From 68690ce99f75dcee487a9758f3dc652f3c5aae04 Mon Sep 17 00:00:00 2001
From: mrovma <martin.mrovec@vsb.cz>
Date: Mon, 20 Nov 2017 18:29:36 +0100
Subject: [PATCH] Initial eclipse commit
---
4neuro/.cproject | 69 +
4neuro/.gitignore | 3 +
4neuro/.gitlab-ci.yml | 9 +
4neuro/.project | 27 +
4neuro/CMakeLists.txt | 65 +
4neuro/Doxyfile | 2481 +++++++++++++++++
4neuro/README.md | 1 +
4neuro/build.sh | 11 +
4neuro/build_docs.sh | 6 +
4neuro/clean.sh | 4 +
4neuro/docs/.gitkeep | 0
4neuro/img/4neuro_logo_small.png | Bin 0 -> 45746 bytes
4neuro/java/src/BPNet.java | 462 +++
4neuro/java/src/BinaryNeuron.java | 15 +
4neuro/java/src/CarDriverClient.java | 528 ++++
4neuro/java/src/Connection.java | 52 +
4neuro/java/src/InputLayerPseudoNeuron.java | 14 +
4neuro/java/src/Interconnections.java | 54 +
4neuro/java/src/InterconnectionsBP.java | 25 +
.../java/src/InterconnectionsMultiLayer.java | 11 +
.../java/src/InvalidInputNumberException.java | 14 +
.../java/src/InvalidLayerNumberException.java | 14 +
.../java/src/InvalidNeuronTypeException.java | 14 +
4neuro/java/src/MultiLayeredNet.java | 58 +
4neuro/java/src/NeuralNet.java | 20 +
4neuro/java/src/Neuron.java | 59 +
4neuro/java/src/Projekt1GUI.java | 581 ++++
4neuro/java/src/Projekt2GUI.java | 784 ++++++
4neuro/java/src/SigmoidalNeuron.java | 53 +
.../java/src/SinglePerceptronNeuralNet.java | 147 +
4neuro/run_tests.sh | 5 +
4neuro/src/CMakeLists.txt | 12 +
4neuro/src/connection_m.f90 | 175 ++
4neuro/src/connection_test.f90 | 86 +
4neuro/src/neuron_dummy_m.f90 | 39 +
35 files changed, 5898 insertions(+)
create mode 100644 4neuro/.cproject
create mode 100644 4neuro/.gitignore
create mode 100644 4neuro/.gitlab-ci.yml
create mode 100644 4neuro/.project
create mode 100644 4neuro/CMakeLists.txt
create mode 100644 4neuro/Doxyfile
create mode 100644 4neuro/README.md
create mode 100644 4neuro/build.sh
create mode 100644 4neuro/build_docs.sh
create mode 100644 4neuro/clean.sh
create mode 100644 4neuro/docs/.gitkeep
create mode 100644 4neuro/img/4neuro_logo_small.png
create mode 100644 4neuro/java/src/BPNet.java
create mode 100644 4neuro/java/src/BinaryNeuron.java
create mode 100644 4neuro/java/src/CarDriverClient.java
create mode 100644 4neuro/java/src/Connection.java
create mode 100644 4neuro/java/src/InputLayerPseudoNeuron.java
create mode 100644 4neuro/java/src/Interconnections.java
create mode 100644 4neuro/java/src/InterconnectionsBP.java
create mode 100644 4neuro/java/src/InterconnectionsMultiLayer.java
create mode 100644 4neuro/java/src/InvalidInputNumberException.java
create mode 100644 4neuro/java/src/InvalidLayerNumberException.java
create mode 100644 4neuro/java/src/InvalidNeuronTypeException.java
create mode 100644 4neuro/java/src/MultiLayeredNet.java
create mode 100644 4neuro/java/src/NeuralNet.java
create mode 100644 4neuro/java/src/Neuron.java
create mode 100644 4neuro/java/src/Projekt1GUI.java
create mode 100644 4neuro/java/src/Projekt2GUI.java
create mode 100644 4neuro/java/src/SigmoidalNeuron.java
create mode 100644 4neuro/java/src/SinglePerceptronNeuralNet.java
create mode 100644 4neuro/run_tests.sh
create mode 100644 4neuro/src/CMakeLists.txt
create mode 100644 4neuro/src/connection_m.f90
create mode 100644 4neuro/src/connection_test.f90
create mode 100644 4neuro/src/neuron_dummy_m.f90
diff --git a/4neuro/.cproject b/4neuro/.cproject
new file mode 100644
index 00000000..cc0bdafa
--- /dev/null
+++ b/4neuro/.cproject
@@ -0,0 +1,69 @@
+<?xml version="1.0" encoding="UTF-8" standalone="no"?>
+<?fileVersion 4.0.0?><cproject storage_type_id="org.eclipse.cdt.core.XmlProjectDescriptionStorage">
+ <storageModule moduleId="org.eclipse.cdt.core.settings">
+ <cconfiguration id="photran.managedbuild.config.gnu.fortran.win32.exe.debug.338229552">
+ <storageModule buildSystemId="org.eclipse.cdt.managedbuilder.core.configurationDataProvider" id="photran.managedbuild.config.gnu.fortran.win32.exe.debug.338229552" moduleId="org.eclipse.cdt.core.settings" name="Debug">
+ <externalSettings/>
+ <extensions>
+ <extension id="org.eclipse.cdt.core.PE" point="org.eclipse.cdt.core.BinaryParser"/>
+ <extension id="org.eclipse.cdt.core.GASErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.GmakeErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.GLDErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.photran.core.GFortranErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.CWDLocator" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.GCCErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ </extensions>
+ </storageModule>
+ <storageModule moduleId="cdtBuildSystem" version="4.0.0">
+ <configuration artifactName="${ProjName}" buildProperties="" cleanCommand="rm -rf" description="" errorParsers="org.eclipse.photran.core.GFortranErrorParser;org.eclipse.cdt.core.GCCErrorParser;org.eclipse.cdt.core.GLDErrorParser;org.eclipse.cdt.core.GASErrorParser;org.eclipse.cdt.core.GmakeErrorParser" id="photran.managedbuild.config.gnu.fortran.win32.exe.debug.338229552" name="Debug" parent="photran.managedbuild.config.gnu.fortran.win32.exe.debug">
+ <folderInfo id="photran.managedbuild.config.gnu.fortran.win32.exe.debug.338229552." name="/" resourcePath="">
+ <toolChain id="photran.managedbuild.toolchain.gnu.fortran.win32.exe.debug.609204123" name="GCC Fortran" superClass="photran.managedbuild.toolchain.gnu.fortran.win32.exe.debug">
+ <targetPlatform archList="all" binaryParser="org.eclipse.cdt.core.PE" id="photran.managedbuild.target.gnu.platform.win32.exe.debug.1367946370" name="Debug Platform" osList="win32" superClass="photran.managedbuild.target.gnu.platform.win32.exe.debug"/>
+ <builder buildPath="${workspace_loc:/4neuro}/Debug" id="photran.managedbuild.target.gnu.builder.win32.exe.debug.1825478107" managedBuildOn="true" name="Gnu Make Builder.Debug" superClass="photran.managedbuild.target.gnu.builder.win32.exe.debug"/>
+ <tool id="photran.managedbuild.tool.gnu.c.compiler.win32.exe.debug.778780997" name="GCC C Compiler" superClass="photran.managedbuild.tool.gnu.c.compiler.win32.exe.debug"/>
+ <tool id="photran.managedbuild.tool.gnu.fortran.compiler.win32.exe.debug.1743211871" name="GNU Fortran Compiler" superClass="photran.managedbuild.tool.gnu.fortran.compiler.win32.exe.debug"/>
+ <tool id="photran.managedbuild.tool.gnu.fortran.linker.win32.exe.debug.437267444" name="GNU Fortran Linker" superClass="photran.managedbuild.tool.gnu.fortran.linker.win32.exe.debug"/>
+ <tool id="photran.managedbuild.tool.gnu.assembler.win32.exe.debug.432119483" name="GCC Assembler" superClass="photran.managedbuild.tool.gnu.assembler.win32.exe.debug"/>
+ </toolChain>
+ </folderInfo>
+ </configuration>
+ </storageModule>
+ <storageModule moduleId="org.eclipse.cdt.core.externalSettings"/>
+ </cconfiguration>
+ <cconfiguration id="photran.managedbuild.config.gnu.fortran.win32.exe.release.1957908145">
+ <storageModule buildSystemId="org.eclipse.cdt.managedbuilder.core.configurationDataProvider" id="photran.managedbuild.config.gnu.fortran.win32.exe.release.1957908145" moduleId="org.eclipse.cdt.core.settings" name="Release">
+ <externalSettings/>
+ <extensions>
+ <extension id="org.eclipse.cdt.core.PE" point="org.eclipse.cdt.core.BinaryParser"/>
+ <extension id="org.eclipse.cdt.core.GASErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.GmakeErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.GLDErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.photran.core.GFortranErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.CWDLocator" point="org.eclipse.cdt.core.ErrorParser"/>
+ <extension id="org.eclipse.cdt.core.GCCErrorParser" point="org.eclipse.cdt.core.ErrorParser"/>
+ </extensions>
+ </storageModule>
+ <storageModule moduleId="cdtBuildSystem" version="4.0.0">
+ <configuration artifactName="${ProjName}" buildProperties="" cleanCommand="rm -rf" description="" errorParsers="org.eclipse.photran.core.GFortranErrorParser;org.eclipse.cdt.core.GCCErrorParser;org.eclipse.cdt.core.GLDErrorParser;org.eclipse.cdt.core.GASErrorParser;org.eclipse.cdt.core.GmakeErrorParser" id="photran.managedbuild.config.gnu.fortran.win32.exe.release.1957908145" name="Release" parent="photran.managedbuild.config.gnu.fortran.win32.exe.release">
+ <folderInfo id="photran.managedbuild.config.gnu.fortran.win32.exe.release.1957908145." name="/" resourcePath="">
+ <toolChain id="photran.managedbuild.toolchain.gnu.fortran.win32.exe.release.1111724220" name="GCC Fortran" superClass="photran.managedbuild.toolchain.gnu.fortran.win32.exe.release">
+ <targetPlatform archList="all" binaryParser="org.eclipse.cdt.core.PE" id="photran.managedbuild.target.gnu.platform.fortran.win32.exe.release.1225476161" name="Release Platform" osList="win32" superClass="photran.managedbuild.target.gnu.platform.fortran.win32.exe.release"/>
+ <builder buildPath="${workspace_loc:/4neuro}/Release" id="photran.managedbuild.target.gnu.builder.win32.exe.release.1043598058" managedBuildOn="true" name="Gnu Make Builder.Release" superClass="photran.managedbuild.target.gnu.builder.win32.exe.release"/>
+ <tool id="photran.managedbuild.tool.gnu.c.compiler.win32.exe.release.1436794482" name="GCC C Compiler" superClass="photran.managedbuild.tool.gnu.c.compiler.win32.exe.release"/>
+ <tool id="photran.managedbuild.tool.gnu.fortran.compiler.win32.exe.release.1119644158" name="GNU Fortran Compiler" superClass="photran.managedbuild.tool.gnu.fortran.compiler.win32.exe.release"/>
+ <tool id="photran.managedbuild.tool.gnu.fortran.linker.win32.exe.release.1754062441" name="GNU Fortran Linker" superClass="photran.managedbuild.tool.gnu.fortran.linker.win32.exe.release"/>
+ <tool id="photran.managedbuild.tool.gnu.assembler.win32.exe.release.1039785129" name="GCC Assembler" superClass="photran.managedbuild.tool.gnu.assembler.win32.exe.release"/>
+ </toolChain>
+ </folderInfo>
+ </configuration>
+ </storageModule>
+ </cconfiguration>
+ </storageModule>
+ <storageModule moduleId="scannerConfiguration">
+ <autodiscovery enabled="true" problemReportingEnabled="true" selectedProfileId=""/>
+ </storageModule>
+ <storageModule moduleId="cdtBuildSystem" version="4.0.0">
+ <project id="4neuro.photran.managedbuild.target.gnu.fortran.win32.exe.1809620819" name="Executable (Gnu Fortran on Windows)" projectType="photran.managedbuild.target.gnu.fortran.win32.exe"/>
+ </storageModule>
+ <storageModule moduleId="org.eclipse.cdt.core.LanguageSettingsProviders"/>
+</cproject>
diff --git a/4neuro/.gitignore b/4neuro/.gitignore
new file mode 100644
index 00000000..4773f0b0
--- /dev/null
+++ b/4neuro/.gitignore
@@ -0,0 +1,3 @@
+*.o
+*.mod
+*.out
diff --git a/4neuro/.gitlab-ci.yml b/4neuro/.gitlab-ci.yml
new file mode 100644
index 00000000..006e53da
--- /dev/null
+++ b/4neuro/.gitlab-ci.yml
@@ -0,0 +1,9 @@
+before_script:
+ - apt-get update
+ - apt-get install -y -qq make gfortran cmake gem
+ - gem install funit
+ - ./build.sh
+
+run_tests:
+ script: "./run_tests.sh"
+
diff --git a/4neuro/.project b/4neuro/.project
new file mode 100644
index 00000000..8d80b121
--- /dev/null
+++ b/4neuro/.project
@@ -0,0 +1,27 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<projectDescription>
+ <name>4neuro</name>
+ <comment></comment>
+ <projects>
+ </projects>
+ <buildSpec>
+ <buildCommand>
+ <name>org.eclipse.cdt.managedbuilder.core.genmakebuilder</name>
+ <triggers>clean,full,incremental,</triggers>
+ <arguments>
+ </arguments>
+ </buildCommand>
+ <buildCommand>
+ <name>org.eclipse.cdt.managedbuilder.core.ScannerConfigBuilder</name>
+ <triggers>full,incremental,</triggers>
+ <arguments>
+ </arguments>
+ </buildCommand>
+ </buildSpec>
+ <natures>
+ <nature>org.eclipse.photran.core.fnature</nature>
+ <nature>org.eclipse.cdt.core.cnature</nature>
+ <nature>org.eclipse.cdt.managedbuilder.core.managedBuildNature</nature>
+ <nature>org.eclipse.cdt.managedbuilder.core.ScannerConfigNature</nature>
+ </natures>
+</projectDescription>
diff --git a/4neuro/CMakeLists.txt b/4neuro/CMakeLists.txt
new file mode 100644
index 00000000..e859c100
--- /dev/null
+++ b/4neuro/CMakeLists.txt
@@ -0,0 +1,65 @@
+cmake_minimum_required(VERSION 3.0)
+project(4Neuro)
+enable_language(Fortran)
+
+#-------------------------------#
+# Default installation location #
+#-------------------------------#
+# Linux: /usr/local
+# Windows: c:/Program Files
+
+#------------#
+# Build type #
+#------------#
+# Default: Release
+# Others: None, Debug
+if (NOT CMAKE_BUILD_TYPE)
+ set (CMAKE_BUILD_TYPE RELEASE CACHE STRING
+ "Choose the type of build, options are: None Debug Release."
+ FORCE)
+endif (NOT CMAKE_BUILD_TYPE)
+
+#--------------------------------#
+# Setting Fortran compiler flags #
+#--------------------------------#
+# TODO overit, jak rychle jede kod s funroll-loops
+# funroll-all-loops a bez prepinace
+
+set(standard "-std=f2008")
+
+if (Fortran_COMPILER_NAME MATCHES "gfortran.*")
+ # gfortran
+ set (CMAKE_Fortran_FLAGS_RELEASE "-funroll-loops -fno-f2c -O3 ${standard}")
+ set (CMAKE_Fortran_FLAGS_DEBUG "-fno-f2c -O0 -g ${standard}")
+elseif (Fortran_COMPILER_NAME MATCHES "ifort.*")
+ # ifort (untested)
+ set (CMAKE_Fortran_FLAGS_RELEASE "-f77rtl -O3 ${standard}")
+ set (CMAKE_Fortran_FLAGS_DEBUG "-f77rtl -O0 -g ${standard}")
+elseif (Fortran_COMPILER_NAME MATCHES "g77")
+ # g77
+ set (CMAKE_Fortran_FLAGS_RELEASE "-funroll-loops -fno-f2c -O3 -m32 ${standard}")
+ set (CMAKE_Fortran_FLAGS_DEBUG "-fno-f2c -O0 -g -m32 ${standard}")
+else (Fortran_COMPILER_NAME MATCHES "gfortran.*")
+ message ("CMAKE_Fortran_COMPILER full path: " ${CMAKE_Fortran_COMPILER})
+ message ("Fortran compiler: " ${Fortran_COMPILER_NAME})
+ message ("No optimized Fortran compiler flags are known, we just try -O2...")
+ set (CMAKE_Fortran_FLAGS_RELEASE "-O2 ${standard}")
+ set (CMAKE_Fortran_FLAGS_DEBUG "-O0 -g ${standard}")
+endif (Fortran_COMPILER_NAME MATCHES "gfortran.*")
+
+#----------------#
+# User variables #
+#----------------#
+set(SRC_DIR src)
+set(BUILD_DIR build)
+set(LIB_DIR lib)
+
+#--------------------#
+# Building libraries #
+#--------------------#
+link_directories("${LIB_DIR}")
+include_directories("${BUILD_DIR}/${LIB_DIR}")
+add_subdirectory("${SRC_DIR}" "${LIB_DIR}")
+
+add_executable(connection_test.out ${SRC_DIR}/connection_test.f90)
+target_link_libraries(connection_test.out connection_m neuron_dummy_m)
diff --git a/4neuro/Doxyfile b/4neuro/Doxyfile
new file mode 100644
index 00000000..7f3029f6
--- /dev/null
+++ b/4neuro/Doxyfile
@@ -0,0 +1,2481 @@
+# Doxyfile 1.8.14
+
+# This file describes the settings to be used by the documentation system
+# doxygen (www.doxygen.org) for a project.
+#
+# All text after a double hash (##) is considered a comment and is placed in
+# front of the TAG it is preceding.
+#
+# All text after a single hash (#) is considered a comment and will be ignored.
+# The format is:
+# TAG = value [value, ...]
+# For lists, items can also be appended using:
+# TAG += value [value, ...]
+# Values that contain spaces should be placed between quotes (\" \").
+
+#---------------------------------------------------------------------------
+# Project related configuration options
+#---------------------------------------------------------------------------
+
+# This tag specifies the encoding used for all characters in the config file
+# that follow. The default is UTF-8 which is also the encoding used for all text
+# before the first occurrence of this tag. Doxygen uses libiconv (or the iconv
+# built into libc) for the transcoding. See
+# https://www.gnu.org/software/libiconv/ for the list of possible encodings.
+# The default value is: UTF-8.
+
+DOXYFILE_ENCODING = UTF-8
+
+# The PROJECT_NAME tag is a single word (or a sequence of words surrounded by
+# double-quotes, unless you are using Doxywizard) that should identify the
+# project for which the documentation is generated. This name is used in the
+# title of most generated pages and in a few other places.
+# The default value is: My Project.
+
+PROJECT_NAME = "4Neuro"
+
+# The PROJECT_NUMBER tag can be used to enter a project or revision number. This
+# could be handy for archiving the generated documentation or if some version
+# control system is used.
+
+PROJECT_NUMBER =
+
+# Using the PROJECT_BRIEF tag one can provide an optional one line description
+# for a project that appears at the top of each page and should give viewer a
+# quick idea about the purpose of the project. Keep the description short.
+
+PROJECT_BRIEF = "Fortran neural networks library"
+
+# With the PROJECT_LOGO tag one can specify a logo or an icon that is included
+# in the documentation. The maximum height of the logo should not exceed 55
+# pixels and the maximum width should not exceed 200 pixels. Doxygen will copy
+# the logo to the output directory.
+
+PROJECT_LOGO = "img/4neuro_logo_small.png"
+
+# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute) path
+# into which the generated documentation will be written. If a relative path is
+# entered, it will be relative to the location where doxygen was started. If
+# left blank the current directory will be used.
+
+OUTPUT_DIRECTORY = "docs"
+
+# If the CREATE_SUBDIRS tag is set to YES then doxygen will create 4096 sub-
+# directories (in 2 levels) under the output directory of each output format and
+# will distribute the generated files over these directories. Enabling this
+# option can be useful when feeding doxygen a huge amount of source files, where
+# putting all generated files in the same directory would otherwise causes
+# performance problems for the file system.
+# The default value is: NO.
+
+CREATE_SUBDIRS = NO
+
+# If the ALLOW_UNICODE_NAMES tag is set to YES, doxygen will allow non-ASCII
+# characters to appear in the names of generated files. If set to NO, non-ASCII
+# characters will be escaped, for example _xE3_x81_x84 will be used for Unicode
+# U+3044.
+# The default value is: NO.
+
+ALLOW_UNICODE_NAMES = NO
+
+# The OUTPUT_LANGUAGE tag is used to specify the language in which all
+# documentation generated by doxygen is written. Doxygen will use this
+# information to generate all constant output in the proper language.
+# Possible values are: Afrikaans, Arabic, Armenian, Brazilian, Catalan, Chinese,
+# Chinese-Traditional, Croatian, Czech, Danish, Dutch, English (United States),
+# Esperanto, Farsi (Persian), Finnish, French, German, Greek, Hungarian,
+# Indonesian, Italian, Japanese, Japanese-en (Japanese with English messages),
+# Korean, Korean-en (Korean with English messages), Latvian, Lithuanian,
+# Macedonian, Norwegian, Persian (Farsi), Polish, Portuguese, Romanian, Russian,
+# Serbian, Serbian-Cyrillic, Slovak, Slovene, Spanish, Swedish, Turkish,
+# Ukrainian and Vietnamese.
+# The default value is: English.
+
+OUTPUT_LANGUAGE = English
+
+# If the BRIEF_MEMBER_DESC tag is set to YES, doxygen will include brief member
+# descriptions after the members that are listed in the file and class
+# documentation (similar to Javadoc). Set to NO to disable this.
+# The default value is: YES.
+
+BRIEF_MEMBER_DESC = YES
+
+# If the REPEAT_BRIEF tag is set to YES, doxygen will prepend the brief
+# description of a member or function before the detailed description
+#
+# Note: If both HIDE_UNDOC_MEMBERS and BRIEF_MEMBER_DESC are set to NO, the
+# brief descriptions will be completely suppressed.
+# The default value is: YES.
+
+REPEAT_BRIEF = YES
+
+# This tag implements a quasi-intelligent brief description abbreviator that is
+# used to form the text in various listings. Each string in this list, if found
+# as the leading text of the brief description, will be stripped from the text
+# and the result, after processing the whole list, is used as the annotated
+# text. Otherwise, the brief description is used as-is. If left blank, the
+# following values are used ($name is automatically replaced with the name of
+# the entity):The $name class, The $name widget, The $name file, is, provides,
+# specifies, contains, represents, a, an and the.
+
+ABBREVIATE_BRIEF = "The $name class" \
+ "The $name widget" \
+ "The $name file" \
+ is \
+ provides \
+ specifies \
+ contains \
+ represents \
+ a \
+ an \
+ the
+
+# If the ALWAYS_DETAILED_SEC and REPEAT_BRIEF tags are both set to YES then
+# doxygen will generate a detailed section even if there is only a brief
+# description.
+# The default value is: NO.
+
+ALWAYS_DETAILED_SEC = NO
+
+# If the INLINE_INHERITED_MEMB tag is set to YES, doxygen will show all
+# inherited members of a class in the documentation of that class as if those
+# members were ordinary class members. Constructors, destructors and assignment
+# operators of the base classes will not be shown.
+# The default value is: NO.
+
+INLINE_INHERITED_MEMB = NO
+
+# If the FULL_PATH_NAMES tag is set to YES, doxygen will prepend the full path
+# before files name in the file list and in the header files. If set to NO the
+# shortest path that makes the file name unique will be used
+# The default value is: YES.
+
+FULL_PATH_NAMES = YES
+
+# The STRIP_FROM_PATH tag can be used to strip a user-defined part of the path.
+# Stripping is only done if one of the specified strings matches the left-hand
+# part of the path. The tag can be used to show relative paths in the file list.
+# If left blank the directory from which doxygen is run is used as the path to
+# strip.
+#
+# Note that you can specify absolute paths here, but also relative paths, which
+# will be relative from the directory where doxygen is started.
+# This tag requires that the tag FULL_PATH_NAMES is set to YES.
+
+STRIP_FROM_PATH =
+
+# The STRIP_FROM_INC_PATH tag can be used to strip a user-defined part of the
+# path mentioned in the documentation of a class, which tells the reader which
+# header file to include in order to use a class. If left blank only the name of
+# the header file containing the class definition is used. Otherwise one should
+# specify the list of include paths that are normally passed to the compiler
+# using the -I flag.
+
+STRIP_FROM_INC_PATH =
+
+# If the SHORT_NAMES tag is set to YES, doxygen will generate much shorter (but
+# less readable) file names. This can be useful is your file systems doesn't
+# support long names like on DOS, Mac, or CD-ROM.
+# The default value is: NO.
+
+SHORT_NAMES = NO
+
+# If the JAVADOC_AUTOBRIEF tag is set to YES then doxygen will interpret the
+# first line (until the first dot) of a Javadoc-style comment as the brief
+# description. If set to NO, the Javadoc-style will behave just like regular Qt-
+# style comments (thus requiring an explicit @brief command for a brief
+# description.)
+# The default value is: NO.
+
+JAVADOC_AUTOBRIEF = NO
+
+# If the QT_AUTOBRIEF tag is set to YES then doxygen will interpret the first
+# line (until the first dot) of a Qt-style comment as the brief description. If
+# set to NO, the Qt-style will behave just like regular Qt-style comments (thus
+# requiring an explicit \brief command for a brief description.)
+# The default value is: NO.
+
+QT_AUTOBRIEF = NO
+
+# The MULTILINE_CPP_IS_BRIEF tag can be set to YES to make doxygen treat a
+# multi-line C++ special comment block (i.e. a block of //! or /// comments) as
+# a brief description. This used to be the default behavior. The new default is
+# to treat a multi-line C++ comment block as a detailed description. Set this
+# tag to YES if you prefer the old behavior instead.
+#
+# Note that setting this tag to YES also means that rational rose comments are
+# not recognized any more.
+# The default value is: NO.
+
+MULTILINE_CPP_IS_BRIEF = NO
+
+# If the INHERIT_DOCS tag is set to YES then an undocumented member inherits the
+# documentation from any documented member that it re-implements.
+# The default value is: YES.
+
+INHERIT_DOCS = YES
+
+# If the SEPARATE_MEMBER_PAGES tag is set to YES then doxygen will produce a new
+# page for each member. If set to NO, the documentation of a member will be part
+# of the file/class/namespace that contains it.
+# The default value is: NO.
+
+SEPARATE_MEMBER_PAGES = NO
+
+# The TAB_SIZE tag can be used to set the number of spaces in a tab. Doxygen
+# uses this value to replace tabs by spaces in code fragments.
+# Minimum value: 1, maximum value: 16, default value: 4.
+
+TAB_SIZE = 4
+
+# This tag can be used to specify a number of aliases that act as commands in
+# the documentation. An alias has the form:
+# name=value
+# For example adding
+# "sideeffect=@par Side Effects:\n"
+# will allow you to put the command \sideeffect (or @sideeffect) in the
+# documentation, which will result in a user-defined paragraph with heading
+# "Side Effects:". You can put \n's in the value part of an alias to insert
+# newlines.
+
+ALIASES =
+
+# This tag can be used to specify a number of word-keyword mappings (TCL only).
+# A mapping has the form "name=value". For example adding "class=itcl::class"
+# will allow you to use the command class in the itcl::class meaning.
+
+TCL_SUBST =
+
+# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C sources
+# only. Doxygen will then generate output that is more tailored for C. For
+# instance, some of the names that are used will be different. The list of all
+# members will be omitted, etc.
+# The default value is: NO.
+
+OPTIMIZE_OUTPUT_FOR_C = NO
+
+# Set the OPTIMIZE_OUTPUT_JAVA tag to YES if your project consists of Java or
+# Python sources only. Doxygen will then generate output that is more tailored
+# for that language. For instance, namespaces will be presented as packages,
+# qualified scopes will look different, etc.
+# The default value is: NO.
+
+OPTIMIZE_OUTPUT_JAVA = NO
+
+# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran
+# sources. Doxygen will then generate output that is tailored for Fortran.
+# The default value is: NO.
+
+OPTIMIZE_FOR_FORTRAN = YES
+
+# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL
+# sources. Doxygen will then generate output that is tailored for VHDL.
+# The default value is: NO.
+
+OPTIMIZE_OUTPUT_VHDL = NO
+
+# Doxygen selects the parser to use depending on the extension of the files it
+# parses. With this tag you can assign which parser to use for a given
+# extension. Doxygen has a built-in mapping, but you can override or extend it
+# using this tag. The format is ext=language, where ext is a file extension, and
+# language is one of the parsers supported by doxygen: IDL, Java, Javascript,
+# C#, C, C++, D, PHP, Objective-C, Python, Fortran (fixed format Fortran:
+# FortranFixed, free formatted Fortran: FortranFree, unknown formatted Fortran:
+# Fortran. In the later case the parser tries to guess whether the code is fixed
+# or free formatted code, this is the default for Fortran type files), VHDL. For
+# instance to make doxygen treat .inc files as Fortran files (default is PHP),
+# and .f files as C (default is Fortran), use: inc=Fortran f=C.
+#
+# Note: For files without extension you can use no_extension as a placeholder.
+#
+# Note that for custom extensions you also need to set FILE_PATTERNS otherwise
+# the files are not read by doxygen.
+
+EXTENSION_MAPPING = f03=FortranFree f08=FortranFree
+
+# If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments
+# according to the Markdown format, which allows for more readable
+# documentation. See http://daringfireball.net/projects/markdown/ for details.
+# The output of markdown processing is further processed by doxygen, so you can
+# mix doxygen, HTML, and XML commands with Markdown formatting. Disable only in
+# case of backward compatibilities issues.
+# The default value is: YES.
+
+MARKDOWN_SUPPORT = YES
+
+# When the TOC_INCLUDE_HEADINGS tag is set to a non-zero value, all headings up
+# to that level are automatically included in the table of contents, even if
+# they do not have an id attribute.
+# Note: This feature currently applies only to Markdown headings.
+# Minimum value: 0, maximum value: 99, default value: 0.
+# This tag requires that the tag MARKDOWN_SUPPORT is set to YES.
+
+TOC_INCLUDE_HEADINGS = 0
+
+# When enabled doxygen tries to link words that correspond to documented
+# classes, or namespaces to their corresponding documentation. Such a link can
+# be prevented in individual cases by putting a % sign in front of the word or
+# globally by setting AUTOLINK_SUPPORT to NO.
+# The default value is: YES.
+
+AUTOLINK_SUPPORT = YES
+
+# If you use STL classes (i.e. std::string, std::vector, etc.) but do not want
+# to include (a tag file for) the STL sources as input, then you should set this
+# tag to YES in order to let doxygen match functions declarations and
+# definitions whose arguments contain STL classes (e.g. func(std::string);
+# versus func(std::string) {}). This also make the inheritance and collaboration
+# diagrams that involve STL classes more complete and accurate.
+# The default value is: NO.
+
+BUILTIN_STL_SUPPORT = NO
+
+# If you use Microsoft's C++/CLI language, you should set this option to YES to
+# enable parsing support.
+# The default value is: NO.
+
+CPP_CLI_SUPPORT = NO
+
+# Set the SIP_SUPPORT tag to YES if your project consists of sip (see:
+# https://www.riverbankcomputing.com/software/sip/intro) sources only. Doxygen
+# will parse them like normal C++ but will assume all classes use public instead
+# of private inheritance when no explicit protection keyword is present.
+# The default value is: NO.
+
+SIP_SUPPORT = NO
+
+# For Microsoft's IDL there are propget and propput attributes to indicate
+# getter and setter methods for a property. Setting this option to YES will make
+# doxygen to replace the get and set methods by a property in the documentation.
+# This will only work if the methods are indeed getting or setting a simple
+# type. If this is not the case, or you want to show the methods anyway, you
+# should set this option to NO.
+# The default value is: YES.
+
+IDL_PROPERTY_SUPPORT = YES
+
+# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC
+# tag is set to YES then doxygen will reuse the documentation of the first
+# member in the group (if any) for the other members of the group. By default
+# all members of a group must be documented explicitly.
+# The default value is: NO.
+
+DISTRIBUTE_GROUP_DOC = NO
+
+# If one adds a struct or class to a group and this option is enabled, then also
+# any nested class or struct is added to the same group. By default this option
+# is disabled and one has to add nested compounds explicitly via \ingroup.
+# The default value is: NO.
+
+GROUP_NESTED_COMPOUNDS = NO
+
+# Set the SUBGROUPING tag to YES to allow class member groups of the same type
+# (for instance a group of public functions) to be put as a subgroup of that
+# type (e.g. under the Public Functions section). Set it to NO to prevent
+# subgrouping. Alternatively, this can be done per class using the
+# \nosubgrouping command.
+# The default value is: YES.
+
+SUBGROUPING = YES
+
+# When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and unions
+# are shown inside the group in which they are included (e.g. using \ingroup)
+# instead of on a separate page (for HTML and Man pages) or section (for LaTeX
+# and RTF).
+#
+# Note that this feature does not work in combination with
+# SEPARATE_MEMBER_PAGES.
+# The default value is: NO.
+
+INLINE_GROUPED_CLASSES = NO
+
+# When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and unions
+# with only public data fields or simple typedef fields will be shown inline in
+# the documentation of the scope in which they are defined (i.e. file,
+# namespace, or group documentation), provided this scope is documented. If set
+# to NO, structs, classes, and unions are shown on a separate page (for HTML and
+# Man pages) or section (for LaTeX and RTF).
+# The default value is: NO.
+
+INLINE_SIMPLE_STRUCTS = NO
+
+# When TYPEDEF_HIDES_STRUCT tag is enabled, a typedef of a struct, union, or
+# enum is documented as struct, union, or enum with the name of the typedef. So
+# typedef struct TypeS {} TypeT, will appear in the documentation as a struct
+# with name TypeT. When disabled the typedef will appear as a member of a file,
+# namespace, or class. And the struct will be named TypeS. This can typically be
+# useful for C code in case the coding convention dictates that all compound
+# types are typedef'ed and only the typedef is referenced, never the tag name.
+# The default value is: NO.
+
+TYPEDEF_HIDES_STRUCT = NO
+
+# The size of the symbol lookup cache can be set using LOOKUP_CACHE_SIZE. This
+# cache is used to resolve symbols given their name and scope. Since this can be
+# an expensive process and often the same symbol appears multiple times in the
+# code, doxygen keeps a cache of pre-resolved symbols. If the cache is too small
+# doxygen will become slower. If the cache is too large, memory is wasted. The
+# cache size is given by this formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range
+# is 0..9, the default is 0, corresponding to a cache size of 2^16=65536
+# symbols. At the end of a run doxygen will report the cache usage and suggest
+# the optimal cache size from a speed point of view.
+# Minimum value: 0, maximum value: 9, default value: 0.
+
+LOOKUP_CACHE_SIZE = 0
+
+#---------------------------------------------------------------------------
+# Build related configuration options
+#---------------------------------------------------------------------------
+
+# If the EXTRACT_ALL tag is set to YES, doxygen will assume all entities in
+# documentation are documented, even if no documentation was available. Private
+# class members and static file members will be hidden unless the
+# EXTRACT_PRIVATE respectively EXTRACT_STATIC tags are set to YES.
+# Note: This will also disable the warnings about undocumented members that are
+# normally produced when WARNINGS is set to YES.
+# The default value is: NO.
+
+EXTRACT_ALL = NO
+
+# If the EXTRACT_PRIVATE tag is set to YES, all private members of a class will
+# be included in the documentation.
+# The default value is: NO.
+
+EXTRACT_PRIVATE = NO
+
+# If the EXTRACT_PACKAGE tag is set to YES, all members with package or internal
+# scope will be included in the documentation.
+# The default value is: NO.
+
+EXTRACT_PACKAGE = NO
+
+# If the EXTRACT_STATIC tag is set to YES, all static members of a file will be
+# included in the documentation.
+# The default value is: NO.
+
+EXTRACT_STATIC = NO
+
+# If the EXTRACT_LOCAL_CLASSES tag is set to YES, classes (and structs) defined
+# locally in source files will be included in the documentation. If set to NO,
+# only classes defined in header files are included. Does not have any effect
+# for Java sources.
+# The default value is: YES.
+
+EXTRACT_LOCAL_CLASSES = YES
+
+# This flag is only useful for Objective-C code. If set to YES, local methods,
+# which are defined in the implementation section but not in the interface are
+# included in the documentation. If set to NO, only methods in the interface are
+# included.
+# The default value is: NO.
+
+EXTRACT_LOCAL_METHODS = NO
+
+# If this flag is set to YES, the members of anonymous namespaces will be
+# extracted and appear in the documentation as a namespace called
+# 'anonymous_namespace{file}', where file will be replaced with the base name of
+# the file that contains the anonymous namespace. By default anonymous namespace
+# are hidden.
+# The default value is: NO.
+
+EXTRACT_ANON_NSPACES = NO
+
+# If the HIDE_UNDOC_MEMBERS tag is set to YES, doxygen will hide all
+# undocumented members inside documented classes or files. If set to NO these
+# members will be included in the various overviews, but no documentation
+# section is generated. This option has no effect if EXTRACT_ALL is enabled.
+# The default value is: NO.
+
+HIDE_UNDOC_MEMBERS = NO
+
+# If the HIDE_UNDOC_CLASSES tag is set to YES, doxygen will hide all
+# undocumented classes that are normally visible in the class hierarchy. If set
+# to NO, these classes will be included in the various overviews. This option
+# has no effect if EXTRACT_ALL is enabled.
+# The default value is: NO.
+
+HIDE_UNDOC_CLASSES = NO
+
+# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, doxygen will hide all friend
+# (class|struct|union) declarations. If set to NO, these declarations will be
+# included in the documentation.
+# The default value is: NO.
+
+HIDE_FRIEND_COMPOUNDS = NO
+
+# If the HIDE_IN_BODY_DOCS tag is set to YES, doxygen will hide any
+# documentation blocks found inside the body of a function. If set to NO, these
+# blocks will be appended to the function's detailed documentation block.
+# The default value is: NO.
+
+HIDE_IN_BODY_DOCS = NO
+
+# The INTERNAL_DOCS tag determines if documentation that is typed after a
+# \internal command is included. If the tag is set to NO then the documentation
+# will be excluded. Set it to YES to include the internal documentation.
+# The default value is: NO.
+
+INTERNAL_DOCS = NO
+
+# If the CASE_SENSE_NAMES tag is set to NO then doxygen will only generate file
+# names in lower-case letters. If set to YES, upper-case letters are also
+# allowed. This is useful if you have classes or files whose names only differ
+# in case and if your file system supports case sensitive file names. Windows
+# and Mac users are advised to set this option to NO.
+# The default value is: system dependent.
+
+CASE_SENSE_NAMES = YES
+
+# If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with
+# their full class and namespace scopes in the documentation. If set to YES, the
+# scope will be hidden.
+# The default value is: NO.
+
+HIDE_SCOPE_NAMES = NO
+
+# If the HIDE_COMPOUND_REFERENCE tag is set to NO (default) then doxygen will
+# append additional text to a page's title, such as Class Reference. If set to
+# YES the compound reference will be hidden.
+# The default value is: NO.
+
+HIDE_COMPOUND_REFERENCE= NO
+
+# If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of
+# the files that are included by a file in the documentation of that file.
+# The default value is: YES.
+
+SHOW_INCLUDE_FILES = YES
+
+# If the SHOW_GROUPED_MEMB_INC tag is set to YES then Doxygen will add for each
+# grouped member an include statement to the documentation, telling the reader
+# which file to include in order to use the member.
+# The default value is: NO.
+
+SHOW_GROUPED_MEMB_INC = NO
+
+# If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include
+# files with double quotes in the documentation rather than with sharp brackets.
+# The default value is: NO.
+
+FORCE_LOCAL_INCLUDES = NO
+
+# If the INLINE_INFO tag is set to YES then a tag [inline] is inserted in the
+# documentation for inline members.
+# The default value is: YES.
+
+INLINE_INFO = YES
+
+# If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the
+# (detailed) documentation of file and class members alphabetically by member
+# name. If set to NO, the members will appear in declaration order.
+# The default value is: YES.
+
+SORT_MEMBER_DOCS = YES
+
+# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief
+# descriptions of file, namespace and class members alphabetically by member
+# name. If set to NO, the members will appear in declaration order. Note that
+# this will also influence the order of the classes in the class list.
+# The default value is: NO.
+
+SORT_BRIEF_DOCS = NO
+
+# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the
+# (brief and detailed) documentation of class members so that constructors and
+# destructors are listed first. If set to NO the constructors will appear in the
+# respective orders defined by SORT_BRIEF_DOCS and SORT_MEMBER_DOCS.
+# Note: If SORT_BRIEF_DOCS is set to NO this option is ignored for sorting brief
+# member documentation.
+# Note: If SORT_MEMBER_DOCS is set to NO this option is ignored for sorting
+# detailed member documentation.
+# The default value is: NO.
+
+SORT_MEMBERS_CTORS_1ST = NO
+
+# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the hierarchy
+# of group names into alphabetical order. If set to NO the group names will
+# appear in their defined order.
+# The default value is: NO.
+
+SORT_GROUP_NAMES = NO
+
+# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be sorted by
+# fully-qualified names, including namespaces. If set to NO, the class list will
+# be sorted only by class name, not including the namespace part.
+# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES.
+# Note: This option applies only to the class list, not to the alphabetical
+# list.
+# The default value is: NO.
+
+SORT_BY_SCOPE_NAME = NO
+
+# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper
+# type resolution of all parameters of a function it will reject a match between
+# the prototype and the implementation of a member function even if there is
+# only one candidate or it is obvious which candidate to choose by doing a
+# simple string match. By disabling STRICT_PROTO_MATCHING doxygen will still
+# accept a match between prototype and implementation in such cases.
+# The default value is: NO.
+
+STRICT_PROTO_MATCHING = NO
+
+# The GENERATE_TODOLIST tag can be used to enable (YES) or disable (NO) the todo
+# list. This list is created by putting \todo commands in the documentation.
+# The default value is: YES.
+
+GENERATE_TODOLIST = YES
+
+# The GENERATE_TESTLIST tag can be used to enable (YES) or disable (NO) the test
+# list. This list is created by putting \test commands in the documentation.
+# The default value is: YES.
+
+GENERATE_TESTLIST = YES
+
+# The GENERATE_BUGLIST tag can be used to enable (YES) or disable (NO) the bug
+# list. This list is created by putting \bug commands in the documentation.
+# The default value is: YES.
+
+GENERATE_BUGLIST = YES
+
+# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or disable (NO)
+# the deprecated list. This list is created by putting \deprecated commands in
+# the documentation.
+# The default value is: YES.
+
+GENERATE_DEPRECATEDLIST= YES
+
+# The ENABLED_SECTIONS tag can be used to enable conditional documentation
+# sections, marked by \if <section_label> ... \endif and \cond <section_label>
+# ... \endcond blocks.
+
+ENABLED_SECTIONS =
+
+# The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the
+# initial value of a variable or macro / define can have for it to appear in the
+# documentation. If the initializer consists of more lines than specified here
+# it will be hidden. Use a value of 0 to hide initializers completely. The
+# appearance of the value of individual variables and macros / defines can be
+# controlled using \showinitializer or \hideinitializer command in the
+# documentation regardless of this setting.
+# Minimum value: 0, maximum value: 10000, default value: 30.
+
+MAX_INITIALIZER_LINES = 30
+
+# Set the SHOW_USED_FILES tag to NO to disable the list of files generated at
+# the bottom of the documentation of classes and structs. If set to YES, the
+# list will mention the files that were used to generate the documentation.
+# The default value is: YES.
+
+SHOW_USED_FILES = YES
+
+# Set the SHOW_FILES tag to NO to disable the generation of the Files page. This
+# will remove the Files entry from the Quick Index and from the Folder Tree View
+# (if specified).
+# The default value is: YES.
+
+SHOW_FILES = YES
+
+# Set the SHOW_NAMESPACES tag to NO to disable the generation of the Namespaces
+# page. This will remove the Namespaces entry from the Quick Index and from the
+# Folder Tree View (if specified).
+# The default value is: YES.
+
+SHOW_NAMESPACES = YES
+
+# The FILE_VERSION_FILTER tag can be used to specify a program or script that
+# doxygen should invoke to get the current version for each file (typically from
+# the version control system). Doxygen will invoke the program by executing (via
+# popen()) the command command input-file, where command is the value of the
+# FILE_VERSION_FILTER tag, and input-file is the name of an input file provided
+# by doxygen. Whatever the program writes to standard output is used as the file
+# version. For an example see the documentation.
+
+FILE_VERSION_FILTER =
+
+# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed
+# by doxygen. The layout file controls the global structure of the generated
+# output files in an output format independent way. To create the layout file
+# that represents doxygen's defaults, run doxygen with the -l option. You can
+# optionally specify a file name after the option, if omitted DoxygenLayout.xml
+# will be used as the name of the layout file.
+#
+# Note that if you run doxygen from a directory containing a file called
+# DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE
+# tag is left empty.
+
+LAYOUT_FILE =
+
+# The CITE_BIB_FILES tag can be used to specify one or more bib files containing
+# the reference definitions. This must be a list of .bib files. The .bib
+# extension is automatically appended if omitted. This requires the bibtex tool
+# to be installed. See also https://en.wikipedia.org/wiki/BibTeX for more info.
+# For LaTeX the style of the bibliography can be controlled using
+# LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the
+# search path. See also \cite for info how to create references.
+
+CITE_BIB_FILES =
+
+#---------------------------------------------------------------------------
+# Configuration options related to warning and progress messages
+#---------------------------------------------------------------------------
+
+# The QUIET tag can be used to turn on/off the messages that are generated to
+# standard output by doxygen. If QUIET is set to YES this implies that the
+# messages are off.
+# The default value is: NO.
+
+QUIET = NO
+
+# The WARNINGS tag can be used to turn on/off the warning messages that are
+# generated to standard error (stderr) by doxygen. If WARNINGS is set to YES
+# this implies that the warnings are on.
+#
+# Tip: Turn warnings on while writing the documentation.
+# The default value is: YES.
+
+WARNINGS = YES
+
+# If the WARN_IF_UNDOCUMENTED tag is set to YES then doxygen will generate
+# warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag
+# will automatically be disabled.
+# The default value is: YES.
+
+WARN_IF_UNDOCUMENTED = YES
+
+# If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for
+# potential errors in the documentation, such as not documenting some parameters
+# in a documented function, or documenting parameters that don't exist or using
+# markup commands wrongly.
+# The default value is: YES.
+
+WARN_IF_DOC_ERROR = YES
+
+# This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that
+# are documented, but have no documentation for their parameters or return
+# value. If set to NO, doxygen will only warn about wrong or incomplete
+# parameter documentation, but not about the absence of documentation.
+# The default value is: NO.
+
+WARN_NO_PARAMDOC = NO
+
+# If the WARN_AS_ERROR tag is set to YES then doxygen will immediately stop when
+# a warning is encountered.
+# The default value is: NO.
+
+WARN_AS_ERROR = NO
+
+# The WARN_FORMAT tag determines the format of the warning messages that doxygen
+# can produce. The string should contain the $file, $line, and $text tags, which
+# will be replaced by the file and line number from which the warning originated
+# and the warning text. Optionally the format may contain $version, which will
+# be replaced by the version of the file (if it could be obtained via
+# FILE_VERSION_FILTER)
+# The default value is: $file:$line: $text.
+
+WARN_FORMAT = "$file:$line: $text"
+
+# The WARN_LOGFILE tag can be used to specify a file to which warning and error
+# messages should be written. If left blank the output is written to standard
+# error (stderr).
+
+WARN_LOGFILE =
+
+#---------------------------------------------------------------------------
+# Configuration options related to the input files
+#---------------------------------------------------------------------------
+
+# The INPUT tag is used to specify the files and/or directories that contain
+# documented source files. You may enter file names like myfile.cpp or
+# directories like /usr/src/myproject. Separate the files or directories with
+# spaces. See also FILE_PATTERNS and EXTENSION_MAPPING
+# Note: If this tag is empty the current directory is searched.
+
+INPUT = "src"
+
+# This tag can be used to specify the character encoding of the source files
+# that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses
+# libiconv (or the iconv built into libc) for the transcoding. See the libiconv
+# documentation (see: https://www.gnu.org/software/libiconv/) for the list of
+# possible encodings.
+# The default value is: UTF-8.
+
+INPUT_ENCODING = UTF-8
+
+# If the value of the INPUT tag contains directories, you can use the
+# FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and
+# *.h) to filter out the source-files in the directories.
+#
+# Note that for custom extensions or not directly supported extensions you also
+# need to set EXTENSION_MAPPING for the extension otherwise the files are not
+# read by doxygen.
+#
+# If left blank the following patterns are tested:*.c, *.cc, *.cxx, *.cpp,
+# *.c++, *.java, *.ii, *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h,
+# *.hh, *.hxx, *.hpp, *.h++, *.cs, *.d, *.php, *.php4, *.php5, *.phtml, *.inc,
+# *.m, *.markdown, *.md, *.mm, *.dox, *.py, *.pyw, *.f90, *.f95, *.f03, *.f08,
+# *.f, *.for, *.tcl, *.vhd, *.vhdl, *.ucf and *.qsf.
+
+FILE_PATTERNS = *.c \
+ *.cc \
+ *.cxx \
+ *.cpp \
+ *.c++ \
+ *.java \
+ *.ii \
+ *.ixx \
+ *.ipp \
+ *.i++ \
+ *.inl \
+ *.idl \
+ *.ddl \
+ *.odl \
+ *.h \
+ *.hh \
+ *.hxx \
+ *.hpp \
+ *.h++ \
+ *.cs \
+ *.d \
+ *.php \
+ *.php4 \
+ *.php5 \
+ *.phtml \
+ *.inc \
+ *.m \
+ *.markdown \
+ *.md \
+ *.mm \
+ *.dox \
+ *.py \
+ *.pyw \
+ *.f90 \
+ *.f95 \
+ *.f03 \
+ *.f08 \
+ *.f \
+ *.for \
+ *.tcl \
+ *.vhd \
+ *.vhdl \
+ *.ucf \
+ *.qsf
+
+# The RECURSIVE tag can be used to specify whether or not subdirectories should
+# be searched for input files as well.
+# The default value is: NO.
+
+RECURSIVE = NO
+
+# The EXCLUDE tag can be used to specify files and/or directories that should be
+# excluded from the INPUT source files. This way you can easily exclude a
+# subdirectory from a directory tree whose root is specified with the INPUT tag.
+#
+# Note that relative paths are relative to the directory from which doxygen is
+# run.
+
+EXCLUDE =
+
+# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
+# directories that are symbolic links (a Unix file system feature) are excluded
+# from the input.
+# The default value is: NO.
+
+EXCLUDE_SYMLINKS = NO
+
+# If the value of the INPUT tag contains directories, you can use the
+# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude
+# certain files from those directories.
+#
+# Note that the wildcards are matched against the file with absolute path, so to
+# exclude all test directories for example use the pattern */test/*
+
+EXCLUDE_PATTERNS =
+
+# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
+# (namespaces, classes, functions, etc.) that should be excluded from the
+# output. The symbol name can be a fully qualified name, a word, or if the
+# wildcard * is used, a substring. Examples: ANamespace, AClass,
+# AClass::ANamespace, ANamespace::*Test
+#
+# Note that the wildcards are matched against the file with absolute path, so to
+# exclude all test directories use the pattern */test/*
+
+EXCLUDE_SYMBOLS =
+
+# The EXAMPLE_PATH tag can be used to specify one or more files or directories
+# that contain example code fragments that are included (see the \include
+# command).
+
+EXAMPLE_PATH =
+
+# If the value of the EXAMPLE_PATH tag contains directories, you can use the
+# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and
+# *.h) to filter out the source-files in the directories. If left blank all
+# files are included.
+
+EXAMPLE_PATTERNS = *
+
+# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be
+# searched for input files to be used with the \include or \dontinclude commands
+# irrespective of the value of the RECURSIVE tag.
+# The default value is: NO.
+
+EXAMPLE_RECURSIVE = NO
+
+# The IMAGE_PATH tag can be used to specify one or more files or directories
+# that contain images that are to be included in the documentation (see the
+# \image command).
+
+IMAGE_PATH =
+
+# The INPUT_FILTER tag can be used to specify a program that doxygen should
+# invoke to filter for each input file. Doxygen will invoke the filter program
+# by executing (via popen()) the command:
+#
+# <filter> <input-file>
+#
+# where <filter> is the value of the INPUT_FILTER tag, and <input-file> is the
+# name of an input file. Doxygen will then use the output that the filter
+# program writes to standard output. If FILTER_PATTERNS is specified, this tag
+# will be ignored.
+#
+# Note that the filter must not add or remove lines; it is applied before the
+# code is scanned, but not when the output code is generated. If lines are added
+# or removed, the anchors will not be placed correctly.
+#
+# Note that for custom extensions or not directly supported extensions you also
+# need to set EXTENSION_MAPPING for the extension otherwise the files are not
+# properly processed by doxygen.
+
+INPUT_FILTER =
+
+# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern
+# basis. Doxygen will compare the file name with each pattern and apply the
+# filter if there is a match. The filters are a list of the form: pattern=filter
+# (like *.cpp=my_cpp_filter). See INPUT_FILTER for further information on how
+# filters are used. If the FILTER_PATTERNS tag is empty or if none of the
+# patterns match the file name, INPUT_FILTER is applied.
+#
+# Note that for custom extensions or not directly supported extensions you also
+# need to set EXTENSION_MAPPING for the extension otherwise the files are not
+# properly processed by doxygen.
+
+FILTER_PATTERNS =
+
+# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using
+# INPUT_FILTER) will also be used to filter the input files that are used for
+# producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES).
+# The default value is: NO.
+
+FILTER_SOURCE_FILES = NO
+
+# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file
+# pattern. A pattern will override the setting for FILTER_PATTERN (if any) and
+# it is also possible to disable source filtering for a specific pattern using
+# *.ext= (so without naming a filter).
+# This tag requires that the tag FILTER_SOURCE_FILES is set to YES.
+
+FILTER_SOURCE_PATTERNS =
+
+# If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that
+# is part of the input, its contents will be placed on the main page
+# (index.html). This can be useful if you have a project on for instance GitHub
+# and want to reuse the introduction page also for the doxygen output.
+
+USE_MDFILE_AS_MAINPAGE =
+
+#---------------------------------------------------------------------------
+# Configuration options related to source browsing
+#---------------------------------------------------------------------------
+
+# If the SOURCE_BROWSER tag is set to YES then a list of source files will be
+# generated. Documented entities will be cross-referenced with these sources.
+#
+# Note: To get rid of all source code in the generated output, make sure that
+# also VERBATIM_HEADERS is set to NO.
+# The default value is: NO.
+
+SOURCE_BROWSER = NO
+
+# Setting the INLINE_SOURCES tag to YES will include the body of functions,
+# classes and enums directly into the documentation.
+# The default value is: NO.
+
+INLINE_SOURCES = NO
+
+# Setting the STRIP_CODE_COMMENTS tag to YES will instruct doxygen to hide any
+# special comment blocks from generated source code fragments. Normal C, C++ and
+# Fortran comments will always remain visible.
+# The default value is: YES.
+
+STRIP_CODE_COMMENTS = YES
+
+# If the REFERENCED_BY_RELATION tag is set to YES then for each documented
+# function all documented functions referencing it will be listed.
+# The default value is: NO.
+
+REFERENCED_BY_RELATION = NO
+
+# If the REFERENCES_RELATION tag is set to YES then for each documented function
+# all documented entities called/used by that function will be listed.
+# The default value is: NO.
+
+REFERENCES_RELATION = NO
+
+# If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set
+# to YES then the hyperlinks from functions in REFERENCES_RELATION and
+# REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will
+# link to the documentation.
+# The default value is: YES.
+
+REFERENCES_LINK_SOURCE = YES
+
+# If SOURCE_TOOLTIPS is enabled (the default) then hovering a hyperlink in the
+# source code will show a tooltip with additional information such as prototype,
+# brief description and links to the definition and documentation. Since this
+# will make the HTML file larger and loading of large files a bit slower, you
+# can opt to disable this feature.
+# The default value is: YES.
+# This tag requires that the tag SOURCE_BROWSER is set to YES.
+
+SOURCE_TOOLTIPS = YES
+
+# If the USE_HTAGS tag is set to YES then the references to source code will
+# point to the HTML generated by the htags(1) tool instead of doxygen built-in
+# source browser. The htags tool is part of GNU's global source tagging system
+# (see https://www.gnu.org/software/global/global.html). You will need version
+# 4.8.6 or higher.
+#
+# To use it do the following:
+# - Install the latest version of global
+# - Enable SOURCE_BROWSER and USE_HTAGS in the config file
+# - Make sure the INPUT points to the root of the source tree
+# - Run doxygen as normal
+#
+# Doxygen will invoke htags (and that will in turn invoke gtags), so these
+# tools must be available from the command line (i.e. in the search path).
+#
+# The result: instead of the source browser generated by doxygen, the links to
+# source code will now point to the output of htags.
+# The default value is: NO.
+# This tag requires that the tag SOURCE_BROWSER is set to YES.
+
+USE_HTAGS = NO
+
+# If the VERBATIM_HEADERS tag is set the YES then doxygen will generate a
+# verbatim copy of the header file for each class for which an include is
+# specified. Set to NO to disable this.
+# See also: Section \class.
+# The default value is: YES.
+
+VERBATIM_HEADERS = YES
+
+#---------------------------------------------------------------------------
+# Configuration options related to the alphabetical class index
+#---------------------------------------------------------------------------
+
+# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index of all
+# compounds will be generated. Enable this if the project contains a lot of
+# classes, structs, unions or interfaces.
+# The default value is: YES.
+
+ALPHABETICAL_INDEX = YES
+
+# The COLS_IN_ALPHA_INDEX tag can be used to specify the number of columns in
+# which the alphabetical index list will be split.
+# Minimum value: 1, maximum value: 20, default value: 5.
+# This tag requires that the tag ALPHABETICAL_INDEX is set to YES.
+
+COLS_IN_ALPHA_INDEX = 5
+
+# In case all classes in a project start with a common prefix, all classes will
+# be put under the same header in the alphabetical index. The IGNORE_PREFIX tag
+# can be used to specify a prefix (or a list of prefixes) that should be ignored
+# while generating the index headers.
+# This tag requires that the tag ALPHABETICAL_INDEX is set to YES.
+
+IGNORE_PREFIX =
+
+#---------------------------------------------------------------------------
+# Configuration options related to the HTML output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_HTML tag is set to YES, doxygen will generate HTML output
+# The default value is: YES.
+
+GENERATE_HTML = YES
+
+# The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a
+# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
+# it.
+# The default directory is: html.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_OUTPUT = html
+
+# The HTML_FILE_EXTENSION tag can be used to specify the file extension for each
+# generated HTML page (for example: .htm, .php, .asp).
+# The default value is: .html.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_FILE_EXTENSION = .html
+
+# The HTML_HEADER tag can be used to specify a user-defined HTML header file for
+# each generated HTML page. If the tag is left blank doxygen will generate a
+# standard header.
+#
+# To get valid HTML the header file that includes any scripts and style sheets
+# that doxygen needs, which is dependent on the configuration options used (e.g.
+# the setting GENERATE_TREEVIEW). It is highly recommended to start with a
+# default header using
+# doxygen -w html new_header.html new_footer.html new_stylesheet.css
+# YourConfigFile
+# and then modify the file new_header.html. See also section "Doxygen usage"
+# for information on how to generate the default header that doxygen normally
+# uses.
+# Note: The header is subject to change so you typically have to regenerate the
+# default header when upgrading to a newer version of doxygen. For a description
+# of the possible markers and block names see the documentation.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_HEADER =
+
+# The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each
+# generated HTML page. If the tag is left blank doxygen will generate a standard
+# footer. See HTML_HEADER for more information on how to generate a default
+# footer and what special commands can be used inside the footer. See also
+# section "Doxygen usage" for information on how to generate the default footer
+# that doxygen normally uses.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_FOOTER =
+
+# The HTML_STYLESHEET tag can be used to specify a user-defined cascading style
+# sheet that is used by each HTML page. It can be used to fine-tune the look of
+# the HTML output. If left blank doxygen will generate a default style sheet.
+# See also section "Doxygen usage" for information on how to generate the style
+# sheet that doxygen normally uses.
+# Note: It is recommended to use HTML_EXTRA_STYLESHEET instead of this tag, as
+# it is more robust and this tag (HTML_STYLESHEET) will in the future become
+# obsolete.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_STYLESHEET =
+
+# The HTML_EXTRA_STYLESHEET tag can be used to specify additional user-defined
+# cascading style sheets that are included after the standard style sheets
+# created by doxygen. Using this option one can overrule certain style aspects.
+# This is preferred over using HTML_STYLESHEET since it does not replace the
+# standard style sheet and is therefore more robust against future updates.
+# Doxygen will copy the style sheet files to the output directory.
+# Note: The order of the extra style sheet files is of importance (e.g. the last
+# style sheet in the list overrules the setting of the previous ones in the
+# list). For an example see the documentation.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_EXTRA_STYLESHEET =
+
+# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or
+# other source files which should be copied to the HTML output directory. Note
+# that these files will be copied to the base HTML output directory. Use the
+# $relpath^ marker in the HTML_HEADER and/or HTML_FOOTER files to load these
+# files. In the HTML_STYLESHEET file, use the file name only. Also note that the
+# files will be copied as-is; there are no commands or markers available.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_EXTRA_FILES =
+
+# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen
+# will adjust the colors in the style sheet and background images according to
+# this color. Hue is specified as an angle on a colorwheel, see
+# https://en.wikipedia.org/wiki/Hue for more information. For instance the value
+# 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300
+# purple, and 360 is red again.
+# Minimum value: 0, maximum value: 359, default value: 220.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_COLORSTYLE_HUE = 220
+
+# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors
+# in the HTML output. For a value of 0 the output will use grayscales only. A
+# value of 255 will produce the most vivid colors.
+# Minimum value: 0, maximum value: 255, default value: 100.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_COLORSTYLE_SAT = 100
+
+# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the
+# luminance component of the colors in the HTML output. Values below 100
+# gradually make the output lighter, whereas values above 100 make the output
+# darker. The value divided by 100 is the actual gamma applied, so 80 represents
+# a gamma of 0.8, The value 220 represents a gamma of 2.2, and 100 does not
+# change the gamma.
+# Minimum value: 40, maximum value: 240, default value: 80.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_COLORSTYLE_GAMMA = 80
+
+# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML
+# page will contain the date and time when the page was generated. Setting this
+# to YES can help to show when doxygen was last run and thus if the
+# documentation is up to date.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_TIMESTAMP = NO
+
+# If the HTML_DYNAMIC_MENUS tag is set to YES then the generated HTML
+# documentation will contain a main index with vertical navigation menus that
+# are dynamically created via Javascript. If disabled, the navigation index will
+# consists of multiple levels of tabs that are statically embedded in every HTML
+# page. Disable this option to support browsers that do not have Javascript,
+# like the Qt help browser.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_DYNAMIC_MENUS = YES
+
+# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML
+# documentation will contain sections that can be hidden and shown after the
+# page has loaded.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_DYNAMIC_SECTIONS = NO
+
+# With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries
+# shown in the various tree structured indices initially; the user can expand
+# and collapse entries dynamically later on. Doxygen will expand the tree to
+# such a level that at most the specified number of entries are visible (unless
+# a fully collapsed tree already exceeds this amount). So setting the number of
+# entries 1 will produce a full collapsed tree by default. 0 is a special value
+# representing an infinite number of entries and will result in a full expanded
+# tree by default.
+# Minimum value: 0, maximum value: 9999, default value: 100.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+HTML_INDEX_NUM_ENTRIES = 100
+
+# If the GENERATE_DOCSET tag is set to YES, additional index files will be
+# generated that can be used as input for Apple's Xcode 3 integrated development
+# environment (see: https://developer.apple.com/tools/xcode/), introduced with
+# OSX 10.5 (Leopard). To create a documentation set, doxygen will generate a
+# Makefile in the HTML output directory. Running make will produce the docset in
+# that directory and running make install will install the docset in
+# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find it at
+# startup. See https://developer.apple.com/tools/creatingdocsetswithdoxygen.html
+# for more information.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_DOCSET = NO
+
+# This tag determines the name of the docset feed. A documentation feed provides
+# an umbrella under which multiple documentation sets from a single provider
+# (such as a company or product suite) can be grouped.
+# The default value is: Doxygen generated docs.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_FEEDNAME = "Doxygen generated docs"
+
+# This tag specifies a string that should uniquely identify the documentation
+# set bundle. This should be a reverse domain-name style string, e.g.
+# com.mycompany.MyDocSet. Doxygen will append .docset to the name.
+# The default value is: org.doxygen.Project.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_BUNDLE_ID = org.doxygen.Project
+
+# The DOCSET_PUBLISHER_ID tag specifies a string that should uniquely identify
+# the documentation publisher. This should be a reverse domain-name style
+# string, e.g. com.mycompany.MyDocSet.documentation.
+# The default value is: org.doxygen.Publisher.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_PUBLISHER_ID = org.doxygen.Publisher
+
+# The DOCSET_PUBLISHER_NAME tag identifies the documentation publisher.
+# The default value is: Publisher.
+# This tag requires that the tag GENERATE_DOCSET is set to YES.
+
+DOCSET_PUBLISHER_NAME = Publisher
+
+# If the GENERATE_HTMLHELP tag is set to YES then doxygen generates three
+# additional HTML index files: index.hhp, index.hhc, and index.hhk. The
+# index.hhp is a project file that can be read by Microsoft's HTML Help Workshop
+# (see: http://www.microsoft.com/en-us/download/details.aspx?id=21138) on
+# Windows.
+#
+# The HTML Help Workshop contains a compiler that can convert all HTML output
+# generated by doxygen into a single compiled HTML file (.chm). Compiled HTML
+# files are now used as the Windows 98 help format, and will replace the old
+# Windows help format (.hlp) on all Windows platforms in the future. Compressed
+# HTML files also contain an index, a table of contents, and you can search for
+# words in the documentation. The HTML workshop also contains a viewer for
+# compressed HTML files.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_HTMLHELP = NO
+
+# The CHM_FILE tag can be used to specify the file name of the resulting .chm
+# file. You can add a path in front of the file if the result should not be
+# written to the html output directory.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+CHM_FILE =
+
+# The HHC_LOCATION tag can be used to specify the location (absolute path
+# including file name) of the HTML help compiler (hhc.exe). If non-empty,
+# doxygen will try to run the HTML help compiler on the generated index.hhp.
+# The file has to be specified with full path.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+HHC_LOCATION =
+
+# The GENERATE_CHI flag controls if a separate .chi index file is generated
+# (YES) or that it should be included in the master .chm file (NO).
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+GENERATE_CHI = NO
+
+# The CHM_INDEX_ENCODING is used to encode HtmlHelp index (hhk), content (hhc)
+# and project file content.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+CHM_INDEX_ENCODING =
+
+# The BINARY_TOC flag controls whether a binary table of contents is generated
+# (YES) or a normal table of contents (NO) in the .chm file. Furthermore it
+# enables the Previous and Next buttons.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+BINARY_TOC = NO
+
+# The TOC_EXPAND flag can be set to YES to add extra items for group members to
+# the table of contents of the HTML help documentation and to the tree view.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTMLHELP is set to YES.
+
+TOC_EXPAND = NO
+
+# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and
+# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated that
+# can be used as input for Qt's qhelpgenerator to generate a Qt Compressed Help
+# (.qch) of the generated HTML documentation.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_QHP = NO
+
+# If the QHG_LOCATION tag is specified, the QCH_FILE tag can be used to specify
+# the file name of the resulting .qch file. The path specified is relative to
+# the HTML output folder.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QCH_FILE =
+
+# The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help
+# Project output. For more information please see Qt Help Project / Namespace
+# (see: http://doc.qt.io/qt-4.8/qthelpproject.html#namespace).
+# The default value is: org.doxygen.Project.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_NAMESPACE = org.doxygen.Project
+
+# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating Qt
+# Help Project output. For more information please see Qt Help Project / Virtual
+# Folders (see: http://doc.qt.io/qt-4.8/qthelpproject.html#virtual-folders).
+# The default value is: doc.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_VIRTUAL_FOLDER = doc
+
+# If the QHP_CUST_FILTER_NAME tag is set, it specifies the name of a custom
+# filter to add. For more information please see Qt Help Project / Custom
+# Filters (see: http://doc.qt.io/qt-4.8/qthelpproject.html#custom-filters).
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_CUST_FILTER_NAME =
+
+# The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the
+# custom filter to add. For more information please see Qt Help Project / Custom
+# Filters (see: http://doc.qt.io/qt-4.8/qthelpproject.html#custom-filters).
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_CUST_FILTER_ATTRS =
+
+# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this
+# project's filter section matches. Qt Help Project / Filter Attributes (see:
+# http://doc.qt.io/qt-4.8/qthelpproject.html#filter-attributes).
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHP_SECT_FILTER_ATTRS =
+
+# The QHG_LOCATION tag can be used to specify the location of Qt's
+# qhelpgenerator. If non-empty doxygen will try to run qhelpgenerator on the
+# generated .qhp file.
+# This tag requires that the tag GENERATE_QHP is set to YES.
+
+QHG_LOCATION =
+
+# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be
+# generated, together with the HTML files, they form an Eclipse help plugin. To
+# install this plugin and make it available under the help contents menu in
+# Eclipse, the contents of the directory containing the HTML and XML files needs
+# to be copied into the plugins directory of eclipse. The name of the directory
+# within the plugins directory should be the same as the ECLIPSE_DOC_ID value.
+# After copying Eclipse needs to be restarted before the help appears.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_ECLIPSEHELP = NO
+
+# A unique identifier for the Eclipse help plugin. When installing the plugin
+# the directory name containing the HTML and XML files should also have this
+# name. Each documentation set should have its own identifier.
+# The default value is: org.doxygen.Project.
+# This tag requires that the tag GENERATE_ECLIPSEHELP is set to YES.
+
+ECLIPSE_DOC_ID = org.doxygen.Project
+
+# If you want full control over the layout of the generated HTML pages it might
+# be necessary to disable the index and replace it with your own. The
+# DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs) at top
+# of each HTML page. A value of NO enables the index and the value YES disables
+# it. Since the tabs in the index contain the same information as the navigation
+# tree, you can set this option to YES if you also set GENERATE_TREEVIEW to YES.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+DISABLE_INDEX = NO
+
+# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index
+# structure should be generated to display hierarchical information. If the tag
+# value is set to YES, a side panel will be generated containing a tree-like
+# index structure (just like the one that is generated for HTML Help). For this
+# to work a browser that supports JavaScript, DHTML, CSS and frames is required
+# (i.e. any modern browser). Windows users are probably better off using the
+# HTML help feature. Via custom style sheets (see HTML_EXTRA_STYLESHEET) one can
+# further fine-tune the look of the index. As an example, the default style
+# sheet generated by doxygen has an example that shows how to put an image at
+# the root of the tree instead of the PROJECT_NAME. Since the tree basically has
+# the same information as the tab index, you could consider setting
+# DISABLE_INDEX to YES when enabling this option.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+GENERATE_TREEVIEW = NO
+
+# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that
+# doxygen will group on one line in the generated HTML documentation.
+#
+# Note that a value of 0 will completely suppress the enum values from appearing
+# in the overview section.
+# Minimum value: 0, maximum value: 20, default value: 4.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+ENUM_VALUES_PER_LINE = 4
+
+# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be used
+# to set the initial width (in pixels) of the frame in which the tree is shown.
+# Minimum value: 0, maximum value: 1500, default value: 250.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+TREEVIEW_WIDTH = 250
+
+# If the EXT_LINKS_IN_WINDOW option is set to YES, doxygen will open links to
+# external symbols imported via tag files in a separate window.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+EXT_LINKS_IN_WINDOW = NO
+
+# Use this tag to change the font size of LaTeX formulas included as images in
+# the HTML documentation. When you change the font size after a successful
+# doxygen run you need to manually remove any form_*.png images from the HTML
+# output directory to force them to be regenerated.
+# Minimum value: 8, maximum value: 50, default value: 10.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+FORMULA_FONTSIZE = 10
+
+# Use the FORMULA_TRANSPARENT tag to determine whether or not the images
+# generated for formulas are transparent PNGs. Transparent PNGs are not
+# supported properly for IE 6.0, but are supported on all modern browsers.
+#
+# Note that when changing this option you need to delete any form_*.png files in
+# the HTML output directory before the changes have effect.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+FORMULA_TRANSPARENT = YES
+
+# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see
+# https://www.mathjax.org) which uses client side Javascript for the rendering
+# instead of using pre-rendered bitmaps. Use this if you do not have LaTeX
+# installed or if you want to formulas look prettier in the HTML output. When
+# enabled you may also need to install MathJax separately and configure the path
+# to it using the MATHJAX_RELPATH option.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+USE_MATHJAX = NO
+
+# When MathJax is enabled you can set the default output format to be used for
+# the MathJax output. See the MathJax site (see:
+# http://docs.mathjax.org/en/latest/output.html) for more details.
+# Possible values are: HTML-CSS (which is slower, but has the best
+# compatibility), NativeMML (i.e. MathML) and SVG.
+# The default value is: HTML-CSS.
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_FORMAT = HTML-CSS
+
+# When MathJax is enabled you need to specify the location relative to the HTML
+# output directory using the MATHJAX_RELPATH option. The destination directory
+# should contain the MathJax.js script. For instance, if the mathjax directory
+# is located at the same level as the HTML output directory, then
+# MATHJAX_RELPATH should be ../mathjax. The default value points to the MathJax
+# Content Delivery Network so you can quickly see the result without installing
+# MathJax. However, it is strongly recommended to install a local copy of
+# MathJax from https://www.mathjax.org before deployment.
+# The default value is: https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/.
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_RELPATH = https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.2/
+
+# The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax
+# extension names that should be enabled during MathJax rendering. For example
+# MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_EXTENSIONS =
+
+# The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces
+# of code that will be used on startup of the MathJax code. See the MathJax site
+# (see: http://docs.mathjax.org/en/latest/output.html) for more details. For an
+# example see the documentation.
+# This tag requires that the tag USE_MATHJAX is set to YES.
+
+MATHJAX_CODEFILE =
+
+# When the SEARCHENGINE tag is enabled doxygen will generate a search box for
+# the HTML output. The underlying search engine uses javascript and DHTML and
+# should work on any modern browser. Note that when using HTML help
+# (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets (GENERATE_DOCSET)
+# there is already a search function so this one should typically be disabled.
+# For large projects the javascript based search engine can be slow, then
+# enabling SERVER_BASED_SEARCH may provide a better solution. It is possible to
+# search using the keyboard; to jump to the search box use <access key> + S
+# (what the <access key> is depends on the OS and browser, but it is typically
+# <CTRL>, <ALT>/<option>, or both). Inside the search box use the <cursor down
+# key> to jump into the search results window, the results can be navigated
+# using the <cursor keys>. Press <Enter> to select an item or <escape> to cancel
+# the search. The filter options can be selected when the cursor is inside the
+# search box by pressing <Shift>+<cursor down>. Also here use the <cursor keys>
+# to select a filter and <Enter> or <escape> to activate or cancel the filter
+# option.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_HTML is set to YES.
+
+SEARCHENGINE = YES
+
+# When the SERVER_BASED_SEARCH tag is enabled the search engine will be
+# implemented using a web server instead of a web client using Javascript. There
+# are two flavors of web server based searching depending on the EXTERNAL_SEARCH
+# setting. When disabled, doxygen will generate a PHP script for searching and
+# an index file used by the script. When EXTERNAL_SEARCH is enabled the indexing
+# and searching needs to be provided by external tools. See the section
+# "External Indexing and Searching" for details.
+# The default value is: NO.
+# This tag requires that the tag SEARCHENGINE is set to YES.
+
+SERVER_BASED_SEARCH = NO
+
+# When EXTERNAL_SEARCH tag is enabled doxygen will no longer generate the PHP
+# script for searching. Instead the search results are written to an XML file
+# which needs to be processed by an external indexer. Doxygen will invoke an
+# external search engine pointed to by the SEARCHENGINE_URL option to obtain the
+# search results.
+#
+# Doxygen ships with an example indexer (doxyindexer) and search engine
+# (doxysearch.cgi) which are based on the open source search engine library
+# Xapian (see: https://xapian.org/).
+#
+# See the section "External Indexing and Searching" for details.
+# The default value is: NO.
+# This tag requires that the tag SEARCHENGINE is set to YES.
+
+EXTERNAL_SEARCH = NO
+
+# The SEARCHENGINE_URL should point to a search engine hosted by a web server
+# which will return the search results when EXTERNAL_SEARCH is enabled.
+#
+# Doxygen ships with an example indexer (doxyindexer) and search engine
+# (doxysearch.cgi) which are based on the open source search engine library
+# Xapian (see: https://xapian.org/). See the section "External Indexing and
+# Searching" for details.
+# This tag requires that the tag SEARCHENGINE is set to YES.
+
+SEARCHENGINE_URL =
+
+# When SERVER_BASED_SEARCH and EXTERNAL_SEARCH are both enabled the unindexed
+# search data is written to a file for indexing by an external tool. With the
+# SEARCHDATA_FILE tag the name of this file can be specified.
+# The default file is: searchdata.xml.
+# This tag requires that the tag SEARCHENGINE is set to YES.
+
+SEARCHDATA_FILE = searchdata.xml
+
+# When SERVER_BASED_SEARCH and EXTERNAL_SEARCH are both enabled the
+# EXTERNAL_SEARCH_ID tag can be used as an identifier for the project. This is
+# useful in combination with EXTRA_SEARCH_MAPPINGS to search through multiple
+# projects and redirect the results back to the right project.
+# This tag requires that the tag SEARCHENGINE is set to YES.
+
+EXTERNAL_SEARCH_ID =
+
+# The EXTRA_SEARCH_MAPPINGS tag can be used to enable searching through doxygen
+# projects other than the one defined by this configuration file, but that are
+# all added to the same external search index. Each project needs to have a
+# unique id set via EXTERNAL_SEARCH_ID. The search mapping then maps the id of
+# to a relative location where the documentation can be found. The format is:
+# EXTRA_SEARCH_MAPPINGS = tagname1=loc1 tagname2=loc2 ...
+# This tag requires that the tag SEARCHENGINE is set to YES.
+
+EXTRA_SEARCH_MAPPINGS =
+
+#---------------------------------------------------------------------------
+# Configuration options related to the LaTeX output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_LATEX tag is set to YES, doxygen will generate LaTeX output.
+# The default value is: YES.
+
+GENERATE_LATEX = YES
+
+# The LATEX_OUTPUT tag is used to specify where the LaTeX docs will be put. If a
+# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
+# it.
+# The default directory is: latex.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_OUTPUT = latex
+
+# The LATEX_CMD_NAME tag can be used to specify the LaTeX command name to be
+# invoked.
+#
+# Note that when enabling USE_PDFLATEX this option is only used for generating
+# bitmaps for formulas in the HTML output, but not in the Makefile that is
+# written to the output directory.
+# The default file is: latex.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_CMD_NAME = latex
+
+# The MAKEINDEX_CMD_NAME tag can be used to specify the command name to generate
+# index for LaTeX.
+# The default file is: makeindex.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+MAKEINDEX_CMD_NAME = makeindex
+
+# If the COMPACT_LATEX tag is set to YES, doxygen generates more compact LaTeX
+# documents. This may be useful for small projects and may help to save some
+# trees in general.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+COMPACT_LATEX = NO
+
+# The PAPER_TYPE tag can be used to set the paper type that is used by the
+# printer.
+# Possible values are: a4 (210 x 297 mm), letter (8.5 x 11 inches), legal (8.5 x
+# 14 inches) and executive (7.25 x 10.5 inches).
+# The default value is: a4.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+PAPER_TYPE = a4
+
+# The EXTRA_PACKAGES tag can be used to specify one or more LaTeX package names
+# that should be included in the LaTeX output. The package can be specified just
+# by its name or with the correct syntax as to be used with the LaTeX
+# \usepackage command. To get the times font for instance you can specify :
+# EXTRA_PACKAGES=times or EXTRA_PACKAGES={times}
+# To use the option intlimits with the amsmath package you can specify:
+# EXTRA_PACKAGES=[intlimits]{amsmath}
+# If left blank no extra packages will be included.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+EXTRA_PACKAGES =
+
+# The LATEX_HEADER tag can be used to specify a personal LaTeX header for the
+# generated LaTeX document. The header should contain everything until the first
+# chapter. If it is left blank doxygen will generate a standard header. See
+# section "Doxygen usage" for information on how to let doxygen write the
+# default header to a separate file.
+#
+# Note: Only use a user-defined header if you know what you are doing! The
+# following commands have a special meaning inside the header: $title,
+# $datetime, $date, $doxygenversion, $projectname, $projectnumber,
+# $projectbrief, $projectlogo. Doxygen will replace $title with the empty
+# string, for the replacement values of the other commands the user is referred
+# to HTML_HEADER.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_HEADER =
+
+# The LATEX_FOOTER tag can be used to specify a personal LaTeX footer for the
+# generated LaTeX document. The footer should contain everything after the last
+# chapter. If it is left blank doxygen will generate a standard footer. See
+# LATEX_HEADER for more information on how to generate a default footer and what
+# special commands can be used inside the footer.
+#
+# Note: Only use a user-defined footer if you know what you are doing!
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_FOOTER =
+
+# The LATEX_EXTRA_STYLESHEET tag can be used to specify additional user-defined
+# LaTeX style sheets that are included after the standard style sheets created
+# by doxygen. Using this option one can overrule certain style aspects. Doxygen
+# will copy the style sheet files to the output directory.
+# Note: The order of the extra style sheet files is of importance (e.g. the last
+# style sheet in the list overrules the setting of the previous ones in the
+# list).
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_EXTRA_STYLESHEET =
+
+# The LATEX_EXTRA_FILES tag can be used to specify one or more extra images or
+# other source files which should be copied to the LATEX_OUTPUT output
+# directory. Note that the files will be copied as-is; there are no commands or
+# markers available.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_EXTRA_FILES =
+
+# If the PDF_HYPERLINKS tag is set to YES, the LaTeX that is generated is
+# prepared for conversion to PDF (using ps2pdf or pdflatex). The PDF file will
+# contain links (just like the HTML output) instead of page references. This
+# makes the output suitable for online browsing using a PDF viewer.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+PDF_HYPERLINKS = YES
+
+# If the USE_PDFLATEX tag is set to YES, doxygen will use pdflatex to generate
+# the PDF file directly from the LaTeX files. Set this option to YES, to get a
+# higher quality PDF documentation.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+USE_PDFLATEX = YES
+
+# If the LATEX_BATCHMODE tag is set to YES, doxygen will add the \batchmode
+# command to the generated LaTeX files. This will instruct LaTeX to keep running
+# if errors occur, instead of asking the user for help. This option is also used
+# when generating formulas in HTML.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_BATCHMODE = NO
+
+# If the LATEX_HIDE_INDICES tag is set to YES then doxygen will not include the
+# index chapters (such as File Index, Compound Index, etc.) in the output.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_HIDE_INDICES = NO
+
+# If the LATEX_SOURCE_CODE tag is set to YES then doxygen will include source
+# code with syntax highlighting in the LaTeX output.
+#
+# Note that which sources are shown also depends on other settings such as
+# SOURCE_BROWSER.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_SOURCE_CODE = NO
+
+# The LATEX_BIB_STYLE tag can be used to specify the style to use for the
+# bibliography, e.g. plainnat, or ieeetr. See
+# https://en.wikipedia.org/wiki/BibTeX and \cite for more info.
+# The default value is: plain.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_BIB_STYLE = plain
+
+# If the LATEX_TIMESTAMP tag is set to YES then the footer of each generated
+# page will contain the date and time when the page was generated. Setting this
+# to NO can help when comparing the output of multiple runs.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_LATEX is set to YES.
+
+LATEX_TIMESTAMP = NO
+
+#---------------------------------------------------------------------------
+# Configuration options related to the RTF output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_RTF tag is set to YES, doxygen will generate RTF output. The
+# RTF output is optimized for Word 97 and may not look too pretty with other RTF
+# readers/editors.
+# The default value is: NO.
+
+GENERATE_RTF = NO
+
+# The RTF_OUTPUT tag is used to specify where the RTF docs will be put. If a
+# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
+# it.
+# The default directory is: rtf.
+# This tag requires that the tag GENERATE_RTF is set to YES.
+
+RTF_OUTPUT = rtf
+
+# If the COMPACT_RTF tag is set to YES, doxygen generates more compact RTF
+# documents. This may be useful for small projects and may help to save some
+# trees in general.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_RTF is set to YES.
+
+COMPACT_RTF = NO
+
+# If the RTF_HYPERLINKS tag is set to YES, the RTF that is generated will
+# contain hyperlink fields. The RTF file will contain links (just like the HTML
+# output) instead of page references. This makes the output suitable for online
+# browsing using Word or some other Word compatible readers that support those
+# fields.
+#
+# Note: WordPad (write) and others do not support links.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_RTF is set to YES.
+
+RTF_HYPERLINKS = NO
+
+# Load stylesheet definitions from file. Syntax is similar to doxygen's config
+# file, i.e. a series of assignments. You only have to provide replacements,
+# missing definitions are set to their default value.
+#
+# See also section "Doxygen usage" for information on how to generate the
+# default style sheet that doxygen normally uses.
+# This tag requires that the tag GENERATE_RTF is set to YES.
+
+RTF_STYLESHEET_FILE =
+
+# Set optional variables used in the generation of an RTF document. Syntax is
+# similar to doxygen's config file. A template extensions file can be generated
+# using doxygen -e rtf extensionFile.
+# This tag requires that the tag GENERATE_RTF is set to YES.
+
+RTF_EXTENSIONS_FILE =
+
+# If the RTF_SOURCE_CODE tag is set to YES then doxygen will include source code
+# with syntax highlighting in the RTF output.
+#
+# Note that which sources are shown also depends on other settings such as
+# SOURCE_BROWSER.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_RTF is set to YES.
+
+RTF_SOURCE_CODE = NO
+
+#---------------------------------------------------------------------------
+# Configuration options related to the man page output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_MAN tag is set to YES, doxygen will generate man pages for
+# classes and files.
+# The default value is: NO.
+
+GENERATE_MAN = NO
+
+# The MAN_OUTPUT tag is used to specify where the man pages will be put. If a
+# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
+# it. A directory man3 will be created inside the directory specified by
+# MAN_OUTPUT.
+# The default directory is: man.
+# This tag requires that the tag GENERATE_MAN is set to YES.
+
+MAN_OUTPUT = man
+
+# The MAN_EXTENSION tag determines the extension that is added to the generated
+# man pages. In case the manual section does not start with a number, the number
+# 3 is prepended. The dot (.) at the beginning of the MAN_EXTENSION tag is
+# optional.
+# The default value is: .3.
+# This tag requires that the tag GENERATE_MAN is set to YES.
+
+MAN_EXTENSION = .3
+
+# The MAN_SUBDIR tag determines the name of the directory created within
+# MAN_OUTPUT in which the man pages are placed. If defaults to man followed by
+# MAN_EXTENSION with the initial . removed.
+# This tag requires that the tag GENERATE_MAN is set to YES.
+
+MAN_SUBDIR =
+
+# If the MAN_LINKS tag is set to YES and doxygen generates man output, then it
+# will generate one additional man file for each entity documented in the real
+# man page(s). These additional files only source the real man page, but without
+# them the man command would be unable to find the correct page.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_MAN is set to YES.
+
+MAN_LINKS = NO
+
+#---------------------------------------------------------------------------
+# Configuration options related to the XML output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_XML tag is set to YES, doxygen will generate an XML file that
+# captures the structure of the code including all documentation.
+# The default value is: NO.
+
+GENERATE_XML = NO
+
+# The XML_OUTPUT tag is used to specify where the XML pages will be put. If a
+# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
+# it.
+# The default directory is: xml.
+# This tag requires that the tag GENERATE_XML is set to YES.
+
+XML_OUTPUT = xml
+
+# If the XML_PROGRAMLISTING tag is set to YES, doxygen will dump the program
+# listings (including syntax highlighting and cross-referencing information) to
+# the XML output. Note that enabling this will significantly increase the size
+# of the XML output.
+# The default value is: YES.
+# This tag requires that the tag GENERATE_XML is set to YES.
+
+XML_PROGRAMLISTING = YES
+
+#---------------------------------------------------------------------------
+# Configuration options related to the DOCBOOK output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_DOCBOOK tag is set to YES, doxygen will generate Docbook files
+# that can be used to generate PDF.
+# The default value is: NO.
+
+GENERATE_DOCBOOK = NO
+
+# The DOCBOOK_OUTPUT tag is used to specify where the Docbook pages will be put.
+# If a relative path is entered the value of OUTPUT_DIRECTORY will be put in
+# front of it.
+# The default directory is: docbook.
+# This tag requires that the tag GENERATE_DOCBOOK is set to YES.
+
+DOCBOOK_OUTPUT = docbook
+
+# If the DOCBOOK_PROGRAMLISTING tag is set to YES, doxygen will include the
+# program listings (including syntax highlighting and cross-referencing
+# information) to the DOCBOOK output. Note that enabling this will significantly
+# increase the size of the DOCBOOK output.
+# The default value is: NO.
+# This tag requires that the tag GENERATE_DOCBOOK is set to YES.
+
+DOCBOOK_PROGRAMLISTING = NO
+
+#---------------------------------------------------------------------------
+# Configuration options for the AutoGen Definitions output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_AUTOGEN_DEF tag is set to YES, doxygen will generate an
+# AutoGen Definitions (see http://autogen.sourceforge.net/) file that captures
+# the structure of the code including all documentation. Note that this feature
+# is still experimental and incomplete at the moment.
+# The default value is: NO.
+
+GENERATE_AUTOGEN_DEF = NO
+
+#---------------------------------------------------------------------------
+# Configuration options related to the Perl module output
+#---------------------------------------------------------------------------
+
+# If the GENERATE_PERLMOD tag is set to YES, doxygen will generate a Perl module
+# file that captures the structure of the code including all documentation.
+#
+# Note that this feature is still experimental and incomplete at the moment.
+# The default value is: NO.
+
+GENERATE_PERLMOD = NO
+
+# If the PERLMOD_LATEX tag is set to YES, doxygen will generate the necessary
+# Makefile rules, Perl scripts and LaTeX code to be able to generate PDF and DVI
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diff --git a/4neuro/README.md b/4neuro/README.md
new file mode 100644
index 00000000..8d70dfde
--- /dev/null
+++ b/4neuro/README.md
@@ -0,0 +1 @@
+4Neuro
diff --git a/4neuro/build.sh b/4neuro/build.sh
new file mode 100644
index 00000000..6231cf85
--- /dev/null
+++ b/4neuro/build.sh
@@ -0,0 +1,11 @@
+#!/bin/bash
+
+echo "Creating folder 'build'...";
+mkdir -p build/lib;
+echo "Folder 'build' was created'";
+
+cd build;
+cmake ..;
+make && echo "Installation complete." || exit -1;
+#make install;
+
diff --git a/4neuro/build_docs.sh b/4neuro/build_docs.sh
new file mode 100644
index 00000000..cb972189
--- /dev/null
+++ b/4neuro/build_docs.sh
@@ -0,0 +1,6 @@
+echo "Generating documentation into folder 'docs'...";
+doxygen >/dev/null && echo "Documenation was generated." || exit -1;
+cd docs/latex;
+echo "Building LaTeX documentation../";
+make >/dev/null && echo "Documentation was built." || exit -1;
+cd ../..;
diff --git a/4neuro/clean.sh b/4neuro/clean.sh
new file mode 100644
index 00000000..6464a48b
--- /dev/null
+++ b/4neuro/clean.sh
@@ -0,0 +1,4 @@
+#!/bin/bash
+
+rm -rf build
+rm -rf docs/*
diff --git a/4neuro/docs/.gitkeep b/4neuro/docs/.gitkeep
new file mode 100644
index 00000000..e69de29b
diff --git a/4neuro/img/4neuro_logo_small.png b/4neuro/img/4neuro_logo_small.png
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diff --git a/4neuro/java/src/BPNet.java b/4neuro/java/src/BPNet.java
new file mode 100644
index 00000000..81f1c988
--- /dev/null
+++ b/4neuro/java/src/BPNet.java
@@ -0,0 +1,462 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+
+public class BPNet extends MultiLayeredNet {
+
+ protected float error;
+
+
+ public float getError() {
+ return error;
+ }
+
+
+ public void setError(float error) {
+ this.error = error;
+ }
+
+
+ protected float tolerance;
+ protected String neuronType;
+ protected float learnCoeff;
+
+
+
+ public BPNet( float tolerance, int nrOfLayers, int nrOfInputs, ArrayList<Integer> nrOfNeuronsPerLayer, float slope, float learnCoeff ) {
+ super(nrOfInputs, nrOfLayers, nrOfNeuronsPerLayer);
+ this.neuronType = "SigmoidalNeuron";
+ this.tolerance = tolerance;
+ this.learnCoeff = learnCoeff;
+
+ for (int i = 0; i < nrOfLayers; i++) {
+ for (int j = 0; j < nrOfNeuronsPerLayer.get(i); j++) {
+ this.neuronLayers.get(i).add(new SigmoidalNeuron(slope));
+ }
+ }
+ for (int i = 0; i < nrOfLayers; i++) {
+ this.interconnectionsLayers.add(new InterconnectionsBP(this.learnCoeff));
+ }
+ for (Neuron neuronIn : this.inputNeuronLayer) {
+ for (Neuron neuronFirstLevel : this.neuronLayers.get(0)) {
+ this.interconnectionsLayers.get(0).addConnection(new Connection(neuronIn, neuronFirstLevel, (float) (Math.random())));
+ }
+ }
+ for (int i = 1; i < nrOfLayers; i++) {
+ for (Neuron neuronIn : this.neuronLayers.get(i-1)) {
+ for (Neuron neuronOut : this.neuronLayers.get(i)) {
+ this.interconnectionsLayers.get(i).addConnection(new Connection(neuronIn, neuronOut, (float) (Math.random())));
+ }
+
+ }
+ }
+
+
+ }
+
+
+ public float getTolerance() {
+ return tolerance;
+ }
+
+ public void setTolerance(float tolerance) {
+ this.tolerance = tolerance;
+ }
+
+
+ @Override
+ public String getNeuronType() {
+ return this.neuronType;
+ }
+
+ @Override
+ public int learn(String trainingSet) {
+ boolean learned = false;
+ int iter = 0;
+ ArrayList<String> trainingElements = new ArrayList<String>(Arrays.asList(trainingSet.split("\n")));
+ while(!learned) {
+ learned = true;
+ this.error = 0;
+ for (int i = 0; i < trainingElements.size(); i++) {
+ learned &= learnStep(trainingElements.get(i));
+ }
+ iter++;
+// System.out.println(iter);
+ }
+ return iter;
+// System.out.println("Learned in " + iter + " whole training set iterations.");
+ }
+
+ public boolean learnStep(String trainingElement) {
+ // Run training Element
+ String[] splitedTrainingElement = trainingElement.split(" ");
+ StringBuffer inputString = new StringBuffer();
+ for (int i = 0; i < this.nrOfInputs; i++) { //Input values
+ inputString.append(splitedTrainingElement[i]);
+ inputString.append(" ");
+ }
+ ArrayList<Float> expectedValues = new ArrayList<Float>();
+ for (int i = this.nrOfInputs; i < splitedTrainingElement.length; i++) { //Expected values
+ expectedValues.add(Float.parseFloat(splitedTrainingElement[i]));
+ }
+ this.run(inputString.substring(0, inputString.length() - 1));
+ // Calculate error
+ float error = 0;
+ for (int i = 0; i < expectedValues.size(); i++) {
+ float y = this.neuronLayers.get(this.nrOfLayers-1).get(i).getState(); //output of ith neuron
+ float o = expectedValues.get(i);
+ error += (float)( 0.5 * Math.pow((y-o), 2));
+ }
+ if (this.error < error) {
+ this.error = error;
+ }
+ if (error > this.tolerance) { //Error is too high -> modify weights
+ // Calculate deltas
+ for (int i = this.nrOfLayers - 1; i >= 0; i -= 1) {
+ for (Neuron n : this.neuronLayers.get(i)) {
+ SigmoidalNeuron neuron = (SigmoidalNeuron)n;
+ if (i == this.nrOfLayers - 1) { //Top layer
+ float y = neuron.getState();
+ float o = expectedValues.get(this.neuronLayers.get(i).indexOf(neuron));
+ float delta = y - o;
+ neuron.setError(delta);
+ } else { //Other layers
+ ArrayList<Connection> connectionsToUpperLayerFromNeuron = new ArrayList<Connection>();
+ // Find all connections, that have "neuron" as input
+ for (Connection c : this.interconnectionsLayers.get(i+1).getConnections()) {
+ if (c.getInputNeuron().equals(neuron))
+ connectionsToUpperLayerFromNeuron.add(c);
+ }
+ float delta = 0;
+ for (Connection c : connectionsToUpperLayerFromNeuron) {
+ float deltaUpper = ((SigmoidalNeuron)c.getOutputNeuron()).getError();
+ float lambdaUpper = ((SigmoidalNeuron)c.getOutputNeuron()).getSlope();
+ float yUpper = c.getOutputNeuron().getState();
+ float w = c.getWeight();
+ delta += deltaUpper*lambdaUpper*yUpper*(1-yUpper)*w;
+ }
+ neuron.setError(delta);
+ }
+ }
+ }
+ // Adjust weights
+ for (Interconnections interconnectionsLayer : this.interconnectionsLayers) {
+ interconnectionsLayer.adjustWeights();
+ }
+ return false;
+ } else {
+ return true;
+ }
+
+
+ }
+
+ public String getOutput() {
+ StringBuffer output = new StringBuffer();
+ ArrayList<Neuron> outputLayer = this.neuronLayers.get(this.nrOfLayers-1);
+ for (int i = 0; i < outputLayer.size(); i++) {
+ output.append(String.valueOf(outputLayer.get(i).getState()));
+ output.append(" ");
+ }
+
+ return output.toString();
+ }
+
+
+
+
+ public void changeSlopeTo(float slope) {
+ for (ArrayList<Neuron> neuronLayer : this.neuronLayers) {
+ for (Neuron neuron : neuronLayer) {
+ ((SigmoidalNeuron)neuron).setSlope(slope);
+ }
+ }
+ }
+
+
+ public void changeLearnCoeffTo(float learnCoeff) {
+ for (Interconnections layer : interconnectionsLayers) {
+ ((InterconnectionsBP)layer).setLearningRate(learnCoeff);
+ }
+
+ }
+
+
+ public void resetWeights() {
+ for (Interconnections layer : interconnectionsLayers) {
+ for (Connection connection : layer.getConnections()) {
+ connection.setWeight((float)Math.random());
+ }
+ }
+
+ }
+
+ public void addNeuron(int layerIndex, float slope) {
+ SigmoidalNeuron newNeuron = new SigmoidalNeuron(slope);
+ neuronLayers.get(layerIndex).add(newNeuron);
+ if ((layerIndex < nrOfLayers) && (layerIndex >= 0)) {
+ Interconnections inputConnectionLayer = this.interconnectionsLayers.get(layerIndex);
+ if (layerIndex == 0) {
+ ArrayList<InputLayerPseudoNeuron> inputNeurons = this.inputNeuronLayer;
+ for (Neuron inputNeuron : inputNeurons) {
+ inputConnectionLayer.addConnection(new Connection(inputNeuron, newNeuron, (float)Math.random()));
+ }
+ } else {
+ ArrayList<Neuron> inputNeurons = this.neuronLayers.get(layerIndex - 1);
+ for (Neuron inputNeuron : inputNeurons) {
+ inputConnectionLayer.addConnection(new Connection(inputNeuron, newNeuron, (float)Math.random()));
+ }
+ }
+
+ if (layerIndex < nrOfLayers - 1) {
+ Interconnections outputConnectionLayer = this.interconnectionsLayers.get(layerIndex + 1);
+ ArrayList<Neuron> outputNeurons = this.neuronLayers.get(layerIndex + 1);
+ for (Neuron outputNeuron : outputNeurons) {
+ outputConnectionLayer.addConnection(new Connection(newNeuron, outputNeuron, (float)Math.random()));
+ }
+ }
+ this.nrOfNeuronsPerLayer.set(layerIndex, this.nrOfNeuronsPerLayer.get(layerIndex) + 1 );
+
+
+ } else {
+
+ throw new InvalidLayerNumberException();
+
+ }
+ }
+
+ public void removeNeuron(int layerIndex) {
+ int nrOfNeuronsInThisLayer = this.nrOfNeuronsPerLayer.get(layerIndex);
+ if ((layerIndex < nrOfLayers) && (layerIndex >= 0)) {
+ if (nrOfNeuronsInThisLayer == 1) {
+
+ removeNeuronLayer(layerIndex);
+
+ } else {
+ Neuron removedNeuron = this.neuronLayers.get(layerIndex).get(nrOfNeuronsInThisLayer - 1);
+ Interconnections inputConnectionLayer = this.interconnectionsLayers.get(layerIndex);
+ ArrayList<Connection> removedConnections = new ArrayList<Connection>();
+ for (Connection connection : inputConnectionLayer.getConnections()) {
+ if (connection.getOutputNeuron().equals(removedNeuron)) {
+ removedConnections.add(connection);
+ }
+ }
+ for (Connection connection : removedConnections) {
+ inputConnectionLayer.getConnections().remove(connection);
+ }
+ removedConnections = new ArrayList<Connection>();
+ if (layerIndex < nrOfLayers - 1) {
+ Interconnections outputConnectionLayer = this.interconnectionsLayers.get(layerIndex + 1);
+ for (Connection connection : outputConnectionLayer.getConnections()) {
+ if (connection.getInputNeuron().equals(removedNeuron)) {
+ removedConnections.add(connection);
+ }
+ }
+ for (Connection connection : removedConnections) {
+ outputConnectionLayer.getConnections().remove(connection);
+ }
+ }
+
+ this.neuronLayers.get(layerIndex).remove(removedNeuron);
+ this.nrOfNeuronsPerLayer.set(layerIndex, this.nrOfNeuronsPerLayer.get(layerIndex) - 1 );
+ }
+
+ } else {
+ throw new InvalidLayerNumberException();
+ }
+ }
+
+ public void addNeuronLayer(int nrOfNeurons, int layerIndex, float slope) {
+ if ((layerIndex < nrOfLayers + 1) && (layerIndex >= 0) && (nrOfNeurons > 0)) {
+
+ this.nrOfLayers++;
+ this.nrOfNeuronsPerLayer.add(layerIndex, nrOfNeurons);
+ // new layer creation
+ ArrayList<Neuron> newNeuronLayer = new ArrayList<Neuron>();
+ for (int i = 0; i < nrOfNeurons; i++) {
+ newNeuronLayer.add(new SigmoidalNeuron(slope));
+ }
+ // old connections removal
+ if (layerIndex < nrOfLayers - 1) { // only if inner layer is added
+ this.interconnectionsLayers.remove(layerIndex);
+ }
+ // new layer adding
+ this.neuronLayers.add(layerIndex, newNeuronLayer);
+ // new connections creation
+ // input
+ Interconnections inputConnLayer = new InterconnectionsBP(learnCoeff);
+ if (layerIndex == 0) {
+ ArrayList<InputLayerPseudoNeuron> inputNeurons = this.inputNeuronLayer;
+ ArrayList<Neuron> outputNeurons = newNeuronLayer; //Layers already shifted
+ for (Neuron inputNeuron : inputNeurons) {
+ for (Neuron outputNeuron : outputNeurons) {
+ inputConnLayer.addConnection(new Connection(inputNeuron, outputNeuron, (float)Math.random()));
+ }
+ }
+ } else {
+ ArrayList<Neuron> inputNeurons = this.neuronLayers.get(layerIndex - 1);
+ ArrayList<Neuron> outputNeurons = newNeuronLayer; //Layers already shifted, this is new layer
+ for (Neuron inputNeuron : inputNeurons) {
+ for (Neuron outputNeuron : outputNeurons) {
+ inputConnLayer.addConnection(new Connection(inputNeuron, outputNeuron, (float)Math.random()));
+ }
+ }
+ }
+ this.interconnectionsLayers.add(layerIndex, inputConnLayer);
+ // output
+ Interconnections outputConnLayer = new InterconnectionsBP(learnCoeff);
+ if (layerIndex < nrOfLayers - 1) {
+ ArrayList<Neuron> inputNeurons = newNeuronLayer;
+ ArrayList<Neuron> outputNeurons = this.neuronLayers.get(layerIndex + 1); //Layers already shifted
+ for (Neuron inputNeuron : inputNeurons) {
+ for (Neuron outputNeuron : outputNeurons) {
+ outputConnLayer.addConnection(new Connection(inputNeuron, outputNeuron, (float)Math.random()));
+ }
+ }
+ this.interconnectionsLayers.add(layerIndex + 1, outputConnLayer);
+ }
+
+
+ } else {
+ throw new InvalidLayerNumberException();
+ }
+
+ }
+
+
+
+ public void removeNeuronLayer(int layerIndex) {
+ if ((layerIndex < nrOfLayers ) && (layerIndex >= 0) && (nrOfLayers > 1)) {
+ // delete output connections
+ if (layerIndex < nrOfLayers - 1) {
+ this.interconnectionsLayers.remove(layerIndex + 1);
+ }
+ // delete input connections
+ this.interconnectionsLayers.remove(layerIndex);
+ // delete neurons on layer
+ this.neuronLayers.remove(layerIndex);
+ this.nrOfNeuronsPerLayer.remove(layerIndex);
+ this.nrOfLayers--;
+ // create new connections
+ if (layerIndex < nrOfLayers + 1) {
+ Interconnections connLayer = new InterconnectionsBP(learnCoeff);
+ if (layerIndex == 0) {
+ ArrayList<InputLayerPseudoNeuron> inputNeurons = this.inputNeuronLayer;
+ ArrayList<Neuron> outputNeurons = this.neuronLayers.get(0);
+ for (Neuron inputNeuron : inputNeurons) {
+ for (Neuron outputNeuron : outputNeurons) {
+ connLayer.addConnection(new Connection(inputNeuron, outputNeuron, (float)Math.random()));
+ }
+ }
+ } else {
+ ArrayList<Neuron> inputNeurons = this.neuronLayers.get(layerIndex - 1);
+ ArrayList<Neuron> outputNeurons = this.neuronLayers.get(layerIndex);
+ for (Neuron inputNeuron : inputNeurons) {
+ for (Neuron outputNeuron : outputNeurons) {
+ connLayer.addConnection(new Connection(inputNeuron, outputNeuron, (float)Math.random()));
+ }
+ }
+ }
+ this.interconnectionsLayers.add(layerIndex, connLayer);
+
+ }
+
+ } else {
+ throw new InvalidLayerNumberException();
+ }
+ }
+
+ @Override
+ public String toString() {
+ return getNeuronMap();
+ }
+
+ public String getNeuronMap() {
+ StringBuffer map = new StringBuffer();
+ for (int i = 0; i < nrOfLayers; i++) {
+ map.append(String.valueOf(nrOfNeuronsPerLayer.get(i)));
+ map.append(" ");
+ }
+ map.deleteCharAt(map.length() - 1);
+ return map.toString();
+ }
+
+ public static void main(String[] args) {
+ ArrayList<Integer> nrOfNeuronsPerLayer = new ArrayList<Integer>();
+ nrOfNeuronsPerLayer.add(10);
+ nrOfNeuronsPerLayer.add(7);
+ nrOfNeuronsPerLayer.add(2);
+ BPNet net = new BPNet( (float)0.01, 3, 5, nrOfNeuronsPerLayer, (float)1.8, (float)0.7); // bigger slope = better resolution
+
+ String trainingSet = "0.4 0.5 1 0.5 1 0 1\n0 0 0 0 0 1 1\n0.1 0.2 0.3 0.4 0.5 0 0\n1 0 1 0 1 1 0\n0.2 0.4 0 0 0.9 0 1";
+ net.learn(trainingSet);
+ net.run("0.4 0.5 1 0.5 1"); //expected 0 1
+ System.out.println(net.getOutput());
+ net.run("0 0 0 0 0"); // 1 1
+ System.out.println(net.getOutput());
+ net.run("0.1 0.2 0.3 0.4 0.5"); // 0 0
+ System.out.println(net.getOutput());
+ net.run("1 0 1 0 1"); // 1 0
+ System.out.println(net.getOutput());
+ net.run("0.2 0.4 0 0 0.9"); // 0 1
+ System.out.println(net.getOutput());
+
+ System.out.println("Not trained elements:");
+ net.run("0.9 0.1 0.9 0.1 0.9"); // expected 1 0
+ System.out.println(net.getOutput());
+ net.run("0.01 0.01 0.01 0.01 0.01"); // expected 1 1
+ System.out.println(net.getOutput());
+ net.run("0.15 0.15 0.35 0.35 0.5"); // 0 0
+ System.out.println(net.getOutput());
+
+ System.out.println(net.getNeuronMap());
+ net.addNeuron(0, 1.8f);
+ System.out.println(net.getNeuronMap());
+ net.addNeuron(1, 1.8f);
+ System.out.println(net.getNeuronMap());
+ net.addNeuron(2, 1.8f);
+ System.out.println(net.getNeuronMap());
+ net.removeNeuron(0);
+ System.out.println(net.getNeuronMap());
+ net.removeNeuron(1);
+ System.out.println(net.getNeuronMap());
+ net.removeNeuron(2);
+ System.out.println(net.getNeuronMap());
+
+ net.addNeuronLayer(5, 0, 1.8f);
+ System.out.println(net.getNeuronMap());
+ net.addNeuronLayer(5, 2, 1.8f);
+ System.out.println(net.getNeuronMap());
+ net.addNeuronLayer(5, 5, 1.8f);
+ System.out.println(net.getNeuronMap());
+
+ net.removeNeuronLayer(5);
+ System.out.println(net.getNeuronMap());
+ net.removeNeuronLayer(2);
+ System.out.println(net.getNeuronMap());
+ net.removeNeuronLayer(0);
+ System.out.println(net.getNeuronMap());
+
+ net.learn(trainingSet);
+ net.run("0.4 0.5 1 0.5 1"); //expected 0 1
+ System.out.println(net.getOutput());
+ net.run("0 0 0 0 0"); // 1 1
+ System.out.println(net.getOutput());
+ net.run("0.1 0.2 0.3 0.4 0.5"); // 0 0
+ System.out.println(net.getOutput());
+ net.run("1 0 1 0 1"); // 1 0
+ System.out.println(net.getOutput());
+ net.run("0.2 0.4 0 0 0.9"); // 0 1
+ System.out.println(net.getOutput());
+
+ System.out.println("Not trained elements:");
+ net.run("0.9 0.1 0.9 0.1 0.9"); // expected 1 0
+ System.out.println(net.getOutput());
+ net.run("0.01 0.01 0.01 0.01 0.01"); // expected 1 1
+ System.out.println(net.getOutput());
+ net.run("0.15 0.15 0.35 0.35 0.5"); // 0 0
+ System.out.println(net.getOutput());
+ }
+
+}
diff --git a/4neuro/java/src/BinaryNeuron.java b/4neuro/java/src/BinaryNeuron.java
new file mode 100644
index 00000000..25a0b26f
--- /dev/null
+++ b/4neuro/java/src/BinaryNeuron.java
@@ -0,0 +1,15 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class BinaryNeuron extends Neuron {
+
+ @Override
+ public void transfer() {
+ if (this.getPotential() > this.getThreshold()) {
+ this.setState(1);
+ } else {
+ this.setState(0);
+ }
+
+ }
+
+}
diff --git a/4neuro/java/src/CarDriverClient.java b/4neuro/java/src/CarDriverClient.java
new file mode 100644
index 00000000..bd5a0b9f
--- /dev/null
+++ b/4neuro/java/src/CarDriverClient.java
@@ -0,0 +1,528 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.io.BufferedReader;
+import java.io.BufferedWriter;
+import java.io.File;
+import java.io.FileReader;
+import java.io.InputStreamReader;
+import java.io.OutputStreamWriter;
+import java.io.IOException;
+import java.io.StreamTokenizer;
+import java.net.ConnectException;
+import java.net.Socket;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Random;
+
+import javax.swing.JOptionPane;
+
+
+/**
+ * Jednoduchy ukazkovy klient.
+ * Pripoji se k zavodnimu serveru a ridi auto.
+ *
+ */
+public class CarDriverClient {
+
+ private Socket socket; // spojeni
+ private BufferedReader in; // cteni se serveru
+ private BufferedWriter out; // zapis na server
+ private BPNet neuralNetwork;
+
+ /**
+ * Pripoji se k zavodu.
+ *
+ * @param host zavodni server
+ * @param port port serveru
+ * @param raceName nazev zavodu, do nehoz se chce klient pripojit
+ * @param driverName jmeno ridice
+ * @throws java.lang.IOException problem s pripojenim
+ */
+ public CarDriverClient(String host, int port, String raceName, String driverName, String carType, BPNet neuralNetwork) throws IOException {
+ // add neural net
+ this.neuralNetwork = neuralNetwork;
+
+ // connect to server
+ socket = new Socket(host, port);
+ out = new BufferedWriter(new OutputStreamWriter(socket.getOutputStream(), "UTF-8"));
+ in = new BufferedReader(new InputStreamReader(socket.getInputStream(), "UTF-8"));
+
+ // connect to race
+ out.write("driver\n"); // protocol specification
+ out.write("race:" + raceName + "\n"); // race name
+ out.write("driver:" + driverName + "\n"); // driver name
+ out.write("color:0000FF\n"); // car color
+ if(carType != null){
+ out.write("car:" + carType + "\n"); // car type
+ }
+ out.write("\n");
+ out.flush();
+
+ // precteni a kontrola dopovedi serveru
+ String line = in.readLine();
+ if (!line.equals("ok")) {
+ // pokud se pripojeni nepodari, je oznamena chyba a vyvolana vyjimka
+ System.err.println("Chyba: " + line);
+ throw new ConnectException(line);
+ }
+ in.readLine(); // precteni prazdneho radku
+ }
+
+ public static List<String> listRaces(String host, int port) throws IOException {
+ // pripojeni k serveru
+ Socket socket = new Socket(host, port);
+ BufferedWriter out = new BufferedWriter(new OutputStreamWriter(socket.getOutputStream(), "UTF-8"));
+ BufferedReader in = new BufferedReader(new InputStreamReader(socket.getInputStream(), "UTF-8"));
+
+ // pripojeni k zavodu
+ out.write("racelist\n"); // specifikace protokolu
+ out.write("\n");
+ out.flush();
+
+ // precteni a kontrola dopovedi serveru
+ String line = in.readLine();
+ if (!line.equals("ok")) {
+ // pokud se pripojeni nepodari, je oznamena chyba a vyvolana vyjimka
+ System.err.println("Chyba: " + line);
+ throw new ConnectException(line);
+ }
+ line = in.readLine(); // precteni prazdneho radku
+ List<String> racelist = new ArrayList<String>();
+ line = in.readLine();
+ System.out.println("Races:");
+ while(line != null && !"".equals(line)){
+ racelist.add(line);
+ System.out.println(line);
+ line = in.readLine();
+ }
+ return racelist;
+ }
+ public static List<String> listCars(String host, int port, String raceName) throws IOException {
+ // pripojeni k serveru
+ Socket socket = new Socket(host, port);
+ BufferedWriter out = new BufferedWriter(new OutputStreamWriter(socket.getOutputStream(), "UTF-8"));
+ BufferedReader in = new BufferedReader(new InputStreamReader(socket.getInputStream(), "UTF-8"));
+
+ // pripojeni k zavodu
+ out.write("carlist\n"); // specifikace protokolu
+ out.write("race:" + raceName + "\n");
+ out.write("\n");
+ out.flush();
+
+ // precteni a kontrola dopovedi serveru
+ String line = in.readLine();
+ if (!line.equals("ok")) {
+ // pokud se pripojeni nepodari, je oznamena chyba a vyvolana vyjimka
+ System.err.println("Chyba: " + line);
+ throw new ConnectException(line);
+ }
+ line = in.readLine(); // precteni prazdneho radku
+ List<String> carList = new ArrayList<String>();
+ line = in.readLine();
+ System.out.println("cars:");
+ while(line != null && !"".equals(line)){
+ carList.add(line);
+ System.out.println(line);
+ line = in.readLine();
+ }
+ return carList;
+ }
+
+ /**
+ * Beh zavodu. Cte data ze serveru. Spousti rizeni auta.
+ * Ukonci se po ukonceni zavodu.
+ *
+ * @throws java.io.IOException problem ve spojeni k serveru
+ */
+ public void run() throws IOException {
+ while (true) { // smycka do konce zavodu
+ String line = in.readLine();
+// System.out.println(line);
+ if (line.equals("round")) { // dalsi kolo v zavode
+ round();
+ } else if (line.equals("finish")) { // konec zavodu konci smucku
+ break;
+ } else {
+ System.err.println("Chyba se serveru: " + line);
+ }
+ }
+ }
+
+ /**
+ * Resi jedno posunuti auta. Precte pozici auta od servru,
+ * vypocte nastaveni rizeni, ktere na server.
+ *
+ * @throws java.io.IOException problem ve spojeni k serveru
+ */
+ public void round() throws IOException {
+ float angle = 0; // uhel k care <0,1>
+ float speed = 0; // rychlost auta <0,1>
+ float distance0 = 0; // vzdalenost od cary <0,1>
+ float distance4 = 0; // vzdalenost od cary za 4m<0,1>
+ float distance8 = 0; // vzdalenost od cary za 8m<0,1>
+ float distance16 = 0; // vzdalenost od cary za 16m<0,1>
+ float distance32 = 0; // vzdalenost od cary za 32m<0,1>
+ float friction = 0;
+ float skid = 0;
+ float checkpoint = 0;
+ float sensorFrontLeft = 0;
+ float sensorFrontMiddleLeft = 0;
+ float sensorFrontMiddleRight = 0;
+ float sensorFrontRight = 0;
+ float sensorFrontRightCorner1 = 0;
+ float sensorFrontRightCorner2 = 0;
+ float sensorRight1 = 0;
+ float sensorRight2 = 0;
+ float sensorRearRightCorner2 = 0;
+ float sensorRearRightCorner1 = 0;
+ float sensorRearRight = 0;
+ float sensorRearLeft = 0;
+ float sensorRearLeftCorner1 = 0;
+ float sensorRearLeftCorner2 = 0;
+ float sensorLeft1 = 0;
+ float sensorLeft2 = 0;
+ float sensorFrontLeftCorner1 = 0;
+ float sensorFrontLeftCorner2 = 0;
+
+ // cteni dat ze serveru
+ String line = in.readLine();
+// System.out.println(line);
+ while (line.length() > 0) {
+ String[] data = line.split(":", 2);
+ String key = data[0];
+ String value = data[1];
+ if (key.equals("angle")) {
+ angle = Float.parseFloat(value);
+ } else if (key.equals("speed")) {
+ speed = Float.parseFloat(value);
+ } else if (key.equals("distance0")) {
+ distance0 = Float.parseFloat(value);
+ } else if (key.equals("distance4")) {
+ distance4 = Float.parseFloat(value);
+ } else if (key.equals("distance8")) {
+ distance8 = Float.parseFloat(value);
+ } else if (key.equals("distance16")) {
+ distance16 = Float.parseFloat(value);
+ } else if (key.equals("distance32")) {
+ distance32 = Float.parseFloat(value);
+ } else if (key.equals("friction")) {
+ friction = Float.parseFloat(value);
+ } else if (key.equals("skid")) {
+ skid = Float.parseFloat(value);
+ } else if (key.equals("checkpoint")) {
+ checkpoint = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontLeft")) {
+ sensorFrontLeft = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontMiddleLeft")) {
+ sensorFrontMiddleLeft = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontMiddleRight")) {
+ sensorFrontMiddleRight = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontRight")) {
+ sensorFrontRight = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontRightCorner1")) {
+ sensorFrontRightCorner1 = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontRightCorner2")) {
+ sensorFrontRightCorner2 = Float.parseFloat(value);
+ } else if (key.equals("sensorRight1")) {
+ sensorRight1 = Float.parseFloat(value);
+ } else if (key.equals("sensorRight2")) {
+ sensorRight2 = Float.parseFloat(value);
+ } else if (key.equals("sensorRearRightCorner2")) {
+ sensorRearRightCorner2 = Float.parseFloat(value);
+ } else if (key.equals("sensorRearRightCorner1")) {
+ sensorRearRightCorner1 = Float.parseFloat(value);
+ } else if (key.equals("sensorRearRight")) {
+ sensorRearRight = Float.parseFloat(value);
+ } else if (key.equals("sensorRearLeft")) {
+ sensorRearLeft = Float.parseFloat(value);
+ } else if (key.equals("sensorRearLeftCorner1")) {
+ sensorRearLeftCorner1 = Float.parseFloat(value);
+ } else if (key.equals("sensorRearLeftCorner2")) {
+ sensorRearLeftCorner2 = Float.parseFloat(value);
+ } else if (key.equals("sensorLeft1")) {
+ sensorLeft1 = Float.parseFloat(value);
+ } else if (key.equals("sensorLeft2")) {
+ sensorLeft2 = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontLeftCorner1")) {
+ sensorFrontLeftCorner1 = Float.parseFloat(value);
+ } else if (key.equals("sensorFrontLeftCorner2")) {
+ sensorFrontLeftCorner2 = Float.parseFloat(value);
+ } else {
+ System.err.println("Chyba se serveru: " + line);
+ }
+ line = in.readLine();
+// System.out.println(line);
+ }
+
+ // vypocet nastaveni rizeni, ktery je mozno zmenit za jiny algoritmus
+ float acc; // zrychleni auta <0,1>
+ float wheel; // otoceni volantem (kolama) <0,1>
+
+ StringBuffer neuralNetInput = new StringBuffer();
+
+
+// float angle = 0; // uhel k care <0,1>
+// float speed = 0; // rychlost auta <0,1>
+// float distance0 = 0; // vzdalenost od cary <0,1>
+// float distance4 = 0; // vzdalenost od cary za 4m<0,1>
+// float distance8 = 0; // vzdalenost od cary za 8m<0,1>
+// float distance16 = 0; // vzdalenost od cary za 16m<0,1>
+// float distance32 = 0; // vzdalenost od cary za 32m<0,1>
+// float friction = 0;
+// float skid = 0;
+// float checkpoint = 0;
+// float sensorFrontLeft = 0;
+// float sensorFrontMiddleLeft = 0;
+// float sensorFrontMiddleRight = 0;
+// float sensorFrontRight = 0;
+// float sensorFrontRightCorner1 = 0;
+// float sensorFrontRightCorner2 = 0;
+// float sensorRight1 = 0;
+// float sensorRight2 = 0;
+// float sensorRearRightCorner2 = 0;
+// float sensorRearRightCorner1 = 0;
+// float sensorRearRight = 0;
+// float sensorRearLeft = 0;
+// float sensorRearLeftCorner1 = 0;
+// float sensorRearLeftCorner2 = 0;
+// float sensorLeft1 = 0;
+// float sensorLeft2 = 0;
+// float sensorFrontLeftCorner1 = 0;
+// float sensorFrontLeftCorner2 = 0;
+
+
+
+// neuralNetInput.append(String.valueOf(angle));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(speed));
+// neuralNetInput.append(" ");
+ neuralNetInput.append("0.5 0.5 ");
+ neuralNetInput.append(String.valueOf(distance0));
+ neuralNetInput.append(" ");
+ neuralNetInput.append(String.valueOf(distance4));
+ neuralNetInput.append(" ");
+ neuralNetInput.append(String.valueOf(distance8));
+ neuralNetInput.append(" ");
+ neuralNetInput.append(String.valueOf(distance16));
+ neuralNetInput.append(" ");
+ neuralNetInput.append(String.valueOf(distance32));
+ neuralNetInput.append(" ");
+ neuralNetInput.append("1 1 0.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0");
+// neuralNetInput.append(String.valueOf(friction));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(skid));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(checkpoint));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontLeft));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontMiddleLeft));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontMiddleRight));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontRight));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontRightCorner1));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontRightCorner2));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRight1));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRight2));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRearRightCorner2));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRearRightCorner1));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRearRight));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRearLeft));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRearLeftCorner1));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorRearLeftCorner2));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorLeft1));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorLeft2));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontLeftCorner1));
+// neuralNetInput.append(" ");
+// neuralNetInput.append(String.valueOf(sensorFrontLeftCorner2));
+
+ neuralNetwork.run(neuralNetInput.toString());
+
+ String output = neuralNetwork.getOutput();
+ String[] outputArray = output.split(" ");
+
+ wheel = Float.parseFloat(outputArray[0]);
+ acc = Float.parseFloat(outputArray[1]);
+
+
+
+
+ // odpoved serveru
+ out.write("ok\n");
+ out.write("acc:" + acc + "\n");
+ out.write("wheel:" + wheel + "\n");
+ out.write("\n");
+ out.flush();
+ }
+
+ /**
+ * Funkce, ktera vytvari a spousti klienta.
+ *
+ * @param args pole argumentu: server port nazev_zavodu jmeno_ridice
+ * @throws java.io.IOException problem ve spojeni k serveru, zavodu
+ */
+ public static void main(String[] args) throws IOException {
+// String host = "java.cs.vsb.cz";
+// int port = 9460;
+ String host = "localhost";
+// int port = 9461; // test
+ int port = 9460; // normal
+ String raceName = "Zavod";
+ String driverName = "basic_client";
+ String carType = null;
+ if (args.length < 4) {
+ // kontrola argumentu programu
+ System.err.println("argumenty: server port nazev_zavodu jmeno_ridice [typ_auta]");
+ List<String> raceList = CarDriverClient.listRaces(host, port);
+ raceName = raceList.get(new Random().nextInt(raceList.size()));
+ List<String> carList = CarDriverClient.listCars(host, port, raceName);
+ carType = carList.get(0);
+ driverName += "_" + carType;
+// host = JOptionPane.showInputDialog("Host:", host);
+// port = Integer.parseInt(JOptionPane.showInputDialog("Port:", Integer.toString(port)));
+// raceName = JOptionPane.showInputDialog("Race name:", raceName);
+// driverName = JOptionPane.showInputDialog("Driver name:", driverName);
+ } else {
+ // nacteni parametu
+ host = args[0];
+ port = Integer.parseInt(args[1]);
+ raceName = args[2];
+ driverName = args[3];
+ if(args.length > 4){
+ carType = args[4];
+ }
+ }
+ // vytvoreni neuronove site
+ ArrayList<Integer> nrOfNeuronsPerLayer = new ArrayList<Integer>();
+ //nrOfNeuronsPerLayer.add(20);
+// nrOfNeuronsPerLayer.add(15);
+// nrOfNeuronsPerLayer.add(10);
+// nrOfNeuronsPerLayer.add(2);
+ nrOfNeuronsPerLayer.add(3);
+ nrOfNeuronsPerLayer.add(3);
+ nrOfNeuronsPerLayer.add(2);
+ BPNet neuralNet = new BPNet(0.1f, 3, 28, nrOfNeuronsPerLayer, 1.4f, 0.4f);
+
+ FileReader fr = new FileReader(new File("C:\\Users\\Martin\\Desktop\\NSProjekty\\testTrainingSet5.txt"));
+ StreamTokenizer tokenizer = new StreamTokenizer(fr);
+ /*for (int i = 0; i < 6; i++ )
+ tokenizer.nextToken();
+ */
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ int nrOfLayers = (int)tokenizer.nval;
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ int nrOfInputs = (int)tokenizer.nval;
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ ArrayList<float[]> inputRanges = new ArrayList<float[]>();
+ ArrayList<String> inputNames = new ArrayList<String>();
+ for (int i = 0; i < nrOfInputs; i++) {
+ String inputName = tokenizer.sval;
+ inputNames.add(inputName);
+ tokenizer.nextToken();
+ float[] dims = new float[2];
+ dims[0] = (float)tokenizer.nval;
+ tokenizer.nextToken();
+ dims[1] = (float)tokenizer.nval;
+ inputRanges.add(dims);
+ tokenizer.nextToken();
+ }
+ /*for (int i = 0; i < 3; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfNeuronsPerLayer = new ArrayList<Integer>();
+ int nrOfOutputs = 0;
+ for (int i = 0; i < nrOfLayers; i++) {
+ nrOfNeuronsPerLayer.add((int)tokenizer.nval);
+ if (i == nrOfLayers - 1) {
+ nrOfOutputs = (int)tokenizer.nval;
+ }
+ tokenizer.nextToken();
+ }
+ for (int i = 0; i < 3; i++ )
+ tokenizer.nextToken();
+ ArrayList<String> outputNames = new ArrayList<String>();
+ for (int i = 0; i < nrOfOutputs; i++) {
+ outputNames.add(tokenizer.sval);
+ tokenizer.nextToken();
+ }
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ float learnCoeff = (float)tokenizer.nval;
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ float inertiaCoeff = (float)tokenizer.nval;
+ /*for (int i = 0; i < 7; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ int nrOfTrainingElements = (int)tokenizer.nval;
+ /*for (int i = 0; i < 4; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ StringBuffer sb = new StringBuffer();
+ for (int i = 0; i < nrOfTrainingElements; i++) {
+ for (int j = 0; j < nrOfInputs; j++) {
+ sb.append(String.valueOf(tokenizer.nval/(inputRanges.get(j)[1]-inputRanges.get(j)[0]) - inputRanges.get(j)[0]/(inputRanges.get(j)[1]-inputRanges.get(j)[0])));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ for (int j = 0; j < nrOfOutputs; j++) {
+ sb.append(String.valueOf(tokenizer.nval));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ sb.deleteCharAt(sb.length() - 1);
+ sb.append("\n");
+ }
+ String trainingData = sb.toString();
+ sb = new StringBuffer();
+ /*for (int i = 0; i < 5; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ int nrOfTestElements = (int)tokenizer.nval;
+ String testData;
+ /*tokenizer.nextToken();*/
+ if (nrOfTestElements > 0) {
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ for (int i = 0; i < nrOfTestElements; i++) {
+ for (int j = 0; j < nrOfInputs; j++) {
+ sb.append(String.valueOf(String.valueOf(tokenizer.nval/(inputRanges.get(j)[1]-inputRanges.get(j)[0]) - inputRanges.get(j)[0]/(inputRanges.get(j)[1]-inputRanges.get(j)[0]))));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ sb.deleteCharAt(sb.lastIndexOf(" "));
+ sb.append("\n");
+ }
+ testData = sb.substring(0,sb.lastIndexOf("\n"));
+ } else {
+ testData = "";
+ }
+ fr.close();
+
+ String trainingSet = trainingData;
+ System.out.println("Learning started.");
+ ;
+ System.out.println("Net learned in " + neuralNet.learn(trainingSet) + " iterations");
+
+ // vytvoreni klienta
+ CarDriverClient driver = new CarDriverClient(host, port, raceName, driverName, carType, neuralNet);
+ // spusteni
+ driver.run();
+ }
+}
diff --git a/4neuro/java/src/Connection.java b/4neuro/java/src/Connection.java
new file mode 100644
index 00000000..d8c451c7
--- /dev/null
+++ b/4neuro/java/src/Connection.java
@@ -0,0 +1,52 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class Connection {
+
+ private Neuron inputNeuron;
+ private Neuron outputNeuron;
+ private float weight;
+
+ public Connection(Neuron inputNeuron, Neuron outputNeuron, float weight) {
+ this.setInputNeuron(inputNeuron);
+ this.setOutputNeuron(outputNeuron);
+ this.setWeight(weight);
+ }
+
+ protected Neuron getInputNeuron() {
+ return inputNeuron;
+ }
+
+ protected void setInputNeuron(Neuron inputNeuron) {
+ this.inputNeuron = inputNeuron;
+ }
+
+ protected Neuron getOutputNeuron() {
+ return outputNeuron;
+ }
+
+ protected void setOutputNeuron(Neuron outputNeuron) {
+ this.outputNeuron = outputNeuron;
+ }
+
+ public float getWeight() {
+ return weight;
+ }
+
+ public void setWeight(float weight) {
+ this.weight = weight;
+ }
+
+ public void adjustWeight(float value) {
+ this.weight += value;
+ }
+
+ public void passSignal() {
+ outputNeuron.adjustPotential(inputNeuron.getState()*this.getWeight());
+ }
+
+ @Override
+ public String toString() {
+ return "Weight: " + this.getWeight();
+ }
+
+}
diff --git a/4neuro/java/src/InputLayerPseudoNeuron.java b/4neuro/java/src/InputLayerPseudoNeuron.java
new file mode 100644
index 00000000..d8489247
--- /dev/null
+++ b/4neuro/java/src/InputLayerPseudoNeuron.java
@@ -0,0 +1,14 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class InputLayerPseudoNeuron extends Neuron {
+
+ public InputLayerPseudoNeuron() {
+ super();
+ }
+
+ @Override
+ public void transfer() {
+ this.setState(this.getPotential());
+ }
+
+}
diff --git a/4neuro/java/src/Interconnections.java b/4neuro/java/src/Interconnections.java
new file mode 100644
index 00000000..8732fb18
--- /dev/null
+++ b/4neuro/java/src/Interconnections.java
@@ -0,0 +1,54 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.util.ArrayList;
+
+public abstract class Interconnections {
+
+ protected ArrayList<Connection> connections;
+
+ public ArrayList<Connection> getConnections() {
+ return connections;
+ }
+
+ public Interconnections() {
+ this.connections = new ArrayList<Connection>();
+ }
+
+ public void addConnection(Connection connection) {
+ this.connections.add(connection);
+ }
+
+// public void passSignal() {
+// for (Connection c : this.connections) {
+//
+// Neuron n = c.getOutputNeuron();
+// n.initialize();
+// for (Connection cn : this.connections) {
+// if (cn.getOutputNeuron().equals(n)) {
+// cn.passSignal();
+// }
+// }
+// n.transfer();
+// }
+// }
+
+ public void passSignal() { // Faster version
+ ArrayList<Neuron> processedNeurons = new ArrayList<Neuron>();
+ for (Connection c : this.connections) {
+
+ Neuron n = c.getOutputNeuron();
+ if (!processedNeurons.contains(n)) {
+ processedNeurons.add(n);
+ n.initialize();
+ for (Connection cn : this.connections) {
+ if (cn.getOutputNeuron().equals(n)) {
+ cn.passSignal();
+ }
+ }
+ n.transfer();
+ }
+ }
+ }
+
+ public abstract void adjustWeights();
+}
diff --git a/4neuro/java/src/InterconnectionsBP.java b/4neuro/java/src/InterconnectionsBP.java
new file mode 100644
index 00000000..fc29d41d
--- /dev/null
+++ b/4neuro/java/src/InterconnectionsBP.java
@@ -0,0 +1,25 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class InterconnectionsBP extends InterconnectionsMultiLayer {
+
+ public InterconnectionsBP(float learningRate) {
+ super(learningRate);
+ }
+
+ public void setLearningRate(float learningRate) {
+ this.learningRate = learningRate;
+ }
+
+ @Override
+ public void adjustWeights() { // backPropagation - set new weights !after! all deltas are calculated
+ for (Connection connection : this.connections) {
+ float delta = ((SigmoidalNeuron)connection.getOutputNeuron()).getError();
+ float lambda = ((SigmoidalNeuron)connection.getOutputNeuron()).getSlope();
+ float y = connection.getOutputNeuron().getState();
+ float x = connection.getInputNeuron().getState();
+ float errorDerivative = delta*lambda*y*(1-y)*x;
+ connection.adjustWeight(-learningRate*errorDerivative);
+ }
+ }
+
+}
diff --git a/4neuro/java/src/InterconnectionsMultiLayer.java b/4neuro/java/src/InterconnectionsMultiLayer.java
new file mode 100644
index 00000000..5785bdfd
--- /dev/null
+++ b/4neuro/java/src/InterconnectionsMultiLayer.java
@@ -0,0 +1,11 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public abstract class InterconnectionsMultiLayer extends Interconnections {
+
+ protected float learningRate; //eta
+
+ public InterconnectionsMultiLayer(float learningRate) {
+ this.learningRate = learningRate;
+ }
+
+}
diff --git a/4neuro/java/src/InvalidInputNumberException.java b/4neuro/java/src/InvalidInputNumberException.java
new file mode 100644
index 00000000..3582a092
--- /dev/null
+++ b/4neuro/java/src/InvalidInputNumberException.java
@@ -0,0 +1,14 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class InvalidInputNumberException extends RuntimeException {
+
+ /**
+ *
+ */
+ private static final long serialVersionUID = -6282750644609100469L;
+
+ public InvalidInputNumberException() {
+ super("Number of input values does not correspond with network input size");
+ }
+
+}
diff --git a/4neuro/java/src/InvalidLayerNumberException.java b/4neuro/java/src/InvalidLayerNumberException.java
new file mode 100644
index 00000000..5e77f8e0
--- /dev/null
+++ b/4neuro/java/src/InvalidLayerNumberException.java
@@ -0,0 +1,14 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class InvalidLayerNumberException extends RuntimeException {
+
+
+ /**
+ *
+ */
+ private static final long serialVersionUID = 1366940285989358521L;
+
+ public InvalidLayerNumberException() {
+ super("Number of layer does not correspond with network");
+ }
+}
diff --git a/4neuro/java/src/InvalidNeuronTypeException.java b/4neuro/java/src/InvalidNeuronTypeException.java
new file mode 100644
index 00000000..a983ab47
--- /dev/null
+++ b/4neuro/java/src/InvalidNeuronTypeException.java
@@ -0,0 +1,14 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class InvalidNeuronTypeException extends RuntimeException {
+
+
+ /**
+ *
+ */
+ private static final long serialVersionUID = 5354372081840990196L;
+
+ public InvalidNeuronTypeException() {
+ super("Wrong Neuron type");
+ }
+}
diff --git a/4neuro/java/src/MultiLayeredNet.java b/4neuro/java/src/MultiLayeredNet.java
new file mode 100644
index 00000000..164170bd
--- /dev/null
+++ b/4neuro/java/src/MultiLayeredNet.java
@@ -0,0 +1,58 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.util.ArrayList;
+
+public abstract class MultiLayeredNet extends NeuralNet {
+
+ protected ArrayList<ArrayList<Neuron>> neuronLayers;
+ protected ArrayList<InputLayerPseudoNeuron> inputNeuronLayer;
+ protected int nrOfInputs;
+ protected int nrOfLayers;
+ protected ArrayList<Integer> nrOfNeuronsPerLayer;
+
+ public MultiLayeredNet(int nrOfInputs, int nrOfLayers, ArrayList<Integer> nrOfNeuronsPerLayer) {
+ super();
+ this.nrOfInputs = nrOfInputs;
+ this.nrOfLayers = nrOfLayers;
+ this.nrOfNeuronsPerLayer = nrOfNeuronsPerLayer;
+ neuronLayers = new ArrayList<ArrayList<Neuron>>(nrOfLayers);
+ inputNeuronLayer = new ArrayList<InputLayerPseudoNeuron>(nrOfInputs);
+ for (int i = 0; i < nrOfLayers; i++) {
+ neuronLayers.add(new ArrayList<Neuron>(nrOfNeuronsPerLayer.get(i)));
+ }
+ for (int i = 0; i < nrOfInputs; i++) {
+ inputNeuronLayer.add(new InputLayerPseudoNeuron());
+ }
+ }
+
+ public MultiLayeredNet() {
+ this(0,0,null);
+ }
+
+ public int getNrOfInputs() {
+ return nrOfInputs;
+ }
+
+ public int getNrOfLayers() {
+ return nrOfLayers;
+ }
+
+ @Override
+ public void run(String input) {
+ String[] inputValues = input.split(" ");
+ if (inputValues.length != nrOfInputs)
+ throw new InvalidInputNumberException();
+ for (int i = 0; i < nrOfInputs; i++) {
+ InputLayerPseudoNeuron in = this.inputNeuronLayer.get(i);
+ in.initialize();
+ in.adjustPotential(Float.parseFloat(inputValues[i]));
+ in.transfer();
+ }
+
+ for (int i = 0; i < nrOfLayers; i++) {
+ Interconnections interconnectionsLayer = interconnectionsLayers.get(i);
+ interconnectionsLayer.passSignal();
+ }
+ }
+
+}
diff --git a/4neuro/java/src/NeuralNet.java b/4neuro/java/src/NeuralNet.java
new file mode 100644
index 00000000..9a666d7f
--- /dev/null
+++ b/4neuro/java/src/NeuralNet.java
@@ -0,0 +1,20 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.util.ArrayList;
+
+public abstract class NeuralNet {
+
+ protected ArrayList<Interconnections> interconnectionsLayers;
+
+ public NeuralNet(ArrayList<Interconnections> interconnectionsLayers) {
+ this.interconnectionsLayers = interconnectionsLayers;
+ }
+
+ public NeuralNet() {
+ this(new ArrayList<Interconnections>());
+ }
+
+ public abstract String getNeuronType();
+ public abstract int learn(String trainingSet);
+ public abstract void run(String input);
+}
diff --git a/4neuro/java/src/Neuron.java b/4neuro/java/src/Neuron.java
new file mode 100644
index 00000000..69260b32
--- /dev/null
+++ b/4neuro/java/src/Neuron.java
@@ -0,0 +1,59 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public abstract class Neuron {
+
+ private float potential; // inner potential
+ private float state; // excitation state
+ private float threshold; // threshold of excitation
+
+
+ public Neuron() {
+ this(0, 0, 0);
+ }
+
+ public Neuron(float potential, float state, float threshold) {
+ this.setPotential(potential);
+ this.setState(state);
+ this.setThreshold(threshold);
+ }
+
+ public void initialize() {
+ this.setPotential(0);
+ this.setState(0);
+ }
+
+ public float getThreshold() {
+ return threshold;
+ }
+
+ public void setThreshold(float threshold) {
+ this.threshold = threshold;
+ }
+
+ public float getState() {
+ return state;
+ }
+
+ protected void setState(float state) {
+ this.state = state;
+ }
+
+ protected float getPotential() {
+ return this.potential;
+ }
+
+ private void setPotential(float potential) {
+ this.potential = potential;
+ }
+
+ public void adjustPotential(float value) {
+ this.potential += value;
+ }
+
+ @Override
+ public String toString() {
+ return "Pot.: " + this.potential + ", State: " + this.state + ", Thr.: " + this.threshold;
+ }
+
+ public abstract void transfer();
+}
diff --git a/4neuro/java/src/Projekt1GUI.java b/4neuro/java/src/Projekt1GUI.java
new file mode 100644
index 00000000..e5c59453
--- /dev/null
+++ b/4neuro/java/src/Projekt1GUI.java
@@ -0,0 +1,581 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.awt.Color;
+import java.awt.EventQueue;
+import java.awt.Rectangle;
+import javax.swing.JFileChooser;
+import javax.swing.JFrame;
+import javax.swing.JMenuBar;
+import javax.swing.JMenu;
+import javax.swing.JMenuItem;
+import javax.swing.JOptionPane;
+import javax.swing.JTable;
+
+import java.awt.event.ActionListener;
+import java.awt.event.ActionEvent;
+import java.awt.event.WindowEvent;
+import java.io.File;
+import java.io.FileNotFoundException;
+import java.io.FileReader;
+import java.io.IOException;
+import java.io.StreamTokenizer;
+import java.util.ArrayList;
+
+import javax.swing.JButton;
+import javax.swing.JScrollPane;
+import javax.swing.JLabel;
+import javax.swing.event.ListSelectionEvent;
+import javax.swing.event.ListSelectionListener;
+import javax.swing.filechooser.FileFilter;
+
+import org.jfree.chart.ChartFactory;
+import org.jfree.chart.ChartPanel;
+import org.jfree.chart.JFreeChart;
+import org.jfree.chart.axis.NumberAxis;
+import org.jfree.chart.plot.XYPlot;
+import org.jfree.chart.renderer.xy.XYLineAndShapeRenderer;
+import org.jfree.chart.renderer.xy.XYSplineRenderer;
+import org.jfree.data.xy.XYSeries;
+import org.jfree.data.xy.XYSeriesCollection;
+import org.jfree.ui.RectangleInsets;
+import org.jfree.util.ShapeUtilities;
+
+public class Projekt1GUI {
+
+ private JFrame frmPerceptron;
+ private SinglePerceptronNeuralNet neuralNet;
+ private File dataFile;
+ private String trainingData;
+ private String testData;
+ private int nrOfInputs;
+ private ArrayList<float[]> inputRanges;
+ private float learnCoeff;
+ private int nrOfTrainingElements;
+ private int nrOfTestElements;
+ private String trainingOutput;
+ private int nrOfTrainingIterations;
+
+ //Swing components
+ private JButton btnLearn;
+ private JTable tableLearn;
+ private JTable tableTest;
+ private JTable tableTrainingProcess;
+ private JScrollPane scrollPaneLearn;
+ private JScrollPane scrollPaneTest;
+ private JScrollPane scrollPaneTrainingProcess;
+ private JButton buttonBackward;
+ private JButton buttonForward;
+ private JButton btnTestData;
+
+ //Chart components
+ private XYSeriesCollection dataset;
+ private ChartPanel pnlChart;
+ private XYLineAndShapeRenderer renderer;
+
+ /**
+ * Launch the application.
+ */
+ public static void main(String[] args) {
+ EventQueue.invokeLater(new Runnable() {
+ public void run() {
+ try {
+ Projekt1GUI window = new Projekt1GUI();
+ window.frmPerceptron.setVisible(true);
+ } catch (Exception e) {
+ e.printStackTrace();
+ }
+ }
+ });
+ }
+
+ /**
+ * Create the application.
+ */
+ public Projekt1GUI() {
+ initialize();
+
+ }
+
+ /**
+ * Initialize the contents of the frame.
+ */
+ private void initialize() {
+ frmPerceptron = new JFrame();
+ frmPerceptron.setTitle("Perceptron");
+ frmPerceptron.setBounds(100, 100, 652, 498);
+ frmPerceptron.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
+ frmPerceptron.getContentPane().setLayout(null);
+
+
+
+ btnLearn = new JButton("Learn");
+ btnLearn.addActionListener(new ActionListener() {
+
+
+ public void actionPerformed(ActionEvent e) {
+ btnLearn.setEnabled(false);
+ btnTestData.setEnabled(true);
+ neuralNet.learn(trainingData);
+ trainingOutput = neuralNet.getTrainingOutput();
+
+ //Show training process table
+ String[] columnNames = new String[nrOfInputs + 1];
+ for (int i = 0; i < nrOfInputs; i++) {
+ columnNames[i] = "w" + String.valueOf(i+1);
+ }
+ columnNames[nrOfInputs] = "Threshold";
+ String[] rows = trainingOutput.split("\n");
+ nrOfTrainingIterations = rows.length;
+ Float[][] fDataTable = new Float[nrOfTrainingIterations][nrOfInputs + 1];
+ for (int i = 0; i < nrOfTrainingIterations; i++) {
+ String[] cells = rows[i].split(" ");
+ for (int j = 0; j < nrOfInputs + 1; j++) {
+ fDataTable[i][j] = Float.valueOf(cells[j]);
+ }
+ }
+ tableTrainingProcess = new JTable( fDataTable, columnNames);
+ tableTrainingProcess.getSelectionModel().addListSelectionListener(new ListSelectionListener(){
+ public void valueChanged(ListSelectionEvent event) {
+
+ if (tableTrainingProcess.getSelectedRow() == 0) {
+ buttonForward.setEnabled(true);
+ buttonBackward.setEnabled(false);
+ }
+ else if (tableTrainingProcess.getSelectedRow() == tableTrainingProcess.getRowCount()-1) {
+ buttonBackward.setEnabled(true);
+ buttonForward.setEnabled(false);
+ }
+ else {
+ buttonBackward.setEnabled(true);
+ buttonForward.setEnabled(true);
+ }
+
+ //redraw chart in 2D
+ if ((nrOfInputs == 2) && (dataset != null)) {
+ float xMin = inputRanges.get(0)[0];
+ float xMax = inputRanges.get(0)[1];
+ float yMin = inputRanges.get(1)[0];
+ float yMax = inputRanges.get(1)[1];
+
+ int selectedRow = tableTrainingProcess.getSelectedRow();
+ float w0 = -(float)tableTrainingProcess.getModel().getValueAt(selectedRow, 2);
+ float w1 = (float)tableTrainingProcess.getModel().getValueAt(selectedRow, 0);
+ float w2 = (float)tableTrainingProcess.getModel().getValueAt(selectedRow, 1);
+ float step = (float)0.01;
+
+ boolean containSeries = false;
+ String key = "Line";
+ for (Object obj : dataset.getSeries()) {
+ if (obj instanceof XYSeries) {
+ XYSeries xys = (XYSeries)obj;
+ if (xys.getKey().equals(key)) {
+ containSeries = true;
+ }
+ }
+ }
+ if (!containSeries) {
+ XYSeries series = new XYSeries(key);
+ dataset.addSeries(series);
+ }
+ for (Object obj : dataset.getSeries()) {
+ if (obj instanceof XYSeries) {
+ XYSeries xys = (XYSeries)obj;
+ if (xys.getKey().equals(key)) {
+ int index = dataset.getSeries().indexOf(xys);
+ xys.clear();
+ for (float x = xMin; x < xMax; x += step) {
+ float y = -w1/w2 * x - w0/w2;
+ if ( (yMin <= y) && (y <= yMax)) {
+ xys.add(x, y);
+ }
+ }
+ renderer.setSeriesPaint(index, Color.RED);
+ }
+ }
+ }
+ }
+ }
+ });
+ scrollPaneTrainingProcess.setViewportView(tableTrainingProcess);
+ tableTrainingProcess.setRowSelectionInterval(0, 0);
+ if (nrOfTrainingIterations > 1)
+ buttonForward.setEnabled(true);
+
+ // in 2D case draw graph
+ if (nrOfInputs == 2) {
+ //Create a chart
+ XYSeries series = new XYSeries("Line");
+ float xMin = 0;//inputRanges.get(0)[0];
+ float xMax = 1;//inputRanges.get(0)[1];
+ float yMin = 0;//inputRanges.get(1)[0];
+ float yMax = 1;//inputRanges.get(1)[1];
+
+ int selectedRow = tableTrainingProcess.getSelectedRow();
+ float w0 = -(float)tableTrainingProcess.getModel().getValueAt(selectedRow, 2);
+ float w1 = (float)tableTrainingProcess.getModel().getValueAt(selectedRow, 0);
+ float w2 = (float)tableTrainingProcess.getModel().getValueAt(selectedRow, 1);
+ float step = (float)0.01;
+ for (float x = xMin; x < xMax; x += step) {
+ float y = -w1/w2 * x - w0/w2;
+ if ( (yMin <= y) && (y <= yMax)) {
+ series.add(x, y);
+ }
+ }
+
+ XYSeries seriesLearnNeg = new XYSeries("LN");
+ XYSeries seriesLearnPoz = new XYSeries("LP");
+ String[] trainingRows = trainingData.split("\n");
+ for (int i = 0; i < nrOfTrainingElements; i++) {
+ String[] trainingElement = trainingRows[i].split(" ");
+ if (Float.valueOf(trainingElement[2]) == 1) {
+ seriesLearnPoz.add(Float.valueOf(trainingElement[0]), Float.valueOf(trainingElement[1]));
+ } else {
+ seriesLearnNeg.add(Float.valueOf(trainingElement[0]), Float.valueOf(trainingElement[1]));
+ }
+ }
+
+
+ dataset = new XYSeriesCollection();
+ dataset.addSeries(series);
+ dataset.addSeries(seriesLearnPoz);
+ dataset.addSeries(seriesLearnNeg);
+
+ //Create chart with name , axis names and dataset
+ JFreeChart chart = ChartFactory.createXYLineChart("", "x1", "x2", dataset);
+ if ((pnlChart != null) && (pnlChart.getParent() == frmPerceptron.getContentPane()))
+ frmPerceptron.getContentPane().remove(pnlChart);
+
+ //Change plot properties
+
+ XYPlot plot = (XYPlot) chart.getPlot();
+ plot.setBackgroundPaint(Color.white);
+ plot.setAxisOffset(new RectangleInsets(0, 0, 0, 0));
+ plot.setDomainGridlinesVisible(false);
+ plot.setDomainGridlinePaint(Color.lightGray);
+ plot.setRangeGridlinePaint(Color.white);
+ //Set axes range
+ //x
+ NumberAxis domain = (NumberAxis) plot.getDomainAxis();
+ domain.setRange(xMin, xMax);
+ //y
+ NumberAxis yRange = (NumberAxis) plot.getRangeAxis();
+ yRange.setRange(yMin, yMax);
+
+ //Set renderer
+
+ renderer = new XYSplineRenderer();
+ renderer.setSeriesShapesVisible(0, false);
+ renderer.setSeriesShapesVisible(1, true);
+ renderer.setSeriesShape(1, ShapeUtilities.createUpTriangle(4));
+ renderer.setSeriesShapesVisible(2, true);
+ renderer.setSeriesShape(2, ShapeUtilities.createDownTriangle(4));
+ renderer.setSeriesPaint(0, Color.RED);
+ renderer.setSeriesPaint(1, Color.BLUE);
+ renderer.setSeriesPaint(2, Color.BLUE);
+ renderer.setSeriesLinesVisible(0, true);
+ renderer.setSeriesLinesVisible(1, false);
+ renderer.setSeriesLinesVisible(2, false);
+ plot.setRenderer(renderer);
+ pnlChart = new ChartPanel(chart);
+ pnlChart.setBounds(309, 267, 273, 150);
+ pnlChart.setDomainZoomable(false);
+ pnlChart.setRangeZoomable(false);
+ pnlChart.getChart().removeLegend();
+ frmPerceptron.getContentPane().add(pnlChart);
+ frmPerceptron.repaint();
+ } else {
+ if (pnlChart != null) {
+ frmPerceptron.getContentPane().remove(pnlChart);
+ frmPerceptron.repaint();
+ }
+ }
+ }
+ });
+ btnLearn.setEnabled(false);
+ btnLearn.setBounds(10, 188, 89, 23);
+ frmPerceptron.getContentPane().add(btnLearn);
+
+ btnTestData = new JButton("Test data");
+ btnTestData.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ btnTestData.setEnabled(false);
+ String[] columnNames = new String[nrOfInputs + 1];
+ for (int i = 0; i < nrOfInputs; i++) {
+ columnNames[i] = "x" + String.valueOf(i+1);
+ }
+ columnNames[nrOfInputs] = "y";
+ Float[][] fDataTable = new Float[nrOfTestElements][nrOfInputs + 1];
+ String[] rows = testData.split("\n");
+ for (int i = 0; i < nrOfTestElements; i++) {
+ String[] cells = rows[i].split(" ");
+ for (int j = 0; j < nrOfInputs; j++) {
+ fDataTable[i][j] = Float.valueOf(cells[j]);
+ }
+ neuralNet.run(rows[i]);
+ String y = neuralNet.getOutput();
+ fDataTable[i][nrOfInputs] = Float.valueOf(y);
+ }
+ tableTest = new JTable( fDataTable, columnNames);
+ scrollPaneTest.setViewportView(tableTest);
+ // in 2D case redraw graph
+ if (nrOfInputs == 2) {
+ XYSeries seriesTestNeg = new XYSeries("TN");
+ XYSeries seriesTestPoz = new XYSeries("TP");
+ String[] testRows = testData.split("\n");
+ for (int i = 0; i < nrOfTestElements; i++) {
+ String[] testElement = testRows[i].split(" ");
+ neuralNet.run(testRows[i]);
+ String y = neuralNet.getOutput();
+ if (Float.valueOf(y) == 1) {
+ seriesTestPoz.add(Float.valueOf(testElement[0]), Float.valueOf(testElement[1]));
+ } else {
+ seriesTestNeg.add(Float.valueOf(testElement[0]), Float.valueOf(testElement[1]));
+ }
+ }
+ dataset.addSeries(seriesTestPoz);
+ dataset.addSeries(seriesTestNeg);
+
+ renderer.setSeriesShapesVisible(3, true);
+ renderer.setSeriesShape(3, ShapeUtilities.createUpTriangle(6));
+ renderer.setSeriesShapesVisible(4, true);
+ renderer.setSeriesShape(4, ShapeUtilities.createDownTriangle(6));
+ renderer.setSeriesPaint(3, Color.GREEN);
+ renderer.setSeriesPaint(4, Color.GREEN);
+ renderer.setSeriesLinesVisible(3, false);
+ renderer.setSeriesLinesVisible(4, false);
+
+ }
+ }
+ });
+ btnTestData.setEnabled(false);
+ btnTestData.setBounds(10, 222, 89, 23);
+ frmPerceptron.getContentPane().add(btnTestData);
+
+ scrollPaneLearn = new JScrollPane();
+ scrollPaneLearn.setBounds(10, 25, 283, 156);
+ frmPerceptron.getContentPane().add(scrollPaneLearn);
+
+ scrollPaneTest = new JScrollPane();
+ scrollPaneTest.setBounds(10, 267, 283, 160);
+ frmPerceptron.getContentPane().add(scrollPaneTest);
+
+ JLabel lblNewLabel = new JLabel("Training data");
+ lblNewLabel.setBounds(10, 11, 116, 14);
+ frmPerceptron.getContentPane().add(lblNewLabel);
+
+ JLabel lblTestData = new JLabel("Test data");
+ lblTestData.setBounds(10, 252, 103, 14);
+ frmPerceptron.getContentPane().add(lblTestData);
+
+ scrollPaneTrainingProcess = new JScrollPane();
+ scrollPaneTrainingProcess.setBounds(303, 25, 283, 156);
+ frmPerceptron.getContentPane().add(scrollPaneTrainingProcess);
+
+ JLabel lblTrainingProcess = new JLabel("Training process");
+ lblTrainingProcess.setBounds(303, 11, 97, 14);
+ frmPerceptron.getContentPane().add(lblTrainingProcess);
+
+ buttonBackward = new JButton("<<");
+ buttonBackward.setEnabled(false);
+ buttonBackward.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent arg0) {
+ int row = tableTrainingProcess.getSelectedRow();
+ int tableRows = tableTrainingProcess.getRowCount();
+ if (row == tableRows - 1) {
+ buttonForward.setEnabled(true);
+ }
+ if (row == 1) {
+ buttonBackward.setEnabled(false);
+ }
+ tableTrainingProcess.setRowSelectionInterval(row-1, row-1);
+ Rectangle rect = tableTrainingProcess.getCellRect(row-1, 0, true);
+ tableTrainingProcess.scrollRectToVisible(rect);
+ }
+ });
+ buttonBackward.setBounds(348, 188, 89, 23);
+ frmPerceptron.getContentPane().add(buttonBackward);
+
+ buttonForward = new JButton(">>");
+ buttonForward.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ int row = tableTrainingProcess.getSelectedRow();
+ int tableRows = tableTrainingProcess.getRowCount();
+ if (row == 0) {
+ buttonBackward.setEnabled(true);
+ }
+ if (row == tableRows - 2) {
+ buttonForward.setEnabled(false);
+ }
+ tableTrainingProcess.setRowSelectionInterval(row+1, row+1);
+ Rectangle rect = tableTrainingProcess.getCellRect(row+1, 0, true);
+ tableTrainingProcess.scrollRectToVisible(rect);
+
+
+ }
+ });
+ buttonForward.setEnabled(false);
+ buttonForward.setBounds(447, 188, 89, 23);
+ frmPerceptron.getContentPane().add(buttonForward);
+
+ JLabel lbldView = new JLabel("2D View");
+ lbldView.setBounds(312, 226, 46, 14);
+ frmPerceptron.getContentPane().add(lbldView);
+
+ JMenuBar menuBar = new JMenuBar();
+ frmPerceptron.setJMenuBar(menuBar);
+
+ JMenu mnFile = new JMenu("File");
+ menuBar.add(mnFile);
+
+ JMenuItem mntmLoadData = new JMenuItem("Load data");
+ mntmLoadData.addActionListener(new ActionListener() {
+
+
+ public void actionPerformed(ActionEvent e) {
+ JFileChooser fc = new JFileChooser();
+ fc.setDialogType(JFileChooser.OPEN_DIALOG);
+ FileFilter filter = new FileFilter() {
+
+ @Override
+ public String getDescription() {
+ // TODO Auto-generated method stub
+ return "Txt files";
+ }
+
+ @Override
+ public boolean accept(File f) {
+ // TODO Auto-generated method stub
+ return (f.getName().endsWith(".txt") || f.isDirectory());
+ }
+ };
+ fc.setFileFilter(filter);
+
+
+
+ if (fc.showOpenDialog(frmPerceptron) == JFileChooser.APPROVE_OPTION) {
+ dataFile = fc.getSelectedFile();
+ FileReader fr;
+ try {
+ //Parse data file
+ fr = new FileReader(dataFile);
+ StreamTokenizer tokenizer = new StreamTokenizer(fr);
+ /*for (int i = 0; i < 6; i++ )
+ tokenizer.nextToken();
+ */
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfInputs = (int)tokenizer.nval;
+ /*tokenizer.nextToken();
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ inputRanges = new ArrayList<float[]>();
+ for (int i = 0; i < nrOfInputs; i++) {
+ float[] dims = new float[2];
+ dims[0] = (float)tokenizer.nval;
+ tokenizer.nextToken();
+ dims[1] = (float)tokenizer.nval;
+ inputRanges.add(dims);
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ }
+ /*for (int i = 0; i < 3; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ learnCoeff = (float)tokenizer.nval;
+ /*for (int i = 0; i < 7; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfTrainingElements = (int)tokenizer.nval;
+ /*for (int i = 0; i < 4; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ StringBuffer sb = new StringBuffer();
+ for (int i = 0; i < nrOfTrainingElements; i++) {
+ for (int j = 0; j < nrOfInputs; j++) {
+ sb.append(String.valueOf(tokenizer.nval/(inputRanges.get(j)[1]-inputRanges.get(j)[0]) - inputRanges.get(j)[0]/(inputRanges.get(j)[1]-inputRanges.get(j)[0])));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ sb.append(String.valueOf(tokenizer.nval));
+ sb.append("\n");
+ tokenizer.nextToken();
+ }
+ trainingData = sb.toString();
+ sb = new StringBuffer();
+ /*for (int i = 0; i < 5; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfTestElements = (int)tokenizer.nval;
+ /*tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ for (int i = 0; i < nrOfTestElements; i++) {
+ for (int j = 0; j < nrOfInputs; j++) {
+ sb.append(String.valueOf(String.valueOf(tokenizer.nval/(inputRanges.get(j)[1]-inputRanges.get(j)[0]) - inputRanges.get(j)[0]/(inputRanges.get(j)[1]-inputRanges.get(j)[0]))));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ sb.deleteCharAt(sb.lastIndexOf(" "));
+ sb.append("\n");
+ }
+
+ testData = sb.substring(0,sb.lastIndexOf("\n"));
+ fr.close();
+ neuralNet = new SinglePerceptronNeuralNet(new BinaryNeuron(), nrOfInputs, learnCoeff);
+ btnLearn.setEnabled(true);
+ //Show learn table
+ String[] columnNames = new String[nrOfInputs + 1];
+ for (int i = 0; i < nrOfInputs; i++) {
+ columnNames[i] = "x" + String.valueOf(i+1);
+ }
+ columnNames[nrOfInputs] = "y";
+ Float[][] fDataTable = new Float[nrOfTrainingElements][nrOfInputs + 1];
+ String[] rows = trainingData.split("\n");
+ for (int i = 0; i < nrOfTrainingElements; i++) {
+ String[] cells = rows[i].split(" ");
+ for (int j = 0; j < nrOfInputs + 1; j++) {
+ fDataTable[i][j] = Float.valueOf(cells[j]);
+ }
+ }
+ tableLearn = new JTable( fDataTable, columnNames);
+ scrollPaneLearn.setViewportView(tableLearn);
+ //Show test table
+ columnNames = new String[nrOfInputs];
+ for (int i = 0; i < nrOfInputs; i++) {
+ columnNames[i] = "x" + String.valueOf(i+1);
+ }
+ fDataTable = new Float[nrOfTestElements][nrOfInputs];
+ rows = testData.split("\n");
+ for (int i = 0; i < nrOfTestElements; i++) {
+ String[] cells = rows[i].split(" ");
+ for (int j = 0; j < nrOfInputs; j++) {
+ fDataTable[i][j] = Float.valueOf(cells[j]);
+ }
+ }
+ tableTest = new JTable( fDataTable, columnNames);
+ scrollPaneTest.setViewportView(tableTest);
+
+ } catch (FileNotFoundException e1) {
+ e1.printStackTrace();
+ JOptionPane.showMessageDialog(null, "Error: File not found");
+ } catch (IOException e1) {
+ // TODO Auto-generated catch block
+ e1.printStackTrace();
+ }
+
+
+ }
+
+ }
+ });
+ mnFile.add(mntmLoadData);
+
+ JMenuItem mntmExit = new JMenuItem("Exit");
+ mntmExit.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent arg0) {
+ frmPerceptron.dispatchEvent(new WindowEvent(frmPerceptron, WindowEvent.WINDOW_CLOSING));
+ }
+ });
+ mnFile.add(mntmExit);
+ }
+}
diff --git a/4neuro/java/src/Projekt2GUI.java b/4neuro/java/src/Projekt2GUI.java
new file mode 100644
index 00000000..1b4406f1
--- /dev/null
+++ b/4neuro/java/src/Projekt2GUI.java
@@ -0,0 +1,784 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.awt.Color;
+import java.awt.EventQueue;
+
+import javax.swing.JFileChooser;
+import javax.swing.JFrame;
+import javax.swing.JMenuBar;
+import javax.swing.JMenu;
+import javax.swing.JMenuItem;
+import javax.swing.JOptionPane;
+import javax.swing.JTable;
+import javax.swing.ScrollPaneConstants;
+
+import java.awt.event.ActionListener;
+import java.awt.event.ActionEvent;
+import java.awt.event.WindowEvent;
+import java.io.BufferedWriter;
+import java.io.File;
+import java.io.FileNotFoundException;
+import java.io.FileReader;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.io.StreamTokenizer;
+import java.text.DecimalFormat;
+import java.util.ArrayList;
+import java.util.Arrays;
+
+import javax.swing.JButton;
+import javax.swing.JScrollPane;
+import javax.swing.JLabel;
+import javax.swing.filechooser.FileFilter;
+import javax.swing.JSpinner;
+import javax.swing.JTextField;
+import javax.swing.SpinnerNumberModel;
+import javax.swing.event.ChangeListener;
+import javax.swing.event.ChangeEvent;
+import javax.swing.JPanel;
+
+import com.thoughtworks.xstream.XStream;
+
+import java.awt.GridLayout;
+
+public class Projekt2GUI {
+
+ private JFrame frmBPnet;
+ private BPNet neuralNet;
+ private File dataFile;
+ private String trainingData;
+ private String testData;
+
+ private int nrOfInputs;
+ private int nrOfOutputs;
+ private int nrOfLayers;
+ private float maxError;
+ private float slope;
+ private float inertiaCoeff;
+ private ArrayList<Integer> nrOfNeuronsPerLayer;
+ private ArrayList<String> inputNames;
+ private ArrayList<String> outputNames;
+
+
+ private ArrayList<float[]> inputRanges;
+ private float learnCoeff;
+
+
+ private int nrOfTrainingElements;
+ private int nrOfTestElements;
+
+ //Swing components
+ private JButton btnLearn;
+ private JTable tableLearn;
+ private JTable tableTest;
+ private JScrollPane scrollPaneLearn;
+ private JScrollPane scrollPaneTest;
+ private JButton btnTestData;
+ private JButton btnDoSpecifiedLearn;
+ private JSpinner spinnerLearnSteps;
+ private JTextField textFieldIterations;
+ private JLabel lblLearned;
+ private JLabel lblLearnCoeff;
+ private JLabel lblSlopeLambda;
+ private JSpinner spinnerLearnCoeff;
+ private JSpinner spinnerSlope;
+ private JLabel lblMaxError;
+ private JSpinner spinnerError;
+ private JLabel lblCurentError;
+ private JTextField textFieldCurrentError;
+ private JTextField textFieldTestElement;
+ private JTextField textFieldTestOutput;
+ private JButton btnTestElement;
+ private JButton btnResetWeights;
+ private JPanel panelTopology;
+ private JButton btnAddLayer;
+ private JSpinner spinnerLayer;
+ private JSpinner spinnerLayerNeurons;
+ private JMenuItem mntmSaveNeuralNet;
+
+
+ /**
+ * Launch the application.
+ */
+ public static void main(String[] args) {
+ EventQueue.invokeLater(new Runnable() {
+ public void run() {
+ try {
+ Projekt2GUI window = new Projekt2GUI();
+ window.frmBPnet.setVisible(true);
+ } catch (Exception e) {
+ e.printStackTrace();
+ }
+ }
+ });
+ }
+
+ /**
+ * Create the application.
+ */
+ public Projekt2GUI() {
+ initialize();
+ }
+
+
+ private void changeAfterLearn() {
+ btnLearn.setEnabled(false);
+ btnTestData.setEnabled(true);
+ btnDoSpecifiedLearn.setEnabled(false);
+ lblLearned.setText("Learned");
+ lblLearned.setForeground(Color.GREEN);
+ spinnerLearnSteps.setEnabled(false);
+ spinnerError.setEnabled(false);
+ spinnerLearnCoeff.setEnabled(false);
+ spinnerSlope.setEnabled(false);
+ textFieldCurrentError.setText(String.valueOf(neuralNet.getError()));
+ btnTestElement.setEnabled(true);
+ textFieldTestElement.setEnabled(true);
+ textFieldTestOutput.setEnabled(true);
+ btnResetWeights.setEnabled(false);
+ btnAddLayer.setEnabled(false);
+ spinnerLayer.setEnabled(false);
+ spinnerLayerNeurons.setEnabled(false);
+ frmBPnet.getContentPane().remove(panelTopology);
+ frmBPnet.revalidate();
+ frmBPnet.repaint();
+ mntmSaveNeuralNet.setEnabled(true);
+ }
+
+ /**
+ * Initialize the contents of the frame.
+ */
+ private void initialize() {
+ //Default values
+ slope = (float)1.1;
+ maxError = (float)0.1;
+
+
+ frmBPnet = new JFrame();
+ frmBPnet.setTitle("Backpropagation network");
+ frmBPnet.setBounds(100, 100, 778, 562);
+ frmBPnet.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
+ frmBPnet.getContentPane().setLayout(null);
+
+
+
+ btnLearn = new JButton("Quick Learn");
+ btnLearn.addActionListener(new ActionListener() {
+
+
+ public void actionPerformed(ActionEvent e) {
+
+ int iterations = neuralNet.learn(trainingData);
+ changeAfterLearn();
+ textFieldIterations.setText(String.valueOf(iterations));
+ //JOptionPane.showMessageDialog(null, "Neural Net learned in " + iterations + " iterations.");
+
+ }
+ });
+ btnLearn.setEnabled(false);
+ btnLearn.setBounds(10, 188, 174, 23);
+ frmBPnet.getContentPane().add(btnLearn);
+
+ btnTestData = new JButton("Test data");
+ btnTestData.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ btnTestData.setEnabled(false);
+
+
+ String[] columnNames = new String[nrOfInputs + nrOfOutputs];
+ for (int i = 0; i < nrOfInputs; i++) {
+ columnNames[i] = inputNames.get(i);
+
+ }
+ for (int i = 0; i < nrOfOutputs; i++) {
+ columnNames[nrOfInputs + i] = outputNames.get(i);
+ }
+ Float[][] fDataTable = new Float[nrOfTestElements][nrOfInputs + nrOfOutputs];
+ String[] rows = testData.split("\n");
+ for (int i = 0; i < nrOfTestElements; i++) {
+ neuralNet.run(rows[i]);
+ String output = neuralNet.getOutput();
+ String[] cells = (rows[i] + " " + output).split(" ");
+ for (int j = 0; j < nrOfInputs + nrOfOutputs; j++) {
+ fDataTable[i][j] = Float.valueOf(cells[j]);
+ }
+ }
+ tableTest = new JTable( fDataTable, columnNames);
+ tableTest.setAutoResizeMode(JTable.AUTO_RESIZE_OFF);
+ scrollPaneTest.setHorizontalScrollBarPolicy(ScrollPaneConstants.HORIZONTAL_SCROLLBAR_ALWAYS);
+ scrollPaneTest.setViewportView(tableTest);
+
+
+ }
+ });
+ btnTestData.setEnabled(false);
+ btnTestData.setBounds(10, 222, 174, 23);
+ frmBPnet.getContentPane().add(btnTestData);
+
+ scrollPaneLearn = new JScrollPane();
+ scrollPaneLearn.setBounds(10, 25, 368, 156);
+ frmBPnet.getContentPane().add(scrollPaneLearn);
+
+ scrollPaneTest = new JScrollPane();
+ scrollPaneTest.setBounds(10, 267, 368, 160);
+ frmBPnet.getContentPane().add(scrollPaneTest);
+
+ JLabel lblNewLabel = new JLabel("Training data");
+ lblNewLabel.setBounds(10, 11, 116, 14);
+ frmBPnet.getContentPane().add(lblNewLabel);
+
+ JLabel lblTestData = new JLabel("Test data");
+ lblTestData.setBounds(10, 252, 103, 14);
+ frmBPnet.getContentPane().add(lblTestData);
+
+ JLabel lblTrainingProcess = new JLabel("Training modification");
+ lblTrainingProcess.setBounds(386, 11, 132, 14);
+ frmBPnet.getContentPane().add(lblTrainingProcess);
+
+ btnDoSpecifiedLearn = new JButton("Do specified learn steps");
+ btnDoSpecifiedLearn.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ boolean learned = false;
+ int iter = 0;
+ int maxIterations = (int)spinnerLearnSteps.getModel().getValue();
+ ArrayList<String> trainingElements = new ArrayList<String>(Arrays.asList(trainingData.split("\n")));
+// float maxError = 0;
+ while(!learned && (iter < maxIterations)) {
+ neuralNet.setError(0);
+ learned = true;
+ for (int i = 0; i < trainingElements.size(); i++) {
+ learned &= neuralNet.learnStep(trainingElements.get(i));
+// if (neuralNet.getError() > maxError) {
+// maxError = neuralNet.getError();
+// }
+ }
+ iter++;
+ textFieldCurrentError.setText(String.valueOf(neuralNet.getError()));
+// System.out.println(iter);
+ }
+ if (learned) {
+ changeAfterLearn();
+ }
+ int currentIter = Integer.parseInt(textFieldIterations.getText());
+ textFieldIterations.setText(String.valueOf(currentIter + iter));
+
+
+ }
+ });
+ btnDoSpecifiedLearn.setEnabled(false);
+ btnDoSpecifiedLearn.setBounds(194, 188, 184, 23);
+ frmBPnet.getContentPane().add(btnDoSpecifiedLearn);
+
+ spinnerLearnSteps = new JSpinner();
+ spinnerLearnSteps.setModel(new SpinnerNumberModel(1, 1, 100000, 1));
+ spinnerLearnSteps.setEnabled(false);
+ spinnerLearnSteps.setBounds(194, 223, 88, 20);
+ frmBPnet.getContentPane().add(spinnerLearnSteps);
+
+ textFieldIterations = new JTextField();
+ textFieldIterations.setEnabled(false);
+ textFieldIterations.setText("0");
+ textFieldIterations.setBounds(292, 223, 86, 20);
+ frmBPnet.getContentPane().add(textFieldIterations);
+ textFieldIterations.setColumns(10);
+
+ lblLearned = new JLabel("Not Learned");
+ lblLearned.setForeground(Color.RED);
+ lblLearned.setBackground(Color.LIGHT_GRAY);
+ lblLearned.setBounds(514, 143, 74, 14);
+ frmBPnet.getContentPane().add(lblLearned);
+
+ lblLearnCoeff = new JLabel("Learn coeff");
+ lblLearnCoeff.setBounds(388, 39, 79, 14);
+ frmBPnet.getContentPane().add(lblLearnCoeff);
+
+ lblSlopeLambda = new JLabel("Slope - lambda");
+ lblSlopeLambda.setBounds(388, 64, 89, 14);
+ frmBPnet.getContentPane().add(lblSlopeLambda);
+
+
+
+ spinnerLearnCoeff = new JSpinner();
+ spinnerLearnCoeff.addChangeListener(new ChangeListener() {
+ public void stateChanged(ChangeEvent e) {
+ learnCoeff = (float)spinnerLearnCoeff.getModel().getValue();
+ if (neuralNet != null)
+ neuralNet.changeLearnCoeffTo(learnCoeff);
+ }
+ });
+ spinnerLearnCoeff.setEnabled(false);
+ spinnerLearnCoeff.setModel(new SpinnerNumberModel(new Float(0.5), new Float(0.05), new Float(1), new Float(0.05)));
+ JSpinner.NumberEditor editor = (JSpinner.NumberEditor)spinnerLearnCoeff.getEditor();
+ DecimalFormat format = editor.getFormat();
+ format.setMinimumFractionDigits(5);
+ spinnerLearnCoeff.setBounds(499, 36, 74, 20);
+ frmBPnet.getContentPane().add(spinnerLearnCoeff);
+
+ slope = (float)1.1;
+ spinnerSlope = new JSpinner();
+ spinnerSlope.addChangeListener(new ChangeListener() {
+ public void stateChanged(ChangeEvent e) {
+ slope = (float)spinnerSlope.getModel().getValue();
+ if (neuralNet != null)
+ neuralNet.changeSlopeTo(slope);
+ }
+ });
+ spinnerSlope.setEnabled(false);
+ spinnerSlope.setBounds(499, 61, 74, 20);
+ spinnerSlope.setModel(new SpinnerNumberModel(new Float(slope), new Float(0.05), null, new Float(0.05)));
+ editor = (JSpinner.NumberEditor)spinnerSlope.getEditor();
+ format = editor.getFormat();
+ format.setMinimumFractionDigits(5);
+ frmBPnet.getContentPane().add(spinnerSlope);
+
+ lblMaxError = new JLabel("Max error");
+ lblMaxError.setBounds(388, 89, 67, 14);
+ frmBPnet.getContentPane().add(lblMaxError);
+
+
+ maxError = (float)0.1;
+ spinnerError = new JSpinner();
+ spinnerError.addChangeListener(new ChangeListener() {
+ public void stateChanged(ChangeEvent e) {
+ maxError = (float)spinnerError.getModel().getValue();
+ if (neuralNet != null)
+ neuralNet.setTolerance(maxError);
+ }
+ });
+ spinnerError.setEnabled(false);
+ spinnerError.setBounds(499, 86, 74, 20);
+ spinnerError.setModel(new SpinnerNumberModel(new Float(maxError), new Float(0.00001), new Float(100), new Float(0.00001)));
+ editor = (JSpinner.NumberEditor)spinnerError.getEditor();
+ format = editor.getFormat();
+ format.setMinimumFractionDigits(5);
+ frmBPnet.getContentPane().add(spinnerError);
+
+ lblCurentError = new JLabel("Current Error");
+ lblCurentError.setBounds(388, 115, 79, 14);
+ frmBPnet.getContentPane().add(lblCurentError);
+
+ textFieldCurrentError = new JTextField();
+ textFieldCurrentError.setEnabled(false);
+ textFieldCurrentError.setBounds(487, 112, 86, 20);
+ frmBPnet.getContentPane().add(textFieldCurrentError);
+ textFieldCurrentError.setColumns(10);
+
+ JLabel lblChangeNetworkTopology = new JLabel("Change network topology");
+ lblChangeNetworkTopology.setBounds(389, 168, 184, 14);
+ frmBPnet.getContentPane().add(lblChangeNetworkTopology);
+
+ textFieldTestElement = new JTextField();
+ textFieldTestElement.setEnabled(false);
+ textFieldTestElement.setBounds(10, 438, 272, 20);
+ frmBPnet.getContentPane().add(textFieldTestElement);
+ textFieldTestElement.setColumns(10);
+
+ btnTestElement = new JButton("Run input");
+ btnTestElement.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ String input = textFieldTestElement.getText();
+ try {
+ neuralNet.run(input);
+ }
+ catch(InvalidInputNumberException exception) {
+ JOptionPane.showMessageDialog(null, "Invalid Input");
+ }
+ finally {
+ String output = neuralNet.getOutput();
+ textFieldTestOutput.setText(output);
+ }
+ }
+ });
+ btnTestElement.setEnabled(false);
+ btnTestElement.setBounds(289, 437, 89, 23);
+ frmBPnet.getContentPane().add(btnTestElement);
+
+ textFieldTestOutput = new JTextField();
+ textFieldTestOutput.setEnabled(false);
+ textFieldTestOutput.setBounds(49, 471, 329, 20);
+ frmBPnet.getContentPane().add(textFieldTestOutput);
+ textFieldTestOutput.setColumns(10);
+
+ JLabel lblOutput = new JLabel("Output");
+ lblOutput.setBounds(10, 474, 46, 14);
+ frmBPnet.getContentPane().add(lblOutput);
+
+ btnResetWeights = new JButton("Reset weights");
+ btnResetWeights.setEnabled(false);
+ btnResetWeights.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ neuralNet.resetWeights();
+ }
+ });
+ btnResetWeights.setBounds(388, 138, 116, 23);
+ frmBPnet.getContentPane().add(btnResetWeights);
+
+ panelTopology = new JPanel();
+ panelTopology.setBounds(386, 213, 366, 214);
+ frmBPnet.getContentPane().add(panelTopology);
+
+ btnAddLayer = new JButton("Add layer");
+ btnAddLayer.setEnabled(false);
+ btnAddLayer.setBounds(386, 188, 89, 23);
+ frmBPnet.getContentPane().add(btnAddLayer);
+
+ spinnerLayer = new JSpinner();
+ spinnerLayer.setEnabled(false);
+ spinnerLayer.setBounds(499, 189, 40, 20);
+ frmBPnet.getContentPane().add(spinnerLayer);
+
+ spinnerLayerNeurons = new JSpinner();
+ spinnerLayerNeurons.setEnabled(false);
+ spinnerLayerNeurons.setBounds(571, 189, 40, 20);
+ frmBPnet.getContentPane().add(spinnerLayerNeurons);
+
+ JLabel lblTo = new JLabel("to");
+ lblTo.setBounds(483, 192, 46, 14);
+ frmBPnet.getContentPane().add(lblTo);
+
+ JLabel lblWith = new JLabel("with");
+ lblWith.setBounds(542, 192, 46, 14);
+ frmBPnet.getContentPane().add(lblWith);
+
+ JLabel lblNeurons = new JLabel("neurons");
+ lblNeurons.setBounds(621, 192, 74, 14);
+ frmBPnet.getContentPane().add(lblNeurons);
+
+
+
+ JMenuBar menuBar = new JMenuBar();
+ frmBPnet.setJMenuBar(menuBar);
+
+
+ JMenu mnFile = new JMenu("File");
+ menuBar.add(mnFile);
+
+ JMenuItem mntmLoadData = new JMenuItem("Load data");
+ mntmLoadData.addActionListener(new ActionListener() {
+
+
+ public void actionPerformed(ActionEvent e) {
+ JFileChooser fc = new JFileChooser();
+ fc.setDialogType(JFileChooser.OPEN_DIALOG);
+ FileFilter filter = new FileFilter() {
+
+ @Override
+ public String getDescription() {
+ return "Txt files";
+ }
+
+ @Override
+ public boolean accept(File f) {
+ return (f.getName().endsWith(".txt") || f.isDirectory());
+ }
+ };
+ fc.setFileFilter(filter);
+
+
+
+ if (fc.showOpenDialog(frmBPnet) == JFileChooser.APPROVE_OPTION) {
+ dataFile = fc.getSelectedFile();
+ FileReader fr;
+ try {
+
+ spinnerLearnSteps.setEnabled(true);
+ spinnerError.setEnabled(true);
+ spinnerLearnCoeff.setEnabled(true);
+ spinnerSlope.setEnabled(true);
+ spinnerLearnCoeff.setValue(new Float((float)spinnerLearnCoeff.getValue()));
+ spinnerSlope.setValue(spinnerSlope.getValue());
+ spinnerError.setValue(spinnerError.getValue());
+
+ //Parse data file
+
+
+
+ fr = new FileReader(dataFile);
+ StreamTokenizer tokenizer = new StreamTokenizer(fr);
+ /*for (int i = 0; i < 6; i++ )
+ tokenizer.nextToken();
+ */
+ while(true) {
+ tokenizer.nextToken();
+ if ((tokenizer.nextToken() == StreamTokenizer.TT_WORD) && tokenizer.sval.equals("vrstev")) {
+ tokenizer.nextToken();
+ break;
+ }
+ }
+ nrOfLayers = (int)tokenizer.nval;
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfInputs = (int)tokenizer.nval;
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ tokenizer.nextToken();
+ inputRanges = new ArrayList<float[]>();
+ inputNames = new ArrayList<String>();
+ for (int i = 0; i < nrOfInputs; i++) {
+ String inputName = tokenizer.sval;
+ inputNames.add(inputName);
+ tokenizer.nextToken();
+ float[] dims = new float[2];
+ dims[0] = (float)tokenizer.nval;
+ tokenizer.nextToken();
+ dims[1] = (float)tokenizer.nval;
+ inputRanges.add(dims);
+ tokenizer.nextToken();
+ }
+ /*for (int i = 0; i < 3; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfNeuronsPerLayer = new ArrayList<Integer>();
+ for (int i = 0; i < nrOfLayers; i++) {
+ nrOfNeuronsPerLayer.add((int)tokenizer.nval);
+ if (i == nrOfLayers - 1) {
+ nrOfOutputs = (int)tokenizer.nval;
+ }
+ tokenizer.nextToken();
+ }
+ for (int i = 0; i < 3; i++ )
+ tokenizer.nextToken();
+ outputNames = new ArrayList<String>();
+ for (int i = 0; i < nrOfOutputs; i++) {
+ outputNames.add(tokenizer.sval);
+ tokenizer.nextToken();
+ }
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ learnCoeff = (float)tokenizer.nval;
+ spinnerLearnCoeff.getModel().setValue(new Float(learnCoeff));
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ inertiaCoeff = (float)tokenizer.nval;
+ /*for (int i = 0; i < 7; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfTrainingElements = (int)tokenizer.nval;
+ /*for (int i = 0; i < 4; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ StringBuffer sb = new StringBuffer();
+ for (int i = 0; i < nrOfTrainingElements; i++) {
+ for (int j = 0; j < nrOfInputs; j++) {
+ sb.append(String.valueOf(tokenizer.nval/(inputRanges.get(j)[1]-inputRanges.get(j)[0]) - inputRanges.get(j)[0]/(inputRanges.get(j)[1]-inputRanges.get(j)[0])));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ for (int j = 0; j < nrOfOutputs; j++) {
+ sb.append(String.valueOf(tokenizer.nval));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ sb.deleteCharAt(sb.length() - 1);
+ sb.append("\n");
+ }
+ trainingData = sb.toString();
+ sb = new StringBuffer();
+ /*for (int i = 0; i < 5; i++ )
+ tokenizer.nextToken();*/
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ nrOfTestElements = (int)tokenizer.nval;
+ /*tokenizer.nextToken();*/
+ if (nrOfTestElements > 0) {
+ while(tokenizer.nextToken() != StreamTokenizer.TT_NUMBER) {}
+ for (int i = 0; i < nrOfTestElements; i++) {
+ for (int j = 0; j < nrOfInputs; j++) {
+ sb.append(String.valueOf(String.valueOf(tokenizer.nval/(inputRanges.get(j)[1]-inputRanges.get(j)[0]) - inputRanges.get(j)[0]/(inputRanges.get(j)[1]-inputRanges.get(j)[0]))));
+ sb.append(" ");
+ tokenizer.nextToken();
+ }
+ sb.deleteCharAt(sb.lastIndexOf(" "));
+ sb.append("\n");
+ }
+ testData = sb.substring(0,sb.lastIndexOf("\n"));
+ } else {
+ testData = "";
+ }
+ fr.close();
+
+
+
+ neuralNet = new BPNet(maxError, nrOfLayers, nrOfInputs, nrOfNeuronsPerLayer, slope, learnCoeff);
+ spinnerError.getModel().setValue(maxError);
+ btnLearn.setEnabled(true);
+ //Show learn table
+ String[] columnNames = new String[nrOfInputs + nrOfOutputs];
+ for (int i = 0; i < nrOfInputs; i++) {
+ columnNames[i] = inputNames.get(i);
+
+ }
+ for (int i = 0; i < nrOfOutputs; i++) {
+ columnNames[nrOfInputs + i] = outputNames.get(i);
+ }
+ Float[][] fDataTable = new Float[nrOfTrainingElements][nrOfInputs + nrOfOutputs];
+ String[] rows = trainingData.split("\n");
+ for (int i = 0; i < nrOfTrainingElements; i++) {
+ String[] cells = rows[i].split(" ");
+ for (int j = 0; j < nrOfInputs + nrOfOutputs; j++) {
+ fDataTable[i][j] = Float.valueOf(cells[j]);
+ }
+ }
+ tableLearn = new JTable( fDataTable, columnNames);
+ tableLearn.setAutoResizeMode(JTable.AUTO_RESIZE_OFF);
+ scrollPaneLearn.setHorizontalScrollBarPolicy(ScrollPaneConstants.HORIZONTAL_SCROLLBAR_ALWAYS);
+ scrollPaneLearn.setViewportView(tableLearn);
+ //Show test table
+ columnNames = new String[nrOfInputs];
+ for (int i = 0; i < nrOfInputs; i++) {
+ columnNames[i] = inputNames.get(i);
+ }
+ fDataTable = new Float[nrOfTestElements][nrOfInputs];
+ rows = testData.split("\n");
+ for (int i = 0; i < nrOfTestElements; i++) {
+ String[] cells = rows[i].split(" ");
+ for (int j = 0; j < nrOfInputs; j++) {
+ fDataTable[i][j] = Float.valueOf(cells[j]);
+ }
+ }
+ tableTest = new JTable( fDataTable, columnNames);
+ tableTest.setAutoResizeMode(JTable.AUTO_RESIZE_OFF);
+ scrollPaneTest.setViewportView(tableTest);
+ btnResetWeights.setEnabled(true);
+ btnDoSpecifiedLearn.setEnabled(true);
+ btnAddLayer.setEnabled(true);
+ spinnerLayer.setEnabled(true);
+ spinnerLayer.setModel(new SpinnerNumberModel(0, 0, neuralNet.getNrOfLayers(), 1));
+ spinnerLayerNeurons.setEnabled(true);
+ spinnerLayerNeurons.setModel(new SpinnerNumberModel(1, 1, null, 1));
+
+ btnAddLayer.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ neuralNet.addNeuronLayer((Integer)spinnerLayerNeurons.getValue(), (Integer)spinnerLayer.getValue(), slope);
+ refreshPanelTopology();
+ }
+ });
+ refreshPanelTopology();
+
+
+ } catch (FileNotFoundException e1) {
+ e1.printStackTrace();
+ JOptionPane.showMessageDialog(null, "Error: File not found");
+ } catch (IOException e1) {
+ e1.printStackTrace();
+ JOptionPane.showMessageDialog(null, "IOException");
+ }
+
+
+ }
+
+ }
+
+ private void refreshPanelTopology() {
+ panelTopology.setLayout(new GridLayout(neuralNet.getNrOfLayers() + 1, 4));
+ panelTopology.removeAll();
+ nrOfLayers = neuralNet.getNrOfLayers();
+ String map = neuralNet.getNeuronMap();
+ String[] layers = map.split(" ");
+ spinnerLayer.setModel(new SpinnerNumberModel(0, 0, neuralNet.getNrOfLayers() - 1, 1));
+ spinnerLayerNeurons.setModel(new SpinnerNumberModel(1, 1, null, 1));
+ for (int i = 0; i < nrOfLayers; i++) {
+ JLabel label = new JLabel(layers[nrOfLayers - 1 - i]);
+ panelTopology.add(label);
+ if (i > 0) {
+ JButton btn1 = new JButton("Rmv neuron");
+ JButton btn2 = new JButton("Rmv layer");
+ JButton btn3 = new JButton("Add neuron");
+ btn1.setName(String.valueOf(nrOfLayers - 1 - i));
+ btn2.setName(String.valueOf(nrOfLayers - 1 - i));
+ btn3.setName(String.valueOf(nrOfLayers - 1 - i));
+ btn1.addActionListener(new ActionListener() {
+
+ @Override
+ public void actionPerformed(ActionEvent e) {
+ String name = ((JButton)e.getSource()).getName();
+ neuralNet.removeNeuron(Integer.parseInt(name));
+ refreshPanelTopology();
+ }
+ });
+ btn2.addActionListener(new ActionListener() {
+
+ @Override
+ public void actionPerformed(ActionEvent e) {
+ String name = ((JButton)e.getSource()).getName();
+ neuralNet.removeNeuronLayer(Integer.parseInt(name));
+ refreshPanelTopology();
+ }
+ });
+ btn3.addActionListener(new ActionListener() {
+
+ @Override
+ public void actionPerformed(ActionEvent e) {
+ String name = ((JButton)e.getSource()).getName();
+ neuralNet.addNeuron(Integer.parseInt(name), slope);
+ refreshPanelTopology();
+
+ }
+ });
+ panelTopology.add(btn1);
+ panelTopology.add(btn2);
+ panelTopology.add(btn3);
+ } else {
+ panelTopology.add(new JLabel(" "));
+ panelTopology.add(new JLabel(" "));
+ panelTopology.add(new JLabel(" "));
+ }
+ }
+ panelTopology.add(new JLabel("Inputs"));
+ panelTopology.add(new JLabel(String.valueOf(neuralNet.getNrOfInputs())));
+ panelTopology.add(new JLabel(" "));
+ panelTopology.add(new JLabel(" "));
+ frmBPnet.revalidate();
+ }
+ });
+ mnFile.add(mntmLoadData);
+
+ JMenuItem mntmExit = new JMenuItem("Exit");
+ mntmExit.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent arg0) {
+ frmBPnet.dispatchEvent(new WindowEvent(frmBPnet, WindowEvent.WINDOW_CLOSING));
+ }
+ });
+
+ mntmSaveNeuralNet = new JMenuItem("Save Neural Net");
+ mntmSaveNeuralNet.addActionListener(new ActionListener() {
+ public void actionPerformed(ActionEvent e) {
+ try {
+ File address = null;
+ JFileChooser fc = new JFileChooser();
+ FileFilter filter = new FileFilter() {
+
+ @Override
+ public String getDescription() {
+ return "Xml files";
+ }
+
+ @Override
+ public boolean accept(File f) {
+ return (f.getName().endsWith(".xml") || f.isDirectory());
+ }
+ };
+ fc.setFileFilter(filter);
+ fc.setCurrentDirectory(new java.io.File("."));
+ //fc.setFileSelectionMode(JFileChooser.SAVE_DIALOG);
+ if (fc.showSaveDialog(frmBPnet) == JFileChooser.APPROVE_OPTION) {
+ address = fc.getSelectedFile();
+ XStream xstream = new XStream();
+ String xml = xstream.toXML(neuralNet);
+ BufferedWriter out = new BufferedWriter(new FileWriter(address));
+ out.write(xml);
+ out.close();
+// BPNet testNet = (BPNet)xstream.fromXML(xml);
+
+ JOptionPane.showMessageDialog(null, "Hotovo");
+ }
+ }
+ catch (Exception ex) {
+ ex.printStackTrace();
+ JOptionPane.showMessageDialog(null, ex.getMessage());
+ }
+
+ }
+ });
+ mntmSaveNeuralNet.setEnabled(false);
+ mnFile.add(mntmSaveNeuralNet);
+ mnFile.add(mntmExit);
+ }
+}
diff --git a/4neuro/java/src/SigmoidalNeuron.java b/4neuro/java/src/SigmoidalNeuron.java
new file mode 100644
index 00000000..706eea0f
--- /dev/null
+++ b/4neuro/java/src/SigmoidalNeuron.java
@@ -0,0 +1,53 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+public class SigmoidalNeuron extends Neuron {
+
+ private float error; //delta
+ private float slope; //lambda
+
+
+
+
+ public void setSlope(float slope) {
+ this.slope = slope;
+ }
+
+
+ public SigmoidalNeuron(float slope) {
+ this.slope = slope;
+ this.error = 0;
+ }
+
+
+ @Override
+ public void transfer() {
+ float z = this.getPotential();
+ float y = (float) (1.0/(1.0 + Math.exp(-slope*z)));
+ this.setState(y);
+ }
+
+
+ public float getSlope() {
+ return slope;
+ }
+
+ public float getError() {
+ return error;
+ }
+
+
+ public void setError(float error) {
+ this.error = error;
+ }
+
+
+ public static void main(String args[]) {
+ SigmoidalNeuron neuron = new SigmoidalNeuron((float)0.5);
+ for (int i = -10; i <= 10; i++) {
+ neuron.initialize();
+ neuron.adjustPotential(i);
+ neuron.transfer();
+ System.out.println(neuron.getState());
+ }
+ }
+}
diff --git a/4neuro/java/src/SinglePerceptronNeuralNet.java b/4neuro/java/src/SinglePerceptronNeuralNet.java
new file mode 100644
index 00000000..e741be25
--- /dev/null
+++ b/4neuro/java/src/SinglePerceptronNeuralNet.java
@@ -0,0 +1,147 @@
+package cz.vsb.mro0010.neuralnetworks;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+
+public class SinglePerceptronNeuralNet extends NeuralNet {
+
+ private Neuron neuron;
+ private int nrOfInputs;
+ private ArrayList<Connection> connections;
+ private ArrayList<InputLayerPseudoNeuron> input;
+ private String trainingOutput;
+ private float learnCoef;
+
+ public SinglePerceptronNeuralNet(Neuron neuron, int nrOfInputs, float learnCoef) {
+ super();
+ this.neuron = neuron;
+ this.nrOfInputs = nrOfInputs;
+ this.input = new ArrayList<InputLayerPseudoNeuron>();
+ this.connections = new ArrayList<Connection>();
+ for (int i = 0; i < this.nrOfInputs; i++) {
+ InputLayerPseudoNeuron inputNeuron = new InputLayerPseudoNeuron();
+ this.input.add(inputNeuron);
+ this.connections.add(new Connection(inputNeuron, neuron, (float)Math.random()));
+ }
+ this.setTrainingOutput(" ");
+ this.learnCoef = learnCoef;
+ }
+
+ @Override
+ public String getNeuronType() {
+ return neuron.getClass().getSimpleName();
+ }
+
+ @Override
+ public int learn(String trainingSet) {
+ ArrayList<String> trainingElements = new ArrayList<String>(Arrays.asList(trainingSet.split("\n")));
+ boolean learned = false;
+ int iterations = 0;
+ StringBuffer trainingProgress = new StringBuffer();
+ for (Connection c : connections) {
+ trainingProgress.append(String.valueOf(c.getWeight()));
+ trainingProgress.append(" ");
+ }
+ trainingProgress.append(String.valueOf(-neuron.getThreshold()));
+ trainingProgress.append("\n");
+ while (!learned) {
+ iterations++;
+ learned = true;
+ for (String element : trainingElements) {
+ String[] sa = element.split(" ");
+ String expectedOutput = sa[sa.length - 1];
+ StringBuffer sb = new StringBuffer();
+ for (int i = 0; i < sa.length - 1; i++) {
+ sb.append(sa[i]);
+ sb.append(" ");
+ }
+ this.run(sb.toString());
+
+ if (Float.parseFloat(expectedOutput) != Float.parseFloat(this.getOutput())) {
+ learned = false;
+ float eo = Float.parseFloat(expectedOutput);
+ float ro = Float.parseFloat(this.getOutput());
+ neuron.setThreshold(neuron.getThreshold() + learnCoef*-(eo-ro)*1); // w_0 = -threshold
+ for (Connection c : connections) {
+ c.adjustWeight(learnCoef*(eo-ro)*c.getInputNeuron().getState());
+ }
+ for (Connection c : connections) {
+ trainingProgress.append(String.valueOf(c.getWeight()));
+ trainingProgress.append(" ");
+ }
+ trainingProgress.append(String.valueOf(neuron.getThreshold()));
+ trainingProgress.append("\n");
+ }
+ }
+ }
+ //System.out.println("Learned! in " + (iterations-1) + " iterations");
+ this.setTrainingOutput(trainingProgress.toString());
+ return iterations;
+ }
+
+ @Override
+ public void run(String inputString) {
+ String[] input = inputString.split(" ");
+ for (int i = 0; i < input.length; i++) {
+ InputLayerPseudoNeuron in = this.input.get(i);
+ in.initialize();
+ in.adjustPotential(Float.parseFloat(input[i]));
+ in.transfer();
+ }
+ neuron.initialize();
+ for (Connection c : connections) {
+ c.passSignal();
+ }
+ neuron.transfer();
+
+ }
+
+ public String getOutput() {
+ String output = String.valueOf(neuron.getState());
+ return output;
+ }
+
+ public String getTrainingOutput() {
+ return trainingOutput;
+ }
+
+ private void setTrainingOutput(String trainingOutput) {
+ this.trainingOutput = trainingOutput;
+ }
+
+ /*public static void main(String[] args) {
+ SinglePerceptronNeuralNet net = new SinglePerceptronNeuralNet(new BinaryNeuron(), 2, (float)0.7);
+ net.neuron.setThreshold((float) Math.random());
+// String learnSet = "1 0.5 0\n0.4 0.8 1\n0.1 0.1 0\n0.6 0.9 1\n0.8 0.7 0\n0.4 1.0 1";
+// net.learn(learnSet);
+// net.run("0.7 0.9");
+// System.out.println(net.getOutput());
+// net.run("0.9 0.7");
+// System.out.println(net.getOutput());
+// net.run("0.2 0.2");
+// System.out.println(net.getOutput());
+// net.run("0.1 1.0");
+// System.out.println(net.getOutput());
+// net.run("1.0 0.1");
+// System.out.println(net.getOutput());
+ String learnSet = "0.7 0.3 0\n0.2 0.6 1\n0.3 0.4 1\n0.9 0.8 0\n0.1 0.2 1\n0.5 0.6 1";
+ net.learn(learnSet);
+ net.run("0.7 0.9");
+ System.out.println(net.getOutput());
+ net.run("0.9 0.7");
+ System.out.println(net.getOutput());
+ net.run("0.2 0.2");
+ System.out.println(net.getOutput());
+ net.run("0.1 1.0");
+ System.out.println(net.getOutput());
+ net.run("1.0 0.1");
+ System.out.println(net.getOutput());
+ net.run("0.6 0.5");
+ System.out.println(net.getOutput());
+ net.run("0.5 0.6");
+ System.out.println(net.getOutput());
+ }*/
+
+
+
+}
diff --git a/4neuro/run_tests.sh b/4neuro/run_tests.sh
new file mode 100644
index 00000000..dd99154e
--- /dev/null
+++ b/4neuro/run_tests.sh
@@ -0,0 +1,5 @@
+#!/bin/bash
+
+cd build;
+
+./connection_test.out
diff --git a/4neuro/src/CMakeLists.txt b/4neuro/src/CMakeLists.txt
new file mode 100644
index 00000000..5a2e0ac7
--- /dev/null
+++ b/4neuro/src/CMakeLists.txt
@@ -0,0 +1,12 @@
+project(Modules)
+enable_language(Fortran)
+
+set(standard "-std=f2008")
+set(CMAKE_Fortran_FLAGS "${standard}")
+
+add_library(neuron_dummy_m SHARED neuron_dummy_m.f90)
+set_target_properties(neuron_dummy_m PROPERTIES LINKER_LANGUAGE Fortran)
+
+add_library(connection_m SHARED connection_m.f90)
+set_target_properties(connection_m PROPERTIES LINKER_LANGUAGE Fortran)
+target_link_libraries(connection_m neuron_dummy_m)
diff --git a/4neuro/src/connection_m.f90 b/4neuro/src/connection_m.f90
new file mode 100644
index 00000000..63582444
--- /dev/null
+++ b/4neuro/src/connection_m.f90
@@ -0,0 +1,175 @@
+!> Module containing classes representing connections (synapses)
+!! in neural networks.
+!!
+!! It uses `neural_t` class.
+!!
+!! @author Martin Beseda
+!! @author Martin Mrovec
+!! @date 2017
+!! @todo Implement destructor
+!! @todo Comment constructor
+module connection_m
+ ! TODO Implement destructor
+ use neuron_dummy_m
+
+ implicit none
+
+ public
+
+ !------------------!------------------------------------------------------------------------
+ ! Type definitions !
+ !------------------!
+
+ !> Represents a connection between two neurons.
+ type, abstract :: connection_t
+ private
+
+ class(neuron_t), pointer :: input_neuron !< Pointer to an input neuron
+ class(neuron_t), pointer :: output_neuron !< Pointer to an output neuron
+ real :: weight !< Weight of the connection
+
+ contains
+
+ !> Initializes the common connection_t class components
+ !! 'input_neuron', 'output_neuron' and 'weight'.
+ !! I.e. serves similarly to an abstract constructor.
+ procedure, private :: init_components => init_components_impl
+
+ !procedure :: destroy_instance => destroy_instance_impl
+
+ !final, deferred :: destructor
+
+ !> Adds a given value to the current weight of the
+ !! connection.
+ !! @param added_value Number (real) to be added to the current weight
+ procedure :: adjust_weight => adjust_weight_impl
+
+ !> Getter for the private 'input_neuron' component
+ !! @return Pointer to the input neuron (type neuron_t, pointer)
+ procedure :: get_input_neuron => get_input_neuron_impl
+
+ !> Getter for the private 'output_neuron' component
+ !! @return Pointer to the output neuron (type neuron_t, pointer)
+ procedure :: get_output_neuron => get_output_neuron_impl
+
+ !> Getter for the private 'weight' component
+ !! @return Weight of the connection (type real)
+ procedure :: get_weight => get_weight_impl
+
+ end type connection_t
+
+ !> Represents a connection between two neurons.
+ !! Able to pass a signal from an input neuron to
+ !! an output one.
+ type, extends(connection_t) :: interval_connection_t
+ contains
+
+ !> Passes (assigns) the product
+ !! input neuron state * weight)
+ !! to an output neuron.
+ procedure :: pass_signal => pass_signal_impl
+ end type interval_connection_t
+
+ !------------!------------------------------------------------------------------------------
+ ! Interfaces !
+ !------------!
+ interface interval_connection_t
+ !> Constructor of interval_connection_t class
+ module procedure :: new_interval_connection
+ end interface interval_connection_t
+
+ contains
+ !------------------------!------------------------------------------------------------------
+ ! Method implementations !
+ ! -----------------------!
+
+ !subroutine destroy_instance_impl(this)
+ ! class(connection_t), pointer, intent(out) :: this
+
+ ! deallocate(this)
+ !end subroutine destroy_instance_impl
+
+ !--------------------!
+ ! class connection_t !
+ !--------------------!
+ subroutine init_components_impl(this, input_neuron, output_neuron, weight)
+ class(connection_t), intent(inout) :: this
+ type(neuron_t), pointer :: input_neuron
+ type(neuron_t), pointer :: output_neuron
+ real, intent(in) :: weight
+
+ !DEC$ IF DEFINED TIME_PROFILING
+ real :: t1, t2 !< Variables used for time measurement
+ call cpu_time(t1)
+ !DEC$ ENDIF
+
+ this%input_neuron => input_neuron
+ this%output_neuron => output_neuron
+ this%weight = weight
+
+
+ !DEC$ IF DEFINED TIME_PROFILING
+ call cpu_time(t2)
+ write(*, "(A)") '+----------------+'
+ write(*, "(A, E15.7, A)") '| TIME PROFILING | Function init_components() was running for ', t2-t1, 's.'
+ write(*, "(A)") '+----------------+'
+ !DEC$ ENDIF
+ end subroutine init_components_impl
+
+ subroutine adjust_weight_impl(this, added_value)
+ class(connection_t), intent(inout) :: this
+ real, intent(in) :: added_value
+
+ this%weight = this%weight + added_value
+ end subroutine adjust_weight_impl
+
+ !-----------------------------!
+ ! class interval_connection_t !
+ !-----------------------------!
+ subroutine pass_signal_impl(this)
+ class(interval_connection_t), intent(in) :: this
+
+ call this%output_neuron%set_state(this%input_neuron%get_state() * this%weight)
+ end subroutine pass_signal_impl
+
+ !--------------!------------------------------------------------------------------------
+ ! Constructors !
+ !--------------!
+ function new_interval_connection(input_neuron, output_neuron, weight) result(ret_obj)
+ type(neuron_t), pointer :: input_neuron
+ type(neuron_t), pointer :: output_neuron
+ real, intent(in) :: weight
+ type(interval_connection_t), pointer :: ret_obj
+
+ allocate(ret_obj)
+
+ call ret_obj%init_components(input_neuron, output_neuron, weight)
+ end function new_interval_connection
+
+ !-------------------!-------------------------------------------------------------------
+ ! Getters & Setters !
+ !-------------------!
+
+ function get_input_neuron_impl(this) result (input_neuron)
+ class(connection_t), target, intent(in) :: this
+ class(neuron_t), pointer :: input_neuron
+
+ input_neuron => this%input_neuron
+ end function get_input_neuron_impl
+
+ function get_output_neuron_impl(this) result (output_neuron)
+ class(connection_t), target, intent(in) :: this
+ class(neuron_t), pointer :: output_neuron
+
+ output_neuron => this%output_neuron
+ end function get_output_neuron_impl
+
+ function get_weight_impl(this) result (weight)
+ class(connection_t), intent(in) :: this
+ real :: weight
+
+ weight = this%weight
+ end function get_weight_impl
+
+ end module connection_m
+
diff --git a/4neuro/src/connection_test.f90 b/4neuro/src/connection_test.f90
new file mode 100644
index 00000000..16883f5f
--- /dev/null
+++ b/4neuro/src/connection_test.f90
@@ -0,0 +1,86 @@
+program connection_test
+ use connection_m
+ use neuron_dummy_m
+
+ type(neuron_t), target :: n1
+ type(neuron_t), target :: n2
+
+ type(neuron_t), pointer :: n1_p
+ type(neuron_t), pointer :: n2_p
+ type(neuron_t), pointer :: dummy_p
+
+ type(interval_connection_t), pointer :: con
+
+ print *, '+---------------------------------------------+'
+ print *, '| STARTING TESTING OF THE MODULE CONNECTION_M |'
+ print *, '+---------------------------------------------+'
+
+ print *, 'Creating instances of the class neuron_t...'
+ n1 = neuron_t(21.3)
+ n2 = neuron_t(13.7)
+ print *, 'neuron_t instances were created successfully.'
+
+ print *, 'Assigning instances to pointer...'
+ n1_p => n1
+ n2_p => n2
+ print *, 'Assignment was successful.'
+
+ print *, 'Creating an instance of the class interval_connection_t...'
+ con => interval_connection_t(n1_p, n2_p, 5.25)
+ print *, 'The instance of the class interval_connection_t was created successfully.'
+
+ print *, 'Testing get_weight() method...'
+ if(con%get_weight() == 5.25) then
+ print *, 'Test of get_weight() was successfull.'
+ else
+ print *, 'ERROR testing method get_weight()!'
+ stop -1
+ end if
+
+ print *, 'Testing adjust_weight() method...'
+ call con%adjust_weight(1.0)
+ if(con%get_weight() == 6.25) then
+ print *, 'Test of adjust_weight() was successful.'
+ else
+ print *, 'ERROR testing method adjust_weight()!'
+ stop -1
+ end if
+
+ print *, 'Assigning input neuron to a pointer using get_input_neuron()...'
+ dummy_p => con%get_input_neuron()
+ print *, 'Assignment was successful.'
+
+ print *, 'Testing method get_state() on the input neuron...'
+ if(dummy_p%get_state() == 21.3) then
+ print *, 'Test was successful.'
+ else
+ print *, 'ERROR using method get_state() on the input neuron!'
+ stop -1
+ end if
+
+ print *, 'Assigning output neuron to a pointer using get_output_neuron()...'
+ dummy_p => con%get_output_neuron()
+ print *, 'Assignment was successful.'
+
+ print *, 'Testing method get_state() on the output neuron...'
+ if(dummy_p%get_state() == 13.7) then
+ print *, 'Test was successful.'
+ else
+ print *, 'ERROR using method get_state() on the output neuron!'
+ stop -1
+ end if
+
+ print *, 'Assigning the value input*weight to the output neuron using method pass_signal()...'
+ call con%pass_signal()
+ print *, 'Retrieving state of the output neuron and testing the value...'
+ if(dummy_p%get_state() == 133.125) then
+ print *, 'Test was successful.'
+ else
+ print *, 'ERROR using method pass_signal()!'
+ stop -1
+ end if
+
+ print *, '+-------------------------------------------------------------+'
+ print *, '| ALL TESTS OF THE MODULE CONNECTION_M WERE RUN SUCCESSFULLY. |'
+ print *, '+-------------------------------------------------------------+'
+end program connection_test
diff --git a/4neuro/src/neuron_dummy_m.f90 b/4neuro/src/neuron_dummy_m.f90
new file mode 100644
index 00000000..63c6a076
--- /dev/null
+++ b/4neuro/src/neuron_dummy_m.f90
@@ -0,0 +1,39 @@
+module neuron_dummy_m
+ implicit none
+
+ public
+
+ ! TODO smazat
+ !> neuron class
+ type :: neuron_t
+ real :: state
+
+ contains
+ procedure :: get_state => get_state_impl
+ procedure :: set_state => set_state_impl
+ end type neuron_t
+
+ contains
+
+ !--------------!
+ ! class neuron_t !
+ !--------------!
+ ! TODO smazat
+ function get_state_impl(this) result(state)
+ class(neuron_t), intent(in) :: this
+ real :: state
+
+ state = this%state
+ end function get_state_impl
+
+ ! TODO smazat
+ subroutine set_state_impl(this, new_state)
+ class(neuron_t), target :: this
+ real, intent(in) :: new_state
+
+ this%state = new_state
+ end subroutine set_state_impl
+
+
+
+end module
--
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