPLAN_CLIENT_ID);
#ifdef GC_TODAYSPLAN_CLIENT_SECRET
if (clientsecret != "") //XXX get rid when pages.cpp goes
params.addQueryItem("client_secret", clientsecret);
else if (service->getSetting(GC_TODAYSPLAN_USERKEY, "").toString() != "")
params.addQueryItem("client_secret", service->getSetting(GC_TODAYSPLAN_USERKEY, "").toString());
else
params.addQueryItem("client_secret", GC_TODAYSPLAN_CLIENT_SECRET);
#endif
params.addQueryItem("grant_type", "authorization_code");
params.addQueryItem("redirect_uri", "https://goldencheetah.github.io/blank.html");
} else if (site == XERT) {
urlstr = QString("https://www.xertonline.com/oauth/token");
params.addQueryItem("username", service->getSetting(GC_XERTUSER, "").toString());
params.addQueryItem("password", service->getSetting(GC_XERTPASS, "").toString());
params.addQueryItem("grant_type", "password");
authheader = QString("%1:%1").arg("xert_public");
}
// all services will need us to send the temporary code received
params.addQueryItem("code", code);
#if QT_VERSION > 0x050000
data.append(params.query(QUrl::FullyEncoded));
#else
data=params.encodedQuery();
#endif
// trade-in the temporary access code retrieved by the Call-Back URL for the finale token
QUrl url = QUrl(urlstr);
QNetworkRequest request = QNetworkRequest(url);
request.setHeader(QNetworkRequest::ContentTypeHeader,"application/x-www-form-urlencoded");
// client id and secret are encoded and sent in the header for POLAR and XERT
if (site == POLAR || site == XERT) request.setRawHeader("Authorization", "Basic " + authheader.toLatin1().toBase64());
// now get the final token - but ignore errors
manager = new QNetworkAccessManager(this);
connect(manager, SIGNAL(sslErrors(QNetworkReply*, const QList<QSslError> & )), this, SLOT(onSslErrors(QNetworkReply*, const QList<QSslError> & )));
//connect(manager, SIGNAL(finished(QNetworkReply*)), this, SLOT(networkRequestFinished(QNetworkReply*)));
QNetworkReply *reply = manager->post(request, data);
QEventLoop loop;
connect(reply, SIGNAL(finished()), &loop, SLOT(quit()));
loop.exec();
networkRequestFinished(reply);
}
}
//
// GOOGLE DRIVE gets the code in the HTML title field (different to other services)
//
void
OAuthManager::loadFinished(bool ok)
{
if (site == GOOGLE_DRIVE || site == KENTUNI) {
if (ok && url.toString().startsWith("https://accounts.google.com/o/oauth2/auth")) {
// retrieve the code from the HTML page title
QString title = view->title();
if (title.contains("code")) {
QString code = title.right(title.length()-title.indexOf("code=")-5);
QByteArray data;
#if QT_VERSION > 0x050000
QUrlQuery params;
#else
QUrl params;
#endif
QString urlstr = "https://www.googleapis.com/oauth2/v3/token?";
params.addQueryItem("client_id", GC_GOOGLE_DRIVE_CLIENT_ID);
if (site == GOOGLE_DRIVE || site == KENTUNI) {
params.addQueryItem("client_secret", GC_GOOGLE_DRIVE_CLIENT_SECRET);
}
params.addQueryItem("code", code);
params.addQueryItem("redirect_uri", "urn:ietf:wg:oauth:2.0:oob");
params.addQueryItem("grant_type", "authorization_code");
#if QT_VERSION > 0x050000
data.append(params.query(QUrl::FullyEncoded));
#else
data=params.encodedQuery();
#endif
// trade-in the temporary access code retrieved by the
// Call-Back URL for the finale token
QUrl url = QUrl(urlstr);
QNetworkRequest request = QNetworkRequest(url);
request.setHeader(QNetworkRequest::ContentTypeHeader, "application/x-www-form-urlencoded");
// not get the final token - ignoring errors
manager = new QNetworkAccessManager(this);
connect(manager, SIGNAL(sslErrors(QNetworkReply*, const QList<QSslError> & )), this, SLOT(onSslErrors(QNetworkReply*, const QList<QSslError> & )));
connect(manager, SIGNAL(finished(QNetworkReply*)), this, SLOT(networkRequestFinished(QNetworkReply*)));
manager->post(request, data);
}
}
}
}
#if QT_VERSION < 0x050000
static QString RawJsonStringGrab(const QByteArray& payload,
const QString& needle) {
// A RegExp based JSON string parser. Not the best, but it does the job.
QString regex =
// This matches the key.
"(" + needle + "|\"" + needle + "\"|'" + needle + "')"
// Matches the separator.
"[\\s]*:[\\s]*"
// matches the value.
"(\"\\S+\"|'\\S+')";
QRegExp q(regex);
if (!q.isValid()) {
// Somehow failed to build the regex.
return "";
}
int start = q.indexIn(payload);
int pos = q.pos(2);
if (start == -1 || pos == -1) {
// Failed to find the key or the value.
return "";
}
QString ret = payload.mid(pos, q.matchedLength() + start - pos);
// Remove " or ' from the value.
ret.remove(0, 1);
ret.remove(ret.size() - 1, 1);
return ret;
}
#endif
//
// STEP 3: REFRESH AND ACCESS TOKEN RECEIVED
//
// this is when we get the refresh or access tokens after a redirect has been loaded
// so pretty much at the end of the process. Each service can have slightly special
// needs and certainly needs to set the right setting anyway.
//
void
OAuthManager::networkRequestFinished(QNetworkReply *reply)
{
// we've been told to ignore responses (used by POLAR, maybe others in future)
if (ignore) return;
// we can handle SSL handshake errors, if we got here then some kind of protocol was agreed
if (reply->error() == QNetworkReply::NoError || reply->error() == QNetworkReply::SslHandshakeFailedError) {
QByteArray payload = reply->readAll(); // JSON
QString refresh_token;
QString access_token;
double polar_userid=0;
// parse the response and extract the tokens, pretty much the same for all services
// although polar choose to also pass a user id, which is needed for future calls
#if QT_VERSION > 0x050000
QJsonParseError parseError;
QJsonDocument document = QJsonDocument::fromJson(payload, &parseError);
if (parseError.error == QJsonParseError::NoError) {
refresh_token = document.object()["refresh_token"].toString();
access_token = document.object()["access_token"].toString();
if (site == POLAR) polar_userid = document.object()["x_user_id"].toDouble();
}
#else
refresh_token = RawJsonStringGrab(payload, "refresh_token");
access_token = RawJsonStringGrab(payload, "access_token");
#endif
// if we failed to extract then we have a big problem
// google uses a refresh token so trap for them only
if (((site == GOOGLE_DRIVE || site == KENTUNI) && refresh_token == "") || access_token == "") {
// Something failed.
// Only Google uses both refresh and access tokens.
QString error = QString(tr("Error retrieving authoriation credentials"));
QMessageBox oautherr(QMessageBox::Critical, tr("Authorization Error"), error);
oautherr.setDetailedText(error);
oautherr.exec();
return;
}
// now set the tokens etc
if (site == DROPBOX) {
service->setSetting(GC_DROPBOX_TOKEN, access_token);
QString info = QString(tr("Dropbox authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == SPORTTRACKS) {
service->setSetting(GC_SPORTTRACKS_TOKEN, access_token);
service->setSetting(GC_SPORTTRACKS_REFRESH_TOKEN, refresh_token);
service->setSetting(GC_SPORTTRACKS_LAST_REFRESH, QDateTime::currentDateTime());
QString info = QString(tr("SportTracks authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == POLAR) {
service->setSetting(GC_POLARFLOW_TOKEN, access_token);
service->setSetting(GC_POLARFLOW_USER_ID, polar_userid);
// we now need to bind the user, this is a one time deal.
QString url = QString("%1/v3/users").arg(GC_POLARFLOW_URL);
// request using the bearer token
QNetworkRequest request(url);
request.setRawHeader("Authorization", (QString("Bearer %1").arg(access_token)).toLatin1());
request.setRawHeader("Accept", "application/json");
request.setRawHeader("Content-Type", "application/json");
// data to post
QByteArray data;
data.append(QString("{\"member-id\":\"%1\"}").arg(context->athlete->cyclist));
// the request will fallback to this method on networkRequestFinished
// but we are done, so set ignore= true to get this function to just
// return without doing anything
ignore=true;
QNetworkReply *bind = manager->post(request, data);
// blocking request
QEventLoop loop;
connect(bind, SIGNAL(finished()), &loop, SLOT(quit()));
loop.exec();
// Bind response lists athlete details, we ignore them for now
QByteArray r = bind->readAll();
//qDebug()<<bind->errorString()<< "bind response="<<r;
QString info = QString(tr("PolarFlow authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == STRAVA) {
service->setSetting(GC_STRAVA_TOKEN, access_token);
QString info = QString(tr("Strava authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == CYCLING_ANALYTICS) {
service->setSetting(GC_CYCLINGANALYTICS_TOKEN, access_token);
QString info = QString(tr("Cycling Analytics authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == KENTUNI) {
service->setSetting(GC_UOK_GOOGLE_DRIVE_REFRESH_TOKEN, refresh_token);
service->setSetting(GC_UOK_GOOGLE_DRIVE_ACCESS_TOKEN, access_token);
service->setSetting(GC_UOK_GOOGLE_DRIVE_LAST_ACCESS_TOKEN_REFRESH, QDateTime::currentDateTime());
QString info = QString(tr("Kent University Google Drive authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == GOOGLE_DRIVE) {
service->setSetting(GC_GOOGLE_DRIVE_REFRESH_TOKEN, refresh_token);
service->setSetting(GC_GOOGLE_DRIVE_ACCESS_TOKEN, access_token);
service->setSetting(GC_GOOGLE_DRIVE_LAST_ACCESS_TOKEN_REFRESH, QDateTime::currentDateTime());
QString info = QString(tr("Google Drive authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == TODAYSPLAN) {
service->setSetting(GC_TODAYSPLAN_TOKEN, access_token);
QString info = QString(tr("Today's Plan authorization was successful."));
QMessageBox information(QMessageBox::Information, tr("Information"), info);
information.exec();
} else if (site == XERT) {
service->setSetting(GC_XERT_TOKEN, access_token);
service->setSetting(GC_XERT_REFRESH_TOKEN, refresh_token);
// Try without Message Box
//QString info = QString(tr("Xert authorization was successful."));
//QMessageBox information(QMessageBox::Information, tr("Information"), info);
//information.exec();
service->message = "Xert authorization was successful.";
}
} else {
// general error getting response
QString error = QString(tr("Error retrieving access token, %1 (%2)")).arg(reply->errorString()).arg(reply->error());
QMessageBox oautherr(QMessageBox::Critical, tr("SSL Token Refresh Error"), error);
oautherr.setDetailedText(error);
oautherr.exec();
}
// job done, dialog can be closed
//accept();
}

View File

@@ -1,128 +0,0 @@
/*
* Copyright (c) 2009 Justin F. Knotzke (jknotzke@shampoo.ca)
*
* 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.
*
* This program is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
* more details.
*
* You should have received a copy of the GNU General Public License along
* with this program; if not, write to the Free Software Foundation, Inc., 51
* Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
#ifndef OAUTHMANAGER_H
#define OAUTHMANAGER_H
#include "GoldenCheetah.h"
#include "Pages.h"
#include "CloudService.h"
#ifdef GC_HAVE_KQOAUTH
#include <kqoauthmanager.h>
#endif
#include <QObject>
#include <QtGui>
#include <QWidget>
#include <QStackedLayout>
#include <QUrl>
#include <QSslSocket>
#ifndef NOWEBKIT
#include <QtWebKit>
#include <QWebView>
#include <QWebFrame>
#endif
// QUrl split into QUrlQuerty in QT5
#if QT_VERSION > 0x050000
#include <QUrlQuery>
#endif
// QWebEngine if on Mac, -or- we don't have webkit
#if defined(NOWEBKIT) || ((QT_VERSION > 0x050000) && defined(Q_OS_MAC))
#include <QWebEngineHistory>
#include <QWebEngineHistoryItem>
#include <QWebEnginePage>
#include <QWebEngineView>
#include <QWebEngineProfile>
#if (QT_VERSION >= 0x050600)
#include <QWebEngineCookieStore>
#endif
#endif
class OAuthManager : QObject
{
Q_OBJECT
G_OBJECT
public:
typedef enum {
NONE=0,
STRAVA,
DROPBOX,
CYCLING_ANALYTICS,
GOOGLE_DRIVE,
SPORTTRACKS,
TODAYSPLAN,
WITHINGS,
POLAR,
KENTUNI,
XERT
} OAuthSite;
// will work with old config via site and new via cloudservice (which is null for calendar and withings for now)
OAuthManager(Context *context, OAuthSite site, CloudService *service, QString baseURL="", QString clientsecret="");
void authorize();
void getTokenWithCode(QString code);
bool sslLibMissing() { return noSSLlib; }
private slots:
// Strava/Cyclinganalytics/Google
void loadFinished(bool ok);
void networkRequestFinished(QNetworkReply *reply);
void onSslErrors(QNetworkReply *reply, const QList<QSslError>&error);
#ifdef GC_HAVE_KQOAUTH
void onTemporaryTokenReceived(QString, QString);
void onAuthorizationReceived(QString, QString);
void onAccessTokenReceived(QString token, QString tokenSecret);
void onAuthorizedRequestDone();
void onRequestReady(QByteArray response);
void onAuthorizationPageRequested (QUrl pageUrl);
#endif
private:
Context *context;
bool noSSLlib;
bool ignore;
OAuthSite site;
CloudService *service;
QString baseURL; // can be passed, but typically is blank (used by Todays Plan)
QString clientsecret; // can be passed, but typicall is blank (used by Todays Plan)
QVBoxLayout *layout;
// QUrl split into QUrlQuerty in QT5
#if defined(NOWEBKIT) || ((QT_VERSION > 0x050000) && defined(Q_OS_MAC))
QWebEngineView *view;
#else
QWebView *view;
#endif
QNetworkAccessManager* manager;
QUrl url;
#ifdef GC_HAVE_KQOAUTH
KQOAuthManager *oauthManager;
KQOAuthRequest *oauthRequest;
#endif
};
#endif // OAUTHMANAGER_H

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@@ -1,4 +0,0 @@
date,weightkg,fatkg,boneskg,musclekg,leankg,fatpercent,comment
2017-01-01T12:00:00Z,2,3,4,5,6,7,Useless data - but valid format
2017-01-02T12:00:00Z,80.15,12.10,5.4,0,32.5,11.57,Test Value
2017-01-03T12:00:00Z,81.15,12.10,5.4,0,32.5,12.57,"Here the comment text contain commas itself, so it needs quotes"
1 date weightkg fatkg boneskg musclekg leankg fatpercent comment
2 2017-01-01T12:00:00Z 2 3 4 5 6 7 Useless data - but valid format
3 2017-01-02T12:00:00Z 80.15 12.10 5.4 0 32.5 11.57 Test Value
4 2017-01-03T12:00:00Z 81.15 12.10 5.4 0 32.5 12.57 Here the comment text contain commas itself, so it needs quotes

View File

@@ -1,4 +0,0 @@
ts,weightkg,fatkg,boneskg,musclekg,leankg,fatpercent,comment
1,2,3,4,5,6,7,Is a technically valid entry but the timestamp is 1 second of Epoch so it will never be in the possible time range
1479632565,80.15,12.10,5.4,0,32.5,11.57,Test Value
1479632865,81.15,12.10,5.4,0,32.5,12.57,"Here the comment text contain commas itself, so it needs quotes"
1 ts weightkg fatkg boneskg musclekg leankg fatpercent comment
2 1 2 3 4 5 6 7 Is a technically valid entry but the timestamp is 1 second of Epoch so it will never be in the possible time range
3 1479632565 80.15 12.10 5.4 0 32.5 11.57 Test Value
4 1479632865 81.15 12.10 5.4 0 32.5 12.57 Here the comment text contain commas itself, so it needs quotes

View File

@@ -1,59 +0,0 @@
Description of File-Format for "Body Measures - .CSV Import" function
---------------------------------------------------------------------
Example for Timestamp is provided here:
----
ts,weightkg,fatkg,boneskg,musclekg,leankg,fatpercent,comment
1,2,3,4,5,6,7,Is a technically valid entry, but the timestamp is 1 second of Epoch
1479632565,80.15,12.10,5.4,0,32.5,1157,Test Value
1479632865,80.15,12.10,5.4,0,32.5,1157,"Here the comment text contain commas itself, so it needs quotes"
----
Example for Date/Time is provided here:
date,weightkg,fatkg,boneskg,musclekg,leankg,fatpercent,comment
2017-01-01T12:00:00Z,2,3,4,5,6,7,Useless data - but valid format
2017-01-02T12:00:00Z,80.15,12.10,5.4,0,32.5,1157,Test Value
2017-01-02T12:00:00Z,80.15,12.10,5.4,0,32.5,1157,"Here the comment text contain commas itself, so it needs quotes"
a) Header Line
First Line of a valid file has to contain header information. This has to be a comma-separated
list of the measures provided in the data lines. You do not need to provide all possible measures,
but at least "ts" and "weightkg".
As mandatory field you need time/date of the measures. There are 2 options:
- "ts" - Unix timestamp (in seconds) since Epoch. The value can be calcuated in XLS - just Google how-to.
OR
- "date" - ISO8601 formatted Date/Time String
The mandatory measure is:
- "weightkg" - Athlete weight in kilograms
The optional measures are:
- "fatkg" - Fat mass in kg
- "boneskg" - Bone mass in kg
- "musclekg" - Muscle mass in kg
- "leankg" - Lean mass in kg
- "fatpercent" - Fat percentage
- "comment" - A description of the measures
Data formats:
- "ts" is a 64Bit Integer - any other time will be rejected
- "date" is a ISO8601 formated date/time
- "comment" is a String - if it contains "commas" itself the string must be enclosed by "string with comma, and more comment"
- all other measures are float/double in format <xxxxxxx.yyy>
There are very strict format checks when importing. Only if the whole
file is correct the data is imported. Any error (even in a single entry)
will block the complete import.
The following error will stop the import.
- Unknown measures in header
- Number of measures in header is different to number in an item
- Item measure in wrong format
- "ts" or "weightkg" is missing

View File

@@ -23,10 +23,6 @@ isinf(p1)
isnan(p1)
LIST / VECTOR REDUCE FUNCTIONS
Vectors are about collecting data from across a date range, specified as
expression[[Date_From:Date_To]]
where dates can be absolute s.t. 2017/09/19 or relative s.t. Date-7
you can use them within a formula using the following functions:
sum(...)
mean(...)
max(...)
@@ -81,9 +77,6 @@ DATA PROCESSOR FUNCTIONS
autoprocess(filter)
postprocess(processor, filter)
DAILY MEASURES ACCESS
measure(date, "group", "field")
RIDE SAMPLE DATA
SECS

View File

@@ -1,47 +0,0 @@
Description of File-Format for "HRV Measures - .CSV Import" function
---------------------------------------------------------------------
Example file:
timestamp_measurement,HR,AVNN,SDNN,rMSSD,pNN50,LF,HF,HRV4T_Recovery_Points
2017-04-01 09:56:21 +0000,43.92,1364.75,84.05,67.54,40.48,0.0418,0.0339,8.37
2017-04-02 09:27:24 +0000,43.42,1348,59.46,56.38,32.56,0.0655,0.0331,8.09
2017-04-03 07:37:03 +0000,41.38,1502.73,76.92,72.04,60.53,0.0476,0.0516,8.47
this was generated by HRV4Training App with unsupported columns and empty lines removed using a spreasheet.
a) Header Line
First Line of a valid file has to contain header information. This has to be a comma-separated
list of the measures provided in the data lines. You do not need to provide all possible measures,
but at least "timestamp_measure" and "rMSSD".
As mandatory field you need time/date of the measures:
- "timestamp_measure" - ISO8601 formatted Date/Time String
The mandatory measure is:
- "rMSSD" - Square root of the mean of the squares of differences between adjacent NN intervals
The optional measures are:
- "HR" - Average HR
- "AVNN" - Average of all NN interval
- "SDNN" - Standard deviation of all NN intervals
- "pNN50" - Percentage of differences between adjacent NN intervals that are greater than 50 ms
- "LF" - Power at Low Frequencies
- "HF" - Power at High Frequencies
- "HRV4T_Recovery_Points" - A log transform of rMSSD
Data formats:
- "date" is a ISO8601 formated date/time
- all other measures are float/double in format <xxxxxxx.yyy>
There are very strict format checks when importing. Only if the whole
file is correct the data is imported. Any error (even in a single entry)
will block the complete import.
The following error will stop the import.
- Unknown measures in header
- Number of measures in header is different to number in an item
- Item measure in wrong format
- "timestamp_measure" or "rMSSD" is missing

View File

@@ -31,8 +31,3 @@ http://localhost:12021 Default base URL
before=yyyy/mm/dd
series=xxx where xxx is one of watts,hr,cad,speed,nm,vam.xPower,NP
Returns an aggregate of the best mean maximal values over the date range
/<athlete>/measures List supported measures groups (Body/Hrv for now)
/<athlete>/measures/<group> Fetch Measures from <group> for a Date Range
since=yyyy/mm/dd
before=yyyy/mm/dd

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@@ -228,7 +228,6 @@ void KQOAuthManager::executeRequest(KQOAuthRequest *request) {
urlWithParams.setQuery(query);
#endif
networkRequest.setUrl(urlWithParams);
qDebug() << "urlWithParams:" << urlWithParams;
// Submit the request including the params.
QNetworkReply *reply = d->networkManager->get(networkRequest);

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@@ -1,75 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Solution of linear systems involved in the Levenberg - Marquardt
// minimization algorithm
// Copyright (C) 2004 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/********************************************************************************
* LAPACK-based implementations for various linear system solvers. The same core
* code is used with appropriate #defines to derive single and double precision
* solver versions, see also Axb_core.c
********************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include "levmar.h"
#include "misc.h"
#if !defined(LM_DBL_PREC) && !defined(LM_SNGL_PREC)
#error At least one of LM_DBL_PREC, LM_SNGL_PREC should be defined!
#endif
#ifdef LM_DBL_PREC
/* double precision definitions */
#define LM_REAL double
#define LM_PREFIX d
#define LM_CNST(x) (x)
#ifndef HAVE_LAPACK
#include <float.h>
#define LM_REAL_EPSILON DBL_EPSILON
#endif
#include "Axb_core.c"
#undef LM_REAL
#undef LM_PREFIX
#undef LM_CNST
#undef LM_REAL_EPSILON
#endif /* LM_DBL_PREC */
#ifdef LM_SNGL_PREC
/* single precision (float) definitions */
#define LM_REAL float
#define LM_PREFIX s
#define __SUBCNST(x) x##F
#define LM_CNST(x) __SUBCNST(x) // force substitution
#ifndef HAVE_LAPACK
#define LM_REAL_EPSILON FLT_EPSILON
#endif
#include "Axb_core.c"
#undef LM_REAL
#undef LM_PREFIX
#undef __SUBCNST
#undef LM_CNST
#undef LM_REAL_EPSILON
#endif /* LM_SNGL_PREC */

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@@ -1,49 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
#ifndef _COMPILER_H_
#define _COMPILER_H_
/* note: intel's icc defines both __ICC & __INTEL_COMPILER.
* Also, some compilers other than gcc define __GNUC__,
* therefore gcc should be checked last
*/
#ifdef _MSC_VER
#define inline __inline // MSVC
#elif !defined(__ICC) && !defined(__INTEL_COMPILER) && !defined(__GNUC__)
#define inline // other than MSVC, ICC, GCC: define empty
#endif
#ifdef _MSC_VER
#define LM_FINITE _finite // MSVC
#elif defined(__ICC) || defined(__INTEL_COMPILER) || defined(__GNUC__)
#define LM_FINITE finite // ICC, GCC
#else
#define LM_FINITE finite // other than MSVC, ICC, GCC, let's hope this will work
#endif
#ifdef _MSC_VER
#define LM_ISINF(x) (!_finite(x) && !_isnan(x)) // MSVC
#elif defined(__ICC) || defined(__INTEL_COMPILER) || defined(__GNUC__)
#define LM_ISINF(x) isinf(x) // ICC, GCC
#else
#define LM_ISINF(x) isinf(x) // other than MSVC, ICC, GCC, let's hope this will work
#endif
#endif /* _COMPILER_H_ */

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@@ -1,398 +0,0 @@
/*
////////////////////////////////////////////////////////////////////////////////////
//
// Prototypes and definitions for the Levenberg - Marquardt minimization algorithm
// Copyright (C) 2004 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
////////////////////////////////////////////////////////////////////////////////////
*/
#ifndef _LEVMAR_H_
#define _LEVMAR_H_
/************************************* Start of configuration options *************************************/
/* Note that when compiling with CMake, this configuration section is automatically generated
* based on the user's input, see levmar.h.in
*/
/* specifies whether to use LAPACK or not. Using LAPACK is strongly recommended */
//#define HAVE_LAPACK
/* specifies whether the PLASMA parallel library for multicore CPUs is available */
/* #undef HAVE_PLASMA */
/* to avoid the overhead of repeated mallocs(), routines in Axb.c can be instructed to
* retain working memory between calls. Such a choice, however, renders these routines
* non-reentrant and is not safe in a shared memory multiprocessing environment.
* Bellow, an attempt is made to issue a warning if this option is turned on and OpenMP
* is being used (note that this will work only if omp.h is included before levmar.h)
*/
#define LINSOLVERS_RETAIN_MEMORY
#if (defined(_OPENMP))
# ifdef LINSOLVERS_RETAIN_MEMORY
# ifdef _MSC_VER
# pragma message("LINSOLVERS_RETAIN_MEMORY is not safe in a multithreaded environment and should be turned off!")
# else
# warning LINSOLVERS_RETAIN_MEMORY is not safe in a multithreaded environment and should be turned off!
# endif /* _MSC_VER */
# endif /* LINSOLVERS_RETAIN_MEMORY */
#endif /* _OPENMP */
/* specifies whether double precision routines will be compiled or not */
#define LM_DBL_PREC
/* specifies whether single precision routines will be compiled or not */
#define LM_SNGL_PREC
/****************** End of configuration options, no changes necessary beyond this point ******************/
#ifdef __cplusplus
extern "C" {
#endif
/* work arrays size for ?levmar_der and ?levmar_dif functions.
* should be multiplied by sizeof(double) or sizeof(float) to be converted to bytes
*/
#define LM_DER_WORKSZ(npar, nmeas) (2*(nmeas) + 4*(npar) + (nmeas)*(npar) + (npar)*(npar))
#define LM_DIF_WORKSZ(npar, nmeas) (4*(nmeas) + 4*(npar) + (nmeas)*(npar) + (npar)*(npar))
/* work arrays size for ?levmar_bc_der and ?levmar_bc_dif functions.
* should be multiplied by sizeof(double) or sizeof(float) to be converted to bytes
*/
#define LM_BC_DER_WORKSZ(npar, nmeas) (2*(nmeas) + 4*(npar) + (nmeas)*(npar) + (npar)*(npar))
#define LM_BC_DIF_WORKSZ(npar, nmeas) LM_BC_DER_WORKSZ((npar), (nmeas)) /* LEVMAR_BC_DIF currently implemented using LEVMAR_BC_DER()! */
/* work arrays size for ?levmar_lec_der and ?levmar_lec_dif functions.
* should be multiplied by sizeof(double) or sizeof(float) to be converted to bytes
*/
#define LM_LEC_DER_WORKSZ(npar, nmeas, nconstr) LM_DER_WORKSZ((npar)-(nconstr), (nmeas))
#define LM_LEC_DIF_WORKSZ(npar, nmeas, nconstr) LM_DIF_WORKSZ((npar)-(nconstr), (nmeas))
/* work arrays size for ?levmar_blec_der and ?levmar_blec_dif functions.
* should be multiplied by sizeof(double) or sizeof(float) to be converted to bytes
*/
#define LM_BLEC_DER_WORKSZ(npar, nmeas, nconstr) LM_LEC_DER_WORKSZ((npar), (nmeas)+(npar), (nconstr))
#define LM_BLEC_DIF_WORKSZ(npar, nmeas, nconstr) LM_LEC_DIF_WORKSZ((npar), (nmeas)+(npar), (nconstr))
/* work arrays size for ?levmar_bleic_der and ?levmar_bleic_dif functions.
* should be multiplied by sizeof(double) or sizeof(float) to be converted to bytes
*/
#define LM_BLEIC_DER_WORKSZ(npar, nmeas, nconstr1, nconstr2) LM_BLEC_DER_WORKSZ((npar)+(nconstr2), (nmeas)+(nconstr2), (nconstr1)+(nconstr2))
#define LM_BLEIC_DIF_WORKSZ(npar, nmeas, nconstr1, nconstr2) LM_BLEC_DIF_WORKSZ((npar)+(nconstr2), (nmeas)+(nconstr2), (nconstr1)+(nconstr2))
#define LM_OPTS_SZ 5 /* max(4, 5) */
#define LM_INFO_SZ 10
#define LM_ERROR -1
#define LM_INIT_MU 1E-03
#define LM_STOP_THRESH 1E-17
#define LM_DIFF_DELTA 1E-06
#define LM_VERSION "2.6 (November 2011)"
#ifdef LM_DBL_PREC
/* double precision LM, with & without Jacobian */
/* unconstrained minimization */
extern int dlevmar_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, int itmax, double *opts,
double *info, double *work, double *covar, void *adata);
extern int dlevmar_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, int itmax, double *opts,
double *info, double *work, double *covar, void *adata);
/* box-constrained minimization */
extern int dlevmar_bc_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub, double *dscl,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
extern int dlevmar_bc_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub, double *dscl,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
#ifdef HAVE_LAPACK
/* linear equation constrained minimization */
extern int dlevmar_lec_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, double *A, double *b, int k,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
extern int dlevmar_lec_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, double *A, double *b, int k,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
/* box & linear equation constrained minimization */
extern int dlevmar_blec_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub, double *A, double *b, int k, double *wghts,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
extern int dlevmar_blec_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub, double *A, double *b, int k, double *wghts,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
/* box, linear equations & inequalities constrained minimization */
extern int dlevmar_bleic_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub,
double *A, double *b, int k1, double *C, double *d, int k2,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
extern int dlevmar_bleic_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub,
double *A, double *b, int k1, double *C, double *d, int k2,
int itmax, double *opts, double *info, double *work, double *covar, void *adata);
/* box & linear inequality constraints */
extern int dlevmar_blic_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub, double *C, double *d, int k2,
int itmax, double opts[4], double info[LM_INFO_SZ], double *work, double *covar, void *adata);
extern int dlevmar_blic_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, double *lb, double *ub, double *C, double *d, int k2,
int itmax, double opts[5], double info[LM_INFO_SZ], double *work, double *covar, void *adata);
/* linear equation & inequality constraints */
extern int dlevmar_leic_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, double *A, double *b, int k1, double *C, double *d, int k2,
int itmax, double opts[4], double info[LM_INFO_SZ], double *work, double *covar, void *adata);
extern int dlevmar_leic_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, double *A, double *b, int k1, double *C, double *d, int k2,
int itmax, double opts[5], double info[LM_INFO_SZ], double *work, double *covar, void *adata);
/* linear inequality constraints */
extern int dlevmar_lic_der(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, double *x, int m, int n, double *C, double *d, int k2,
int itmax, double opts[4], double info[LM_INFO_SZ], double *work, double *covar, void *adata);
extern int dlevmar_lic_dif(
void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *x, int m, int n, double *C, double *d, int k2,
int itmax, double opts[5], double info[LM_INFO_SZ], double *work, double *covar, void *adata);
#endif /* HAVE_LAPACK */
#endif /* LM_DBL_PREC */
#ifdef LM_SNGL_PREC
/* single precision LM, with & without Jacobian */
/* unconstrained minimization */
extern int slevmar_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, int itmax, float *opts,
float *info, float *work, float *covar, void *adata);
extern int slevmar_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, int itmax, float *opts,
float *info, float *work, float *covar, void *adata);
/* box-constrained minimization */
extern int slevmar_bc_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub, float *dscl,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
extern int slevmar_bc_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub, float *dscl,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
#ifdef HAVE_LAPACK
/* linear equation constrained minimization */
extern int slevmar_lec_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, float *A, float *b, int k,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
extern int slevmar_lec_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, float *A, float *b, int k,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
/* box & linear equation constrained minimization */
extern int slevmar_blec_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub, float *A, float *b, int k, float *wghts,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
extern int slevmar_blec_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub, float *A, float *b, int k, float *wghts,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
/* box, linear equations & inequalities constrained minimization */
extern int slevmar_bleic_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub,
float *A, float *b, int k1, float *C, float *d, int k2,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
extern int slevmar_bleic_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub,
float *A, float *b, int k1, float *C, float *d, int k2,
int itmax, float *opts, float *info, float *work, float *covar, void *adata);
/* box & linear inequality constraints */
extern int slevmar_blic_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub, float *C, float *d, int k2,
int itmax, float opts[4], float info[LM_INFO_SZ], float *work, float *covar, void *adata);
extern int slevmar_blic_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, float *lb, float *ub, float *C, float *d, int k2,
int itmax, float opts[5], float info[LM_INFO_SZ], float *work, float *covar, void *adata);
/* linear equality & inequality constraints */
extern int slevmar_leic_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, float *A, float *b, int k1, float *C, float *d, int k2,
int itmax, float opts[4], float info[LM_INFO_SZ], float *work, float *covar, void *adata);
extern int slevmar_leic_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, float *A, float *b, int k1, float *C, float *d, int k2,
int itmax, float opts[5], float info[LM_INFO_SZ], float *work, float *covar, void *adata);
/* linear inequality constraints */
extern int slevmar_lic_der(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, float *x, int m, int n, float *C, float *d, int k2,
int itmax, float opts[4], float info[LM_INFO_SZ], float *work, float *covar, void *adata);
extern int slevmar_lic_dif(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, float *C, float *d, int k2,
int itmax, float opts[5], float info[LM_INFO_SZ], float *work, float *covar, void *adata);
#endif /* HAVE_LAPACK */
#endif /* LM_SNGL_PREC */
/* linear system solvers */
#ifdef HAVE_LAPACK
#ifdef LM_DBL_PREC
extern int dAx_eq_b_QR(double *A, double *B, double *x, int m);
extern int dAx_eq_b_QRLS(double *A, double *B, double *x, int m, int n);
extern int dAx_eq_b_Chol(double *A, double *B, double *x, int m);
extern int dAx_eq_b_LU(double *A, double *B, double *x, int m);
extern int dAx_eq_b_SVD(double *A, double *B, double *x, int m);
extern int dAx_eq_b_BK(double *A, double *B, double *x, int m);
#endif /* LM_DBL_PREC */
#ifdef LM_SNGL_PREC
extern int sAx_eq_b_QR(float *A, float *B, float *x, int m);
extern int sAx_eq_b_QRLS(float *A, float *B, float *x, int m, int n);
extern int sAx_eq_b_Chol(float *A, float *B, float *x, int m);
extern int sAx_eq_b_LU(float *A, float *B, float *x, int m);
extern int sAx_eq_b_SVD(float *A, float *B, float *x, int m);
extern int sAx_eq_b_BK(float *A, float *B, float *x, int m);
#endif /* LM_SNGL_PREC */
#else /* no LAPACK */
#ifdef LM_DBL_PREC
extern int dAx_eq_b_LU_noLapack(double *A, double *B, double *x, int n);
#endif /* LM_DBL_PREC */
#ifdef LM_SNGL_PREC
extern int sAx_eq_b_LU_noLapack(float *A, float *B, float *x, int n);
#endif /* LM_SNGL_PREC */
#endif /* HAVE_LAPACK */
#ifdef HAVE_PLASMA
#ifdef LM_DBL_PREC
extern int dAx_eq_b_PLASMA_Chol(double *A, double *B, double *x, int m);
#endif
#ifdef LM_SNGL_PREC
extern int sAx_eq_b_PLASMA_Chol(float *A, float *B, float *x, int m);
#endif
extern void levmar_PLASMA_setnbcores(int cores);
#endif /* HAVE_PLASMA */
/* Jacobian verification, double & single precision */
#ifdef LM_DBL_PREC
extern void dlevmar_chkjac(
void (*func)(double *p, double *hx, int m, int n, void *adata),
void (*jacf)(double *p, double *j, int m, int n, void *adata),
double *p, int m, int n, void *adata, double *err);
#endif /* LM_DBL_PREC */
#ifdef LM_SNGL_PREC
extern void slevmar_chkjac(
void (*func)(float *p, float *hx, int m, int n, void *adata),
void (*jacf)(float *p, float *j, int m, int n, void *adata),
float *p, int m, int n, void *adata, float *err);
#endif /* LM_SNGL_PREC */
/* miscellaneous: standard deviation, coefficient of determination (R2),
* Pearson's correlation coefficient for best-fit parameters
*/
#ifdef LM_DBL_PREC
extern double dlevmar_stddev( double *covar, int m, int i);
extern double dlevmar_corcoef(double *covar, int m, int i, int j);
extern double dlevmar_R2(void (*func)(double *p, double *hx, int m, int n, void *adata), double *p, double *x, int m, int n, void *adata);
#endif /* LM_DBL_PREC */
#ifdef LM_SNGL_PREC
extern float slevmar_stddev( float *covar, int m, int i);
extern float slevmar_corcoef(float *covar, int m, int i, int j);
extern float slevmar_R2(void (*func)(float *p, float *hx, int m, int n, void *adata), float *p, float *x, int m, int n, void *adata);
extern void slevmar_locscale(
void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *x, int m, int n, void *adata,
int howto, float locscl[2], float **residptr);
extern int slevmar_outlid(float *r, int n, float thresh, float ls[2], char *outlmap);
#endif /* LM_SNGL_PREC */
#ifdef __cplusplus
}
#endif
#endif /* _LEVMAR_H_ */

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@@ -1,83 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/********************************************************************************
* Levenberg-Marquardt nonlinear minimization. The same core code is used with
* appropriate #defines to derive single and double precision versions, see
* also lm_core.c
********************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include "levmar.h"
#include "compiler.h"
#include "misc.h"
#define EPSILON 1E-12
#define ONE_THIRD 0.3333333334 /* 1.0/3.0 */
#if !defined(LM_DBL_PREC) && !defined(LM_SNGL_PREC)
#error At least one of LM_DBL_PREC, LM_SNGL_PREC should be defined!
#endif
#ifdef LM_SNGL_PREC
/* single precision (float) definitions */
#define LM_REAL float
#define LM_PREFIX s
#define LM_REAL_MAX FLT_MAX
#define LM_REAL_MIN -FLT_MAX
#define LM_REAL_EPSILON FLT_EPSILON
#define __SUBCNST(x) x##F
#define LM_CNST(x) __SUBCNST(x) // force substitution
#include "lm_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_EPSILON
#undef LM_REAL_MIN
#undef __SUBCNST
#undef LM_CNST
#endif /* LM_SNGL_PREC */
#ifdef LM_DBL_PREC
/* double precision definitions */
#define LM_REAL double
#define LM_PREFIX d
#define LM_REAL_MAX DBL_MAX
#define LM_REAL_MIN -DBL_MAX
#define LM_REAL_EPSILON DBL_EPSILON
#define LM_CNST(x) (x)
#include "lm_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_EPSILON
#undef LM_REAL_MIN
#undef LM_CNST
#endif /* LM_DBL_PREC */

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@@ -1,11 +0,0 @@
#ifndef _DEPR_LM_H_
#define _DEPR_LM_H_
#ifdef _MSC_VER
#pragma message("lm.h is deprecated, please use levmar.h instead!")
#else
#error lm.h is deprecated, please use levmar.h instead!
#endif /* _MSC_VER */
#endif /* _DEPR_LM_H_ */

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@@ -1,858 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
#ifndef LM_REAL // not included by lm.c
#error This file should not be compiled directly!
#endif
/* precision-specific definitions */
#define LEVMAR_DER LM_ADD_PREFIX(levmar_der)
#define LEVMAR_DIF LM_ADD_PREFIX(levmar_dif)
#define LEVMAR_FDIF_FORW_JAC_APPROX LM_ADD_PREFIX(levmar_fdif_forw_jac_approx)
#define LEVMAR_FDIF_CENT_JAC_APPROX LM_ADD_PREFIX(levmar_fdif_cent_jac_approx)
#define LEVMAR_TRANS_MAT_MAT_MULT LM_ADD_PREFIX(levmar_trans_mat_mat_mult)
#define LEVMAR_L2NRMXMY LM_ADD_PREFIX(levmar_L2nrmxmy)
#define LEVMAR_COVAR LM_ADD_PREFIX(levmar_covar)
#ifdef HAVE_LAPACK
#define AX_EQ_B_LU LM_ADD_PREFIX(Ax_eq_b_LU)
#define AX_EQ_B_CHOL LM_ADD_PREFIX(Ax_eq_b_Chol)
#define AX_EQ_B_QR LM_ADD_PREFIX(Ax_eq_b_QR)
#define AX_EQ_B_QRLS LM_ADD_PREFIX(Ax_eq_b_QRLS)
#define AX_EQ_B_SVD LM_ADD_PREFIX(Ax_eq_b_SVD)
#define AX_EQ_B_BK LM_ADD_PREFIX(Ax_eq_b_BK)
#else
#define AX_EQ_B_LU LM_ADD_PREFIX(Ax_eq_b_LU_noLapack)
#endif /* HAVE_LAPACK */
#ifdef HAVE_PLASMA
#define AX_EQ_B_PLASMA_CHOL LM_ADD_PREFIX(Ax_eq_b_PLASMA_Chol)
#endif
/*
* This function seeks the parameter vector p that best describes the measurements vector x.
* More precisely, given a vector function func : R^m --> R^n with n>=m,
* it finds p s.t. func(p) ~= x, i.e. the squared second order (i.e. L2) norm of
* e=x-func(p) is minimized.
*
* This function requires an analytic Jacobian. In case the latter is unavailable,
* use LEVMAR_DIF() bellow
*
* Returns the number of iterations (>=0) if successful, LM_ERROR if failed
*
* For more details, see K. Madsen, H.B. Nielsen and O. Tingleff's lecture notes on
* non-linear least squares at http://www.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf
*/
int LEVMAR_DER(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata), /* function to evaluate the Jacobian \part x / \part p */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[4], /* I: minim. options [\mu, \epsilon1, \epsilon2, \epsilon3]. Respectively the scale factor for initial \mu,
* stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2. Set to NULL for defaults to be used
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_DER_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func & jacf.
* Set to NULL if not needed
*/
{
register int i, j, k, l;
int worksz, freework=0, issolved;
/* temp work arrays */
LM_REAL *e, /* nx1 */
*hx, /* \hat{x}_i, nx1 */
*jacTe, /* J^T e_i mx1 */
*jac, /* nxm */
*jacTjac, /* mxm */
*Dp, /* mx1 */
*diag_jacTjac, /* diagonal of J^T J, mx1 */
*pDp; /* p + Dp, mx1 */
register LM_REAL mu, /* damping constant */
tmp; /* mainly used in matrix & vector multiplications */
LM_REAL p_eL2, jacTe_inf, pDp_eL2; /* ||e(p)||_2, ||J^T e||_inf, ||e(p+Dp)||_2 */
LM_REAL p_L2, Dp_L2=LM_REAL_MAX, dF, dL;
LM_REAL tau, eps1, eps2, eps2_sq, eps3;
LM_REAL init_p_eL2;
int nu=2, nu2, stop=0, nfev, njev=0, nlss=0;
const int nm=n*m;
int (*linsolver)(LM_REAL *A, LM_REAL *B, LM_REAL *x, int m)=NULL;
mu=jacTe_inf=0.0; /* -Wall */
if(n<m){
fprintf(stderr, LCAT(LEVMAR_DER, "(): cannot solve a problem with fewer measurements [%d] than unknowns [%d]\n"), n, m);
return LM_ERROR;
}
if(!jacf){
fprintf(stderr, RCAT("No function specified for computing the Jacobian in ", LEVMAR_DER)
RCAT("().\nIf no such function is available, use ", LEVMAR_DIF) RCAT("() rather than ", LEVMAR_DER) "()\n");
return LM_ERROR;
}
if(opts){
tau=opts[0];
eps1=opts[1];
eps2=opts[2];
eps2_sq=opts[2]*opts[2];
eps3=opts[3];
}
else{ // use default values
tau=LM_CNST(LM_INIT_MU);
eps1=LM_CNST(LM_STOP_THRESH);
eps2=LM_CNST(LM_STOP_THRESH);
eps2_sq=LM_CNST(LM_STOP_THRESH)*LM_CNST(LM_STOP_THRESH);
eps3=LM_CNST(LM_STOP_THRESH);
}
if(!work){
worksz=LM_DER_WORKSZ(m, n); //2*n+4*m + n*m + m*m;
work=(LM_REAL *)malloc(worksz*sizeof(LM_REAL)); /* allocate a big chunk in one step */
if(!work){
fprintf(stderr, LCAT(LEVMAR_DER, "(): memory allocation request failed\n"));
return LM_ERROR;
}
freework=1;
}
/* set up work arrays */
e=work;
hx=e + n;
jacTe=hx + n;
jac=jacTe + m;
jacTjac=jac + nm;
Dp=jacTjac + m*m;
diag_jacTjac=Dp + m;
pDp=diag_jacTjac + m;
/* compute e=x - f(p) and its L2 norm */
(*func)(p, hx, m, n, adata); nfev=1;
/* ### e=x-hx, p_eL2=||e|| */
#if 1
p_eL2=LEVMAR_L2NRMXMY(e, x, hx, n);
#else
for(i=0, p_eL2=0.0; i<n; ++i){
e[i]=tmp=x[i]-hx[i];
p_eL2+=tmp*tmp;
}
#endif
init_p_eL2=p_eL2;
if(!LM_FINITE(p_eL2)) stop=7;
for(k=0; k<itmax && !stop; ++k){
/* Note that p and e have been updated at a previous iteration */
if(p_eL2<=eps3){ /* error is small */
stop=6;
break;
}
/* Compute the Jacobian J at p, J^T J, J^T e, ||J^T e||_inf and ||p||^2.
* Since J^T J is symmetric, its computation can be sped up by computing
* only its upper triangular part and copying it to the lower part
*/
(*jacf)(p, jac, m, n, adata); ++njev;
/* J^T J, J^T e */
if(nm<__BLOCKSZ__SQ){ // this is a small problem
/* J^T*J_ij = \sum_l J^T_il * J_lj = \sum_l J_li * J_lj.
* Thus, the product J^T J can be computed using an outer loop for
* l that adds J_li*J_lj to each element ij of the result. Note that
* with this scheme, the accesses to J and JtJ are always along rows,
* therefore induces less cache misses compared to the straightforward
* algorithm for computing the product (i.e., l loop is innermost one).
* A similar scheme applies to the computation of J^T e.
* However, for large minimization problems (i.e., involving a large number
* of unknowns and measurements) for which J/J^T J rows are too large to
* fit in the L1 cache, even this scheme incures many cache misses. In
* such cases, a cache-efficient blocking scheme is preferable.
*
* Thanks to John Nitao of Lawrence Livermore Lab for pointing out this
* performance problem.
*
* Note that the non-blocking algorithm is faster on small
* problems since in this case it avoids the overheads of blocking.
*/
/* looping downwards saves a few computations */
register int l;
register LM_REAL alpha, *jaclm, *jacTjacim;
for(i=m*m; i-->0; )
jacTjac[i]=0.0;
for(i=m; i-->0; )
jacTe[i]=0.0;
for(l=n; l-->0; ){
jaclm=jac+l*m;
for(i=m; i-->0; ){
jacTjacim=jacTjac+i*m;
alpha=jaclm[i]; //jac[l*m+i];
for(j=i+1; j-->0; ) /* j<=i computes lower triangular part only */
jacTjacim[j]+=jaclm[j]*alpha; //jacTjac[i*m+j]+=jac[l*m+j]*alpha
/* J^T e */
jacTe[i]+=alpha*e[l];
}
}
for(i=m; i-->0; ) /* copy to upper part */
for(j=i+1; j<m; ++j)
jacTjac[i*m+j]=jacTjac[j*m+i];
}
else{ // this is a large problem
/* Cache efficient computation of J^T J based on blocking
*/
LEVMAR_TRANS_MAT_MAT_MULT(jac, jacTjac, n, m);
/* cache efficient computation of J^T e */
for(i=0; i<m; ++i)
jacTe[i]=0.0;
for(i=0; i<n; ++i){
register LM_REAL *jacrow;
for(l=0, jacrow=jac+i*m, tmp=e[i]; l<m; ++l)
jacTe[l]+=jacrow[l]*tmp;
}
}
/* Compute ||J^T e||_inf and ||p||^2 */
for(i=0, p_L2=jacTe_inf=0.0; i<m; ++i){
if(jacTe_inf < (tmp=FABS(jacTe[i]))) jacTe_inf=tmp;
diag_jacTjac[i]=jacTjac[i*m+i]; /* save diagonal entries so that augmentation can be later canceled */
p_L2+=p[i]*p[i];
}
//p_L2=sqrt(p_L2);
#if 0
if(!(k%100)){
printf("Current estimate: ");
for(i=0; i<m; ++i)
printf("%.9g ", p[i]);
printf("-- errors %.9g %0.9g\n", jacTe_inf, p_eL2);
}
#endif
/* check for convergence */
if((jacTe_inf <= eps1)){
Dp_L2=0.0; /* no increment for p in this case */
stop=1;
break;
}
/* compute initial damping factor */
if(k==0){
for(i=0, tmp=LM_REAL_MIN; i<m; ++i)
if(diag_jacTjac[i]>tmp) tmp=diag_jacTjac[i]; /* find max diagonal element */
mu=tau*tmp;
}
/* determine increment using adaptive damping */
while(1){
/* augment normal equations */
for(i=0; i<m; ++i)
jacTjac[i*m+i]+=mu;
/* solve augmented equations */
#ifdef HAVE_LAPACK
/* 7 alternatives are available: LU, Cholesky + Cholesky with PLASMA, LDLt, 2 variants of QR decomposition and SVD.
* For matrices with dimensions of at least a few hundreds, the PLASMA implementation of Cholesky is the fastest.
* From the serial solvers, Cholesky is the fastest but might occasionally be inapplicable due to numerical round-off;
* QR is slower but more robust; SVD is the slowest but most robust; LU is quite robust but
* slower than LDLt; LDLt offers a good tradeoff between robustness and speed
*/
issolved=AX_EQ_B_BK(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_BK;
//issolved=AX_EQ_B_LU(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_LU;
//issolved=AX_EQ_B_CHOL(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_CHOL;
#ifdef HAVE_PLASMA
//issolved=AX_EQ_B_PLASMA_CHOL(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_PLASMA_CHOL;
#endif
//issolved=AX_EQ_B_QR(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_QR;
//issolved=AX_EQ_B_QRLS(jacTjac, jacTe, Dp, m, m); ++nlss; linsolver=(int (*)(LM_REAL *A, LM_REAL *B, LM_REAL *x, int m))AX_EQ_B_QRLS;
//issolved=AX_EQ_B_SVD(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_SVD;
#else
/* use the LU included with levmar */
issolved=AX_EQ_B_LU(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_LU;
#endif /* HAVE_LAPACK */
if(issolved){
/* compute p's new estimate and ||Dp||^2 */
for(i=0, Dp_L2=0.0; i<m; ++i){
pDp[i]=p[i] + (tmp=Dp[i]);
Dp_L2+=tmp*tmp;
}
//Dp_L2=sqrt(Dp_L2);
if(Dp_L2<=eps2_sq*p_L2){ /* relative change in p is small, stop */
//if(Dp_L2<=eps2*(p_L2 + eps2)){ /* relative change in p is small, stop */
stop=2;
break;
}
if(Dp_L2>=(p_L2+eps2)/(LM_CNST(EPSILON)*LM_CNST(EPSILON))){ /* almost singular */
//if(Dp_L2>=(p_L2+eps2)/LM_CNST(EPSILON)){ /* almost singular */
stop=4;
break;
}
(*func)(pDp, hx, m, n, adata); ++nfev; /* evaluate function at p + Dp */
/* compute ||e(pDp)||_2 */
/* ### hx=x-hx, pDp_eL2=||hx|| */
#if 1
pDp_eL2=LEVMAR_L2NRMXMY(hx, x, hx, n);
#else
for(i=0, pDp_eL2=0.0; i<n; ++i){
hx[i]=tmp=x[i]-hx[i];
pDp_eL2+=tmp*tmp;
}
#endif
if(!LM_FINITE(pDp_eL2)){ /* sum of squares is not finite, most probably due to a user error.
* This check makes sure that the inner loop does not run indefinitely.
* Thanks to Steve Danauskas for reporting such cases
*/
stop=7;
break;
}
for(i=0, dL=0.0; i<m; ++i)
dL+=Dp[i]*(mu*Dp[i]+jacTe[i]);
dF=p_eL2-pDp_eL2;
if(dL>0.0 && dF>0.0){ /* reduction in error, increment is accepted */
tmp=(LM_CNST(2.0)*dF/dL-LM_CNST(1.0));
tmp=LM_CNST(1.0)-tmp*tmp*tmp;
mu=mu*( (tmp>=LM_CNST(ONE_THIRD))? tmp : LM_CNST(ONE_THIRD) );
nu=2;
for(i=0 ; i<m; ++i) /* update p's estimate */
p[i]=pDp[i];
for(i=0; i<n; ++i) /* update e and ||e||_2 */
e[i]=hx[i];
p_eL2=pDp_eL2;
break;
}
}
/* if this point is reached, either the linear system could not be solved or
* the error did not reduce; in any case, the increment must be rejected
*/
mu*=nu;
nu2=nu<<1; // 2*nu;
if(nu2<=nu){ /* nu has wrapped around (overflown). Thanks to Frank Jordan for spotting this case */
stop=5;
break;
}
nu=nu2;
for(i=0; i<m; ++i) /* restore diagonal J^T J entries */
jacTjac[i*m+i]=diag_jacTjac[i];
} /* inner loop */
}
if(k>=itmax) stop=3;
for(i=0; i<m; ++i) /* restore diagonal J^T J entries */
jacTjac[i*m+i]=diag_jacTjac[i];
if(info){
info[0]=init_p_eL2;
info[1]=p_eL2;
info[2]=jacTe_inf;
info[3]=Dp_L2;
for(i=0, tmp=LM_REAL_MIN; i<m; ++i)
if(tmp<jacTjac[i*m+i]) tmp=jacTjac[i*m+i];
info[4]=mu/tmp;
info[5]=(LM_REAL)k;
info[6]=(LM_REAL)stop;
info[7]=(LM_REAL)nfev;
info[8]=(LM_REAL)njev;
info[9]=(LM_REAL)nlss;
}
/* covariance matrix */
if(covar){
LEVMAR_COVAR(jacTjac, covar, p_eL2, m, n);
}
if(freework) free(work);
#ifdef LINSOLVERS_RETAIN_MEMORY
if(linsolver) (*linsolver)(NULL, NULL, NULL, 0);
#endif
return (stop!=4 && stop!=7)? k : LM_ERROR;
}
/* Secant version of the LEVMAR_DER() function above: the Jacobian is approximated with
* the aid of finite differences (forward or central, see the comment for the opts argument)
*/
int LEVMAR_DIF(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[5], /* I: opts[0-4] = minim. options [\mu, \epsilon1, \epsilon2, \epsilon3, \delta]. Respectively the
* scale factor for initial \mu, stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2 and
* the step used in difference approximation to the Jacobian. Set to NULL for defaults to be used.
* If \delta<0, the Jacobian is approximated with central differences which are more accurate
* (but slower!) compared to the forward differences employed by default.
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_DIF_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func.
* Set to NULL if not needed
*/
{
register int i, j, k, l;
int worksz, freework=0, issolved;
/* temp work arrays */
LM_REAL *e, /* nx1 */
*hx, /* \hat{x}_i, nx1 */
*jacTe, /* J^T e_i mx1 */
*jac, /* nxm */
*jacTjac, /* mxm */
*Dp, /* mx1 */
*diag_jacTjac, /* diagonal of J^T J, mx1 */
*pDp, /* p + Dp, mx1 */
*wrk, /* nx1 */
*wrk2; /* nx1, used only for holding a temporary e vector and when differentiating with central differences */
int using_ffdif=1;
register LM_REAL mu, /* damping constant */
tmp; /* mainly used in matrix & vector multiplications */
LM_REAL p_eL2, jacTe_inf, pDp_eL2; /* ||e(p)||_2, ||J^T e||_inf, ||e(p+Dp)||_2 */
LM_REAL p_L2, Dp_L2=LM_REAL_MAX, dF, dL;
LM_REAL tau, eps1, eps2, eps2_sq, eps3, delta;
LM_REAL init_p_eL2;
int nu, nu2, stop=0, nfev, njap=0, nlss=0, K=(m>=10)? m: 10, updjac, updp=1, newjac;
const int nm=n*m;
int (*linsolver)(LM_REAL *A, LM_REAL *B, LM_REAL *x, int m)=NULL;
mu=jacTe_inf=p_L2=0.0; /* -Wall */
updjac=newjac=0; /* -Wall */
if(n<m){
fprintf(stderr, LCAT(LEVMAR_DIF, "(): cannot solve a problem with fewer measurements [%d] than unknowns [%d]\n"), n, m);
return LM_ERROR;
}
if(opts){
tau=opts[0];
eps1=opts[1];
eps2=opts[2];
eps2_sq=opts[2]*opts[2];
eps3=opts[3];
delta=opts[4];
if(delta<0.0){
delta=-delta; /* make positive */
using_ffdif=0; /* use central differencing */
}
}
else{ // use default values
tau=LM_CNST(LM_INIT_MU);
eps1=LM_CNST(LM_STOP_THRESH);
eps2=LM_CNST(LM_STOP_THRESH);
eps2_sq=LM_CNST(LM_STOP_THRESH)*LM_CNST(LM_STOP_THRESH);
eps3=LM_CNST(LM_STOP_THRESH);
delta=LM_CNST(LM_DIFF_DELTA);
}
if(!work){
worksz=LM_DIF_WORKSZ(m, n); //4*n+4*m + n*m + m*m;
work=(LM_REAL *)malloc(worksz*sizeof(LM_REAL)); /* allocate a big chunk in one step */
if(!work){
fprintf(stderr, LCAT(LEVMAR_DIF, "(): memory allocation request failed\n"));
return LM_ERROR;
}
freework=1;
}
/* set up work arrays */
e=work;
hx=e + n;
jacTe=hx + n;
jac=jacTe + m;
jacTjac=jac + nm;
Dp=jacTjac + m*m;
diag_jacTjac=Dp + m;
pDp=diag_jacTjac + m;
wrk=pDp + m;
wrk2=wrk + n;
/* compute e=x - f(p) and its L2 norm */
(*func)(p, hx, m, n, adata); nfev=1;
/* ### e=x-hx, p_eL2=||e|| */
#if 1
p_eL2=LEVMAR_L2NRMXMY(e, x, hx, n);
#else
for(i=0, p_eL2=0.0; i<n; ++i){
e[i]=tmp=x[i]-hx[i];
p_eL2+=tmp*tmp;
}
#endif
init_p_eL2=p_eL2;
if(!LM_FINITE(p_eL2)) stop=7;
nu=20; /* force computation of J */
for(k=0; k<itmax && !stop; ++k){
/* Note that p and e have been updated at a previous iteration */
if(p_eL2<=eps3){ /* error is small */
stop=6;
break;
}
/* Compute the Jacobian J at p, J^T J, J^T e, ||J^T e||_inf and ||p||^2.
* The symmetry of J^T J is again exploited for speed
*/
if((updp && nu>16) || updjac==K){ /* compute difference approximation to J */
if(using_ffdif){ /* use forward differences */
LEVMAR_FDIF_FORW_JAC_APPROX(func, p, hx, wrk, delta, jac, m, n, adata);
++njap; nfev+=m;
}
else{ /* use central differences */
LEVMAR_FDIF_CENT_JAC_APPROX(func, p, wrk, wrk2, delta, jac, m, n, adata);
++njap; nfev+=2*m;
}
nu=2; updjac=0; updp=0; newjac=1;
}
if(newjac){ /* Jacobian has changed, recompute J^T J, J^t e, etc */
newjac=0;
/* J^T J, J^T e */
if(nm<=__BLOCKSZ__SQ){ // this is a small problem
/* J^T*J_ij = \sum_l J^T_il * J_lj = \sum_l J_li * J_lj.
* Thus, the product J^T J can be computed using an outer loop for
* l that adds J_li*J_lj to each element ij of the result. Note that
* with this scheme, the accesses to J and JtJ are always along rows,
* therefore induces less cache misses compared to the straightforward
* algorithm for computing the product (i.e., l loop is innermost one).
* A similar scheme applies to the computation of J^T e.
* However, for large minimization problems (i.e., involving a large number
* of unknowns and measurements) for which J/J^T J rows are too large to
* fit in the L1 cache, even this scheme incures many cache misses. In
* such cases, a cache-efficient blocking scheme is preferable.
*
* Thanks to John Nitao of Lawrence Livermore Lab for pointing out this
* performance problem.
*
* Note that the non-blocking algorithm is faster on small
* problems since in this case it avoids the overheads of blocking.
*/
register int l;
register LM_REAL alpha, *jaclm, *jacTjacim;
/* looping downwards saves a few computations */
for(i=m*m; i-->0; )
jacTjac[i]=0.0;
for(i=m; i-->0; )
jacTe[i]=0.0;
for(l=n; l-->0; ){
jaclm=jac+l*m;
for(i=m; i-->0; ){
jacTjacim=jacTjac+i*m;
alpha=jaclm[i]; //jac[l*m+i];
for(j=i+1; j-->0; ) /* j<=i computes lower triangular part only */
jacTjacim[j]+=jaclm[j]*alpha; //jacTjac[i*m+j]+=jac[l*m+j]*alpha
/* J^T e */
jacTe[i]+=alpha*e[l];
}
}
for(i=m; i-->0; ) /* copy to upper part */
for(j=i+1; j<m; ++j)
jacTjac[i*m+j]=jacTjac[j*m+i];
}
else{ // this is a large problem
/* Cache efficient computation of J^T J based on blocking
*/
LEVMAR_TRANS_MAT_MAT_MULT(jac, jacTjac, n, m);
/* cache efficient computation of J^T e */
for(i=0; i<m; ++i)
jacTe[i]=0.0;
for(i=0; i<n; ++i){
register LM_REAL *jacrow;
for(l=0, jacrow=jac+i*m, tmp=e[i]; l<m; ++l)
jacTe[l]+=jacrow[l]*tmp;
}
}
/* Compute ||J^T e||_inf and ||p||^2 */
for(i=0, p_L2=jacTe_inf=0.0; i<m; ++i){
if(jacTe_inf < (tmp=FABS(jacTe[i]))) jacTe_inf=tmp;
diag_jacTjac[i]=jacTjac[i*m+i]; /* save diagonal entries so that augmentation can be later canceled */
p_L2+=p[i]*p[i];
}
//p_L2=sqrt(p_L2);
}
#if 0
if(!(k%100)){
printf("Current estimate: ");
for(i=0; i<m; ++i)
printf("%.9g ", p[i]);
printf("-- errors %.9g %0.9g\n", jacTe_inf, p_eL2);
}
#endif
/* check for convergence */
if((jacTe_inf <= eps1)){
Dp_L2=0.0; /* no increment for p in this case */
stop=1;
break;
}
/* compute initial damping factor */
if(k==0){
for(i=0, tmp=LM_REAL_MIN; i<m; ++i)
if(diag_jacTjac[i]>tmp) tmp=diag_jacTjac[i]; /* find max diagonal element */
mu=tau*tmp;
}
/* determine increment using adaptive damping */
/* augment normal equations */
for(i=0; i<m; ++i)
jacTjac[i*m+i]+=mu;
/* solve augmented equations */
#ifdef HAVE_LAPACK
/* 7 alternatives are available: LU, Cholesky + Cholesky with PLASMA, LDLt, 2 variants of QR decomposition and SVD.
* For matrices with dimensions of at least a few hundreds, the PLASMA implementation of Cholesky is the fastest.
* From the serial solvers, Cholesky is the fastest but might occasionally be inapplicable due to numerical round-off;
* QR is slower but more robust; SVD is the slowest but most robust; LU is quite robust but
* slower than LDLt; LDLt offers a good tradeoff between robustness and speed
*/
issolved=AX_EQ_B_BK(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_BK;
//issolved=AX_EQ_B_LU(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_LU;
//issolved=AX_EQ_B_CHOL(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_CHOL;
#ifdef HAVE_PLASMA
//issolved=AX_EQ_B_PLASMA_CHOL(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_PLASMA_CHOL;
#endif
//issolved=AX_EQ_B_QR(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_QR;
//issolved=AX_EQ_B_QRLS(jacTjac, jacTe, Dp, m, m); ++nlss; linsolver=(int (*)(LM_REAL *A, LM_REAL *B, LM_REAL *x, int m))AX_EQ_B_QRLS;
//issolved=AX_EQ_B_SVD(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_SVD;
#else
/* use the LU included with levmar */
issolved=AX_EQ_B_LU(jacTjac, jacTe, Dp, m); ++nlss; linsolver=AX_EQ_B_LU;
#endif /* HAVE_LAPACK */
if(issolved){
/* compute p's new estimate and ||Dp||^2 */
for(i=0, Dp_L2=0.0; i<m; ++i){
pDp[i]=p[i] + (tmp=Dp[i]);
Dp_L2+=tmp*tmp;
}
//Dp_L2=sqrt(Dp_L2);
if(Dp_L2<=eps2_sq*p_L2){ /* relative change in p is small, stop */
//if(Dp_L2<=eps2*(p_L2 + eps2)){ /* relative change in p is small, stop */
stop=2;
break;
}
if(Dp_L2>=(p_L2+eps2)/(LM_CNST(EPSILON)*LM_CNST(EPSILON))){ /* almost singular */
//if(Dp_L2>=(p_L2+eps2)/LM_CNST(EPSILON)){ /* almost singular */
stop=4;
break;
}
(*func)(pDp, wrk, m, n, adata); ++nfev; /* evaluate function at p + Dp */
/* compute ||e(pDp)||_2 */
/* ### wrk2=x-wrk, pDp_eL2=||wrk2|| */
#if 1
pDp_eL2=LEVMAR_L2NRMXMY(wrk2, x, wrk, n);
#else
for(i=0, pDp_eL2=0.0; i<n; ++i){
wrk2[i]=tmp=x[i]-wrk[i];
pDp_eL2+=tmp*tmp;
}
#endif
if(!LM_FINITE(pDp_eL2)){ /* sum of squares is not finite, most probably due to a user error.
* This check makes sure that the loop terminates early in the case
* of invalid input. Thanks to Steve Danauskas for suggesting it
*/
stop=7;
break;
}
dF=p_eL2-pDp_eL2;
if(updp || dF>0){ /* update jac */
for(i=0; i<n; ++i){
for(l=0, tmp=0.0; l<m; ++l)
tmp+=jac[i*m+l]*Dp[l]; /* (J * Dp)[i] */
tmp=(wrk[i] - hx[i] - tmp)/Dp_L2; /* (f(p+dp)[i] - f(p)[i] - (J * Dp)[i])/(dp^T*dp) */
for(j=0; j<m; ++j)
jac[i*m+j]+=tmp*Dp[j];
}
++updjac;
newjac=1;
}
for(i=0, dL=0.0; i<m; ++i)
dL+=Dp[i]*(mu*Dp[i]+jacTe[i]);
if(dL>0.0 && dF>0.0){ /* reduction in error, increment is accepted */
tmp=(LM_CNST(2.0)*dF/dL-LM_CNST(1.0));
tmp=LM_CNST(1.0)-tmp*tmp*tmp;
mu=mu*( (tmp>=LM_CNST(ONE_THIRD))? tmp : LM_CNST(ONE_THIRD) );
nu=2;
for(i=0 ; i<m; ++i) /* update p's estimate */
p[i]=pDp[i];
for(i=0; i<n; ++i){ /* update e, hx and ||e||_2 */
e[i]=wrk2[i]; //x[i]-wrk[i];
hx[i]=wrk[i];
}
p_eL2=pDp_eL2;
updp=1;
continue;
}
}
/* if this point is reached, either the linear system could not be solved or
* the error did not reduce; in any case, the increment must be rejected
*/
mu*=nu;
nu2=nu<<1; // 2*nu;
if(nu2<=nu){ /* nu has wrapped around (overflown). Thanks to Frank Jordan for spotting this case */
stop=5;
break;
}
nu=nu2;
for(i=0; i<m; ++i) /* restore diagonal J^T J entries */
jacTjac[i*m+i]=diag_jacTjac[i];
}
if(k>=itmax) stop=3;
for(i=0; i<m; ++i) /* restore diagonal J^T J entries */
jacTjac[i*m+i]=diag_jacTjac[i];
if(info){
info[0]=init_p_eL2;
info[1]=p_eL2;
info[2]=jacTe_inf;
info[3]=Dp_L2;
for(i=0, tmp=LM_REAL_MIN; i<m; ++i)
if(tmp<jacTjac[i*m+i]) tmp=jacTjac[i*m+i];
info[4]=mu/tmp;
info[5]=(LM_REAL)k;
info[6]=(LM_REAL)stop;
info[7]=(LM_REAL)nfev;
info[8]=(LM_REAL)njap;
info[9]=(LM_REAL)nlss;
}
/* covariance matrix */
if(covar){
LEVMAR_COVAR(jacTjac, covar, p_eL2, m, n);
}
if(freework) free(work);
#ifdef LINSOLVERS_RETAIN_MEMORY
if(linsolver) (*linsolver)(NULL, NULL, NULL, 0);
#endif
return (stop!=4 && stop!=7)? k : LM_ERROR;
}
/* undefine everything. THIS MUST REMAIN AT THE END OF THE FILE */
#undef LEVMAR_DER
#undef LEVMAR_DIF
#undef LEVMAR_FDIF_FORW_JAC_APPROX
#undef LEVMAR_FDIF_CENT_JAC_APPROX
#undef LEVMAR_COVAR
#undef LEVMAR_TRANS_MAT_MAT_MULT
#undef LEVMAR_L2NRMXMY
#undef AX_EQ_B_LU
#undef AX_EQ_B_CHOL
#undef AX_EQ_B_PLASMA_CHOL
#undef AX_EQ_B_QR
#undef AX_EQ_B_QRLS
#undef AX_EQ_B_SVD
#undef AX_EQ_B_BK

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@@ -1,87 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004-05 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/********************************************************************************
* Box-constrained Levenberg-Marquardt nonlinear minimization. The same core code
* is used with appropriate #defines to derive single and double precision versions,
* see also lmbc_core.c
********************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include "levmar.h"
#include "compiler.h"
#include "misc.h"
#define EPSILON 1E-12
#define ONE_THIRD 0.3333333334 /* 1.0/3.0 */
#define _LSITMAX_ 150 /* max #iterations for line search */
#define _POW_ 2.1
#if !defined(LM_DBL_PREC) && !defined(LM_SNGL_PREC)
#error At least one of LM_DBL_PREC, LM_SNGL_PREC should be defined!
#endif
#ifdef LM_SNGL_PREC
/* single precision (float) definitions */
#define LM_REAL float
#define LM_PREFIX s
#define LM_REAL_MAX FLT_MAX
#define LM_REAL_MIN -FLT_MAX
#define LM_REAL_EPSILON FLT_EPSILON
#define __SUBCNST(x) x##F
#define LM_CNST(x) __SUBCNST(x) // force substitution
#include "lmbc_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_MIN
#undef LM_REAL_EPSILON
#undef __SUBCNST
#undef LM_CNST
#endif /* LM_SNGL_PREC */
#ifdef LM_DBL_PREC
/* double precision definitions */
#define LM_REAL double
#define LM_PREFIX d
#define LM_REAL_MAX DBL_MAX
#define LM_REAL_MIN -DBL_MAX
#define LM_REAL_EPSILON DBL_EPSILON
#define LM_CNST(x) (x)
#include "lmbc_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_MIN
#undef LM_REAL_EPSILON
#undef LM_CNST
#endif /* LM_DBL_PREC */

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@@ -1,87 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004-06 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/********************************************************************************
* combined box and linear equation constraints Levenberg-Marquardt nonlinear
* minimization. The same core code is used with appropriate #defines to derive
* single and double precision versions, see also lmblec_core.c
********************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include "levmar.h"
#include "misc.h"
#ifndef HAVE_LAPACK
#ifdef _MSC_VER
#pragma message("Combined box and linearly constrained optimization requires LAPACK and was not compiled!")
#else
#warning Combined box and linearly constrained optimization requires LAPACK and was not compiled!
#endif // _MSC_VER
#else // LAPACK present
#if !defined(LM_DBL_PREC) && !defined(LM_SNGL_PREC)
#error At least one of LM_DBL_PREC, LM_SNGL_PREC should be defined!
#endif
#ifdef LM_SNGL_PREC
/* single precision (float) definitions */
#define LM_REAL float
#define LM_PREFIX s
#define LM_REAL_MAX FLT_MAX
#define LM_REAL_MIN -FLT_MAX
#define __SUBCNST(x) x##F
#define LM_CNST(x) __SUBCNST(x) // force substitution
#include "lmblec_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_MIN
#undef __SUBCNST
#undef LM_CNST
#endif /* LM_SNGL_PREC */
#ifdef LM_DBL_PREC
/* double precision definitions */
#define LM_REAL double
#define LM_PREFIX d
#define LM_REAL_MAX DBL_MAX
#define LM_REAL_MIN -DBL_MAX
#define LM_CNST(x) (x)
#include "lmblec_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_MIN
#undef LM_CNST
#endif /* LM_DBL_PREC */
#endif /* HAVE_LAPACK */

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@@ -1,413 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004-06 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/*******************************************************************************
* This file implements combined box and linear equation constraints.
*
* Note that the algorithm implementing linearly constrained minimization does
* so by a change in parameters that transforms the original program into an
* unconstrained one. To employ the same idea for implementing box & linear
* constraints would require the transformation of box constraints on the
* original parameters to box constraints for the new parameter set. This
* being impossible, a different approach is used here for finding the minimum.
* The trick is to remove the box constraints by augmenting the function to
* be fitted with penalty terms and then solve the resulting problem (which
* involves linear constrains only) with the functions in lmlec.c
*
* More specifically, for the constraint a<=x[i]<=b to hold, the term C[i]=
* (2*x[i]-(a+b))/(b-a) should be within [-1, 1]. This is enforced by adding
* the penalty term w[i]*max((C[i])^2-1, 0) to the objective function, where
* w[i] is a large weight. In the case of constraints of the form a<=x[i],
* the term C[i]=a-x[i] has to be non positive, thus the penalty term is
* w[i]*max(C[i], 0). If x[i]<=b, C[i]=x[i]-b has to be non negative and
* the penalty is w[i]*max(C[i], 0). The derivatives needed for the Jacobian
* are as follows:
* For the constraint a<=x[i]<=b: 4*(2*x[i]-(a+b))/(b-a)^2 if x[i] not in [a, b],
* 0 otherwise
* For the constraint a<=x[i]: -1 if x[i]<=a, 0 otherwise
* For the constraint x[i]<=b: 1 if b<=x[i], 0 otherwise
*
* Note that for the above to work, the weights w[i] should be large enough;
* depending on your minimization problem, the default values might need some
* tweaking (see arg "wghts" below).
*******************************************************************************/
#ifndef LM_REAL // not included by lmblec.c
#error This file should not be compiled directly!
#endif
#define __MAX__(x, y) (((x)>=(y))? (x) : (y))
#define __BC_WEIGHT__ LM_CNST(1E+04)
#define __BC_INTERVAL__ 0
#define __BC_LOW__ 1
#define __BC_HIGH__ 2
/* precision-specific definitions */
#define LEVMAR_BOX_CHECK LM_ADD_PREFIX(levmar_box_check)
#define LMBLEC_DATA LM_ADD_PREFIX(lmblec_data)
#define LMBLEC_FUNC LM_ADD_PREFIX(lmblec_func)
#define LMBLEC_JACF LM_ADD_PREFIX(lmblec_jacf)
#define LEVMAR_LEC_DER LM_ADD_PREFIX(levmar_lec_der)
#define LEVMAR_LEC_DIF LM_ADD_PREFIX(levmar_lec_dif)
#define LEVMAR_BLEC_DER LM_ADD_PREFIX(levmar_blec_der)
#define LEVMAR_BLEC_DIF LM_ADD_PREFIX(levmar_blec_dif)
#define LEVMAR_COVAR LM_ADD_PREFIX(levmar_covar)
struct LMBLEC_DATA{
LM_REAL *x, *lb, *ub, *w;
int *bctype;
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata);
void (*jacf)(LM_REAL *p, LM_REAL *jac, int m, int n, void *adata);
void *adata;
};
/* augmented measurements */
static void LMBLEC_FUNC(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata)
{
struct LMBLEC_DATA *data=(struct LMBLEC_DATA *)adata;
int nn;
register int i, j, *typ;
register LM_REAL *lb, *ub, *w, tmp;
nn=n-m;
lb=data->lb;
ub=data->ub;
w=data->w;
typ=data->bctype;
(*(data->func))(p, hx, m, nn, data->adata);
for(i=nn, j=0; i<n; ++i, ++j){
switch(typ[j]){
case __BC_INTERVAL__:
tmp=(LM_CNST(2.0)*p[j]-(lb[j]+ub[j]))/(ub[j]-lb[j]);
hx[i]=w[j]*__MAX__(tmp*tmp-LM_CNST(1.0), LM_CNST(0.0));
break;
case __BC_LOW__:
hx[i]=w[j]*__MAX__(lb[j]-p[j], LM_CNST(0.0));
break;
case __BC_HIGH__:
hx[i]=w[j]*__MAX__(p[j]-ub[j], LM_CNST(0.0));
break;
}
}
}
/* augmented Jacobian */
static void LMBLEC_JACF(LM_REAL *p, LM_REAL *jac, int m, int n, void *adata)
{
struct LMBLEC_DATA *data=(struct LMBLEC_DATA *)adata;
int nn, *typ;
register int i, j;
register LM_REAL *lb, *ub, *w, tmp;
nn=n-m;
lb=data->lb;
ub=data->ub;
w=data->w;
typ=data->bctype;
(*(data->jacf))(p, jac, m, nn, data->adata);
/* clear all extra rows */
for(i=nn*m; i<n*m; ++i)
jac[i]=0.0;
for(i=nn, j=0; i<n; ++i, ++j){
switch(typ[j]){
case __BC_INTERVAL__:
if(lb[j]<=p[j] && p[j]<=ub[j])
continue; // corresp. jac element already 0
/* out of interval */
tmp=ub[j]-lb[j];
tmp=LM_CNST(4.0)*(LM_CNST(2.0)*p[j]-(lb[j]+ub[j]))/(tmp*tmp);
jac[i*m+j]=w[j]*tmp;
break;
case __BC_LOW__: // (lb[j]<=p[j])? 0.0 : -1.0;
if(lb[j]<=p[j])
continue; // corresp. jac element already 0
/* smaller than lower bound */
jac[i*m+j]=-w[j];
break;
case __BC_HIGH__: // (p[j]<=ub[j])? 0.0 : 1.0;
if(p[j]<=ub[j])
continue; // corresp. jac element already 0
/* greater than upper bound */
jac[i*m+j]=w[j];
break;
}
}
}
/*
* This function seeks the parameter vector p that best describes the measurements
* vector x under box & linear constraints.
* More precisely, given a vector function func : R^m --> R^n with n>=m,
* it finds p s.t. func(p) ~= x, i.e. the squared second order (i.e. L2) norm of
* e=x-func(p) is minimized under the constraints lb[i]<=p[i]<=ub[i] and A p=b;
* A is kxm, b kx1. Note that this function DOES NOT check the satisfiability of
* the specified box and linear equation constraints.
* If no lower bound constraint applies for p[i], use -DBL_MAX/-FLT_MAX for lb[i];
* If no upper bound constraint applies for p[i], use DBL_MAX/FLT_MAX for ub[i].
*
* This function requires an analytic Jacobian. In case the latter is unavailable,
* use LEVMAR_BLEC_DIF() bellow
*
* Returns the number of iterations (>=0) if successful, LM_ERROR if failed
*
* For more details on the algorithm implemented by this function, please refer to
* the comments in the top of this file.
*
*/
int LEVMAR_BLEC_DER(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata), /* function to evaluate the Jacobian \part x / \part p */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
LM_REAL *lb, /* I: vector of lower bounds. If NULL, no lower bounds apply */
LM_REAL *ub, /* I: vector of upper bounds. If NULL, no upper bounds apply */
LM_REAL *A, /* I: constraints matrix, kxm */
LM_REAL *b, /* I: right hand constraints vector, kx1 */
int k, /* I: number of constraints (i.e. A's #rows) */
LM_REAL *wghts, /* mx1 weights for penalty terms, defaults used if NULL */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[4], /* I: minim. options [\mu, \epsilon1, \epsilon2, \epsilon3]. Respectively the scale factor for initial \mu,
* stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2. Set to NULL for defaults to be used
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_BLEC_DER_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func & jacf.
* Set to NULL if not needed
*/
{
struct LMBLEC_DATA data;
int ret;
LM_REAL locinfo[LM_INFO_SZ];
register int i;
if(!jacf){
fprintf(stderr, RCAT("No function specified for computing the Jacobian in ", LEVMAR_BLEC_DER)
RCAT("().\nIf no such function is available, use ", LEVMAR_BLEC_DIF) RCAT("() rather than ", LEVMAR_BLEC_DER) "()\n");
return LM_ERROR;
}
if(!lb && !ub){
fprintf(stderr, RCAT(LCAT(LEVMAR_BLEC_DER, "(): lower and upper bounds for box constraints cannot be both NULL, use "),
LEVMAR_LEC_DER) "() in this case!\n");
return LM_ERROR;
}
if(!LEVMAR_BOX_CHECK(lb, ub, m)){
fprintf(stderr, LCAT(LEVMAR_BLEC_DER, "(): at least one lower bound exceeds the upper one\n"));
return LM_ERROR;
}
/* measurement vector needs to be extended by m */
if(x){ /* nonzero x */
data.x=(LM_REAL *)malloc((n+m)*sizeof(LM_REAL));
if(!data.x){
fprintf(stderr, LCAT(LEVMAR_BLEC_DER, "(): memory allocation request #1 failed\n"));
return LM_ERROR;
}
for(i=0; i<n; ++i)
data.x[i]=x[i];
for(i=n; i<n+m; ++i)
data.x[i]=0.0;
}
else
data.x=NULL;
data.w=(LM_REAL *)malloc(m*sizeof(LM_REAL) + m*sizeof(int)); /* should be arranged in that order for proper doubles alignment */
if(!data.w){
fprintf(stderr, LCAT(LEVMAR_BLEC_DER, "(): memory allocation request #2 failed\n"));
if(data.x) free(data.x);
return LM_ERROR;
}
data.bctype=(int *)(data.w+m);
/* note: at this point, one of lb, ub are not NULL */
for(i=0; i<m; ++i){
data.w[i]=(!wghts)? __BC_WEIGHT__ : wghts[i];
if(!lb) data.bctype[i]=__BC_HIGH__;
else if(!ub) data.bctype[i]=__BC_LOW__;
else if(ub[i]!=LM_REAL_MAX && lb[i]!=LM_REAL_MIN) data.bctype[i]=__BC_INTERVAL__;
else if(lb[i]!=LM_REAL_MIN) data.bctype[i]=__BC_LOW__;
else data.bctype[i]=__BC_HIGH__;
}
data.lb=lb;
data.ub=ub;
data.func=func;
data.jacf=jacf;
data.adata=adata;
if(!info) info=locinfo; /* make sure that LEVMAR_LEC_DER() is called with non-null info */
ret=LEVMAR_LEC_DER(LMBLEC_FUNC, LMBLEC_JACF, p, data.x, m, n+m, A, b, k, itmax, opts, info, work, covar, (void *)&data);
if(data.x) free(data.x);
free(data.w);
return ret;
}
/* Similar to the LEVMAR_BLEC_DER() function above, except that the Jacobian is approximated
* with the aid of finite differences (forward or central, see the comment for the opts argument)
*/
int LEVMAR_BLEC_DIF(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
LM_REAL *lb, /* I: vector of lower bounds. If NULL, no lower bounds apply */
LM_REAL *ub, /* I: vector of upper bounds. If NULL, no upper bounds apply */
LM_REAL *A, /* I: constraints matrix, kxm */
LM_REAL *b, /* I: right hand constraints vector, kx1 */
int k, /* I: number of constraints (i.e. A's #rows) */
LM_REAL *wghts, /* mx1 weights for penalty terms, defaults used if NULL */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[5], /* I: opts[0-3] = minim. options [\mu, \epsilon1, \epsilon2, \epsilon3, \delta]. Respectively the
* scale factor for initial \mu, stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2 and
* the step used in difference approximation to the Jacobian. Set to NULL for defaults to be used.
* If \delta<0, the Jacobian is approximated with central differences which are more accurate
* (but slower!) compared to the forward differences employed by default.
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_BLEC_DIF_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func.
* Set to NULL if not needed
*/
{
struct LMBLEC_DATA data;
int ret;
register int i;
LM_REAL locinfo[LM_INFO_SZ];
if(!lb && !ub){
fprintf(stderr, RCAT(LCAT(LEVMAR_BLEC_DIF, "(): lower and upper bounds for box constraints cannot be both NULL, use "),
LEVMAR_LEC_DIF) "() in this case!\n");
return LM_ERROR;
}
if(!LEVMAR_BOX_CHECK(lb, ub, m)){
fprintf(stderr, LCAT(LEVMAR_BLEC_DER, "(): at least one lower bound exceeds the upper one\n"));
return LM_ERROR;
}
/* measurement vector needs to be extended by m */
if(x){ /* nonzero x */
data.x=(LM_REAL *)malloc((n+m)*sizeof(LM_REAL));
if(!data.x){
fprintf(stderr, LCAT(LEVMAR_BLEC_DER, "(): memory allocation request #1 failed\n"));
return LM_ERROR;
}
for(i=0; i<n; ++i)
data.x[i]=x[i];
for(i=n; i<n+m; ++i)
data.x[i]=0.0;
}
else
data.x=NULL;
data.w=(LM_REAL *)malloc(m*sizeof(LM_REAL) + m*sizeof(int)); /* should be arranged in that order for proper doubles alignment */
if(!data.w){
fprintf(stderr, LCAT(LEVMAR_BLEC_DER, "(): memory allocation request #2 failed\n"));
if(data.x) free(data.x);
return LM_ERROR;
}
data.bctype=(int *)(data.w+m);
/* note: at this point, one of lb, ub are not NULL */
for(i=0; i<m; ++i){
data.w[i]=(!wghts)? __BC_WEIGHT__ : wghts[i];
if(!lb) data.bctype[i]=__BC_HIGH__;
else if(!ub) data.bctype[i]=__BC_LOW__;
else if(ub[i]!=LM_REAL_MAX && lb[i]!=LM_REAL_MIN) data.bctype[i]=__BC_INTERVAL__;
else if(lb[i]!=LM_REAL_MIN) data.bctype[i]=__BC_LOW__;
else data.bctype[i]=__BC_HIGH__;
}
data.lb=lb;
data.ub=ub;
data.func=func;
data.jacf=NULL;
data.adata=adata;
if(!info) info=locinfo; /* make sure that LEVMAR_LEC_DIF() is called with non-null info */
ret=LEVMAR_LEC_DIF(LMBLEC_FUNC, p, data.x, m, n+m, A, b, k, itmax, opts, info, work, covar, (void *)&data);
if(data.x) free(data.x);
free(data.w);
return ret;
}
/* undefine all. THIS MUST REMAIN AT THE END OF THE FILE */
#undef LEVMAR_BOX_CHECK
#undef LMBLEC_DATA
#undef LMBLEC_FUNC
#undef LMBLEC_JACF
#undef LEVMAR_COVAR
#undef LEVMAR_LEC_DER
#undef LEVMAR_LEC_DIF
#undef LEVMAR_BLEC_DER
#undef LEVMAR_BLEC_DIF

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@@ -1,89 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2009 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/*******************************************************************************
* Wrappers for linear inequality constrained Levenberg-Marquardt minimization.
* The same core code is used with appropriate #defines to derive single and
* double precision versions, see also lmbleic_core.c
*******************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include "levmar.h"
#include "misc.h"
#ifndef HAVE_LAPACK
#ifdef _MSC_VER
#pragma message("Linear inequalities constrained optimization requires LAPACK and was not compiled!")
#else
#warning Linear inequalities constrained optimization requires LAPACK and was not compiled!
#endif // _MSC_VER
#else // LAPACK present
#if !defined(LM_DBL_PREC) && !defined(LM_SNGL_PREC)
#error At least one of LM_DBL_PREC, LM_SNGL_PREC should be defined!
#endif
#ifdef LM_SNGL_PREC
/* single precision (float) definitions */
#define LM_REAL float
#define LM_PREFIX s
#define LM_REAL_MAX FLT_MAX
#define LM_REAL_MIN -FLT_MAX
#define __SUBCNST(x) x##F
#define LM_CNST(x) __SUBCNST(x) // force substitution
#include "lmbleic_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_MIN
#undef __SUBCNST
#undef LM_CNST
#endif /* LM_SNGL_PREC */
#ifdef LM_DBL_PREC
/* double precision definitions */
#define LM_REAL double
#define LM_PREFIX d
#define LM_REAL_MAX DBL_MAX
#define LM_REAL_MIN -DBL_MAX
#define LM_CNST(x) (x)
#include "lmbleic_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_MAX
#undef LM_REAL_MIN
#undef LM_CNST
#endif /* LM_DBL_PREC */
#endif /* HAVE_LAPACK */

View File

@@ -1,506 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2009 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
#ifndef LM_REAL // not included by lmbleic.c
#error This file should not be compiled directly!
#endif
/* precision-specific definitions */
#define LMBLEIC_DATA LM_ADD_PREFIX(lmbleic_data)
#define LMBLEIC_ELIM LM_ADD_PREFIX(lmbleic_elim)
#define LMBLEIC_FUNC LM_ADD_PREFIX(lmbleic_func)
#define LMBLEIC_JACF LM_ADD_PREFIX(lmbleic_jacf)
#define LEVMAR_BLEIC_DER LM_ADD_PREFIX(levmar_bleic_der)
#define LEVMAR_BLEIC_DIF LM_ADD_PREFIX(levmar_bleic_dif)
#define LEVMAR_BLIC_DER LM_ADD_PREFIX(levmar_blic_der)
#define LEVMAR_BLIC_DIF LM_ADD_PREFIX(levmar_blic_dif)
#define LEVMAR_LEIC_DER LM_ADD_PREFIX(levmar_leic_der)
#define LEVMAR_LEIC_DIF LM_ADD_PREFIX(levmar_leic_dif)
#define LEVMAR_LIC_DER LM_ADD_PREFIX(levmar_lic_der)
#define LEVMAR_LIC_DIF LM_ADD_PREFIX(levmar_lic_dif)
#define LEVMAR_BLEC_DER LM_ADD_PREFIX(levmar_blec_der)
#define LEVMAR_BLEC_DIF LM_ADD_PREFIX(levmar_blec_dif)
#define LEVMAR_TRANS_MAT_MAT_MULT LM_ADD_PREFIX(levmar_trans_mat_mat_mult)
#define LEVMAR_COVAR LM_ADD_PREFIX(levmar_covar)
#define LEVMAR_FDIF_FORW_JAC_APPROX LM_ADD_PREFIX(levmar_fdif_forw_jac_approx)
struct LMBLEIC_DATA{
LM_REAL *jac;
int nineqcnstr; // #inequality constraints
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata);
void (*jacf)(LM_REAL *p, LM_REAL *jac, int m, int n, void *adata);
void *adata;
};
/* wrapper ensuring that the user-supplied function is called with the right number of variables (i.e. m) */
static void LMBLEIC_FUNC(LM_REAL *pext, LM_REAL *hx, int mm, int n, void *adata)
{
struct LMBLEIC_DATA *data=(struct LMBLEIC_DATA *)adata;
int m;
m=mm-data->nineqcnstr;
(*(data->func))(pext, hx, m, n, data->adata);
}
/* wrapper for computing the Jacobian at pext. The Jacobian is nxmm */
static void LMBLEIC_JACF(LM_REAL *pext, LM_REAL *jacext, int mm, int n, void *adata)
{
struct LMBLEIC_DATA *data=(struct LMBLEIC_DATA *)adata;
int m;
register int i, j;
LM_REAL *jac, *jacim, *jacextimm;
m=mm-data->nineqcnstr;
jac=data->jac;
(*(data->jacf))(pext, jac, m, n, data->adata);
for(i=0; i<n; ++i){
jacextimm=jacext+i*mm;
jacim=jac+i*m;
for(j=0; j<m; ++j)
jacextimm[j]=jacim[j]; //jacext[i*mm+j]=jac[i*m+j];
for(j=m; j<mm; ++j)
jacextimm[j]=0.0; //jacext[i*mm+j]=0.0;
}
}
/*
* This function is similar to LEVMAR_DER except that the minimization is
* performed subject to the box constraints lb[i]<=p[i]<=ub[i], the linear
* equation constraints A*p=b, A being k1xm, b k1x1, and the linear inequality
* constraints C*p>=d, C being k2xm, d k2x1.
*
* The inequalities are converted to equations by introducing surplus variables,
* i.e. c^T*p >= d becomes c^T*p - y = d, with y>=0. To transform all inequalities
* to equations, a total of k2 surplus variables are introduced; a problem with only
* box and linear constraints results then and is solved with LEVMAR_BLEC_DER()
* Note that opposite direction inequalities should be converted to the desired
* direction by negating, i.e. c^T*p <= d becomes -c^T*p >= -d
*
* This function requires an analytic Jacobian. In case the latter is unavailable,
* use LEVMAR_BLEIC_DIF() bellow
*
*/
int LEVMAR_BLEIC_DER(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata), /* function to evaluate the Jacobian \part x / \part p */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
LM_REAL *lb, /* I: vector of lower bounds. If NULL, no lower bounds apply */
LM_REAL *ub, /* I: vector of upper bounds. If NULL, no upper bounds apply */
LM_REAL *A, /* I: equality constraints matrix, k1xm. If NULL, no linear equation constraints apply */
LM_REAL *b, /* I: right hand constraints vector, k1x1 */
int k1, /* I: number of constraints (i.e. A's #rows) */
LM_REAL *C, /* I: inequality constraints matrix, k2xm */
LM_REAL *d, /* I: right hand constraints vector, k2x1 */
int k2, /* I: number of inequality constraints (i.e. C's #rows) */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[4], /* I: minim. options [\mu, \epsilon1, \epsilon2, \epsilon3]. Respectively the scale factor for initial \mu,
* stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2. Set to NULL for defaults to be used
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_BLEIC_DER_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func & jacf.
* Set to NULL if not needed
*/
{
struct LMBLEIC_DATA data;
LM_REAL *ptr, *pext, *Aext, *bext, *covext; /* corresponding to p, A, b, covar for the full set of variables;
pext=[p, surplus], pext is mm, Aext is (k1+k2)xmm, bext (k1+k2), covext is mmxmm
*/
LM_REAL *lbext, *ubext; // corresponding to lb, ub for the full set of variables
int mm, ret, k12;
register int i, j, ii;
register LM_REAL tmp;
LM_REAL locinfo[LM_INFO_SZ];
if(!jacf){
fprintf(stderr, RCAT("No function specified for computing the Jacobian in ", LEVMAR_BLEIC_DER)
RCAT("().\nIf no such function is available, use ", LEVMAR_BLEIC_DIF) RCAT("() rather than ", LEVMAR_BLEIC_DER) "()\n");
return LM_ERROR;
}
if(!C || !d){
fprintf(stderr, RCAT(LCAT(LEVMAR_BLEIC_DER, "(): missing inequality constraints, use "), LEVMAR_BLEC_DER) "() in this case!\n");
return LM_ERROR;
}
if(!A || !b) k1=0; // sanity check
mm=m+k2;
if(n<m-k1){
fprintf(stderr, LCAT(LEVMAR_BLEIC_DER, "(): cannot solve a problem with fewer measurements + equality constraints [%d + %d] than unknowns [%d]\n"), n, k1, m);
return LM_ERROR;
}
k12=k1+k2;
ptr=(LM_REAL *)malloc((3*mm + k12*mm + k12 + n*m + (covar? mm*mm : 0))*sizeof(LM_REAL));
if(!ptr){
fprintf(stderr, LCAT(LEVMAR_BLEIC_DER, "(): memory allocation request failed\n"));
return LM_ERROR;
}
pext=ptr;
lbext=pext+mm;
ubext=lbext+mm;
Aext=ubext+mm;
bext=Aext+k12*mm;
data.jac=bext+k12;
covext=covar? data.jac+n*m : NULL;
data.nineqcnstr=k2;
data.func=func;
data.jacf=jacf;
data.adata=adata;
/* compute y s.t. C*p - y=d, i.e. y=C*p-d.
* y is stored in the last k2 elements of pext
*/
for(i=0; i<k2; ++i){
for(j=0, tmp=0.0; j<m; ++j)
tmp+=C[i*m+j]*p[j];
pext[j=i+m]=tmp-d[i];
/* surplus variables must be >=0 */
lbext[j]=0.0;
ubext[j]=LM_REAL_MAX;
}
/* set the first m elements of pext equal to p */
for(i=0; i<m; ++i){
pext[i]=p[i];
lbext[i]=lb? lb[i] : LM_REAL_MIN;
ubext[i]=ub? ub[i] : LM_REAL_MAX;
}
/* setup the constraints matrix */
/* original linear equation constraints */
for(i=0; i<k1; ++i){
for(j=0; j<m; ++j)
Aext[i*mm+j]=A[i*m+j];
for(j=m; j<mm; ++j)
Aext[i*mm+j]=0.0;
bext[i]=b[i];
}
/* linear equation constraints resulting from surplus variables */
for(i=0, ii=k1; i<k2; ++i, ++ii){
for(j=0; j<m; ++j)
Aext[ii*mm+j]=C[i*m+j];
for(j=m; j<mm; ++j)
Aext[ii*mm+j]=0.0;
Aext[ii*mm+m+i]=-1.0;
bext[ii]=d[i];
}
if(!info) info=locinfo; /* make sure that LEVMAR_BLEC_DER() is called with non-null info */
/* note that the default weights for the penalty terms are being used below */
ret=LEVMAR_BLEC_DER(LMBLEIC_FUNC, LMBLEIC_JACF, pext, x, mm, n, lbext, ubext, Aext, bext, k12, NULL, itmax, opts, info, work, covext, (void *)&data);
/* copy back the minimizer */
for(i=0; i<m; ++i)
p[i]=pext[i];
#if 0
printf("Surplus variables for the minimizer:\n");
for(i=m; i<mm; ++i)
printf("%g ", pext[i]);
printf("\n\n");
#endif
if(covar){
for(i=0; i<m; ++i){
for(j=0; j<m; ++j)
covar[i*m+j]=covext[i*mm+j];
}
}
free(ptr);
return ret;
}
/* Similar to the LEVMAR_BLEIC_DER() function above, except that the Jacobian is approximated
* with the aid of finite differences (forward or central, see the comment for the opts argument)
*/
int LEVMAR_BLEIC_DIF(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
LM_REAL *lb, /* I: vector of lower bounds. If NULL, no lower bounds apply */
LM_REAL *ub, /* I: vector of upper bounds. If NULL, no upper bounds apply */
LM_REAL *A, /* I: equality constraints matrix, k1xm. If NULL, no linear equation constraints apply */
LM_REAL *b, /* I: right hand constraints vector, k1x1 */
int k1, /* I: number of constraints (i.e. A's #rows) */
LM_REAL *C, /* I: inequality constraints matrix, k2xm */
LM_REAL *d, /* I: right hand constraints vector, k2x1 */
int k2, /* I: number of inequality constraints (i.e. C's #rows) */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[5], /* I: opts[0-3] = minim. options [\mu, \epsilon1, \epsilon2, \epsilon3, \delta]. Respectively the
* scale factor for initial \mu, stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2 and
* the step used in difference approximation to the Jacobian. Set to NULL for defaults to be used.
* If \delta<0, the Jacobian is approximated with central differences which are more accurate
* (but slower!) compared to the forward differences employed by default.
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_BLEIC_DIF_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func.
* Set to NULL if not needed
*/
{
struct LMBLEIC_DATA data;
LM_REAL *ptr, *pext, *Aext, *bext, *covext; /* corresponding to p, A, b, covar for the full set of variables;
pext=[p, surplus], pext is mm, Aext is (k1+k2)xmm, bext (k1+k2), covext is mmxmm
*/
LM_REAL *lbext, *ubext; // corresponding to lb, ub for the full set of variables
int mm, ret, k12;
register int i, j, ii;
register LM_REAL tmp;
LM_REAL locinfo[LM_INFO_SZ];
if(!C || !d){
fprintf(stderr, RCAT(LCAT(LEVMAR_BLEIC_DIF, "(): missing inequality constraints, use "), LEVMAR_BLEC_DIF) "() in this case!\n");
return LM_ERROR;
}
if(!A || !b) k1=0; // sanity check
mm=m+k2;
if(n<m-k1){
fprintf(stderr, LCAT(LEVMAR_BLEIC_DIF, "(): cannot solve a problem with fewer measurements + equality constraints [%d + %d] than unknowns [%d]\n"), n, k1, m);
return LM_ERROR;
}
k12=k1+k2;
ptr=(LM_REAL *)malloc((3*mm + k12*mm + k12 + (covar? mm*mm : 0))*sizeof(LM_REAL));
if(!ptr){
fprintf(stderr, LCAT(LEVMAR_BLEIC_DIF, "(): memory allocation request failed\n"));
return LM_ERROR;
}
pext=ptr;
lbext=pext+mm;
ubext=lbext+mm;
Aext=ubext+mm;
bext=Aext+k12*mm;
data.jac=NULL;
covext=covar? bext+k12 : NULL;
data.nineqcnstr=k2;
data.func=func;
data.jacf=NULL;
data.adata=adata;
/* compute y s.t. C*p - y=d, i.e. y=C*p-d.
* y is stored in the last k2 elements of pext
*/
for(i=0; i<k2; ++i){
for(j=0, tmp=0.0; j<m; ++j)
tmp+=C[i*m+j]*p[j];
pext[j=i+m]=tmp-d[i];
/* surplus variables must be >=0 */
lbext[j]=0.0;
ubext[j]=LM_REAL_MAX;
}
/* set the first m elements of pext equal to p */
for(i=0; i<m; ++i){
pext[i]=p[i];
lbext[i]=lb? lb[i] : LM_REAL_MIN;
ubext[i]=ub? ub[i] : LM_REAL_MAX;
}
/* setup the constraints matrix */
/* original linear equation constraints */
for(i=0; i<k1; ++i){
for(j=0; j<m; ++j)
Aext[i*mm+j]=A[i*m+j];
for(j=m; j<mm; ++j)
Aext[i*mm+j]=0.0;
bext[i]=b[i];
}
/* linear equation constraints resulting from surplus variables */
for(i=0, ii=k1; i<k2; ++i, ++ii){
for(j=0; j<m; ++j)
Aext[ii*mm+j]=C[i*m+j];
for(j=m; j<mm; ++j)
Aext[ii*mm+j]=0.0;
Aext[ii*mm+m+i]=-1.0;
bext[ii]=d[i];
}
if(!info) info=locinfo; /* make sure that LEVMAR_BLEC_DIF() is called with non-null info */
/* note that the default weights for the penalty terms are being used below */
ret=LEVMAR_BLEC_DIF(LMBLEIC_FUNC, pext, x, mm, n, lbext, ubext, Aext, bext, k12, NULL, itmax, opts, info, work, covext, (void *)&data);
/* copy back the minimizer */
for(i=0; i<m; ++i)
p[i]=pext[i];
#if 0
printf("Surplus variables for the minimizer:\n");
for(i=m; i<mm; ++i)
printf("%g ", pext[i]);
printf("\n\n");
#endif
if(covar){
for(i=0; i<m; ++i){
for(j=0; j<m; ++j)
covar[i*m+j]=covext[i*mm+j];
}
}
free(ptr);
return ret;
}
/* convenience wrappers to LEVMAR_BLEIC_DER/LEVMAR_BLEIC_DIF */
/* box & linear inequality constraints */
int LEVMAR_BLIC_DER(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata),
LM_REAL *p, LM_REAL *x, int m, int n,
LM_REAL *lb, LM_REAL *ub,
LM_REAL *C, LM_REAL *d, int k2,
int itmax, LM_REAL opts[4], LM_REAL info[LM_INFO_SZ], LM_REAL *work, LM_REAL *covar, void *adata)
{
return LEVMAR_BLEIC_DER(func, jacf, p, x, m, n, lb, ub, NULL, NULL, 0, C, d, k2, itmax, opts, info, work, covar, adata);
}
int LEVMAR_BLIC_DIF(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
LM_REAL *p, LM_REAL *x, int m, int n,
LM_REAL *lb, LM_REAL *ub,
LM_REAL *C, LM_REAL *d, int k2,
int itmax, LM_REAL opts[5], LM_REAL info[LM_INFO_SZ], LM_REAL *work, LM_REAL *covar, void *adata)
{
return LEVMAR_BLEIC_DIF(func, p, x, m, n, lb, ub, NULL, NULL, 0, C, d, k2, itmax, opts, info, work, covar, adata);
}
/* linear equation & inequality constraints */
int LEVMAR_LEIC_DER(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata),
LM_REAL *p, LM_REAL *x, int m, int n,
LM_REAL *A, LM_REAL *b, int k1,
LM_REAL *C, LM_REAL *d, int k2,
int itmax, LM_REAL opts[4], LM_REAL info[LM_INFO_SZ], LM_REAL *work, LM_REAL *covar, void *adata)
{
return LEVMAR_BLEIC_DER(func, jacf, p, x, m, n, NULL, NULL, A, b, k1, C, d, k2, itmax, opts, info, work, covar, adata);
}
int LEVMAR_LEIC_DIF(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
LM_REAL *p, LM_REAL *x, int m, int n,
LM_REAL *A, LM_REAL *b, int k1,
LM_REAL *C, LM_REAL *d, int k2,
int itmax, LM_REAL opts[5], LM_REAL info[LM_INFO_SZ], LM_REAL *work, LM_REAL *covar, void *adata)
{
return LEVMAR_BLEIC_DIF(func, p, x, m, n, NULL, NULL, A, b, k1, C, d, k2, itmax, opts, info, work, covar, adata);
}
/* linear inequality constraints */
int LEVMAR_LIC_DER(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata),
LM_REAL *p, LM_REAL *x, int m, int n,
LM_REAL *C, LM_REAL *d, int k2,
int itmax, LM_REAL opts[4], LM_REAL info[LM_INFO_SZ], LM_REAL *work, LM_REAL *covar, void *adata)
{
return LEVMAR_BLEIC_DER(func, jacf, p, x, m, n, NULL, NULL, NULL, NULL, 0, C, d, k2, itmax, opts, info, work, covar, adata);
}
int LEVMAR_LIC_DIF(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
LM_REAL *p, LM_REAL *x, int m, int n,
LM_REAL *C, LM_REAL *d, int k2,
int itmax, LM_REAL opts[5], LM_REAL info[LM_INFO_SZ], LM_REAL *work, LM_REAL *covar, void *adata)
{
return LEVMAR_BLEIC_DIF(func, p, x, m, n, NULL, NULL, NULL, NULL, 0, C, d, k2, itmax, opts, info, work, covar, adata);
}
/* undefine all. THIS MUST REMAIN AT THE END OF THE FILE */
#undef LMBLEIC_DATA
#undef LMBLEIC_ELIM
#undef LMBLEIC_FUNC
#undef LMBLEIC_JACF
#undef LEVMAR_FDIF_FORW_JAC_APPROX
#undef LEVMAR_COVAR
#undef LEVMAR_TRANS_MAT_MAT_MULT
#undef LEVMAR_BLEIC_DER
#undef LEVMAR_BLEIC_DIF
#undef LEVMAR_BLIC_DER
#undef LEVMAR_BLIC_DIF
#undef LEVMAR_LEIC_DER
#undef LEVMAR_LEIC_DIF
#undef LEVMAR_LIC_DER
#undef LEVMAR_LIC_DIF
#undef LEVMAR_BLEC_DER
#undef LEVMAR_BLEC_DIF

View File

@@ -1,80 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004-05 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/*******************************************************************************
* Wrappers for linearly constrained Levenberg-Marquardt minimization. The same
* core code is used with appropriate #defines to derive single and double
* precision versions, see also lmlec_core.c
*******************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include "levmar.h"
#include "misc.h"
#ifndef HAVE_LAPACK
#ifdef _MSC_VER
#pragma message("Linearly constrained optimization requires LAPACK and was not compiled!")
#else
#warning Linearly constrained optimization requires LAPACK and was not compiled!
#endif // _MSC_VER
#else // LAPACK present
#if !defined(LM_DBL_PREC) && !defined(LM_SNGL_PREC)
#error At least one of LM_DBL_PREC, LM_SNGL_PREC should be defined!
#endif
#ifdef LM_SNGL_PREC
/* single precision (float) definitions */
#define LM_REAL float
#define LM_PREFIX s
#define __SUBCNST(x) x##F
#define LM_CNST(x) __SUBCNST(x) // force substitution
#include "lmlec_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef __SUBCNST
#undef LM_CNST
#endif /* LM_SNGL_PREC */
#ifdef LM_DBL_PREC
/* double precision definitions */
#define LM_REAL double
#define LM_PREFIX d
#define LM_CNST(x) (x)
#include "lmlec_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_CNST
#endif /* LM_DBL_PREC */
#endif /* HAVE_LAPACK */

View File

@@ -1,656 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004-05 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
#ifndef LM_REAL // not included by lmlec.c
#error This file should not be compiled directly!
#endif
/* precision-specific definitions */
#define LMLEC_DATA LM_ADD_PREFIX(lmlec_data)
#define LMLEC_ELIM LM_ADD_PREFIX(lmlec_elim)
#define LMLEC_FUNC LM_ADD_PREFIX(lmlec_func)
#define LMLEC_JACF LM_ADD_PREFIX(lmlec_jacf)
#define LEVMAR_LEC_DER LM_ADD_PREFIX(levmar_lec_der)
#define LEVMAR_LEC_DIF LM_ADD_PREFIX(levmar_lec_dif)
#define LEVMAR_DER LM_ADD_PREFIX(levmar_der)
#define LEVMAR_DIF LM_ADD_PREFIX(levmar_dif)
#define LEVMAR_TRANS_MAT_MAT_MULT LM_ADD_PREFIX(levmar_trans_mat_mat_mult)
#define LEVMAR_COVAR LM_ADD_PREFIX(levmar_covar)
#define LEVMAR_FDIF_FORW_JAC_APPROX LM_ADD_PREFIX(levmar_fdif_forw_jac_approx)
#define GEQP3 LM_MK_LAPACK_NAME(geqp3)
#define ORGQR LM_MK_LAPACK_NAME(orgqr)
#define TRTRI LM_MK_LAPACK_NAME(trtri)
struct LMLEC_DATA{
LM_REAL *c, *Z, *p, *jac;
int ncnstr;
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata);
void (*jacf)(LM_REAL *p, LM_REAL *jac, int m, int n, void *adata);
void *adata;
};
/* prototypes for LAPACK routines */
#ifdef __cplusplus
extern "C" {
#endif
extern int GEQP3(int *m, int *n, LM_REAL *a, int *lda, int *jpvt,
LM_REAL *tau, LM_REAL *work, int *lwork, int *info);
extern int ORGQR(int *m, int *n, int *k, LM_REAL *a, int *lda, LM_REAL *tau,
LM_REAL *work, int *lwork, int *info);
extern int TRTRI(char *uplo, char *diag, int *n, LM_REAL *a, int *lda, int *info);
#ifdef __cplusplus
}
#endif
/*
* This function implements an elimination strategy for linearly constrained
* optimization problems. The strategy relies on QR decomposition to transform
* an optimization problem constrained by Ax=b to an equivalent, unconstrained
* one. Also referred to as "null space" or "reduced Hessian" method.
* See pp. 430-433 (chap. 15) of "Numerical Optimization" by Nocedal-Wright
* for details.
*
* A is mxn with m<=n and rank(A)=m
* Two matrices Y and Z of dimensions nxm and nx(n-m) are computed from A^T so that
* their columns are orthonormal and every x can be written as x=Y*b + Z*x_z=
* c + Z*x_z, where c=Y*b is a fixed vector of dimension n and x_z is an
* arbitrary vector of dimension n-m. Then, the problem of minimizing f(x)
* subject to Ax=b is equivalent to minimizing f(c + Z*x_z) with no constraints.
* The computed Y and Z are such that any solution of Ax=b can be written as
* x=Y*x_y + Z*x_z for some x_y, x_z. Furthermore, A*Y is nonsingular, A*Z=0
* and Z spans the null space of A.
*
* The function accepts A, b and computes c, Y, Z. If b or c is NULL, c is not
* computed. Also, Y can be NULL in which case it is not referenced.
* The function returns LM_ERROR in case of error, A's computed rank if successful
*
*/
static int LMLEC_ELIM(LM_REAL *A, LM_REAL *b, LM_REAL *c, LM_REAL *Y, LM_REAL *Z, int m, int n)
{
static LM_REAL eps=LM_CNST(-1.0);
LM_REAL *buf=NULL;
LM_REAL *a, *tau, *work, *r, aux;
register LM_REAL tmp;
int a_sz, jpvt_sz, tau_sz, r_sz, Y_sz, worksz;
int info, rank, *jpvt, tot_sz, mintmn, tm, tn;
register int i, j, k;
if(m>n){
fprintf(stderr, RCAT("matrix of constraints cannot have more rows than columns in", LMLEC_ELIM) "()!\n");
return LM_ERROR;
}
tm=n; tn=m; // transpose dimensions
mintmn=m;
/* calculate required memory size */
worksz=-1; // workspace query. Optimal work size is returned in aux
//ORGQR((int *)&tm, (int *)&tm, (int *)&mintmn, NULL, (int *)&tm, NULL, (LM_REAL *)&aux, &worksz, &info);
GEQP3((int *)&tm, (int *)&tn, NULL, (int *)&tm, NULL, NULL, (LM_REAL *)&aux, (int *)&worksz, &info);
worksz=(int)aux;
a_sz=tm*tm; // tm*tn is enough for xgeqp3()
jpvt_sz=tn;
tau_sz=mintmn;
r_sz=mintmn*mintmn; // actually smaller if a is not of full row rank
Y_sz=(Y)? 0 : tm*tn;
tot_sz=(a_sz + tau_sz + r_sz + worksz + Y_sz)*sizeof(LM_REAL) + jpvt_sz*sizeof(int); /* should be arranged in that order for proper doubles alignment */
buf=(LM_REAL *)malloc(tot_sz); /* allocate a "big" memory chunk at once */
if(!buf){
fprintf(stderr, RCAT("Memory allocation request failed in ", LMLEC_ELIM) "()\n");
return LM_ERROR;
}
a=buf;
tau=a+a_sz;
r=tau+tau_sz;
work=r+r_sz;
if(!Y){
Y=work+worksz;
jpvt=(int *)(Y+Y_sz);
}
else
jpvt=(int *)(work+worksz);
/* copy input array so that LAPACK won't destroy it. Note that copying is
* done in row-major order, which equals A^T in column-major
*/
for(i=0; i<tm*tn; ++i)
a[i]=A[i];
/* clear jpvt */
for(i=0; i<jpvt_sz; ++i) jpvt[i]=0;
/* rank revealing QR decomposition of A^T*/
GEQP3((int *)&tm, (int *)&tn, a, (int *)&tm, jpvt, tau, work, (int *)&worksz, &info);
//dgeqpf_((int *)&tm, (int *)&tn, a, (int *)&tm, jpvt, tau, work, &info);
/* error checking */
if(info!=0){
if(info<0){
fprintf(stderr, RCAT(RCAT("LAPACK error: illegal value for argument %d of ", GEQP3) " in ", LMLEC_ELIM) "()\n", -info);
}
else if(info>0){
fprintf(stderr, RCAT(RCAT("unknown LAPACK error (%d) for ", GEQP3) " in ", LMLEC_ELIM) "()\n", info);
}
free(buf);
return LM_ERROR;
}
/* the upper triangular part of a now contains the upper triangle of the unpermuted R */
if(eps<0.0){
LM_REAL aux;
/* compute machine epsilon. DBL_EPSILON should do also */
for(eps=LM_CNST(1.0); aux=eps+LM_CNST(1.0), aux-LM_CNST(1.0)>0.0; eps*=LM_CNST(0.5))
;
eps*=LM_CNST(2.0);
}
tmp=tm*LM_CNST(10.0)*eps*FABS(a[0]); // threshold. tm is max(tm, tn)
tmp=(tmp>LM_CNST(1E-12))? tmp : LM_CNST(1E-12); // ensure that threshold is not too small
/* compute A^T's numerical rank by counting the non-zeros in R's diagonal */
for(i=rank=0; i<mintmn; ++i)
if(a[i*(tm+1)]>tmp || a[i*(tm+1)]<-tmp) ++rank; /* loop across R's diagonal elements */
else break; /* diagonal is arranged in absolute decreasing order */
if(rank<tn){
fprintf(stderr, RCAT("\nConstraints matrix in ", LMLEC_ELIM) "() is not of full row rank (i.e. %d < %d)!\n"
"Make sure that you do not specify redundant or inconsistent constraints.\n\n", rank, tn);
free(buf);
return LM_ERROR;
}
/* compute the permuted inverse transpose of R */
/* first, copy R from the upper triangular part of a to the lower part of r (thus transposing it). R is rank x rank */
for(j=0; j<rank; ++j){
for(i=0; i<=j; ++i)
r[j+i*rank]=a[i+j*tm];
for(i=j+1; i<rank; ++i)
r[j+i*rank]=0.0; // upper part is zero
}
/* r now contains R^T */
/* compute the inverse */
TRTRI("L", "N", (int *)&rank, r, (int *)&rank, &info);
/* error checking */
if(info!=0){
if(info<0){
fprintf(stderr, RCAT(RCAT("LAPACK error: illegal value for argument %d of ", TRTRI) " in ", LMLEC_ELIM) "()\n", -info);
}
else if(info>0){
fprintf(stderr, RCAT(RCAT("A(%d, %d) is exactly zero for ", TRTRI) " (singular matrix) in ", LMLEC_ELIM) "()\n", info, info);
}
free(buf);
return LM_ERROR;
}
/* finally, permute R^-T using Y as intermediate storage */
for(j=0; j<rank; ++j)
for(i=0, k=jpvt[j]-1; i<rank; ++i)
Y[i+k*rank]=r[i+j*rank];
for(i=0; i<rank*rank; ++i) // copy back to r
r[i]=Y[i];
/* resize a to be tm x tm, filling with zeroes */
for(i=tm*tn; i<tm*tm; ++i)
a[i]=0.0;
/* compute Q in a as the product of elementary reflectors. Q is tm x tm */
ORGQR((int *)&tm, (int *)&tm, (int *)&mintmn, a, (int *)&tm, tau, work, &worksz, &info);
/* error checking */
if(info!=0){
if(info<0){
fprintf(stderr, RCAT(RCAT("LAPACK error: illegal value for argument %d of ", ORGQR) " in ", LMLEC_ELIM) "()\n", -info);
}
else if(info>0){
fprintf(stderr, RCAT(RCAT("unknown LAPACK error (%d) for ", ORGQR) " in ", LMLEC_ELIM) "()\n", info);
}
free(buf);
return LM_ERROR;
}
/* compute Y=Q_1*R^-T*P^T. Y is tm x rank */
for(i=0; i<tm; ++i)
for(j=0; j<rank; ++j){
for(k=0, tmp=0.0; k<rank; ++k)
tmp+=a[i+k*tm]*r[k+j*rank];
Y[i*rank+j]=tmp;
}
if(b && c){
/* compute c=Y*b */
for(i=0; i<tm; ++i){
for(j=0, tmp=0.0; j<rank; ++j)
tmp+=Y[i*rank+j]*b[j];
c[i]=tmp;
}
}
/* copy Q_2 into Z. Z is tm x (tm-rank) */
for(j=0; j<tm-rank; ++j)
for(i=0, k=j+rank; i<tm; ++i)
Z[i*(tm-rank)+j]=a[i+k*tm];
free(buf);
return rank;
}
/* constrained measurements: given pp, compute the measurements at c + Z*pp */
static void LMLEC_FUNC(LM_REAL *pp, LM_REAL *hx, int mm, int n, void *adata)
{
struct LMLEC_DATA *data=(struct LMLEC_DATA *)adata;
int m;
register int i, j;
register LM_REAL sum;
LM_REAL *c, *Z, *p, *Zimm;
m=mm+data->ncnstr;
c=data->c;
Z=data->Z;
p=data->p;
/* p=c + Z*pp */
for(i=0; i<m; ++i){
Zimm=Z+i*mm;
for(j=0, sum=c[i]; j<mm; ++j)
sum+=Zimm[j]*pp[j]; // sum+=Z[i*mm+j]*pp[j];
p[i]=sum;
}
(*(data->func))(p, hx, m, n, data->adata);
}
/* constrained Jacobian: given pp, compute the Jacobian at c + Z*pp
* Using the chain rule, the Jacobian with respect to pp equals the
* product of the Jacobian with respect to p (at c + Z*pp) times Z
*/
static void LMLEC_JACF(LM_REAL *pp, LM_REAL *jacjac, int mm, int n, void *adata)
{
struct LMLEC_DATA *data=(struct LMLEC_DATA *)adata;
int m;
register int i, j, l;
register LM_REAL sum, *aux1, *aux2;
LM_REAL *c, *Z, *p, *jac;
m=mm+data->ncnstr;
c=data->c;
Z=data->Z;
p=data->p;
jac=data->jac;
/* p=c + Z*pp */
for(i=0; i<m; ++i){
aux1=Z+i*mm;
for(j=0, sum=c[i]; j<mm; ++j)
sum+=aux1[j]*pp[j]; // sum+=Z[i*mm+j]*pp[j];
p[i]=sum;
}
(*(data->jacf))(p, jac, m, n, data->adata);
/* compute jac*Z in jacjac */
if(n*m<=__BLOCKSZ__SQ){ // this is a small problem
/* This is the straightforward way to compute jac*Z. However, due to
* its noncontinuous memory access pattern, it incures many cache misses when
* applied to large minimization problems (i.e. problems involving a large
* number of free variables and measurements), in which jac is too large to
* fit in the L1 cache. For such problems, a cache-efficient blocking scheme
* is preferable. On the other hand, the straightforward algorithm is faster
* on small problems since in this case it avoids the overheads of blocking.
*/
for(i=0; i<n; ++i){
aux1=jac+i*m;
aux2=jacjac+i*mm;
for(j=0; j<mm; ++j){
for(l=0, sum=0.0; l<m; ++l)
sum+=aux1[l]*Z[l*mm+j]; // sum+=jac[i*m+l]*Z[l*mm+j];
aux2[j]=sum; // jacjac[i*mm+j]=sum;
}
}
}
else{ // this is a large problem
/* Cache efficient computation of jac*Z based on blocking
*/
#define __MIN__(x, y) (((x)<=(y))? (x) : (y))
register int jj, ll;
for(jj=0; jj<mm; jj+=__BLOCKSZ__){
for(i=0; i<n; ++i){
aux1=jacjac+i*mm;
for(j=jj; j<__MIN__(jj+__BLOCKSZ__, mm); ++j)
aux1[j]=0.0; //jacjac[i*mm+j]=0.0;
}
for(ll=0; ll<m; ll+=__BLOCKSZ__){
for(i=0; i<n; ++i){
aux1=jacjac+i*mm; aux2=jac+i*m;
for(j=jj; j<__MIN__(jj+__BLOCKSZ__, mm); ++j){
sum=0.0;
for(l=ll; l<__MIN__(ll+__BLOCKSZ__, m); ++l)
sum+=aux2[l]*Z[l*mm+j]; //jac[i*m+l]*Z[l*mm+j];
aux1[j]+=sum; //jacjac[i*mm+j]+=sum;
}
}
}
}
}
}
#undef __MIN__
/*
* This function is similar to LEVMAR_DER except that the minimization
* is performed subject to the linear constraints A p=b, A is kxm, b kx1
*
* This function requires an analytic Jacobian. In case the latter is unavailable,
* use LEVMAR_LEC_DIF() bellow
*
*/
int LEVMAR_LEC_DER(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata), /* function to evaluate the Jacobian \part x / \part p */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
LM_REAL *A, /* I: constraints matrix, kxm */
LM_REAL *b, /* I: right hand constraints vector, kx1 */
int k, /* I: number of constraints (i.e. A's #rows) */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[4], /* I: minim. options [\mu, \epsilon1, \epsilon2, \epsilon3]. Respectively the scale factor for initial \mu,
* stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2. Set to NULL for defaults to be used
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_LEC_DER_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func & jacf.
* Set to NULL if not needed
*/
{
struct LMLEC_DATA data;
LM_REAL *ptr, *Z, *pp, *p0, *Zimm; /* Z is mxmm */
int mm, ret;
register int i, j;
register LM_REAL tmp;
LM_REAL locinfo[LM_INFO_SZ];
if(!jacf){
fprintf(stderr, RCAT("No function specified for computing the Jacobian in ", LEVMAR_LEC_DER)
RCAT("().\nIf no such function is available, use ", LEVMAR_LEC_DIF) RCAT("() rather than ", LEVMAR_LEC_DER) "()\n");
return LM_ERROR;
}
mm=m-k;
if(n<mm){
fprintf(stderr, LCAT(LEVMAR_LEC_DER, "(): cannot solve a problem with fewer measurements + equality constraints [%d + %d] than unknowns [%d]\n"), n, k, m);
return LM_ERROR;
}
ptr=(LM_REAL *)malloc((2*m + m*mm + n*m + mm)*sizeof(LM_REAL));
if(!ptr){
fprintf(stderr, LCAT(LEVMAR_LEC_DER, "(): memory allocation request failed\n"));
return LM_ERROR;
}
data.p=p;
p0=ptr;
data.c=p0+m;
data.Z=Z=data.c+m;
data.jac=data.Z+m*mm;
pp=data.jac+n*m;
data.ncnstr=k;
data.func=func;
data.jacf=jacf;
data.adata=adata;
ret=LMLEC_ELIM(A, b, data.c, NULL, Z, k, m); // compute c, Z
if(ret==LM_ERROR){
free(ptr);
return LM_ERROR;
}
/* compute pp s.t. p = c + Z*pp or (Z^T Z)*pp=Z^T*(p-c)
* Due to orthogonality, Z^T Z = I and the last equation
* becomes pp=Z^T*(p-c). Also, save the starting p in p0
*/
for(i=0; i<m; ++i){
p0[i]=p[i];
p[i]-=data.c[i];
}
/* Z^T*(p-c) */
for(i=0; i<mm; ++i){
for(j=0, tmp=0.0; j<m; ++j)
tmp+=Z[j*mm+i]*p[j];
pp[i]=tmp;
}
/* compute the p corresponding to pp (i.e. c + Z*pp) and compare with p0 */
for(i=0; i<m; ++i){
Zimm=Z+i*mm;
for(j=0, tmp=data.c[i]; j<mm; ++j)
tmp+=Zimm[j]*pp[j]; // tmp+=Z[i*mm+j]*pp[j];
if(FABS(tmp-p0[i])>LM_CNST(1E-03))
fprintf(stderr, RCAT("Warning: component %d of starting point not feasible in ", LEVMAR_LEC_DER) "()! [%.10g reset to %.10g]\n",
i, p0[i], tmp);
}
if(!info) info=locinfo; /* make sure that LEVMAR_DER() is called with non-null info */
/* note that covariance computation is not requested from LEVMAR_DER() */
ret=LEVMAR_DER(LMLEC_FUNC, LMLEC_JACF, pp, x, mm, n, itmax, opts, info, work, NULL, (void *)&data);
/* p=c + Z*pp */
for(i=0; i<m; ++i){
Zimm=Z+i*mm;
for(j=0, tmp=data.c[i]; j<mm; ++j)
tmp+=Zimm[j]*pp[j]; // tmp+=Z[i*mm+j]*pp[j];
p[i]=tmp;
}
/* compute the covariance from the Jacobian in data.jac */
if(covar){
LEVMAR_TRANS_MAT_MAT_MULT(data.jac, covar, n, m); /* covar = J^T J */
LEVMAR_COVAR(covar, covar, info[1], m, n);
}
free(ptr);
return ret;
}
/* Similar to the LEVMAR_LEC_DER() function above, except that the Jacobian is approximated
* with the aid of finite differences (forward or central, see the comment for the opts argument)
*/
int LEVMAR_LEC_DIF(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata), /* functional relation describing measurements. A p \in R^m yields a \hat{x} \in R^n */
LM_REAL *p, /* I/O: initial parameter estimates. On output has the estimated solution */
LM_REAL *x, /* I: measurement vector. NULL implies a zero vector */
int m, /* I: parameter vector dimension (i.e. #unknowns) */
int n, /* I: measurement vector dimension */
LM_REAL *A, /* I: constraints matrix, kxm */
LM_REAL *b, /* I: right hand constraints vector, kx1 */
int k, /* I: number of constraints (i.e. A's #rows) */
int itmax, /* I: maximum number of iterations */
LM_REAL opts[5], /* I: opts[0-3] = minim. options [\mu, \epsilon1, \epsilon2, \epsilon3, \delta]. Respectively the
* scale factor for initial \mu, stopping thresholds for ||J^T e||_inf, ||Dp||_2 and ||e||_2 and
* the step used in difference approximation to the Jacobian. Set to NULL for defaults to be used.
* If \delta<0, the Jacobian is approximated with central differences which are more accurate
* (but slower!) compared to the forward differences employed by default.
*/
LM_REAL info[LM_INFO_SZ],
/* O: information regarding the minimization. Set to NULL if don't care
* info[0]= ||e||_2 at initial p.
* info[1-4]=[ ||e||_2, ||J^T e||_inf, ||Dp||_2, mu/max[J^T J]_ii ], all computed at estimated p.
* info[5]= # iterations,
* info[6]=reason for terminating: 1 - stopped by small gradient J^T e
* 2 - stopped by small Dp
* 3 - stopped by itmax
* 4 - singular matrix. Restart from current p with increased mu
* 5 - no further error reduction is possible. Restart with increased mu
* 6 - stopped by small ||e||_2
* 7 - stopped by invalid (i.e. NaN or Inf) "func" values. This is a user error
* info[7]= # function evaluations
* info[8]= # Jacobian evaluations
* info[9]= # linear systems solved, i.e. # attempts for reducing error
*/
LM_REAL *work, /* working memory at least LM_LEC_DIF_WORKSZ() reals large, allocated if NULL */
LM_REAL *covar, /* O: Covariance matrix corresponding to LS solution; mxm. Set to NULL if not needed. */
void *adata) /* pointer to possibly additional data, passed uninterpreted to func.
* Set to NULL if not needed
*/
{
struct LMLEC_DATA data;
LM_REAL *ptr, *Z, *pp, *p0, *Zimm; /* Z is mxmm */
int mm, ret;
register int i, j;
register LM_REAL tmp;
LM_REAL locinfo[LM_INFO_SZ];
mm=m-k;
if(n<mm){
fprintf(stderr, LCAT(LEVMAR_LEC_DIF, "(): cannot solve a problem with fewer measurements + equality constraints [%d + %d] than unknowns [%d]\n"), n, k, m);
return LM_ERROR;
}
ptr=(LM_REAL *)malloc((2*m + m*mm + mm)*sizeof(LM_REAL));
if(!ptr){
fprintf(stderr, LCAT(LEVMAR_LEC_DIF, "(): memory allocation request failed\n"));
return LM_ERROR;
}
data.p=p;
p0=ptr;
data.c=p0+m;
data.Z=Z=data.c+m;
data.jac=NULL;
pp=data.Z+m*mm;
data.ncnstr=k;
data.func=func;
data.jacf=NULL;
data.adata=adata;
ret=LMLEC_ELIM(A, b, data.c, NULL, Z, k, m); // compute c, Z
if(ret==LM_ERROR){
free(ptr);
return LM_ERROR;
}
/* compute pp s.t. p = c + Z*pp or (Z^T Z)*pp=Z^T*(p-c)
* Due to orthogonality, Z^T Z = I and the last equation
* becomes pp=Z^T*(p-c). Also, save the starting p in p0
*/
for(i=0; i<m; ++i){
p0[i]=p[i];
p[i]-=data.c[i];
}
/* Z^T*(p-c) */
for(i=0; i<mm; ++i){
for(j=0, tmp=0.0; j<m; ++j)
tmp+=Z[j*mm+i]*p[j];
pp[i]=tmp;
}
/* compute the p corresponding to pp (i.e. c + Z*pp) and compare with p0 */
for(i=0; i<m; ++i){
Zimm=Z+i*mm;
for(j=0, tmp=data.c[i]; j<mm; ++j)
tmp+=Zimm[j]*pp[j]; // tmp+=Z[i*mm+j]*pp[j];
if(FABS(tmp-p0[i])>LM_CNST(1E-03))
fprintf(stderr, RCAT("Warning: component %d of starting point not feasible in ", LEVMAR_LEC_DIF) "()! [%.10g reset to %.10g]\n",
i, p0[i], tmp);
}
if(!info) info=locinfo; /* make sure that LEVMAR_DIF() is called with non-null info */
/* note that covariance computation is not requested from LEVMAR_DIF() */
ret=LEVMAR_DIF(LMLEC_FUNC, pp, x, mm, n, itmax, opts, info, work, NULL, (void *)&data);
/* p=c + Z*pp */
for(i=0; i<m; ++i){
Zimm=Z+i*mm;
for(j=0, tmp=data.c[i]; j<mm; ++j)
tmp+=Zimm[j]*pp[j]; // tmp+=Z[i*mm+j]*pp[j];
p[i]=tmp;
}
/* compute the Jacobian with finite differences and use it to estimate the covariance */
if(covar){
LM_REAL *hx, *wrk, *jac;
hx=(LM_REAL *)malloc((2*n+n*m)*sizeof(LM_REAL));
if(!hx){
fprintf(stderr, LCAT(LEVMAR_LEC_DIF, "(): memory allocation request failed\n"));
free(ptr);
return LM_ERROR;
}
wrk=hx+n;
jac=wrk+n;
(*func)(p, hx, m, n, adata); /* evaluate function at p */
LEVMAR_FDIF_FORW_JAC_APPROX(func, p, hx, wrk, (LM_REAL)LM_DIFF_DELTA, jac, m, n, adata); /* compute the Jacobian at p */
LEVMAR_TRANS_MAT_MAT_MULT(jac, covar, n, m); /* covar = J^T J */
LEVMAR_COVAR(covar, covar, info[1], m, n);
free(hx);
}
free(ptr);
return ret;
}
/* undefine all. THIS MUST REMAIN AT THE END OF THE FILE */
#undef LMLEC_DATA
#undef LMLEC_ELIM
#undef LMLEC_FUNC
#undef LMLEC_JACF
#undef LEVMAR_FDIF_FORW_JAC_APPROX
#undef LEVMAR_COVAR
#undef LEVMAR_TRANS_MAT_MAT_MULT
#undef LEVMAR_LEC_DER
#undef LEVMAR_LEC_DIF
#undef LEVMAR_DER
#undef LEVMAR_DIF
#undef GEQP3
#undef ORGQR
#undef TRTRI

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@@ -1,70 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004-05 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
/********************************************************************************
* Miscelaneous functions for Levenberg-Marquardt nonlinear minimization. The
* same core code is used with appropriate #defines to derive single and double
* precision versions, see also misc_core.c
********************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include "levmar.h"
#include "misc.h"
#if !defined(LM_DBL_PREC) && !defined(LM_SNGL_PREC)
#error At least one of LM_DBL_PREC, LM_SNGL_PREC should be defined!
#endif
#ifdef LM_SNGL_PREC
/* single precision (float) definitions */
#define LM_REAL float
#define LM_PREFIX s
#define LM_REAL_EPSILON FLT_EPSILON
#define __SUBCNST(x) x##F
#define LM_CNST(x) __SUBCNST(x) // force substitution
#include "misc_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_EPSILON
#undef __SUBCNST
#undef LM_CNST
#endif /* LM_SNGL_PREC */
#ifdef LM_DBL_PREC
/* double precision definitions */
#define LM_REAL double
#define LM_PREFIX d
#define LM_REAL_EPSILON DBL_EPSILON
#define LM_CNST(x) (x)
#include "misc_core.c" // read in core code
#undef LM_REAL
#undef LM_PREFIX
#undef LM_REAL_EPSILON
#undef LM_CNST
#endif /* LM_DBL_PREC */

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@@ -1,114 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
#ifndef _MISC_H_
#define _MISC_H_
/* common suffix for LAPACK subroutines. Define empty in case of no prefix. */
#define LM_LAPACK_SUFFIX _
//#define LM_LAPACK_SUFFIX // define empty
/* common prefix for BLAS subroutines. Leave undefined in case of no prefix.
* You might also need to modify LM_BLAS_PREFIX below
*/
/* f2c'd BLAS */
//#define LM_BLAS_PREFIX f2c_
/* C BLAS */
//#define LM_BLAS_PREFIX cblas_
/* common suffix for BLAS subroutines */
//#define LM_BLAS_SUFFIX // define empty if a f2c_ or cblas_ prefix was defined for LM_BLAS_PREFIX above
#define LM_BLAS_SUFFIX _ // use this in case of no BLAS prefix
#define LCAT_(a, b) #a b
#define LCAT(a, b) LCAT_(a, b) // force substitution
#define RCAT_(a, b) a #b
#define RCAT(a, b) RCAT_(a, b) // force substitution
#define LM_MK_LAPACK_NAME(s) LM_ADD_PREFIX(LM_CAT_(s, LM_LAPACK_SUFFIX))
#ifdef LM_BLAS_PREFIX
#define LM_MK_BLAS_NAME(s) LM_CAT_(LM_BLAS_PREFIX, LM_ADD_PREFIX(LM_CAT_(s, LM_BLAS_SUFFIX)))
#else
#define LM_MK_BLAS_NAME(s) LM_ADD_PREFIX(LM_CAT_(s, LM_BLAS_SUFFIX))
#endif
#define __BLOCKSZ__ 32 /* block size for cache-friendly matrix-matrix multiply. It should be
* such that __BLOCKSZ__^2*sizeof(LM_REAL) is smaller than the CPU (L1)
* data cache size. Notice that a value of 32 when LM_REAL=double assumes
* an 8Kb L1 data cache (32*32*8=8K). This is a concervative choice since
* newer Pentium 4s have a L1 data cache of size 16K, capable of holding
* up to 45x45 double blocks.
*/
#define __BLOCKSZ__SQ (__BLOCKSZ__)*(__BLOCKSZ__)
/* add a prefix in front of a token */
#define LM_CAT__(a, b) a ## b
#define LM_CAT_(a, b) LM_CAT__(a, b) // force substitution
#define LM_ADD_PREFIX(s) LM_CAT_(LM_PREFIX, s)
#define FABS(x) (((x)>=0.0)? (x) : -(x))
#ifdef __cplusplus
extern "C" {
#endif
/* blocking-based matrix multiply */
extern void slevmar_trans_mat_mat_mult(float *a, float *b, int n, int m);
extern void dlevmar_trans_mat_mat_mult(double *a, double *b, int n, int m);
/* forward finite differences */
extern void slevmar_fdif_forw_jac_approx(void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *hx, float *hxx, float delta,
float *jac, int m, int n, void *adata);
extern void dlevmar_fdif_forw_jac_approx(void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *hx, double *hxx, double delta,
double *jac, int m, int n, void *adata);
/* central finite differences */
extern void slevmar_fdif_cent_jac_approx(void (*func)(float *p, float *hx, int m, int n, void *adata),
float *p, float *hxm, float *hxp, float delta,
float *jac, int m, int n, void *adata);
extern void dlevmar_fdif_cent_jac_approx(void (*func)(double *p, double *hx, int m, int n, void *adata),
double *p, double *hxm, double *hxp, double delta,
double *jac, int m, int n, void *adata);
/* e=x-y and ||e|| */
extern float slevmar_L2nrmxmy(float *e, float *x, float *y, int n);
extern double dlevmar_L2nrmxmy(double *e, double *x, double *y, int n);
/* covariance of LS fit */
extern int slevmar_covar(float *JtJ, float *C, float sumsq, int m, int n);
extern int dlevmar_covar(double *JtJ, double *C, double sumsq, int m, int n);
/* box constraints consistency check */
extern int slevmar_box_check(float *lb, float *ub, int m);
extern int dlevmar_box_check(double *lb, double *ub, int m);
/* Cholesky */
extern int slevmar_chol(float *C, float *W, int m);
extern int dlevmar_chol(double *C, double *W, int m);
#ifdef __cplusplus
}
#endif
#endif /* _MISC_H_ */

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@@ -1,826 +0,0 @@
/////////////////////////////////////////////////////////////////////////////////
//
// Levenberg - Marquardt non-linear minimization algorithm
// Copyright (C) 2004-05 Manolis Lourakis (lourakis at ics forth gr)
// Institute of Computer Science, Foundation for Research & Technology - Hellas
// Heraklion, Crete, Greece.
//
// 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.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
/////////////////////////////////////////////////////////////////////////////////
#ifndef LM_REAL // not included by misc.c
#error This file should not be compiled directly!
#endif
/* precision-specific definitions */
#define LEVMAR_CHKJAC LM_ADD_PREFIX(levmar_chkjac)
#define LEVMAR_FDIF_FORW_JAC_APPROX LM_ADD_PREFIX(levmar_fdif_forw_jac_approx)
#define LEVMAR_FDIF_CENT_JAC_APPROX LM_ADD_PREFIX(levmar_fdif_cent_jac_approx)
#define LEVMAR_TRANS_MAT_MAT_MULT LM_ADD_PREFIX(levmar_trans_mat_mat_mult)
#define LEVMAR_COVAR LM_ADD_PREFIX(levmar_covar)
#define LEVMAR_STDDEV LM_ADD_PREFIX(levmar_stddev)
#define LEVMAR_CORCOEF LM_ADD_PREFIX(levmar_corcoef)
#define LEVMAR_R2 LM_ADD_PREFIX(levmar_R2)
#define LEVMAR_BOX_CHECK LM_ADD_PREFIX(levmar_box_check)
#define LEVMAR_L2NRMXMY LM_ADD_PREFIX(levmar_L2nrmxmy)
#ifdef HAVE_LAPACK
#define LEVMAR_PSEUDOINVERSE LM_ADD_PREFIX(levmar_pseudoinverse)
static int LEVMAR_PSEUDOINVERSE(LM_REAL *A, LM_REAL *B, int m);
#ifdef __cplusplus
extern "C" {
#endif
/* BLAS matrix multiplication, LAPACK SVD & Cholesky routines */
#define GEMM LM_MK_BLAS_NAME(gemm)
/* C := alpha*op( A )*op( B ) + beta*C */
extern void GEMM(char *transa, char *transb, int *m, int *n, int *k,
LM_REAL *alpha, LM_REAL *a, int *lda, LM_REAL *b, int *ldb, LM_REAL *beta, LM_REAL *c, int *ldc);
#define GESVD LM_MK_LAPACK_NAME(gesvd)
#define GESDD LM_MK_LAPACK_NAME(gesdd)
extern int GESVD(char *jobu, char *jobvt, int *m, int *n, LM_REAL *a, int *lda, LM_REAL *s, LM_REAL *u, int *ldu,
LM_REAL *vt, int *ldvt, LM_REAL *work, int *lwork, int *info);
/* lapack 3.0 new SVD routine, faster than xgesvd() */
extern int GESDD(char *jobz, int *m, int *n, LM_REAL *a, int *lda, LM_REAL *s, LM_REAL *u, int *ldu, LM_REAL *vt, int *ldvt,
LM_REAL *work, int *lwork, int *iwork, int *info);
/* Cholesky decomposition */
#define POTF2 LM_MK_LAPACK_NAME(potf2)
extern int POTF2(char *uplo, int *n, LM_REAL *a, int *lda, int *info);
#ifdef __cplusplus
}
#endif
#define LEVMAR_CHOLESKY LM_ADD_PREFIX(levmar_chol)
#else /* !HAVE_LAPACK */
#define LEVMAR_LUINVERSE LM_ADD_PREFIX(levmar_LUinverse_noLapack)
static int LEVMAR_LUINVERSE(LM_REAL *A, LM_REAL *B, int m);
#endif /* HAVE_LAPACK */
/* blocked multiplication of the transpose of the nxm matrix a with itself (i.e. a^T a)
* using a block size of bsize. The product is returned in b.
* Since a^T a is symmetric, its computation can be sped up by computing only its
* upper triangular part and copying it to the lower part.
*
* More details on blocking can be found at
* http://www-2.cs.cmu.edu/afs/cs/academic/class/15213-f02/www/R07/section_a/Recitation07-SectionA.pdf
*/
void LEVMAR_TRANS_MAT_MAT_MULT(LM_REAL *a, LM_REAL *b, int n, int m)
{
#ifdef HAVE_LAPACK /* use BLAS matrix multiply */
LM_REAL alpha=LM_CNST(1.0), beta=LM_CNST(0.0);
/* Fool BLAS to compute a^T*a avoiding transposing a: a is equivalent to a^T in column major,
* therefore BLAS computes a*a^T with a and a*a^T in column major, which is equivalent to
* computing a^T*a in row major!
*/
GEMM("N", "T", &m, &m, &n, &alpha, a, &m, a, &m, &beta, b, &m);
#else /* no LAPACK, use blocking-based multiply */
register int i, j, k, jj, kk;
register LM_REAL sum, *bim, *akm;
const int bsize=__BLOCKSZ__;
#define __MIN__(x, y) (((x)<=(y))? (x) : (y))
#define __MAX__(x, y) (((x)>=(y))? (x) : (y))
/* compute upper triangular part using blocking */
for(jj=0; jj<m; jj+=bsize){
for(i=0; i<m; ++i){
bim=b+i*m;
for(j=__MAX__(jj, i); j<__MIN__(jj+bsize, m); ++j)
bim[j]=0.0; //b[i*m+j]=0.0;
}
for(kk=0; kk<n; kk+=bsize){
for(i=0; i<m; ++i){
bim=b+i*m;
for(j=__MAX__(jj, i); j<__MIN__(jj+bsize, m); ++j){
sum=0.0;
for(k=kk; k<__MIN__(kk+bsize, n); ++k){
akm=a+k*m;
sum+=akm[i]*akm[j]; //a[k*m+i]*a[k*m+j];
}
bim[j]+=sum; //b[i*m+j]+=sum;
}
}
}
}
/* copy upper triangular part to the lower one */
for(i=0; i<m; ++i)
for(j=0; j<i; ++j)
b[i*m+j]=b[j*m+i];
#undef __MIN__
#undef __MAX__
#endif /* HAVE_LAPACK */
}
/* forward finite difference approximation to the Jacobian of func */
void LEVMAR_FDIF_FORW_JAC_APPROX(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
/* function to differentiate */
LM_REAL *p, /* I: current parameter estimate, mx1 */
LM_REAL *hx, /* I: func evaluated at p, i.e. hx=func(p), nx1 */
LM_REAL *hxx, /* W/O: work array for evaluating func(p+delta), nx1 */
LM_REAL delta, /* increment for computing the Jacobian */
LM_REAL *jac, /* O: array for storing approximated Jacobian, nxm */
int m,
int n,
void *adata)
{
register int i, j;
LM_REAL tmp;
register LM_REAL d;
for(j=0; j<m; ++j){
/* determine d=max(1E-04*|p[j]|, delta), see HZ */
d=LM_CNST(1E-04)*p[j]; // force evaluation
d=FABS(d);
if(d<delta)
d=delta;
tmp=p[j];
p[j]+=d;
(*func)(p, hxx, m, n, adata);
p[j]=tmp; /* restore */
d=LM_CNST(1.0)/d; /* invert so that divisions can be carried out faster as multiplications */
for(i=0; i<n; ++i){
jac[i*m+j]=(hxx[i]-hx[i])*d;
}
}
}
/* central finite difference approximation to the Jacobian of func */
void LEVMAR_FDIF_CENT_JAC_APPROX(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
/* function to differentiate */
LM_REAL *p, /* I: current parameter estimate, mx1 */
LM_REAL *hxm, /* W/O: work array for evaluating func(p-delta), nx1 */
LM_REAL *hxp, /* W/O: work array for evaluating func(p+delta), nx1 */
LM_REAL delta, /* increment for computing the Jacobian */
LM_REAL *jac, /* O: array for storing approximated Jacobian, nxm */
int m,
int n,
void *adata)
{
register int i, j;
LM_REAL tmp;
register LM_REAL d;
for(j=0; j<m; ++j){
/* determine d=max(1E-04*|p[j]|, delta), see HZ */
d=LM_CNST(1E-04)*p[j]; // force evaluation
d=FABS(d);
if(d<delta)
d=delta;
tmp=p[j];
p[j]-=d;
(*func)(p, hxm, m, n, adata);
p[j]=tmp+d;
(*func)(p, hxp, m, n, adata);
p[j]=tmp; /* restore */
d=LM_CNST(0.5)/d; /* invert so that divisions can be carried out faster as multiplications */
for(i=0; i<n; ++i){
jac[i*m+j]=(hxp[i]-hxm[i])*d;
}
}
}
/*
* Check the Jacobian of a n-valued nonlinear function in m variables
* evaluated at a point p, for consistency with the function itself.
*
* Based on fortran77 subroutine CHKDER by
* Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More
* Argonne National Laboratory. MINPACK project. March 1980.
*
*
* func points to a function from R^m --> R^n: Given a p in R^m it yields hx in R^n
* jacf points to a function implementing the Jacobian of func, whose correctness
* is to be tested. Given a p in R^m, jacf computes into the nxm matrix j the
* Jacobian of func at p. Note that row i of j corresponds to the gradient of
* the i-th component of func, evaluated at p.
* p is an input array of length m containing the point of evaluation.
* m is the number of variables
* n is the number of functions
* adata points to possible additional data and is passed uninterpreted
* to func, jacf.
* err is an array of length n. On output, err contains measures
* of correctness of the respective gradients. if there is
* no severe loss of significance, then if err[i] is 1.0 the
* i-th gradient is correct, while if err[i] is 0.0 the i-th
* gradient is incorrect. For values of err between 0.0 and 1.0,
* the categorization is less certain. In general, a value of
* err[i] greater than 0.5 indicates that the i-th gradient is
* probably correct, while a value of err[i] less than 0.5
* indicates that the i-th gradient is probably incorrect.
*
*
* The function does not perform reliably if cancellation or
* rounding errors cause a severe loss of significance in the
* evaluation of a function. therefore, none of the components
* of p should be unusually small (in particular, zero) or any
* other value which may cause loss of significance.
*/
void LEVMAR_CHKJAC(
void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
void (*jacf)(LM_REAL *p, LM_REAL *j, int m, int n, void *adata),
LM_REAL *p, int m, int n, void *adata, LM_REAL *err)
{
LM_REAL factor=LM_CNST(100.0);
LM_REAL one=LM_CNST(1.0);
LM_REAL zero=LM_CNST(0.0);
LM_REAL *fvec, *fjac, *pp, *fvecp, *buf;
register int i, j;
LM_REAL eps, epsf, temp, epsmch;
LM_REAL epslog;
int fvec_sz=n, fjac_sz=n*m, pp_sz=m, fvecp_sz=n;
epsmch=LM_REAL_EPSILON;
eps=(LM_REAL)sqrt(epsmch);
buf=(LM_REAL *)malloc((fvec_sz + fjac_sz + pp_sz + fvecp_sz)*sizeof(LM_REAL));
if(!buf){
fprintf(stderr, LCAT(LEVMAR_CHKJAC, "(): memory allocation request failed\n"));
exit(1);
}
fvec=buf;
fjac=fvec+fvec_sz;
pp=fjac+fjac_sz;
fvecp=pp+pp_sz;
/* compute fvec=func(p) */
(*func)(p, fvec, m, n, adata);
/* compute the Jacobian at p */
(*jacf)(p, fjac, m, n, adata);
/* compute pp */
for(j=0; j<m; ++j){
temp=eps*FABS(p[j]);
if(temp==zero) temp=eps;
pp[j]=p[j]+temp;
}
/* compute fvecp=func(pp) */
(*func)(pp, fvecp, m, n, adata);
epsf=factor*epsmch;
epslog=(LM_REAL)log10(eps);
for(i=0; i<n; ++i)
err[i]=zero;
for(j=0; j<m; ++j){
temp=FABS(p[j]);
if(temp==zero) temp=one;
for(i=0; i<n; ++i)
err[i]+=temp*fjac[i*m+j];
}
for(i=0; i<n; ++i){
temp=one;
if(fvec[i]!=zero && fvecp[i]!=zero && FABS(fvecp[i]-fvec[i])>=epsf*FABS(fvec[i]))
temp=eps*FABS((fvecp[i]-fvec[i])/eps - err[i])/(FABS(fvec[i])+FABS(fvecp[i]));
err[i]=one;
if(temp>epsmch && temp<eps)
err[i]=((LM_REAL)log10(temp) - epslog)/epslog;
if(temp>=eps) err[i]=zero;
}
free(buf);
return;
}
#ifdef HAVE_LAPACK
/*
* This function computes the pseudoinverse of a square matrix A
* into B using SVD. A and B can coincide
*
* The function returns 0 in case of error (e.g. A is singular),
* the rank of A if successful
*
* A, B are mxm
*
*/
static int LEVMAR_PSEUDOINVERSE(LM_REAL *A, LM_REAL *B, int m)
{
LM_REAL *buf=NULL;
int buf_sz=0;
static LM_REAL eps=LM_CNST(-1.0);
register int i, j;
LM_REAL *a, *u, *s, *vt, *work;
int a_sz, u_sz, s_sz, vt_sz, tot_sz;
LM_REAL thresh, one_over_denom;
int info, rank, worksz, *iwork, iworksz;
/* calculate required memory size */
worksz=5*m; // min worksize for GESVD
//worksz=m*(7*m+4); // min worksize for GESDD
iworksz=8*m;
a_sz=m*m;
u_sz=m*m; s_sz=m; vt_sz=m*m;
tot_sz=(a_sz + u_sz + s_sz + vt_sz + worksz)*sizeof(LM_REAL) + iworksz*sizeof(int); /* should be arranged in that order for proper doubles alignment */
buf_sz=tot_sz;
buf=(LM_REAL *)malloc(buf_sz);
if(!buf){
fprintf(stderr, RCAT("memory allocation in ", LEVMAR_PSEUDOINVERSE) "() failed!\n");
return 0; /* error */
}
a=buf;
u=a+a_sz;
s=u+u_sz;
vt=s+s_sz;
work=vt+vt_sz;
iwork=(int *)(work+worksz);
/* store A (column major!) into a */
for(i=0; i<m; i++)
for(j=0; j<m; j++)
a[i+j*m]=A[i*m+j];
/* SVD decomposition of A */
GESVD("A", "A", (int *)&m, (int *)&m, a, (int *)&m, s, u, (int *)&m, vt, (int *)&m, work, (int *)&worksz, &info);
//GESDD("A", (int *)&m, (int *)&m, a, (int *)&m, s, u, (int *)&m, vt, (int *)&m, work, (int *)&worksz, iwork, &info);
/* error treatment */
if(info!=0){
if(info<0){
fprintf(stderr, RCAT(RCAT(RCAT("LAPACK error: illegal value for argument %d of ", GESVD), "/" GESDD) " in ", LEVMAR_PSEUDOINVERSE) "()\n", -info);
}
else{
fprintf(stderr, RCAT("LAPACK error: dgesdd (dbdsdc)/dgesvd (dbdsqr) failed to converge in ", LEVMAR_PSEUDOINVERSE) "() [info=%d]\n", info);
}
free(buf);
return 0;
}
if(eps<0.0){
LM_REAL aux;
/* compute machine epsilon */
for(eps=LM_CNST(1.0); aux=eps+LM_CNST(1.0), aux-LM_CNST(1.0)>0.0; eps*=LM_CNST(0.5))
;
eps*=LM_CNST(2.0);
}
/* compute the pseudoinverse in B */
for(i=0; i<a_sz; i++) B[i]=0.0; /* initialize to zero */
for(rank=0, thresh=eps*s[0]; rank<m && s[rank]>thresh; rank++){
one_over_denom=LM_CNST(1.0)/s[rank];
for(j=0; j<m; j++)
for(i=0; i<m; i++)
B[i*m+j]+=vt[rank+i*m]*u[j+rank*m]*one_over_denom;
}
free(buf);
return rank;
}
#else // no LAPACK
/*
* This function computes the inverse of A in B. A and B can coincide
*
* The function employs LAPACK-free LU decomposition of A to solve m linear
* systems A*B_i=I_i, where B_i and I_i are the i-th columns of B and I.
*
* A and B are mxm
*
* The function returns 0 in case of error, 1 if successful
*
*/
static int LEVMAR_LUINVERSE(LM_REAL *A, LM_REAL *B, int m)
{
void *buf=NULL;
int buf_sz=0;
register int i, j, k, l;
int *idx, maxi=-1, idx_sz, a_sz, x_sz, work_sz, tot_sz;
LM_REAL *a, *x, *work, max, sum, tmp;
/* calculate required memory size */
idx_sz=m;
a_sz=m*m;
x_sz=m;
work_sz=m;
tot_sz=(a_sz + x_sz + work_sz)*sizeof(LM_REAL) + idx_sz*sizeof(int); /* should be arranged in that order for proper doubles alignment */
buf_sz=tot_sz;
buf=(void *)malloc(tot_sz);
if(!buf){
fprintf(stderr, RCAT("memory allocation in ", LEVMAR_LUINVERSE) "() failed!\n");
return 0; /* error */
}
a=buf;
x=a+a_sz;
work=x+x_sz;
idx=(int *)(work+work_sz);
/* avoid destroying A by copying it to a */
for(i=0; i<a_sz; ++i) a[i]=A[i];
/* compute the LU decomposition of a row permutation of matrix a; the permutation itself is saved in idx[] */
for(i=0; i<m; ++i){
max=0.0;
for(j=0; j<m; ++j)
if((tmp=FABS(a[i*m+j]))>max)
max=tmp;
if(max==0.0){
fprintf(stderr, RCAT("Singular matrix A in ", LEVMAR_LUINVERSE) "()!\n");
free(buf);
return 0;
}
work[i]=LM_CNST(1.0)/max;
}
for(j=0; j<m; ++j){
for(i=0; i<j; ++i){
sum=a[i*m+j];
for(k=0; k<i; ++k)
sum-=a[i*m+k]*a[k*m+j];
a[i*m+j]=sum;
}
max=0.0;
for(i=j; i<m; ++i){
sum=a[i*m+j];
for(k=0; k<j; ++k)
sum-=a[i*m+k]*a[k*m+j];
a[i*m+j]=sum;
if((tmp=work[i]*FABS(sum))>=max){
max=tmp;
maxi=i;
}
}
if(j!=maxi){
for(k=0; k<m; ++k){
tmp=a[maxi*m+k];
a[maxi*m+k]=a[j*m+k];
a[j*m+k]=tmp;
}
work[maxi]=work[j];
}
idx[j]=maxi;
if(a[j*m+j]==0.0)
a[j*m+j]=LM_REAL_EPSILON;
if(j!=m-1){
tmp=LM_CNST(1.0)/(a[j*m+j]);
for(i=j+1; i<m; ++i)
a[i*m+j]*=tmp;
}
}
/* The decomposition has now replaced a. Solve the m linear systems using
* forward and back substitution
*/
for(l=0; l<m; ++l){
for(i=0; i<m; ++i) x[i]=0.0;
x[l]=LM_CNST(1.0);
for(i=k=0; i<m; ++i){
j=idx[i];
sum=x[j];
x[j]=x[i];
if(k!=0)
for(j=k-1; j<i; ++j)
sum-=a[i*m+j]*x[j];
else
if(sum!=0.0)
k=i+1;
x[i]=sum;
}
for(i=m-1; i>=0; --i){
sum=x[i];
for(j=i+1; j<m; ++j)
sum-=a[i*m+j]*x[j];
x[i]=sum/a[i*m+i];
}
for(i=0; i<m; ++i)
B[i*m+l]=x[i];
}
free(buf);
return 1;
}
#endif /* HAVE_LAPACK */
/*
* This function computes in C the covariance matrix corresponding to a least
* squares fit. JtJ is the approximate Hessian at the solution (i.e. J^T*J, where
* J is the Jacobian at the solution), sumsq is the sum of squared residuals
* (i.e. goodnes of fit) at the solution, m is the number of parameters (variables)
* and n the number of observations. JtJ can coincide with C.
*
* if JtJ is of full rank, C is computed as sumsq/(n-m)*(JtJ)^-1
* otherwise and if LAPACK is available, C=sumsq/(n-r)*(JtJ)^+
* where r is JtJ's rank and ^+ denotes the pseudoinverse
* The diagonal of C is made up from the estimates of the variances
* of the estimated regression coefficients.
* See the documentation of routine E04YCF from the NAG fortran lib
*
* The function returns the rank of JtJ if successful, 0 on error
*
* A and C are mxm
*
*/
int LEVMAR_COVAR(LM_REAL *JtJ, LM_REAL *C, LM_REAL sumsq, int m, int n)
{
register int i;
int rnk;
LM_REAL fact;
#ifdef HAVE_LAPACK
rnk=LEVMAR_PSEUDOINVERSE(JtJ, C, m);
if(!rnk) return 0;
#else
#ifdef _MSC_VER
#pragma message("LAPACK not available, LU will be used for matrix inversion when computing the covariance; this might be unstable at times")
#else
#warning LAPACK not available, LU will be used for matrix inversion when computing the covariance; this might be unstable at times
#endif // _MSC_VER
rnk=LEVMAR_LUINVERSE(JtJ, C, m);
if(!rnk) return 0;
rnk=m; /* assume full rank */
#endif /* HAVE_LAPACK */
fact=sumsq/(LM_REAL)(n-rnk);
for(i=0; i<m*m; ++i)
C[i]*=fact;
return rnk;
}
/* standard deviation of the best-fit parameter i.
* covar is the mxm covariance matrix of the best-fit parameters (see also LEVMAR_COVAR()).
*
* The standard deviation is computed as \sigma_{i} = \sqrt{C_{ii}}
*/
LM_REAL LEVMAR_STDDEV(LM_REAL *covar, int m, int i)
{
return (LM_REAL)sqrt(covar[i*m+i]);
}
/* Pearson's correlation coefficient of the best-fit parameters i and j.
* covar is the mxm covariance matrix of the best-fit parameters (see also LEVMAR_COVAR()).
*
* The coefficient is computed as \rho_{ij} = C_{ij} / sqrt(C_{ii} C_{jj})
*/
LM_REAL LEVMAR_CORCOEF(LM_REAL *covar, int m, int i, int j)
{
return (LM_REAL)(covar[i*m+j]/sqrt(covar[i*m+i]*covar[j*m+j]));
}
/* coefficient of determination.
* see http://en.wikipedia.org/wiki/Coefficient_of_determination
*/
LM_REAL LEVMAR_R2(void (*func)(LM_REAL *p, LM_REAL *hx, int m, int n, void *adata),
LM_REAL *p, LM_REAL *x, int m, int n, void *adata)
{
register int i;
register LM_REAL tmp;
LM_REAL SSerr, // sum of squared errors, i.e. residual sum of squares \sum_i (x_i-hx_i)^2
SStot, // \sum_i (x_i-xavg)^2
*hx, xavg;
if((hx=(LM_REAL *)malloc(n*sizeof(LM_REAL)))==NULL){
fprintf(stderr, RCAT("memory allocation request failed in ", LEVMAR_R2) "()\n");
exit(1);
}
/* hx=f(p) */
(*func)(p, hx, m, n, adata);
for(i=n, tmp=0.0; i-->0; )
tmp+=x[i];
xavg=tmp/(LM_REAL)n;
if(x)
for(i=n, SSerr=SStot=0.0; i-->0; ){
tmp=x[i]-hx[i];
SSerr+=tmp*tmp;
tmp=x[i]-xavg;
SStot+=tmp*tmp;
}
else /* x==0 */
for(i=n, SSerr=SStot=0.0; i-->0; ){
tmp=-hx[i];
SSerr+=tmp*tmp;
tmp=-xavg;
SStot+=tmp*tmp;
}
free(hx);
return LM_CNST(1.0) - SSerr/SStot;
}
/* check box constraints for consistency */
int LEVMAR_BOX_CHECK(LM_REAL *lb, LM_REAL *ub, int m)
{
register int i;
if(!lb || !ub) return 1;
for(i=0; i<m; ++i)
if(lb[i]>ub[i]) return 0;
return 1;
}
#ifdef HAVE_LAPACK
/* compute the Cholesky decomposition of C in W, s.t. C=W^t W and W is upper triangular */
int LEVMAR_CHOLESKY(LM_REAL *C, LM_REAL *W, int m)
{
register int i, j;
int info;
/* copy weights array C to W so that LAPACK won't destroy it;
* C is assumed symmetric, hence no transposition is needed
*/
for(i=0, j=m*m; i<j; ++i)
W[i]=C[i];
/* Cholesky decomposition */
POTF2("L", (int *)&m, W, (int *)&m, (int *)&info);
/* error treatment */
if(info!=0){
if(info<0){
fprintf(stderr, "LAPACK error: illegal value for argument %d of dpotf2 in %s\n", -info, LCAT(LEVMAR_CHOLESKY, "()"));
}
else{
fprintf(stderr, "LAPACK error: the leading minor of order %d is not positive definite,\n%s()\n", info,
RCAT("and the Cholesky factorization could not be completed in ", LEVMAR_CHOLESKY));
}
return LM_ERROR;
}
/* the decomposition is in the lower part of W (in column-major order!).
* zeroing the upper part makes it lower triangular which is equivalent to
* upper triangular in row-major order
*/
for(i=0; i<m; i++)
for(j=i+1; j<m; j++)
W[i+j*m]=0.0;
return 0;
}
#endif /* HAVE_LAPACK */
/* Compute e=x-y for two n-vectors x and y and return the squared L2 norm of e.
* e can coincide with either x or y; x can be NULL, in which case it is assumed
* to be equal to the zero vector.
* Uses loop unrolling and blocking to reduce bookkeeping overhead & pipeline
* stalls and increase instruction-level parallelism; see http://www.abarnett.demon.co.uk/tutorial.html
*/
LM_REAL LEVMAR_L2NRMXMY(LM_REAL *e, LM_REAL *x, LM_REAL *y, int n)
{
const int blocksize=8, bpwr=3; /* 8=2^3 */
register int i;
int j1, j2, j3, j4, j5, j6, j7;
int blockn;
register LM_REAL sum0=0.0, sum1=0.0, sum2=0.0, sum3=0.0;
/* n may not be divisible by blocksize,
* go as near as we can first, then tidy up.
*/
blockn = (n>>bpwr)<<bpwr; /* (n / blocksize) * blocksize; */
/* unroll the loop in blocks of `blocksize'; looping downwards gains some more speed */
if(x){
for(i=blockn-1; i>0; i-=blocksize){
e[i ]=x[i ]-y[i ]; sum0+=e[i ]*e[i ];
j1=i-1; e[j1]=x[j1]-y[j1]; sum1+=e[j1]*e[j1];
j2=i-2; e[j2]=x[j2]-y[j2]; sum2+=e[j2]*e[j2];
j3=i-3; e[j3]=x[j3]-y[j3]; sum3+=e[j3]*e[j3];
j4=i-4; e[j4]=x[j4]-y[j4]; sum0+=e[j4]*e[j4];
j5=i-5; e[j5]=x[j5]-y[j5]; sum1+=e[j5]*e[j5];
j6=i-6; e[j6]=x[j6]-y[j6]; sum2+=e[j6]*e[j6];
j7=i-7; e[j7]=x[j7]-y[j7]; sum3+=e[j7]*e[j7];
}
/*
* There may be some left to do.
* This could be done as a simple for() loop,
* but a switch is faster (and more interesting)
*/
i=blockn;
if(i<n){
/* Jump into the case at the place that will allow
* us to finish off the appropriate number of items.
*/
switch(n - i){
case 7 : e[i]=x[i]-y[i]; sum0+=e[i]*e[i]; ++i;
case 6 : e[i]=x[i]-y[i]; sum1+=e[i]*e[i]; ++i;
case 5 : e[i]=x[i]-y[i]; sum2+=e[i]*e[i]; ++i;
case 4 : e[i]=x[i]-y[i]; sum3+=e[i]*e[i]; ++i;
case 3 : e[i]=x[i]-y[i]; sum0+=e[i]*e[i]; ++i;
case 2 : e[i]=x[i]-y[i]; sum1+=e[i]*e[i]; ++i;
case 1 : e[i]=x[i]-y[i]; sum2+=e[i]*e[i]; //++i;
}
}
}
else{ /* x==0 */
for(i=blockn-1; i>0; i-=blocksize){
e[i ]=-y[i ]; sum0+=e[i ]*e[i ];
j1=i-1; e[j1]=-y[j1]; sum1+=e[j1]*e[j1];
j2=i-2; e[j2]=-y[j2]; sum2+=e[j2]*e[j2];
j3=i-3; e[j3]=-y[j3]; sum3+=e[j3]*e[j3];
j4=i-4; e[j4]=-y[j4]; sum0+=e[j4]*e[j4];
j5=i-5; e[j5]=-y[j5]; sum1+=e[j5]*e[j5];
j6=i-6; e[j6]=-y[j6]; sum2+=e[j6]*e[j6];
j7=i-7; e[j7]=-y[j7]; sum3+=e[j7]*e[j7];
}
/*
* There may be some left to do.
* This could be done as a simple for() loop,
* but a switch is faster (and more interesting)
*/
i=blockn;
if(i<n){
/* Jump into the case at the place that will allow
* us to finish off the appropriate number of items.
*/
switch(n - i){
case 7 : e[i]=-y[i]; sum0+=e[i]*e[i]; ++i;
case 6 : e[i]=-y[i]; sum1+=e[i]*e[i]; ++i;
case 5 : e[i]=-y[i]; sum2+=e[i]*e[i]; ++i;
case 4 : e[i]=-y[i]; sum3+=e[i]*e[i]; ++i;
case 3 : e[i]=-y[i]; sum0+=e[i]*e[i]; ++i;
case 2 : e[i]=-y[i]; sum1+=e[i]*e[i]; ++i;
case 1 : e[i]=-y[i]; sum2+=e[i]*e[i]; //++i;
}
}
}
return sum0+sum1+sum2+sum3;
}
/* undefine everything. THIS MUST REMAIN AT THE END OF THE FILE */
#undef POTF2
#undef GESVD
#undef GESDD
#undef GEMM
#undef LEVMAR_PSEUDOINVERSE
#undef LEVMAR_LUINVERSE
#undef LEVMAR_BOX_CHECK
#undef LEVMAR_CHOLESKY
#undef LEVMAR_COVAR
#undef LEVMAR_STDDEV
#undef LEVMAR_CORCOEF
#undef LEVMAR_R2
#undef LEVMAR_CHKJAC
#undef LEVMAR_FDIF_FORW_JAC_APPROX
#undef LEVMAR_FDIF_CENT_JAC_APPROX
#undef LEVMAR_TRANS_MAT_MAT_MULT
#undef LEVMAR_L2NRMXMY

View File

@@ -1,30 +0,0 @@
The package lmfit is distributed under the FreeBSD License:
--
Copyright (c) 1980-1999 University of Chicago,
as operator of Argonne National Laboratory
Copyright (c) 2004-2015 Joachim Wuttke, Forschungszentrum Juelich GmbH
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.
This software is provided by the copyright holders and contributors "as is"
and any express or implied warranties, including, but not limited to, the
implied warranties of merchantability and fitness for a particular purpose
are disclaimed. In no event shall the copyright holder or contributors
be liable for any direct, indirect, incidental, special, exemplary, or
consequential damages (including, but not limited to, procurement of
substitute goods or services; loss of use, data, or profits; or business
interruption) however caused and on any theory of liability, whether in
contract, strict liability, or tort (including negligence or otherwise)
arising in any way out of the use of this software, even if advised of the
possibility of such damage.
--

View File

@@ -1,52 +0,0 @@
/*
* Library: lmfit (Levenberg-Marquardt least squares fitting)
*
* File: lmcurve.c
*
* Contents: Implements lmcurve, a simplified API for curve fitting
* using the generic Levenberg-Marquardt routine lmmin.
*
* Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
*
* License: see ../COPYING (FreeBSD)
*
* Homepage: apps.jcns.fz-juelich.de/lmfit
*
* Note to programmers: Don't patch and fork, but copy and modify!
* If you need to compute residues differently, then please do not patch
* lmcurve.h and lmcurve.c, but copy them, and create differently named
* versions of lmcurve_data_struct, lmcurve_evaluate, and lmcurve of your own.
*/
#include "lmmin.h"
typedef struct {
const double *const t;
const double *const y;
double (*const g) (const double t, const double *par);
} lmcurve_data_struct;
void lmcurve_evaluate(
const double *const par, const int m_dat, const void *const data,
double *const fvec, int *const info)
{
for (int i = 0; i < m_dat; i++ )
fvec[i] =
((lmcurve_data_struct*)data)->y[i] -
((lmcurve_data_struct*)data)->g(
((lmcurve_data_struct*)data)->t[i], par );
}
void lmcurve(
const int n_par, double *const par, const int m_dat,
const double *const t, const double *const y,
double (*const g)(const double t, const double *const par),
const lm_control_struct *const control, lm_status_struct *const status)
{
lmcurve_data_struct data = {t, y, g};
lmmin(n_par, par, m_dat, NULL, (const void *const) &data,
lmcurve_evaluate, control, status);
}

View File

@@ -1,45 +0,0 @@
/*
* Library: lmfit (Levenberg-Marquardt least squares fitting)
*
* File: lmcurve.h
*
* Contents: Declares lmcurve, a simplified API for curve fitting
* using the generic Levenberg-Marquardt routine lmmin.
*
* Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
*
* License: see ../COPYING (FreeBSD)
*
* Homepage: apps.jcns.fz-juelich.de/lmfit
*
* Note to programmers: Don't patch and fork, but copy and variate!
* If you need to compute residues differently, then please do not patch
* lmcurve.h, but copy it to a differently named file, and change lmcurve()
* into a differently named function declaration, like we have done in
* lmcurve_tyd.h.
*/
#ifndef LMCURVE_H
#define LMCURVE_H
#undef __BEGIN_DECLS
#undef __END_DECLS
#ifdef __cplusplus
#define __BEGIN_DECLS extern "C" {
#define __END_DECLS }
#else
#define __BEGIN_DECLS /* empty */
#define __END_DECLS /* empty */
#endif
#include<lmstruct.h>
__BEGIN_DECLS
void lmcurve(
const int n_par, double* par, const int m_dat,
const double* t, const double* y,
double (*g)(const double t, const double* par),
const lm_control_struct* control, lm_status_struct* status);
__END_DECLS
#endif /* LMCURVE_H */

View File

@@ -1,39 +0,0 @@
/*
* Library: lmfit (Levenberg-Marquardt least squares fitting)
*
* File: lmcurve_tyd.h
*
* Contents: Declares lmcurve_tyd(), a variant of lmcurve() that weighs
* data points y(t) with the inverse of the standard deviations dy.
*
* Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
*
* License: see ../COPYING (FreeBSD)
*
* Homepage: apps.jcns.fz-juelich.de/lmfit
*/
#ifndef LMCURVETYD_H
#define LMCURVETYD_H
#undef __BEGIN_DECLS
#undef __END_DECLS
#ifdef __cplusplus
#define __BEGIN_DECLS extern "C" {
#define __END_DECLS }
#else
#define __BEGIN_DECLS /* empty */
#define __END_DECLS /* empty */
#endif
#include <lmstruct.h>
__BEGIN_DECLS
void lmcurve_tyd(
const int n_par, double* par, const int m_dat,
const double* t, const double* y, const double* dy,
double (*f)(double t, const double* par),
const lm_control_struct* control, lm_status_struct* status);
__END_DECLS
#endif /* LMCURVETYD_H */

File diff suppressed because it is too large Load Diff

View File

@@ -1,84 +0,0 @@
/*
* Library: lmfit (Levenberg-Marquardt least squares fitting)
*
* File: lmmin.h
*
* Contents: Declarations for Levenberg-Marquardt minimization.
*
* Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
*
* License: see ../COPYING (FreeBSD)
*
* Homepage: apps.jcns.fz-juelich.de/lmfit
*/
#ifndef LMMIN_H
#define LMMIN_H
#undef __BEGIN_DECLS
#undef __END_DECLS
#ifdef __cplusplus
#define __BEGIN_DECLS extern "C" {
#define __END_DECLS }
#else
#define __BEGIN_DECLS /* empty */
#define __END_DECLS /* empty */
#endif
#include "lmstruct.h"
__BEGIN_DECLS
/* Levenberg-Marquardt minimization. */
void lmmin(
const int n_par, double* par, const int m_dat, const double* y,
const void* data,
void (*evaluate)(
const double* par, const int m_dat, const void* data,
double* fvec, int* userbreak),
const lm_control_struct* control, lm_status_struct* status);
/*
* This routine contains the core algorithm of our library.
*
* It minimizes the sum of the squares of m nonlinear functions
* in n variables by a modified Levenberg-Marquardt algorithm.
* The function evaluation is done by the user-provided routine 'evaluate'.
* The Jacobian is then calculated by a forward-difference approximation.
*
* Parameters:
*
* n_par is the number of variables (INPUT, positive integer).
*
* par is the solution vector (INPUT/OUTPUT, array of length n).
* On input it must be set to an estimated solution.
* On output it yields the final estimate of the solution.
*
* m_dat is the number of functions to be minimized (INPUT, positive integer).
* It must fulfill m>=n.
*
* y contains data to be fitted. Use a null pointer if there are no data.
*
* data is a pointer that is ignored by lmmin; it is however forwarded
* to the user-supplied functions evaluate and printout.
* In a typical application, it contains experimental data to be fitted.
*
* evaluate is a user-supplied function that calculates the m functions.
* Parameters:
* n, x, m, data as above.
* fvec is an array of length m; on OUTPUT, it must contain the
* m function values for the parameter vector x.
* userbreak is an integer pointer. When *userbreak is set to a
* nonzero value, lmmin will terminate.
*
* control contains INPUT variables that control the fit algorithm,
* as declared and explained in lmstruct.h
*
* status contains OUTPUT variables that inform about the fit result,
* as declared and explained in lmstruct.h
*/
/* Refined calculation of Eucledian norm. */
double lm_enorm(const int, const double*);
double lm_fnorm(const int, const double*, const double*);
__END_DECLS
#endif /* LMMIN_H */

View File

@@ -1,81 +0,0 @@
/*
* Library: lmfit (Levenberg-Marquardt least squares fitting)
*
* File: lmstruct.h
*
* Contents: Declarations of parameter records, used in lmmin.h and lmcurve.h
*
* Copyright: Joachim Wuttke, Forschungszentrum Juelich GmbH (2004-2013)
*
* License: see ../COPYING (FreeBSD)
*
* Homepage: apps.jcns.fz-juelich.de/lmfit
*/
#ifndef LMSTRUCT_H
#define LMSTRUCT_H
#undef __BEGIN_DECLS
#undef __END_DECLS
#ifdef __cplusplus
#define __BEGIN_DECLS extern "C" {
#define __END_DECLS }
#else
#define __BEGIN_DECLS /* empty */
#define __END_DECLS /* empty */
#endif
__BEGIN_DECLS
#include <stdio.h>
/* Collection of input parameters for fit control. */
typedef struct {
double ftol; /* Relative error desired in the sum of squares.
Termination occurs when both the actual and
predicted relative reductions in the sum of squares
are at most ftol. */
double xtol; /* Relative error between last two approximations.
Termination occurs when the relative error between
two consecutive iterates is at most xtol. */
double gtol; /* Orthogonality desired between fvec and its derivs.
Termination occurs when the cosine of the angle
between fvec and any column of the Jacobian is at
most gtol in absolute value. */
double epsilon; /* Step used to calculate the Jacobian, should be
slightly larger than the relative error in the
user-supplied functions. */
double stepbound; /* Used in determining the initial step bound. This
bound is set to the product of stepbound and the
Euclidean norm of diag*x if nonzero, or else to
stepbound itself. In most cases stepbound should lie
in the interval (0.1,100.0). Generally, the value
100.0 is recommended. */
int patience; /* Used to set the maximum number of function evaluations
to patience*(number_of_parameters+1). */
int scale_diag; /* If 1, the variables will be rescaled internally.
Recommended value is 1. */
FILE* msgfile; /* Progress messages will be written to this file. */
int verbosity; /* OR'ed: 1: print some messages; 2: print Jacobian. */
int n_maxpri; /* -1, or max number of parameters to print. */
int m_maxpri; /* -1, or max number of residuals to print. */
} lm_control_struct;
/* Collection of output parameters for status info. */
typedef struct {
double fnorm; /* norm of the residue vector fvec. */
int nfev; /* actual number of iterations. */
int outcome; /* Status indicator. Nonnegative values are used as index
for the message text lm_infmsg, set in lmmin.c. */
int userbreak; /* Set when function evaluation requests termination. */
} lm_status_struct;
/* Preset (and recommended) control parameter settings. */
extern const lm_control_struct lm_control_double;
extern const lm_control_struct lm_control_float;
/* Preset message texts. */
extern const char* lm_infmsg[];
extern const char* lm_shortmsg[];
__END_DECLS
#endif /* LMSTRUCT_H */

View File

@@ -241,8 +241,8 @@ inline void MVJSONUtils::replace(string & target, ///< text to be modi
)
{
size_t pos = 0;
const size_t oldLen = oldStr.length();
const size_t newLen = newStr.length();
unsigned int oldLen = oldStr.length();
unsigned int newLen = newStr.length();
for (;;)
{

View File

@@ -38,11 +38,7 @@ void QwtPlotGappedCurve::drawSeries(QPainter *painter, const QwtScaleMap &xMap,
// First non-missed point will be the start of curve section.
double x = sample(i).x();
double y = sample(i).y();
double yprev = 0;
if (i>0) yprev = sample(i-1).y();
if ((y < (naValue_ + -0.001) || y > (naValue_ + 0.001)) && (x - last <= gapValue_) &&
(yprev < (naValue_ + -0.001) || yprev > (naValue_ + 0.001))) {
if ((y < (naValue_ + -0.001) || y > (naValue_ + 0.001)) && x - last <= gapValue_) {
int start = i-1;
int end = i;

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