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Johann Dreo 2011-01-27 11:36:55 +01:00
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# ignore html files
*.html
# ignore all textual files
*.txt
# ignore object and archive files
*.[oa]
# ignore auto-saved files
*~
\#*\#
# excepted these manually configured files
!CMakeLists.txt
!README.txt
!application/
!build/
!doc/
!lib/
!src/
!test/
build/

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The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
Authors:
N:Johann Dréo
P:nojhan
E:johann.dreo@thalesgroup.com
D:2010-07-01
C:original design and code
N:Caner Candan
P:
E:caner.candan@thalesgroup.com
D:2010-07-01
C:original design and code
As of 2011-01-25, Thales SA disclaims all copyright interest in the Evolving Distribution Objects (EDO) framework.

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######################################################################################
### 1) Set the application properties
######################################################################################
# Checks cmake version compatibility
CMAKE_MINIMUM_REQUIRED(VERSION 2.6)
PROJECT(EDO)
SET(PROJECT_VERSION_MAJOR 1)
SET(PROJECT_VERSION_MINOR 0)
SET(PROJECT_VERSION_PATCH 0)
SET(PROJECT_VERSION "${PROJECT_VERSION_MAJOR}.${PROJECT_VERSION_MINOR}.${PROJECT_VERSION_PATCH}")
######################################################################################
######################################################################################
### 2) Include useful features
######################################################################################
INCLUDE(FindDoxygen)
INCLUDE(FindPkgConfig)
PKG_CHECK_MODULES(EO eo REQUIRED)
PKG_CHECK_MODULES(MO mo REQUIRED)
FIND_PACKAGE(Boost 1.33.0)
INCLUDE_DIRECTORIES(
${EO_INCLUDE_DIRS}
${MO_INCLUDE_DIRS}
${Boost_INCLUDE_DIRS}
# /Dev/ometah-0.3/common
)
######################################################################################
######################################################################################
### 3) Include header files path
######################################################################################
INCLUDE_DIRECTORIES(
${CMAKE_CURRENT_SOURCE_DIR}/src
)
######################################################################################
######################################################################################
### 4) Set compiler definitions
######################################################################################
IF(UNIX)
# enable warnings
ADD_DEFINITIONS( -Wall -W -Wextra )
# ADD_DEFINITIONS( -Weffc++)
# ADD_DEFINITIONS( -g3 )
ENDIF()
######################################################################################
######################################################################################
### 5) Prepare some variables for CMAKE usage
######################################################################################
SET(SAMPLE_SRCS)
######################################################################################
######################################################################################
### 6) Now where we go ?
######################################################################################
ADD_SUBDIRECTORY(src)
ADD_SUBDIRECTORY(application)
ADD_SUBDIRECTORY(test)
ADD_SUBDIRECTORY(doc)
######################################################################################
######################################################################################
### 7) Create executable, link libraries and prepare target
######################################################################################
SET(LIBRARY_OUTPUT_PATH ${CMAKE_BINARY_DIR}/lib)
LINK_DIRECTORIES(${LIBRARY_OUTPUT_PATH})
ADD_LIBRARY(edo STATIC ${SAMPLE_SRCS})
INSTALL(TARGETS edo ARCHIVE DESTINATION lib COMPONENT libraries)
######################################################################################
######################################################################################
### 8) Install pkg-config config file for EO
######################################################################################
INSTALL(FILES edo.pc DESTINATION lib/pkgconfig COMPONENT headers)
######################################################################################
######################################################################################
### 9) Include packaging
######################################################################################
INCLUDE(Packaging.cmake)
######################################################################################

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######################################################################################
### 1) Check dependencies
######################################################################################
IF (NOT DEFINED PROJECT_NAME OR
NOT DEFINED PROJECT_VERSION_MAJOR OR
NOT DEFINED PROJECT_VERSION_MINOR OR
NOT DEFINED PROJECT_VERSION_PATCH OR
NOT DEFINED PROJECT_VERSION)
MESSAGE(FATAL_ERROR "Be sure you have defined PROJECT_NAME and PROJECT_VERSION*.")
ENDIF()
######################################################################################
######################################################################################
### 2) Set up components
######################################################################################
SET(CPACK_COMPONENTS_ALL libraries)
SET(CPACK_ALL_INSTALL_TYPES Full)
SET(CPACK_COMPONENT_LIBRARIES_DISPLAY_NAME "Distribution Objects")
SET(CPACK_COMPONENT_LIBRARIES_DESCRIPTION "Distribution Objects library")
SET(CPACK_COMPONENT_LIBRARIES_GROUP "Devel")
SET(CPACK_COMPONENT_LIBRARIES_INSTALL_TYPES Full)
######################################################################################
######################################################################################
### 3) Set up general information about packaging
######################################################################################
# For more details: http://www.cmake.org/Wiki/CMake:Component_Install_With_CPack
#cpack package information
SET(CPACK_PACKAGE_DESCRIPTION_FILE "${CMAKE_CURRENT_SOURCE_DIR}/README")
SET(CPACK_PACKAGE_DESCRIPTION "Distribution Objects")
SET(CPACK_RESOURCE_FILE_LICENSE "${CMAKE_CURRENT_SOURCE_DIR}/COPYING")
SET(CPACK_PACKAGE_DESCRIPTION_SUMMARY "Distribution Objects")
SET(CPACK_PACKAGE_VENDOR "Thales")
SET(CPACK_PACKAGE_CONTACT "caner.candan@thalesgroup.com")
SET(CPACK_PACKAGE_VERSION ${PROJECT_VERSION})
SET(CPACK_STRIP_FILES ${PROJECT_NAME})
SET(CPACK_SOURCE_STRIP_FILES "bin/${PROJECT_NAME}")
SET(CPACK_PACKAGE_EXECUTABLES "${PROJECT_NAME}" "${PROJECT_NAME}")
SET(CPACK_PACKAGE_VERSION_MAJOR "${PROJECT_VERSION_MAJOR}")
SET(CPACK_PACKAGE_VERSION_MINOR "${PROJECT_VERSION_MINOR}")
SET(CPACK_PACKAGE_VERSION_PATCH "${PROJECT_VERSION_PATCH}")
SET(CPACK_PACKAGE_INSTALL_DIRECTORY "${PROJECT_NAME} ${PROJECT_VERSION_MAJOR}.${PROJECT_VERSION_MINOR}")
######################################################################################
######################################################################################
### 4) Set up debian packaging information
######################################################################################
SET(CPACK_DEBIAN_PACKAGE_DEPENDS "libstdc++6, libgcc1, libc6, libxml2, libmpich2-1.2, eo, mo")
SET(CPACK_DEBIAN_PACKAGE_SECTION "devel")
SET(CPACK_DEBIAN_PACKAGE_PRIORITY "optional")
######################################################################################
######################################################################################
### 5) And finally, include cpack, this is the last thing to do.
######################################################################################
INCLUDE(CPack)
######################################################################################

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This package contains the source code for EDO.
# Step 1 - Configuration
------------------------
Rename the "install.cmake-dist" file as "install.cmake" and edit it, inserting the FULL PATH
to your ParadisEO distribution.
On Windows write your path with double antislash (ex: C:\\Users\\...)
# Step 2 - Build process
------------------------
ParadisEO is assumed to be compiled. To download ParadisEO, please visit http://paradiseo.gforge.inria.fr/.
Go to the DO/build/ directory and lunch cmake:
(Unix) > cmake ..
(Windows) > cmake .. -G"Visual Studio 9 2008"
Note for windows users: if you don't use VisualStudio 9, enter the name of your generator instead of "VisualStudio 9 2008".
# Step 3 - Compilation
----------------------
In the edo/build/ directory:
(Unix) > make
(Windows) Open the VisualStudio solution and compile it, compile also the target install.
You can refer to this tutorial if you don't know how to compile a solution: http://paradiseo.gforge.inria.fr/index.php?n=Paradiseo.VisualCTutorial
# Step 4 - Execution
---------------------
A toy example is given to test the components. You can run these tests as following.
To define problem-related components for your own problem, please refer to the tutorials available on the website : http://paradiseo.gforge.inria.fr/.
In the edo/build/ directory:
(Unix) > ctest
Windows users, please refer to this tutorial: http://paradiseo.gforge.inria.fr/index.php?n=Paradiseo.VisualCTutorial
In the directory "application", there are several directory such as eda_sa which instantiate EDA-SA solver.
(Unix) After compilation you can run the binary "build/eda_sa" and see results. Parameters can be modified from command line.
(Windows) Add argument "eda_sa.param" and execute the corresponding algorithms.
Windows users, please refer to this tutorial: http://paradiseo.gforge.inria.fr/index.php?n=Paradiseo.VisualCTutorial
# Documentation
---------------
The API-documentation is available in doc/html/index.html
# Things to keep in mind when using EDO
----------------------------------------
* By default, the EO random generator's seed is initialized by the number of seconds since the epoch (with time(0)). It is available in the status file dumped at each execution. Please, keep in mind that if you start two run at the same second without modifying the seed, you will get exactly the same results.
* Execution times are measured with the boost:timer, that measure wallclock time. Additionaly, it could not measure times larger than approximatively 596.5 hours (or even less). See http://www.boost.org/doc/libs/1_33_1/libs/timer/timer.htm
* The q-quantile computation use averaging at discontinuities (in R, it correspond to the R-2 method, in SAS, SAS-5). For more explanations, see http://en.wikipedia.org/wiki/Quantile#Estimating_the_quantiles_of_a_population and http://stat.ethz.ch/R-manual/R-devel/library/stats/html/quantile.html
* You can send a SIGUSR1 to a process to get some information (written down in the log file) on the current state of the search.

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######################################################################################
### 1) Where do we go now ?!?
######################################################################################
INCLUDE_DIRECTORIES(
${CMAKE_CURRENT_SOURCE_DIR}/common
)
ADD_SUBDIRECTORY(common)
ADD_SUBDIRECTORY(eda_sa)
ADD_SUBDIRECTORY(eda)
#ADD_SUBDIRECTORY(sa)
######################################################################################

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PROJECT(common)
SET(RESOURCES
gplot.py
ggobi.py
boxplot_eda_n_edasa.py
)
FOREACH(file ${RESOURCES})
EXECUTE_PROCESS(
COMMAND ${CMAKE_COMMAND} -E copy_if_different
${CMAKE_CURRENT_SOURCE_DIR}/${file}
${DO_BINARY_DIR}/${file}
)
ENDFOREACH(file)

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#ifndef _Rosenbrock_h
#define _Rosenbrock_h
#include <eo>
#include <es.h>
#include <es/eoRealInitBounded.h>
#include <es/eoRealOp.h>
#include <es/eoEsChromInit.h>
#include <es/eoRealOp.h>
#include <es/make_real.h>
#include <apply.h>
#include <eoProportionalCombinedOp.h>
template < typename EOT >
class Rosenbrock : public eoEvalFunc< EOT >
{
public:
typedef typename EOT::AtomType AtomType;
virtual void operator()( EOT& p )
{
if (!p.invalid())
return;
p.fitness( _evaluate( p ) );
}
private:
AtomType _evaluate( EOT& p )
{
AtomType r = 0.0;
for (unsigned int i = 0; i < p.size() - 1; ++i)
{
r += p[i] * p[i];
}
return r;
}
};
#endif // !_Rosenbrock_h

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#ifndef _Sphere_h
#define _Sphere_h
#include <eo>
#include <es.h>
#include <es/eoRealInitBounded.h>
#include <es/eoRealOp.h>
#include <es/eoEsChromInit.h>
#include <es/eoRealOp.h>
#include <es/make_real.h>
#include <apply.h>
#include <eoProportionalCombinedOp.h>
template < typename EOT >
class Sphere : public eoEvalFunc< EOT >
{
public:
typedef typename EOT::AtomType AtomType;
virtual void operator()( EOT& p )
{
if (!p.invalid())
return;
p.fitness( _evaluate( p ) );
}
private:
AtomType _evaluate( EOT& p )
{
AtomType r = 0.0;
for (unsigned int i = 0; i < p.size() - 1; ++i)
{
r += p[i] * p[i];
}
return r;
}
};
#endif // !_Sphere_h

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#!/usr/bin/env python
from pylab import *
#from pprint import pprint
FILE_LOCATIONS = 'EDA_ResPop/list_of_files.txt'
data = []
locations = [ line.split()[0] for line in open( FILE_LOCATIONS ) ]
#pprint( locations )
for cur_file in locations:
fitnesses = [ float(line.split()[0]) for line in open( cur_file ).readlines()[1:-1] ]
data.append( fitnesses[1:] )
#pprint( data )
boxplot( data )
# FILE_LOCATIONS = 'EDASA_ResPop/list_of_files.txt'
# data = []
# locations = [ line.split()[0] for line in open( FILE_LOCATIONS ) ]
# #pprint( locations )
# for cur_file in locations:
# fitnesses = [ float(line.split()[0]) for line in open( cur_file ).readlines()[1:-1] ]
# data.append( fitnesses[1:] )
# #pprint( data )
# boxplot( data )
show()

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#!/usr/bin/env python
from pprint import *
import sys, os
if __name__ == '__main__':
# parameter phase
if len(sys.argv) < 2:
print 'Usage: %s [FILE]' % sys.argv[0]
sys.exit()
filename = sys.argv[1]
lines = open(filename).readlines()
# formatting phase
try:
results = [ x.split() for x in lines[1:-1] ]
except IOError, e:
print 'Error: %s' % e
sys.exit()
# dimension estimating phase
popsize = int(lines[0].split()[0])
dimsize = int(results[0][1])
# printing phase
print 'popsize: %d' % popsize
print 'dimsize: %d' % dimsize
print
pprint( results )
# cvs converting phase
i = 1
for x in results:
x.insert(0, '"%d"' % i)
i += 1
header = ['""', '"fitness"', '"dimsize"']
for i in range(0, dimsize):
header.append( '"dim%d"' % i )
results.insert(0, header)
# cvs printing phase
file_results = '\n'.join( [ ','.join( x ) for x in results ] )
print
print file_results
try:
open('%s.csv' % filename, 'w').write(file_results + '\n')
except IOError, e:
print 'Error: %s' % e
sys.exit()
# ggobi plotting phase
os.system('ggobi %s.csv' % filename)

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#!/usr/bin/env python
"""plot.py -- Plot EDA-SA results file"""
import os, time, math, tempfile
import numpy
try:
import Gnuplot, Gnuplot.PlotItems, Gnuplot.funcutils
except ImportError:
# kludge in case Gnuplot hasn't been installed as a module yet:
import __init__
Gnuplot = __init__
import PlotItems
Gnuplot.PlotItems = PlotItems
import funcutils
Gnuplot.funcutils = funcutils
import optparse, logging, sys
LEVELS = {'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL}
def logger(level_name, filename='plot.log'):
logging.basicConfig(
level=logging.DEBUG,
format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',
filename=filename, filemode='a'
)
console = logging.StreamHandler()
console.setLevel(LEVELS.get(level_name, logging.NOTSET))
console.setFormatter(logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s'))
logging.getLogger('').addHandler(console)
def parser(parser=optparse.OptionParser()):
parser.add_option('-v', '--verbose', choices=LEVELS.keys(), default='warning', help='set a verbose level')
parser.add_option('-f', '--files', help='give some input sample files separated by comma (cf. gen1,gen2,...)', default='')
parser.add_option('-r', '--respop', help='define the population results containing folder', default='./ResPop')
parser.add_option('-o', '--output', help='give an output filename for logging', default='plot.log')
parser.add_option('-d', '--dimension', help='give a dimension size', default=2)
parser.add_option('-m', '--multiplot', action="store_true", help='plot all graphics in one window', dest="multiplot", default=True)
parser.add_option('-p', '--plot', action="store_false", help='plot graphics separetly, one by window', dest="multiplot")
parser.add_option('-w', '--windowid', help='give the window id you want to display, 0 means we display all ones, this option should be combined with -p', default=0)
parser.add_option('-G', '--graphicsdirectory', help='give a directory name for graphics, this option should be combined with -u', default='plot')
parser.add_option('-g', '--graphicsprefixname', help='give a prefix name for graphics, this option should be combined with -u', default='plot')
parser.add_option('-t', '--terminal', action="store_true", help='display graphics on gnuplot windows', dest="terminal", default=True)
parser.add_option('-u', '--png', action="store_false", help='display graphics on png files', dest="terminal")
options, args = parser.parse_args()
logger(options.verbose, options.output)
return options
options = parser()
def wait(str=None, prompt='Press return to show results...\n'):
if str is not None:
print str
raw_input(prompt)
def draw2DRect(min=(0,0), max=(1,1), color='black', state=None, g=None):
if g == None: g = Gnuplot.Gnuplot()
if state != None: state.append(g)
xmin, ymin = min
xmax, ymax = max
cmd = 'set arrow from %s,%s to %s,%s nohead lc rgb "%s"'
g(cmd % (xmin, ymin, xmin, ymax, color))
g(cmd % (xmin, ymax, xmax, ymax, color))
g(cmd % (xmax, ymax, xmax, ymin, color))
g(cmd % (xmax, ymin, xmin, ymin, color))
return g
def draw3DRect(min=(0,0,0), max=(1,1,1), state=None, g=None):
if g == None: g = Gnuplot.Gnuplot()
if state != None: state.append(g)
# TODO
return g
def getSortedFiles(path):
assert path != None
if options.files == '':
filelist = os.listdir(path)
filelist.sort()
else:
filelist = options.files.split(',')
checkFileErrors(path, filelist)
return filelist
def checkFileErrors(path, filelist):
for filename in filelist:
for line in open('%s/%s' % (path, filename)):
if '-nan' in line:
logging.warning("checkFileErrors: %s/%s file contains bad value, it is going to be skipped" % (path, filename))
filelist.remove(filename)
break
def plotXPointYFitness(path, fields='3:1', state=None, g=None):
if g == None:
g = Gnuplot.Gnuplot()
if not options.terminal:
g('set terminal png')
g('set output \'%s/%s_%s.png\'' % (options.graphicsdirectory, options.graphicsprefixname, 'plotXPointYFitness'))
if state != None: state.append(g)
g.title('Fitness observation')
g.xlabel('Coordinates')
g.ylabel('Fitness (Quality)')
files=[]
for filename in getSortedFiles(path):
files.append(Gnuplot.File(path + '/' + filename, using=fields,
with_='points',
#title='distribution \'' + filename + '\''
title=""
)
)
if len(files) > 0:
g.plot(*files)
return g
def plotXYPointZFitness(path, fields='4:3:1', state=None, g=None):
if g == None:
g = Gnuplot.Gnuplot()
if not options.terminal:
g('set terminal png')
g('set output \'%s/%s_%s.png\'' % (options.graphicsdirectory, options.graphicsprefixname, 'plotXYPointZFitness'))
if state != None: state.append(g)
g.title('Fitness observation in 3-D')
g.xlabel('x-axes')
g.ylabel('y-axes')
g.zlabel('Fitness (Quality)')
files=[]
for filename in getSortedFiles(path):
files.append(Gnuplot.File(path + '/' + filename, using=fields,
with_='points',
#title='distribution \'' + filename + '\''
title=""
)
)
if len(files) > 0:
g.splot(*files)
return g
def plotXYPoint(path, fields='3:4', state=None, g=None):
if g == None:
g = Gnuplot.Gnuplot()
if not options.terminal:
g('set terminal png')
g('set output \'%s/%s_%s.png\'' % (options.graphicsdirectory, options.graphicsprefixname, 'plotXYPoint'))
if state != None: state.append(g)
g.title('Points observation in 2-D')
g.xlabel('x-axes')
g.ylabel('y-axes')
files=[]
for filename in getSortedFiles(path):
files.append(Gnuplot.File(path + '/' + filename, using=fields,
with_='points',
#title='distribution \'' + filename + '\''
title=""
)
)
if len(files) > 0:
g.plot(*files)
return g
def plotXYZPoint(path, fields='3:4:5', state=None, g=None):
if g == None:
g = Gnuplot.Gnuplot()
if not options.terminal:
g('set terminal png')
g('set output \'%s/%s_%s.png\'' % (options.graphicsdirectory, options.graphicsprefixname, 'plotXYZPoint'))
if state != None: state.append(g)
g.title('Points observation in 3-D')
g.xlabel('x-axes')
g.ylabel('y-axes')
g.zlabel('z-axes')
files=[]
for filename in getSortedFiles(path):
files.append(Gnuplot.File(path + '/' + filename, using=fields,
with_='points',
#title='distribution \'' + filename + '\''
title=""
)
)
if len(files) > 0:
g.splot(*files)
return g
def plotParams(path, field='1', state=None, g=None):
if g == None:
g = Gnuplot.Gnuplot()
if not options.terminal:
g('set terminal png')
g('set output \'%s/%s_%s.png\'' % (options.graphicsdirectory, options.graphicsprefixname, 'plotXYZPoint'))
if state != None: state.append(g)
g.title('Hyper-volume comparaison through all dimensions')
g.xlabel('Iterations')
g.ylabel('Hyper-volume')
g.plot(Gnuplot.File(path, with_='lines', using=field,
title='multivariate distribution narrowing'))
return g
def plot2DRectFromFiles(path, state=None, g=None, plot=True):
if g == None:
g = Gnuplot.Gnuplot()
if not options.terminal:
g('set terminal png')
g('set output \'%s_%s.png\'' % (options.graphicsprefixname, 'plot2DRectFromFiles'))
if state != None: state.append(g)
g.title('Rectangle drawing observation')
g.xlabel('x-axes')
g.ylabel('y-axes')
x1,x2,y1,y2 = 0,0,0,0
colors = ['red', 'orange', 'blue', 'green', 'gold', 'yellow', 'gray']
#colors = open('rgb.txt', 'r').readlines()
colors_size = len(colors)
i = 0 # for color
for filename in getSortedFiles(path):
line = open(path + '/' + filename, 'r').readline()
fields = line.split(' ')
if not fields[0] == '2':
print 'plot2DRectFromFiles: higher than 2 dimensions not possible to draw'
return
xmin,ymin,xmax,ymax = fields[1:5]
#print xmin,ymin,xmax,ymax
cur_color = colors[i % colors_size]
draw2DRect((xmin,ymin), (xmax,ymax), cur_color, g=g)
g('set obj rect from %s,%s to %s,%s back lw 1.0 fc rgb "%s" fillstyle solid 1.00 border -1'
% (xmin,ymin,xmax,ymax,cur_color)
)
if plot:
if float(xmin) < x1: x1 = float(xmin)
if float(ymin) < y1: y1 = float(ymin)
if float(xmax) > x2: x2 = float(xmax)
if float(ymax) > y2: y2 = float(ymax)
#print x1,y1,x2,y2
i += 1
#print x1,y1,x2,y2
if plot:
g.plot('[%s:%s][%s:%s] -9999 notitle' % (x1, x2, y1, y2))
return g
def main():
gstate = []
n = int(options.dimension)
w = int(options.windowid)
r = options.respop
if not options.terminal:
try:
os.mkdir(options.graphicsdirectory)
except OSError:
pass
if options.multiplot:
g = Gnuplot.Gnuplot()
if not options.terminal:
g('set terminal png')
g('set output \'%s/%s_%s.png\'' % (options.graphicsdirectory, options.graphicsprefixname, 'multiplot'))
g('set parametric')
g('set nokey')
g('set noxtic')
g('set noytic')
g('set noztic')
g('set size 1.0, 1.0')
g('set origin 0.0, 0.0')
g('set multiplot')
g('set size 0.5, 0.5')
g('set origin 0.0, 0.5')
if n >= 1:
plotXPointYFitness(r, state=gstate, g=g)
g('set size 0.5, 0.5')
g('set origin 0.0, 0.0')
if n >= 2:
plotXPointYFitness(r, '4:1', state=gstate, g=g)
g('set size 0.5, 0.5')
g('set origin 0.5, 0.5')
if n >= 2:
plotXYPointZFitness(r, state=gstate, g=g)
g('set size 0.5, 0.5')
g('set origin 0.5, 0.0')
if n >= 2:
plotXYPoint(r, state=gstate, g=g)
elif n >= 3:
plotXYZPoint(r, state=gstate, g=g)
g('set nomultiplot')
else:
if n >= 1 and w in [0, 1]:
plotXPointYFitness(r, state=gstate)
if n >= 2 and w in [0, 2]:
plotXPointYFitness(r, '4:1', state=gstate)
if n >= 2 and w in [0, 3]:
plotXYPointZFitness(r, state=gstate)
if n >= 3 and w in [0, 4]:
plotXYZPoint(r, state=gstate)
if n >= 2 and w in [0, 5]:
plotXYPoint(r, state=gstate)
# if n >= 1:
# plotParams('./ResParams.txt', state=gstate)
# if n >= 2:
# plot2DRectFromFiles('./ResBounds', state=gstate)
# plotXYPoint(r, state=gstate)
# g = plot2DRectFromFiles('./ResBounds', state=gstate, plot=False)
# plotXYPoint(r, g=g)
if options.terminal:
wait(prompt='Press return to end the plot.\n')
# when executed, just run main():
if __name__ == '__main__':
logging.debug('### plotting started ###')
main()
logging.debug('### plotting ended ###')

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PROJECT(eda)
FIND_PACKAGE(Boost 1.33.0)
INCLUDE_DIRECTORIES(${CMAKE_CURRENT_SOURCE_DIR})
INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS})
LINK_DIRECTORIES(${Boost_LIBRARY_DIRS})
SET(RESOURCES
${PROJECT_NAME}.param
)
FOREACH(file ${RESOURCES})
EXECUTE_PROCESS(
COMMAND ${CMAKE_COMMAND} -E copy_if_different
${CMAKE_CURRENT_SOURCE_DIR}/${file}
${EDO_BINARY_DIR}/${file}
)
ENDFOREACH(file)
FILE(GLOB SOURCES *.cpp)
SET(EXECUTABLE_OUTPUT_PATH ${EDO_BINARY_DIR})
ADD_EXECUTABLE(${PROJECT_NAME} ${SOURCES})
TARGET_LINK_LIBRARIES(${PROJECT_NAME} edo edoutils ${EO_LIBRARIES} ${MO_LIBRARIES} ${Boost_LIBRARIES})

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--rho=0 # -p : <etropolis sample size
--alpha=0 # -a : Temperature dicrease rate
--threshold=0.1 # -t : Temperature threshold stopping criteria
--sample-size=10 # -P : Sample size
--dimension-size=10 # -d : Dimension size
--temperature=100 # -T : Initial temperature
#--verbose # Enable verbose mode

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#include <eo>
#include <mo>
#include <utils/eoLogger.h>
#include <utils/eoParserLogger.h>
#include <eoEvalFuncCounterBounder.h>
#include <do/make_pop.h>
#include <do/make_run.h>
#include <do/make_continue.h>
#include <do/make_checkpoint.h>
#include <edo>
#include "Rosenbrock.h"
#include "Sphere.h"
typedef eoReal<eoMinimizingFitness> EOT;
typedef edoNormalMulti< EOT > Distrib;
int main(int ac, char** av)
{
eoParserLogger parser(ac, av);
// Letters used by the following declarations:
// a d i p t
std::string section("Algorithm parameters");
// FIXME: default value to check
//double initial_temperature = parser.createParam((double)10e5, "temperature", "Initial temperature", 'i', section).value(); // i
eoState state;
//-----------------------------------------------------------------------------
// Instantiate all needed parameters for EDA algorithm
//-----------------------------------------------------------------------------
double selection_rate = parser.createParam((double)0.5, "selection_rate", "Selection Rate", 'R', section).value(); // R
eoSelect< EOT >* selector = new eoDetSelect< EOT >( selection_rate );
state.storeFunctor(selector);
edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >();
state.storeFunctor(estimator);
eoSelectOne< EOT >* selectone = new eoDetTournamentSelect< EOT >( 2 );
state.storeFunctor(selectone);
edoModifierMass< Distrib >* modifier = new edoNormalMultiCenter< EOT >();
state.storeFunctor(modifier);
eoEvalFunc< EOT >* plainEval = new Rosenbrock< EOT >();
state.storeFunctor(plainEval);
unsigned long max_eval = parser.getORcreateParam((unsigned long)0, "maxEval", "Maximum number of evaluations (0 = none)", 'E', "Stopping criterion").value(); // E
eoEvalFuncCounterBounder< EOT > eval(*plainEval, max_eval);
eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5);
state.storeFunctor(gen);
unsigned int dimension_size = parser.createParam((unsigned int)10, "dimension-size", "Dimension size", 'd', section).value(); // d
eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( dimension_size, *gen );
state.storeFunctor(init);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (1) Population init and sampler
//-----------------------------------------------------------------------------
// Generation of population from do_make_pop (creates parameters, manages persistance and so on...)
// ... and creates the parameters: L P r S
// this first sampler creates a uniform distribution independently from our distribution (it does not use doUniform).
eoPop< EOT >& pop = do_make_pop(parser, state, *init);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (2) First evaluation before starting the research algorithm
//-----------------------------------------------------------------------------
apply(eval, pop);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare bounder class to set bounds of sampling.
// This is used by doSampler.
//-----------------------------------------------------------------------------
edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5),
EOT(pop[0].size(), 5),
*gen);
state.storeFunctor(bounder);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare sampler class with a specific distribution
//-----------------------------------------------------------------------------
edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder );
state.storeFunctor(sampler);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Metropolis sample parameters
//-----------------------------------------------------------------------------
//unsigned int popSize = parser.getORcreateParam((unsigned int)20, "popSize", "Population Size", 'P', "Evolution Engine").value();
//moContinuator< moDummyNeighbor<EOT> >* sa_continue = new moIterContinuator< moDummyNeighbor<EOT> >( popSize );
//state.storeFunctor(sa_continue);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// SA parameters
//-----------------------------------------------------------------------------
//double threshold_temperature = parser.createParam((double)0.1, "threshold", "Minimal temperature at which stop", 't', section).value(); // t
//double alpha = parser.createParam((double)0.1, "alpha", "Temperature decrease rate", 'a', section).value(); // a
//moCoolingSchedule<EOT>* cooling_schedule = new moSimpleCoolingSchedule<EOT>(initial_temperature, alpha, 0, threshold_temperature);
//state.storeFunctor(cooling_schedule);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// stopping criteria
// ... and creates the parameter letters: C E g G s T
//-----------------------------------------------------------------------------
eoContinue< EOT >& eo_continue = do_make_continue(parser, state, eval);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// population output
//-----------------------------------------------------------------------------
eoCheckPoint< EOT >& pop_continue = do_make_checkpoint(parser, state, eval, eo_continue);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// distribution output
//-----------------------------------------------------------------------------
edoDummyContinue< Distrib >* dummy_continue = new edoDummyContinue< Distrib >();
state.storeFunctor(dummy_continue);
edoCheckPoint< Distrib >* distribution_continue = new edoCheckPoint< Distrib >( *dummy_continue );
state.storeFunctor(distribution_continue);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// eoEPRemplacement causes the using of the current and previous
// sample for sampling.
//-----------------------------------------------------------------------------
eoReplacement< EOT >* replacor = new eoEPReplacement< EOT >(pop.size());
// Below, use eoGenerationalReplacement to sample only on the current sample
//eoReplacement< EOT >* replacor = new eoGenerationalReplacement< EOT >(); // FIXME: to define the size
state.storeFunctor(replacor);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Some stuff to display helper when we are using -h option
//-----------------------------------------------------------------------------
if (parser.userNeedsHelp())
{
parser.printHelp(std::cout);
exit(1);
}
// Help + Verbose routines
make_verbose(parser);
make_help(parser);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// population output (after helper)
//
// FIXME: theses objects are instanciate there in order to avoid a folder
// removing as doFileSnapshot does within ctor.
//-----------------------------------------------------------------------------
edoPopStat< EOT >* popStat = new edoPopStat<EOT>;
state.storeFunctor(popStat);
pop_continue.add(*popStat);
edoFileSnapshot* fileSnapshot = new edoFileSnapshot("EDA_ResPop");
state.storeFunctor(fileSnapshot);
fileSnapshot->add(*popStat);
pop_continue.add(*fileSnapshot);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// distribution output (after helper)
//-----------------------------------------------------------------------------
edoDistribStat< Distrib >* distrib_stat = new edoStatNormalMulti< EOT >();
state.storeFunctor(distrib_stat);
distribution_continue->add( *distrib_stat );
// eoMonitor* stdout_monitor = new eoStdoutMonitor();
// state.storeFunctor(stdout_monitor);
// stdout_monitor->add(*distrib_stat);
// distribution_continue->add( *stdout_monitor );
eoFileMonitor* file_monitor = new eoFileMonitor("eda_distribution_bounds.txt");
state.storeFunctor(file_monitor);
file_monitor->add(*distrib_stat);
distribution_continue->add( *file_monitor );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// EDA algorithm configuration
//-----------------------------------------------------------------------------
edoAlgo< Distrib >* algo = new edoEDA< Distrib >
(*selector, *estimator, *selectone, *modifier, *sampler,
pop_continue, *distribution_continue,
eval,
//*sa_continue, *cooling_schedule, initial_temperature,
*replacor);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Beginning of the algorithm call
//-----------------------------------------------------------------------------
try
{
do_run(*algo, pop);
}
catch (eoEvalFuncCounterBounderException& e)
{
eo::log << eo::warnings << "warning: " << e.what() << std::endl;
}
catch (std::exception& e)
{
eo::log << eo::errors << "error: " << e.what() << std::endl;
exit(EXIT_FAILURE);
}
//-----------------------------------------------------------------------------
return 0;
}

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PROJECT(eda_sa)
FIND_PACKAGE(Boost 1.33.0)
INCLUDE_DIRECTORIES(${CMAKE_CURRENT_SOURCE_DIR})
INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS})
LINK_DIRECTORIES(${Boost_LIBRARY_DIRS})
SET(RESOURCES
${PROJECT_NAME}.param
)
FOREACH(file ${RESOURCES})
EXECUTE_PROCESS(
COMMAND ${CMAKE_COMMAND} -E copy_if_different
${CMAKE_CURRENT_SOURCE_DIR}/${file}
${EDO_BINARY_DIR}/${file}
)
ENDFOREACH(file)
FILE(GLOB SOURCES *.cpp)
SET(EXECUTABLE_OUTPUT_PATH ${EDO_BINARY_DIR})
ADD_EXECUTABLE(${PROJECT_NAME} ${SOURCES})
TARGET_LINK_LIBRARIES(${PROJECT_NAME} edo edoutils ${EO_LIBRARIES} ${MO_LIBRARIES} ${Boost_LIBRARIES})

7
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--rho=0 # -p : <etropolis sample size
--alpha=0 # -a : Temperature dicrease rate
--threshold=0.1 # -t : Temperature threshold stopping criteria
--sample-size=10 # -P : Sample size
--dimension-size=10 # -d : Dimension size
--temperature=100 # -T : Initial temperature
#--verbose # Enable verbose mode

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#include <eo>
#include <mo>
#include <utils/eoLogger.h>
#include <utils/eoParserLogger.h>
#include <eoEvalFuncCounterBounder.h>
#include <do/make_pop.h>
#include <do/make_run.h>
#include <do/make_continue.h>
#include <do/make_checkpoint.h>
#include <edo>
#include "Rosenbrock.h"
#include "Sphere.h"
typedef eoReal<eoMinimizingFitness> EOT;
typedef edoNormalMulti< EOT > Distrib;
int main(int ac, char** av)
{
eoParserLogger parser(ac, av);
// Letters used by the following declarations:
// a d i p t
std::string section("Algorithm parameters");
// FIXME: default value to check
double initial_temperature = parser.createParam((double)10e5, "temperature", "Initial temperature", 'i', section).value(); // i
eoState state;
//-----------------------------------------------------------------------------
// Instantiate all needed parameters for EDASA algorithm
//-----------------------------------------------------------------------------
double selection_rate = parser.createParam((double)0.5, "selection_rate", "Selection Rate", 'R', section).value(); // R
eoSelect< EOT >* selector = new eoDetSelect< EOT >( selection_rate );
state.storeFunctor(selector);
edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >();
state.storeFunctor(estimator);
eoSelectOne< EOT >* selectone = new eoDetTournamentSelect< EOT >( 2 );
state.storeFunctor(selectone);
edoModifierMass< Distrib >* modifier = new edoNormalMultiCenter< EOT >();
state.storeFunctor(modifier);
eoEvalFunc< EOT >* plainEval = new Rosenbrock< EOT >();
state.storeFunctor(plainEval);
unsigned long max_eval = parser.getORcreateParam((unsigned long)0, "maxEval", "Maximum number of evaluations (0 = none)", 'E', "Stopping criterion").value(); // E
eoEvalFuncCounterBounder< EOT > eval(*plainEval, max_eval);
eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5);
state.storeFunctor(gen);
unsigned int dimension_size = parser.createParam((unsigned int)10, "dimension-size", "Dimension size", 'd', section).value(); // d
eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( dimension_size, *gen );
state.storeFunctor(init);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (1) Population init and sampler
//-----------------------------------------------------------------------------
// Generation of population from do_make_pop (creates parameters, manages persistance and so on...)
// ... and creates the parameters: L P r S
// this first sampler creates a uniform distribution independently from our distribution (it does not use doUniform).
eoPop< EOT >& pop = do_make_pop(parser, state, *init);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (2) First evaluation before starting the research algorithm
//-----------------------------------------------------------------------------
apply(eval, pop);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare bounder class to set bounds of sampling.
// This is used by doSampler.
//-----------------------------------------------------------------------------
edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5),
EOT(pop[0].size(), 5),
*gen);
state.storeFunctor(bounder);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare sampler class with a specific distribution
//-----------------------------------------------------------------------------
edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder );
state.storeFunctor(sampler);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Metropolis sample parameters
//-----------------------------------------------------------------------------
unsigned int popSize = parser.getORcreateParam((unsigned int)20, "popSize", "Population Size", 'P', "Evolution Engine").value();
moContinuator< moDummyNeighbor<EOT> >* sa_continue = new moIterContinuator< moDummyNeighbor<EOT> >( popSize );
state.storeFunctor(sa_continue);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// SA parameters
//-----------------------------------------------------------------------------
double threshold_temperature = parser.createParam((double)0.1, "threshold", "Minimal temperature at which stop", 't', section).value(); // t
double alpha = parser.createParam((double)0.1, "alpha", "Temperature decrease rate", 'a', section).value(); // a
moCoolingSchedule<EOT>* cooling_schedule = new moSimpleCoolingSchedule<EOT>(initial_temperature, alpha, 0, threshold_temperature);
state.storeFunctor(cooling_schedule);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// stopping criteria
// ... and creates the parameter letters: C E g G s T
//-----------------------------------------------------------------------------
eoContinue< EOT >& eo_continue = do_make_continue(parser, state, eval);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// population output
//-----------------------------------------------------------------------------
eoCheckPoint< EOT >& pop_continue = do_make_checkpoint(parser, state, eval, eo_continue);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// distribution output
//-----------------------------------------------------------------------------
edoDummyContinue< Distrib >* dummy_continue = new edoDummyContinue< Distrib >();
state.storeFunctor(dummy_continue);
edoCheckPoint< Distrib >* distribution_continue = new edoCheckPoint< Distrib >( *dummy_continue );
state.storeFunctor(distribution_continue);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// eoEPRemplacement causes the using of the current and previous
// sample for sampling.
//-----------------------------------------------------------------------------
eoReplacement< EOT >* replacor = new eoEPReplacement< EOT >(pop.size());
// Below, use eoGenerationalReplacement to sample only on the current sample
//eoReplacement< EOT >* replacor = new eoGenerationalReplacement< EOT >(); // FIXME: to define the size
state.storeFunctor(replacor);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Some stuff to display helper when we are using -h option
//-----------------------------------------------------------------------------
if (parser.userNeedsHelp())
{
parser.printHelp(std::cout);
exit(1);
}
// Help + Verbose routines
make_verbose(parser);
make_help(parser);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// population output (after helper)
//
// FIXME: theses objects are instanciate there in order to avoid a folder
// removing as edoFileSnapshot does within ctor.
//-----------------------------------------------------------------------------
edoPopStat< EOT >* popStat = new edoPopStat<EOT>;
state.storeFunctor(popStat);
pop_continue.add(*popStat);
edoFileSnapshot* fileSnapshot = new edoFileSnapshot("EDASA_ResPop");
state.storeFunctor(fileSnapshot);
fileSnapshot->add(*popStat);
pop_continue.add(*fileSnapshot);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// distribution output (after helper)
//-----------------------------------------------------------------------------
edoDistribStat< Distrib >* distrib_stat = new edoStatNormalMulti< EOT >();
state.storeFunctor(distrib_stat);
distribution_continue->add( *distrib_stat );
// eoMonitor* stdout_monitor = new eoStdoutMonitor();
// state.storeFunctor(stdout_monitor);
// stdout_monitor->add(*distrib_stat);
// distribution_continue->add( *stdout_monitor );
eoFileMonitor* file_monitor = new eoFileMonitor("eda_sa_distribution_bounds.txt");
state.storeFunctor(file_monitor);
file_monitor->add(*distrib_stat);
distribution_continue->add( *file_monitor );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// EDASA algorithm configuration
//-----------------------------------------------------------------------------
edoAlgo< Distrib >* algo = new edoEDASA< Distrib >
(*selector, *estimator, *selectone, *modifier, *sampler,
pop_continue, *distribution_continue,
eval, *sa_continue, *cooling_schedule,
initial_temperature, *replacor);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Beginning of the algorithm call
//-----------------------------------------------------------------------------
try
{
do_run(*algo, pop);
}
catch (eoEvalFuncCounterBounderException& e)
{
eo::log << eo::warnings << "warning: " << e.what() << std::endl;
}
catch (std::exception& e)
{
eo::log << eo::errors << "error: " << e.what() << std::endl;
exit(EXIT_FAILURE);
}
//-----------------------------------------------------------------------------
return 0;
}

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#!/usr/bin/env sh
mkdir -p debug
cd debug
cmake -DCMAKE_BUILD_TYPE=Debug ..
make
cd ..

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#!/usr/bin/env sh
mkdir -p release
cd release
cmake ..
make
cd ..

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distclean Executable file
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#!/usr/bin/env sh
rm -rf debug
rm -rf release

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#######################################################################################
### Doc generation using Doxygen
#######################################################################################
IF (DOXYGEN_FOUND)
SET(DOC_DIR ${CMAKE_BINARY_DIR}/doc CACHE PATH "documentation directory")
SET(DOC_CONFIG_FILE "doxyfile" CACHE PATH "documentation configuration file")
# define the doc target
IF (DOXYGEN_EXECUTABLE)
ADD_CUSTOM_TARGET(doc
COMMAND ${DOXYGEN_EXECUTABLE} ${DOC_CONFIG_FILE}
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
)
ENDIF (DOXYGEN_EXECUTABLE)
# configure doxyfile file
CONFIGURE_FILE(
"${CMAKE_CURRENT_SOURCE_DIR}/${DOC_CONFIG_FILE}.cmake"
"${CMAKE_CURRENT_BINARY_DIR}/${DOC_CONFIG_FILE}"
)
INSTALL(
DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
DESTINATION share/edo COMPONENT libraries
PATTERN "CMakeFiles" EXCLUDE
PATTERN "cmake_install.cmake" EXCLUDE
PATTERN "Makefile" EXCLUDE
PATTERN "doxyfile" EXCLUDE
)
ELSE (DOXYGEN_FOUND)
MESSAGE(STATUS "Unable to generate the documentation, Doxygen package not found")
ENDIF (DOXYGEN_FOUND)
#######################################################################################

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File diff suppressed because it is too large Load diff

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edo.pc Normal file
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# Package Information for pkg-config
prefix=/usr
exec_prefix=${prefix}
libdir=${exec_prefix}/lib
includedir=${prefix}/include/edo
Name: Evolving Distribution Objects
Description: Evolving Distribution Objects
Version: 1.0
Libs: -L${libdir} -ledo -ledoutils
Cflags: -I${includedir}

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#!/usr/bin/env sh
cd release
cpack -G DEB
cd ..

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package_rpm Executable file
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@ -0,0 +1,5 @@
#!/usr/bin/env sh
cd release
cpack -G RPM
cd ..

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######################################################################################
### 1) Set all needed source files for the project
######################################################################################
FILE(GLOB HDRS *.h edo)
INSTALL(FILES ${HDRS} DESTINATION include/edo COMPONENT headers)
FILE(GLOB SOURCES *.cpp)
SET(SAMPLE_SRCS ${SOURCES} PARENT_SCOPE)
######################################################################################
######################################################################################
### 2) Where must cmake go now ?
######################################################################################
ADD_SUBDIRECTORY(utils)
######################################################################################

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edo_
#define _edo_
#include "edoAlgo.h"
#include "edoEDASA.h"
#include "edoEDA.h"
#include "edoDistrib.h"
#include "edoUniform.h"
#include "edoNormalMono.h"
#include "edoNormalMulti.h"
#include "edoEstimator.h"
#include "edoEstimatorUniform.h"
#include "edoEstimatorNormalMono.h"
#include "edoEstimatorNormalMulti.h"
#include "edoModifier.h"
#include "edoModifierDispersion.h"
#include "edoModifierMass.h"
#include "edoUniformCenter.h"
#include "edoNormalMonoCenter.h"
#include "edoNormalMultiCenter.h"
#include "edoSampler.h"
#include "edoSamplerUniform.h"
#include "edoSamplerNormalMono.h"
#include "edoSamplerNormalMulti.h"
#include "edoVectorBounds.h"
#include "edoBounder.h"
#include "edoBounderNo.h"
#include "edoBounderBound.h"
#include "edoBounderRng.h"
#include "edoContinue.h"
#include "utils/edoCheckPoint.h"
#include "utils/edoStat.h"
#include "utils/edoStatUniform.h"
#include "utils/edoStatNormalMono.h"
#include "utils/edoStatNormalMulti.h"
#include "utils/edoFileSnapshot.h"
#include "utils/edoPopStat.h"
#endif // !_edo_
// Local Variables:
// mode: C++
// End:

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Caner Candan <caner.candan@thalesgroup.com>
*/
#include "edo"

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoAlgo_h
#define _edoAlgo_h
#include <eoAlgo.h>
template < typename D >
class edoAlgo : public eoAlgo< typename D::EOType >
{
//! Alias for the type
typedef typename D::EOType EOT;
public:
virtual ~edoAlgo(){}
};
#endif // !_edoAlgo_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoBounder_h
#define _edoBounder_h
#include <eoFunctor.h>
template < typename EOT >
class edoBounder : public eoUF< EOT&, void >
{
public:
edoBounder( EOT min = EOT(1, 0), EOT max = EOT(1, 0) )
: _min(min), _max(max)
{
assert(_min.size() > 0);
assert(_min.size() == _max.size());
}
// virtual void operator()( EOT& ) = 0 (provided by eoUF< A1, R >)
EOT& min(){return _min;}
EOT& max(){return _max;}
private:
EOT _min;
EOT _max;
};
#endif // !_edoBounder_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoBounderBound_h
#define _edoBounderBound_h
#include "edoBounder.h"
template < typename EOT >
class edoBounderBound : public edoBounder< EOT >
{
public:
edoBounderBound( EOT min, EOT max )
: edoBounder< EOT >( min, max )
{}
void operator()( EOT& x )
{
unsigned int size = x.size();
assert(size > 0);
for (unsigned int d = 0; d < size; ++d) // browse all dimensions
{
if (x[d] < this->min()[d])
{
x[d] = this->min()[d];
continue;
}
if (x[d] > this->max()[d])
{
x[d] = this->max()[d];
}
}
}
};
#endif // !_edoBounderBound_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoBounderNo_h
#define _edoBounderNo_h
#include "edoBounder.h"
template < typename EOT >
class edoBounderNo : public edoBounder< EOT >
{
public:
void operator()( EOT& ) {}
};
#endif // !_edoBounderNo_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoBounderRng_h
#define _edoBounderRng_h
#include "edoBounder.h"
template < typename EOT >
class edoBounderRng : public edoBounder< EOT >
{
public:
edoBounderRng( EOT min, EOT max, eoRndGenerator< double > & rng )
: edoBounder< EOT >( min, max ), _rng(rng)
{}
void operator()( EOT& x )
{
unsigned int size = x.size();
assert(size > 0);
for (unsigned int d = 0; d < size; ++d) // browse all dimensions
{
// FIXME: attention: les bornes RNG ont les memes bornes quelque soit les dimensions idealement on voudrait avoir des bornes differentes pour chaque dimensions.
if (x[d] < this->min()[d] || x[d] > this->max()[d])
{
x[d] = _rng();
}
}
}
private:
eoRndGenerator< double> & _rng;
};
#endif // !_edoBounderRng_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
*/
#ifndef _edoBounderUniform_h
#define _edoBounderUniform_h
#include "edoBounder.h"
template < typename EOT >
class edoBounderUniform : public edoBounder< EOT >
{
public:
edoBounderUniform( EOT min, EOT max )
: edoBounder< EOT >( min, max )
{}
void operator()( EOT& sol )
{
unsigned int size = sol.size();
assert(size > 0);
for (unsigned int d = 0; d < size; ++d) {
if ( sol[d] < this->min()[d] || sol[d] > this->max()[d]) {
// use EO's global "rng"
sol[d] = rng.uniform( this->min()[d], this->max()[d] );
}
} // for d in size
}
};
#endif // !_edoBounderUniform_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _doContinue_h
#define _doContinue_h
#include <eoFunctor.h>
#include <eoPersistent.h>
//! edoContinue< EOT > classe fitted to Distribution Object library
template < typename D >
class edoContinue : public eoUF< const D&, bool >, public eoPersistent
{
public:
virtual std::string className(void) const { return "edoContinue"; }
void readFrom(std::istream&)
{
/* It should be implemented by subclasses ! */
}
void printOn(std::ostream&) const
{
/* It should be implemented by subclasses ! */
}
};
template < typename D >
class edoDummyContinue : public edoContinue< D >
{
bool operator()(const D&){ return true; }
virtual std::string className() const { return "edoDummyContinue"; }
};
#endif // !_edoContinue_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoDistrib_h
#define _edoDistrib_h
#include <eoFunctor.h>
template < typename EOT >
class edoDistrib : public eoFunctorBase
{
public:
//! Alias for the type
typedef EOT EOType;
virtual ~edoDistrib(){}
};
#endif // !_edoDistrib_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoEDA_h
#define _edoEDA_h
#include <eo>
#include <mo>
#include <utils/eoRNG.h>
#include "edoAlgo.h"
#include "edoEstimator.h"
#include "edoModifierMass.h"
#include "edoSampler.h"
#include "edoContinue.h"
template < typename D >
class edoEDA : public edoAlgo< D >
{
public:
//! Alias for the type EOT
typedef typename D::EOType EOT;
//! Alias for the atom type
typedef typename EOT::AtomType AtomType;
//! Alias for the fitness
typedef typename EOT::Fitness Fitness;
public:
//! edoEDA constructor
/*!
All the boxes used by a EDASA need to be given.
\param selector Population Selector
\param estimator Distribution Estimator
\param selectone SelectOne
\param modifier Distribution Modifier
\param sampler Distribution Sampler
\param pop_continue Population Continuator
\param distribution_continue Distribution Continuator
\param evaluation Evaluation function.
\param sa_continue Stopping criterion.
\param cooling_schedule Cooling schedule, describes how the temperature is modified.
\param initial_temperature The initial temperature.
\param replacor Population replacor
*/
edoEDA (eoSelect< EOT > & selector,
edoEstimator< D > & estimator,
eoSelectOne< EOT > & selectone,
edoModifierMass< D > & modifier,
edoSampler< D > & sampler,
eoContinue< EOT > & pop_continue,
edoContinue< D > & distribution_continue,
eoEvalFunc < EOT > & evaluation,
//moContinuator< moDummyNeighbor<EOT> > & sa_continue,
//moCoolingSchedule<EOT> & cooling_schedule,
//double initial_temperature,
eoReplacement< EOT > & replacor
)
: _selector(selector),
_estimator(estimator),
_selectone(selectone),
_modifier(modifier),
_sampler(sampler),
_pop_continue(pop_continue),
_distribution_continue(distribution_continue),
_evaluation(evaluation),
//_sa_continue(sa_continue),
//_cooling_schedule(cooling_schedule),
//_initial_temperature(initial_temperature),
_replacor(replacor)
{}
//! function that launches the EDASA algorithm.
/*!
As a moTS or a moHC, the EDASA can be used for HYBRIDATION in an evolutionary algorithm.
\param pop A population to improve.
\return TRUE.
*/
void operator ()(eoPop< EOT > & pop)
{
assert(pop.size() > 0);
//double temperature = _initial_temperature;
eoPop< EOT > current_pop;
eoPop< EOT > selected_pop;
//-------------------------------------------------------------
// Estimating a first time the distribution parameter thanks
// to population.
//-------------------------------------------------------------
D distrib = _estimator(pop);
double size = distrib.size();
assert(size > 0);
//-------------------------------------------------------------
do
{
//-------------------------------------------------------------
// (3) Selection of the best points in the population
//-------------------------------------------------------------
selected_pop.clear();
_selector(pop, selected_pop);
assert( selected_pop.size() > 0 );
//-------------------------------------------------------------
//-------------------------------------------------------------
// (4) Estimation of the distribution parameters
//-------------------------------------------------------------
distrib = _estimator(selected_pop);
//-------------------------------------------------------------
// TODO: utiliser selected_pop ou pop ???
assert(selected_pop.size() > 0);
//-------------------------------------------------------------
// Init of a variable contening a point with the bestest fitnesses
//-------------------------------------------------------------
EOT current_solution = _selectone(selected_pop);
//-------------------------------------------------------------
//-------------------------------------------------------------
// Fit the current solution with the distribution parameters (bounds)
//-------------------------------------------------------------
// FIXME: si besoin de modifier la dispersion de la distribution
// _modifier_dispersion(distribution, selected_pop);
_modifier(distrib, current_solution);
//-------------------------------------------------------------
//-------------------------------------------------------------
// Evaluating a first time the current solution
//-------------------------------------------------------------
_evaluation( current_solution );
//-------------------------------------------------------------
//-------------------------------------------------------------
// Building of the sampler in current_pop
//-------------------------------------------------------------
//_sa_continue.init( current_solution );
current_pop.clear();
for ( unsigned int i = 0; i < pop.size(); ++i )
//do
{
EOT candidate_solution = _sampler(distrib);
_evaluation( candidate_solution );
// TODO: verifier le critere d'acceptation
if ( candidate_solution.fitness() < current_solution.fitness()
// || rng.uniform() < exp( ::fabs(candidate_solution.fitness() - current_solution.fitness()) / temperature )
)
{
current_pop.push_back(candidate_solution);
current_solution = candidate_solution;
}
}
//while ( _sa_continue( current_solution) );
//-------------------------------------------------------------
_replacor(pop, current_pop); // copy current_pop in pop
pop.sort();
//if ( ! _cooling_schedule( temperature ) ){ eo::log << eo::debug << "_cooling_schedule" << std::endl; break; }
if ( ! _distribution_continue( distrib ) ){ eo::log << eo::debug << "_distribution_continue" << std::endl; break; }
if ( ! _pop_continue( pop ) ){ eo::log << eo::debug << "_pop_continue" << std::endl; break; }
}
while ( 1 );
}
private:
//! A EOT selector
eoSelect < EOT > & _selector;
//! A EOT estimator. It is going to estimate distribution parameters.
edoEstimator< D > & _estimator;
//! SelectOne
eoSelectOne< EOT > & _selectone;
//! A D modifier
edoModifierMass< D > & _modifier;
//! A D sampler
edoSampler< D > & _sampler;
//! A EOT population continuator
eoContinue < EOT > & _pop_continue;
//! A D continuator
edoContinue < D > & _distribution_continue;
//! A full evaluation function.
eoEvalFunc < EOT > & _evaluation;
//! Stopping criterion before temperature update
//moContinuator< moDummyNeighbor<EOT> > & _sa_continue;
//! The cooling schedule
//moCoolingSchedule<EOT> & _cooling_schedule;
//! Initial temperature
//double _initial_temperature;
//! A EOT replacor
eoReplacement < EOT > & _replacor;
};
#endif // !_edoEDA_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoEDASA_h
#define _edoEDASA_h
#include <eo>
#include <mo>
#include <utils/eoRNG.h>
#include "edoAlgo.h"
#include "edoEstimator.h"
#include "edoModifierMass.h"
#include "edoSampler.h"
#include "edoContinue.h"
template < typename D >
class edoEDASA : public edoAlgo< D >
{
public:
//! Alias for the type EOT
typedef typename D::EOType EOT;
//! Alias for the atom type
typedef typename EOT::AtomType AtomType;
//! Alias for the fitness
typedef typename EOT::Fitness Fitness;
public:
//! edoEDASA constructor
/*!
All the boxes used by a EDASA need to be given.
\param selector Population Selector
\param estimator Distribution Estimator
\param selectone SelectOne
\param modifier Distribution Modifier
\param sampler Distribution Sampler
\param pop_continue Population Continuator
\param distribution_continue Distribution Continuator
\param evaluation Evaluation function.
\param sa_continue Stopping criterion.
\param cooling_schedule Cooling schedule, describes how the temperature is modified.
\param initial_temperature The initial temperature.
\param replacor Population replacor
*/
edoEDASA (eoSelect< EOT > & selector,
edoEstimator< D > & estimator,
eoSelectOne< EOT > & selectone,
edoModifierMass< D > & modifier,
edoSampler< D > & sampler,
eoContinue< EOT > & pop_continue,
edoContinue< D > & distribution_continue,
eoEvalFunc < EOT > & evaluation,
moContinuator< moDummyNeighbor<EOT> > & sa_continue,
moCoolingSchedule<EOT> & cooling_schedule,
double initial_temperature,
eoReplacement< EOT > & replacor
)
: _selector(selector),
_estimator(estimator),
_selectone(selectone),
_modifier(modifier),
_sampler(sampler),
_pop_continue(pop_continue),
_distribution_continue(distribution_continue),
_evaluation(evaluation),
_sa_continue(sa_continue),
_cooling_schedule(cooling_schedule),
_initial_temperature(initial_temperature),
_replacor(replacor)
{}
//! function that launches the EDASA algorithm.
/*!
As a moTS or a moHC, the EDASA can be used for HYBRIDATION in an evolutionary algorithm.
\param pop A population to improve.
\return TRUE.
*/
void operator ()(eoPop< EOT > & pop)
{
assert(pop.size() > 0);
double temperature = _initial_temperature;
eoPop< EOT > current_pop;
eoPop< EOT > selected_pop;
//-------------------------------------------------------------
// Estimating a first time the distribution parameter thanks
// to population.
//-------------------------------------------------------------
D distrib = _estimator(pop);
double size = distrib.size();
assert(size > 0);
//-------------------------------------------------------------
do
{
//-------------------------------------------------------------
// (3) Selection of the best points in the population
//-------------------------------------------------------------
selected_pop.clear();
_selector(pop, selected_pop);
assert( selected_pop.size() > 0 );
//-------------------------------------------------------------
//-------------------------------------------------------------
// (4) Estimation of the distribution parameters
//-------------------------------------------------------------
distrib = _estimator(selected_pop);
//-------------------------------------------------------------
// TODO: utiliser selected_pop ou pop ???
assert(selected_pop.size() > 0);
//-------------------------------------------------------------
// Init of a variable contening a point with the bestest fitnesses
//-------------------------------------------------------------
EOT current_solution = _selectone(selected_pop);
//-------------------------------------------------------------
//-------------------------------------------------------------
// Fit the current solution with the distribution parameters (bounds)
//-------------------------------------------------------------
// FIXME: si besoin de modifier la dispersion de la distribution
// _modifier_dispersion(distribution, selected_pop);
_modifier(distrib, current_solution);
//-------------------------------------------------------------
//-------------------------------------------------------------
// Evaluating a first time the current solution
//-------------------------------------------------------------
_evaluation( current_solution );
//-------------------------------------------------------------
//-------------------------------------------------------------
// Building of the sampler in current_pop
//-------------------------------------------------------------
_sa_continue.init( current_solution );
current_pop.clear();
do
{
EOT candidate_solution = _sampler(distrib);
_evaluation( candidate_solution );
// TODO: verifier le critere d'acceptation
if ( candidate_solution.fitness() < current_solution.fitness() ||
rng.uniform() < exp( ::fabs(candidate_solution.fitness() - current_solution.fitness()) / temperature ) )
{
current_pop.push_back(candidate_solution);
current_solution = candidate_solution;
}
}
while ( _sa_continue( current_solution ) );
//-------------------------------------------------------------
_replacor(pop, current_pop); // copy current_pop in pop
pop.sort();
if ( ! _cooling_schedule( temperature ) ){ eo::log << eo::debug << "_cooling_schedule" << std::endl; break; }
if ( ! _distribution_continue( distrib ) ){ eo::log << eo::debug << "_distribution_continue" << std::endl; break; }
if ( ! _pop_continue( pop ) ){ eo::log << eo::debug << "_pop_continue" << std::endl; break; }
}
while ( 1 );
}
private:
//! A EOT selector
eoSelect < EOT > & _selector;
//! A EOT estimator. It is going to estimate distribution parameters.
edoEstimator< D > & _estimator;
//! SelectOne
eoSelectOne< EOT > & _selectone;
//! A D modifier
edoModifierMass< D > & _modifier;
//! A D sampler
edoSampler< D > & _sampler;
//! A EOT population continuator
eoContinue < EOT > & _pop_continue;
//! A D continuator
edoContinue < D > & _distribution_continue;
//! A full evaluation function.
eoEvalFunc < EOT > & _evaluation;
//! Stopping criterion before temperature update
moContinuator< moDummyNeighbor<EOT> > & _sa_continue;
//! The cooling schedule
moCoolingSchedule<EOT> & _cooling_schedule;
//! Initial temperature
double _initial_temperature;
//! A EOT replacor
eoReplacement < EOT > & _replacor;
};
#endif // !_edoEDASA_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoEstimator_h
#define _edoEstimator_h
#include <eoPop.h>
#include <eoFunctor.h>
template < typename D >
class edoEstimator : public eoUF< eoPop< typename D::EOType >&, D >
{
public:
typedef typename D::EOType EOType;
// virtual D operator() ( eoPop< EOT >& )=0 (provided by eoUF< A1, R >)
};
#endif // !_edoEstimator_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoEstimatorNormalMono_h
#define _edoEstimatorNormalMono_h
#include "edoEstimator.h"
#include "edoNormalMono.h"
template < typename EOT >
class edoEstimatorNormalMono : public edoEstimator< edoNormalMono< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
class Variance
{
public:
Variance() : _sumvar(0){}
void update(AtomType v)
{
_n++;
AtomType d = v - _mean;
_mean += 1 / _n * d;
_sumvar += (_n - 1) / _n * d * d;
}
AtomType get_mean() const {return _mean;}
AtomType get_var() const {return _sumvar / (_n - 1);}
AtomType get_std() const {return sqrt( get_var() );}
private:
AtomType _n;
AtomType _mean;
AtomType _sumvar;
};
public:
edoNormalMono< EOT > operator()(eoPop<EOT>& pop)
{
unsigned int popsize = pop.size();
assert(popsize > 0);
unsigned int dimsize = pop[0].size();
assert(dimsize > 0);
std::vector< Variance > var( dimsize );
for (unsigned int i = 0; i < popsize; ++i)
{
for (unsigned int d = 0; d < dimsize; ++d)
{
var[d].update( pop[i][d] );
}
}
EOT mean( dimsize );
EOT variance( dimsize );
for (unsigned int d = 0; d < dimsize; ++d)
{
mean[d] = var[d].get_mean();
variance[d] = var[d].get_var();
}
return edoNormalMono< EOT >( mean, variance );
}
};
#endif // !_edoEstimatorNormalMono_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoEstimatorNormalMulti_h
#define _edoEstimatorNormalMulti_h
#include "edoEstimator.h"
#include "edoNormalMulti.h"
template < typename EOT >
class edoEstimatorNormalMulti : public edoEstimator< edoNormalMulti< EOT > >
{
public:
class CovMatrix
{
public:
typedef typename EOT::AtomType AtomType;
CovMatrix( const eoPop< EOT >& pop )
{
//-------------------------------------------------------------
// Some checks before starting to estimate covar
//-------------------------------------------------------------
unsigned int p_size = pop.size(); // population size
assert(p_size > 0);
unsigned int s_size = pop[0].size(); // solution size
assert(s_size > 0);
//-------------------------------------------------------------
//-------------------------------------------------------------
// Copy the population to an ublas matrix
//-------------------------------------------------------------
ublas::matrix< AtomType > sample( p_size, s_size );
for (unsigned int i = 0; i < p_size; ++i)
{
for (unsigned int j = 0; j < s_size; ++j)
{
sample(i, j) = pop[i][j];
}
}
//-------------------------------------------------------------
_varcovar.resize(s_size, s_size);
//-------------------------------------------------------------
// variance-covariance matrix are symmetric (and semi-definite
// positive), thus a triangular storage is sufficient
//
// variance-covariance matrix computation : transpose(A) * A
//-------------------------------------------------------------
ublas::symmetric_matrix< AtomType, ublas::lower > var = ublas::prod( ublas::trans( sample ), sample );
// Be sure that the symmetric matrix got the good size
assert(var.size1() == s_size);
assert(var.size2() == s_size);
assert(var.size1() == _varcovar.size1());
assert(var.size2() == _varcovar.size2());
//-------------------------------------------------------------
// TODO: to remove the comment below
// for (unsigned int i = 0; i < s_size; ++i)
// {
// // triangular LOWER matrix, thus j is not going further than i
// for (unsigned int j = 0; j <= i; ++j)
// {
// // we want a reducted covariance matrix
// _varcovar(i, j) = var(i, j) / p_size;
// }
// }
_varcovar = var / p_size;
_mean.resize(s_size); // FIXME: check if it is really used because of the assignation below
// unit vector
ublas::scalar_vector< AtomType > u( p_size, 1 );
// sum over columns
_mean = ublas::prod( ublas::trans( sample ), u );
// division by n
_mean /= p_size;
}
const ublas::symmetric_matrix< AtomType, ublas::lower >& get_varcovar() const {return _varcovar;}
const ublas::vector< AtomType >& get_mean() const {return _mean;}
private:
ublas::symmetric_matrix< AtomType, ublas::lower > _varcovar;
ublas::vector< AtomType > _mean;
};
public:
typedef typename EOT::AtomType AtomType;
edoNormalMulti< EOT > operator()(eoPop<EOT>& pop)
{
unsigned int popsize = pop.size();
assert(popsize > 0);
unsigned int dimsize = pop[0].size();
assert(dimsize > 0);
CovMatrix cov( pop );
return edoNormalMulti< EOT >( cov.get_mean(), cov.get_varcovar() );
}
};
#endif // !_edoEstimatorNormalMulti_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoEstimatorUniform_h
#define _edoEstimatorUniform_h
#include "edoEstimator.h"
#include "edoUniform.h"
// TODO: calcule de la moyenne + covariance dans une classe derivee
template < typename EOT >
class edoEstimatorUniform : public edoEstimator< edoUniform< EOT > >
{
public:
edoUniform< EOT > operator()(eoPop<EOT>& pop)
{
unsigned int size = pop.size();
assert(size > 0);
EOT min = pop[0];
EOT max = pop[0];
for (unsigned int i = 1; i < size; ++i)
{
unsigned int size = pop[i].size();
assert(size > 0);
// possibilité d'utiliser std::min_element et std::max_element mais exige 2 pass au lieu d'1.
for (unsigned int d = 0; d < size; ++d)
{
if (pop[i][d] < min[d])
min[d] = pop[i][d];
if (pop[i][d] > max[d])
max[d] = pop[i][d];
}
}
return edoUniform< EOT >(min, max);
}
};
#endif // !_edoEstimatorUniform_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoModifier_h
#define _edoModifier_h
template < typename D >
class edoModifier
{
public:
virtual ~edoModifier(){}
typedef typename D::EOType EOType;
};
#endif // !_edoModifier_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoModifierDispersion_h
#define _edoModifierDispersion_h
#include <eoPop.h>
#include <eoFunctor.h>
#include "edoModifier.h"
template < typename D >
class edoModifierDispersion : public edoModifier< D >, public eoBF< D&, eoPop< typename D::EOType >&, void >
{
public:
// virtual void operator() ( D&, eoPop< D::EOType >& )=0 (provided by eoBF< A1, A2, R >)
};
#endif // !_edoModifierDispersion_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoModifierMass_h
#define _edoModifierMass_h
#include <eoFunctor.h>
#include "edoModifier.h"
template < typename D >
class edoModifierMass : public edoModifier< D >, public eoBF< D&, typename D::EOType&, void >
{
public:
//typedef typename D::EOType::AtomType AtomType; // does not work !!!
// virtual void operator() ( D&, D::EOType& )=0 (provided by eoBF< A1, A2, R >)
};
#endif // !_edoModifierMass_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoNormalMono_h
#define _edoNormalMono_h
#include "edoDistrib.h"
template < typename EOT >
class edoNormalMono : public edoDistrib< EOT >
{
public:
edoNormalMono( const EOT& mean, const EOT& variance )
: _mean(mean), _variance(variance)
{
assert(_mean.size() > 0);
assert(_mean.size() == _variance.size());
}
unsigned int size()
{
assert(_mean.size() == _variance.size());
return _mean.size();
}
EOT mean(){return _mean;}
EOT variance(){return _variance;}
private:
EOT _mean;
EOT _variance;
};
#endif // !_edoNormalMono_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoNormalMonoCenter_h
#define _edoNormalMonoCenter_h
#include "edoModifierMass.h"
#include "edoNormalMono.h"
template < typename EOT >
class edoNormalMonoCenter : public edoModifierMass< edoNormalMono< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
void operator() ( edoNormalMono< EOT >& distrib, EOT& mass )
{
distrib.mean() = mass;
}
};
#endif // !_edoNormalMonoCenter_h

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// (c) Thales group, 2010
/*
Authors:
Johann Dreo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoNormalMulti_h
#define _edoNormalMulti_h
#include <boost/numeric/ublas/symmetric.hpp>
#include <boost/numeric/ublas/lu.hpp>
#include "edoDistrib.h"
namespace ublas = boost::numeric::ublas;
template < typename EOT >
class edoNormalMulti : public edoDistrib< EOT >
{
public:
typedef typename EOT::AtomType AtomType;
edoNormalMulti
(
const ublas::vector< AtomType >& mean,
const ublas::symmetric_matrix< AtomType, ublas::lower >& varcovar
)
: _mean(mean), _varcovar(varcovar)
{
assert(_mean.size() > 0);
assert(_mean.size() == _varcovar.size1());
assert(_mean.size() == _varcovar.size2());
}
unsigned int size()
{
assert(_mean.size() == _varcovar.size1());
assert(_mean.size() == _varcovar.size2());
return _mean.size();
}
ublas::vector< AtomType > mean() const {return _mean;}
ublas::symmetric_matrix< AtomType, ublas::lower > varcovar() const {return _varcovar;}
private:
ublas::vector< AtomType > _mean;
ublas::symmetric_matrix< AtomType, ublas::lower > _varcovar;
};
#endif // !_edoNormalMulti_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoNormalMultiCenter_h
#define _edoNormalMultiCenter_h
#include "edoModifierMass.h"
#include "edoNormalMulti.h"
template < typename EOT >
class edoNormalMultiCenter : public edoModifierMass< edoNormalMulti< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
void operator() ( edoNormalMulti< EOT >& distrib, EOT& mass )
{
ublas::vector< AtomType > mean( distrib.size() );
std::copy( mass.begin(), mass.end(), mean.begin() );
distrib.mean() = mean;
}
};
#endif // !_edoNormalMultiCenter_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoSampler_h
#define _edoSampler_h
#include <eoFunctor.h>
#include "edoBounder.h"
#include "edoBounderNo.h"
template < typename D >
class edoSampler : public eoUF< D&, typename D::EOType >
{
public:
typedef typename D::EOType EOType;
edoSampler(edoBounder< EOType > & bounder)
: /*_dummy_bounder(),*/ _bounder(bounder)
{}
/*
edoSampler()
: _dummy_bounder(), _bounder( _dummy_bounder )
{}
*/
// virtual EOType operator()( D& ) = 0 (provided by eoUF< A1, R >)
virtual EOType sample( D& ) = 0;
EOType operator()( D& distrib )
{
unsigned int size = distrib.size();
assert(size > 0);
//-------------------------------------------------------------
// Point we want to sample to get higher a set of points
// (coordinates in n dimension)
// x = {x1, x2, ..., xn}
// the sample method is implemented in the derivated class
//-------------------------------------------------------------
EOType solution(sample(distrib));
//-------------------------------------------------------------
//-------------------------------------------------------------
// Now we are bounding the distribution thanks to min and max
// parameters.
//-------------------------------------------------------------
_bounder(solution);
//-------------------------------------------------------------
return solution;
}
private:
//edoBounderNo<EOType> _dummy_bounder;
//! Bounder functor
edoBounder< EOType > & _bounder;
};
#endif // !_edoSampler_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoSamplerNormalMono_h
#define _edoSamplerNormalMono_h
#include <utils/eoRNG.h>
#include "edoSampler.h"
#include "edoNormalMono.h"
#include "edoBounder.h"
/**
* edoSamplerNormalMono
* This class uses the NormalMono distribution parameters (bounds) to return
* a random position used for population sampling.
*/
template < typename EOT >
class edoSamplerNormalMono : public edoSampler< edoNormalMono< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
edoSamplerNormalMono( edoBounder< EOT > & bounder )
: edoSampler< edoNormalMono< EOT > >( bounder )
{}
EOT sample( edoNormalMono< EOT >& distrib )
{
unsigned int size = distrib.size();
assert(size > 0);
//-------------------------------------------------------------
// Point we want to sample to get higher a set of points
// (coordinates in n dimension)
// x = {x1, x2, ..., xn}
//-------------------------------------------------------------
EOT solution;
//-------------------------------------------------------------
//-------------------------------------------------------------
// Sampling all dimensions
//-------------------------------------------------------------
for (unsigned int i = 0; i < size; ++i)
{
AtomType mean = distrib.mean()[i];
AtomType variance = distrib.variance()[i];
AtomType random = rng.normal(mean, variance);
assert(variance >= 0);
solution.push_back(random);
}
//-------------------------------------------------------------
return solution;
}
};
#endif // !_edoSamplerNormalMono_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoSamplerNormalMulti_h
#define _edoSamplerNormalMulti_h
#include <edoSampler.h>
#include <boost/numeric/ublas/lu.hpp>
#include <boost/numeric/ublas/symmetric.hpp>
template< class EOT >
class edoSamplerNormalMulti : public edoSampler< edoNormalMulti< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
class Cholesky
{
public:
Cholesky( const ublas::symmetric_matrix< AtomType, ublas::lower >& V)
{
unsigned int Vl = V.size1();
assert(Vl > 0);
unsigned int Vc = V.size2();
assert(Vc > 0);
assert( Vl == Vc );
_L.resize(Vl, Vc);
unsigned int i,j,k;
// first column
i=0;
// diagonal
j=0;
_L(0, 0) = sqrt( V(0, 0) );
// end of the column
for ( j = 1; j < Vc; ++j )
{
_L(j, 0) = V(0, j) / _L(0, 0);
}
// end of the matrix
for ( i = 1; i < Vl; ++i ) // each column
{
// diagonal
double sum = 0.0;
for ( k = 0; k < i; ++k)
{
sum += _L(i, k) * _L(i, k);
}
_L(i,i) = sqrt( fabs( V(i,i) - sum) );
for ( j = i + 1; j < Vl; ++j ) // rows
{
// one element
sum = 0.0;
for ( k = 0; k < i; ++k )
{
sum += _L(j, k) * _L(i, k);
}
_L(j, i) = (V(j, i) - sum) / _L(i, i);
}
}
}
const ublas::symmetric_matrix< AtomType, ublas::lower >& get_L() const {return _L;}
private:
ublas::symmetric_matrix< AtomType, ublas::lower > _L;
};
edoSamplerNormalMulti( edoBounder< EOT > & bounder )
: edoSampler< edoNormalMulti< EOT > >( bounder )
{}
EOT sample( edoNormalMulti< EOT >& distrib )
{
unsigned int size = distrib.size();
assert(size > 0);
//-------------------------------------------------------------
// Cholesky factorisation gererating matrix L from covariance
// matrix V.
// We must use cholesky.get_L() to get the resulting matrix.
//
// L = cholesky decomposition of varcovar
//-------------------------------------------------------------
Cholesky cholesky( distrib.varcovar() );
ublas::symmetric_matrix< AtomType, ublas::lower > L = cholesky.get_L();
//-------------------------------------------------------------
//-------------------------------------------------------------
// T = vector of size elements drawn in N(0,1) rng.normal(1.0)
//-------------------------------------------------------------
ublas::vector< AtomType > T( size );
for ( unsigned int i = 0; i < size; ++i )
{
T( i ) = rng.normal( 1.0 );
}
//-------------------------------------------------------------
//-------------------------------------------------------------
// LT = prod( L, T )
//-------------------------------------------------------------
ublas::vector< AtomType > LT = ublas::prod( L, T );
//-------------------------------------------------------------
//-------------------------------------------------------------
// solution = means + LT
//-------------------------------------------------------------
ublas::vector< AtomType > mean = distrib.mean();
ublas::vector< AtomType > ublas_solution = mean + LT;
EOT solution( size );
std::copy( ublas_solution.begin(), ublas_solution.end(), solution.begin() );
//-------------------------------------------------------------
return solution;
}
};
#endif // !_edoSamplerNormalMulti_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoSamplerUniform_h
#define _edoSamplerUniform_h
#include <utils/eoRNG.h>
#include "edoSampler.h"
#include "edoUniform.h"
/**
* edoSamplerUniform
* This class uses the Uniform distribution parameters (bounds) to return
* a random position used for population sampling.
*/
template < typename EOT, class D=edoUniform<EOT> > // FIXME: D template name is there really used ?!?
class edoSamplerUniform : public edoSampler< edoUniform< EOT > >
{
public:
typedef D Distrib;
edoSamplerUniform(edoBounder< EOT > & bounder)
: edoSampler< edoUniform<EOT> >(bounder) // FIXME: Why D is not used here ?
{}
/*
edoSamplerUniform()
: edoSampler< edoUniform<EOT> >()
{}
*/
EOT sample( edoUniform< EOT >& distrib )
{
unsigned int size = distrib.size();
assert(size > 0);
//-------------------------------------------------------------
// Point we want to sample to get higher a set of points
// (coordinates in n dimension)
// x = {x1, x2, ..., xn}
//-------------------------------------------------------------
EOT solution;
//-------------------------------------------------------------
//-------------------------------------------------------------
// Sampling all dimensions
//-------------------------------------------------------------
for (unsigned int i = 0; i < size; ++i)
{
double min = distrib.min()[i];
double max = distrib.max()[i];
double random = rng.uniform(min, max);
assert(min <= random && random <= max);
solution.push_back(random);
}
//-------------------------------------------------------------
return solution;
}
};
#endif // !_edoSamplerUniform_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoUniform_h
#define _edoUniform_h
#include "edoDistrib.h"
#include "edoVectorBounds.h"
template < typename EOT >
class edoUniform : public edoDistrib< EOT >, public edoVectorBounds< EOT >
{
public:
edoUniform(EOT min, EOT max)
: edoVectorBounds< EOT >(min, max)
{}
};
#endif // !_edoUniform_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoUniformCenter_h
#define _edoUniformCenter_h
#include "edoModifierMass.h"
#include "edoUniform.h"
template < typename EOT >
class edoUniformCenter : public edoModifierMass< edoUniform< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
void operator() ( edoUniform< EOT >& distrib, EOT& mass )
{
for (unsigned int i = 0, n = mass.size(); i < n; ++i)
{
AtomType& min = distrib.min()[i];
AtomType& max = distrib.max()[i];
AtomType range = (max - min) / 2;
min = mass[i] - range;
max = mass[i] + range;
}
}
};
#endif // !_edoUniformCenter_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoVectorBounds_h
#define _edoVectorBounds_h
template < typename EOT >
class edoVectorBounds
{
public:
edoVectorBounds(EOT min, EOT max)
: _min(min), _max(max)
{
assert(_min.size() > 0);
assert(_min.size() == _max.size());
}
EOT min(){return _min;}
EOT max(){return _max;}
unsigned int size()
{
assert(_min.size() == _max.size());
return _min.size();
}
private:
EOT _min;
EOT _max;
};
#endif // !_edoVectorBounds_h

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######################################################################################
### 1) Set all needed source files for the project
######################################################################################
FILE(GLOB SOURCES *.cpp)
SET(LIBRARY_OUTPUT_PATH ${CMAKE_BINARY_DIR}/lib)
ADD_LIBRARY(edoutils ${SOURCES})
INSTALL(TARGETS edoutils ARCHIVE DESTINATION lib COMPONENT libraries)
FILE(GLOB HDRS *.h utils)
INSTALL(FILES ${HDRS} DESTINATION include/edo/utils COMPONENT headers)
######################################################################################

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoCheckPoint_h
#define _edoCheckPoint_h
#include <utils/eoUpdater.h>
#include <utils/eoMonitor.h>
#include "edoContinue.h"
#include "edoStat.h"
//! eoCheckPoint< EOT > classe fitted to Distribution Object library
template < typename D >
class edoCheckPoint : public edoContinue< D >
{
public:
typedef typename D::EOType EOType;
edoCheckPoint(edoContinue< D >& _cont)
{
_continuators.push_back( &_cont );
}
bool operator()(const D& distrib)
{
for ( unsigned int i = 0, size = _stats.size(); i < size; ++i )
{
(*_stats[i])( distrib );
}
for ( unsigned int i = 0, size = _updaters.size(); i < size; ++i )
{
(*_updaters[i])();
}
for ( unsigned int i = 0, size = _monitors.size(); i < size; ++i )
{
(*_monitors[i])();
}
bool bContinue = true;
for ( unsigned int i = 0, size = _continuators.size(); i < size; ++i )
{
if ( !(*_continuators[i])( distrib ) )
{
bContinue = false;
}
}
if ( !bContinue )
{
for ( unsigned int i = 0, size = _stats.size(); i < size; ++i )
{
_stats[i]->lastCall( distrib );
}
for ( unsigned int i = 0, size = _updaters.size(); i < size; ++i )
{
_updaters[i]->lastCall();
}
for ( unsigned int i = 0, size = _monitors.size(); i < size; ++i )
{
_monitors[i]->lastCall();
}
}
return bContinue;
}
void add(edoContinue< D >& cont) { _continuators.push_back( &cont ); }
void add(edoStatBase< D >& stat) { _stats.push_back( &stat ); }
void add(eoMonitor& mon) { _monitors.push_back( &mon ); }
void add(eoUpdater& upd) { _updaters.push_back( &upd ); }
virtual std::string className(void) const { return "edoCheckPoint"; }
std::string allClassNames() const
{
std::string s("\n" + className() + "\n");
s += "Stats\n";
for ( unsigned int i = 0, size = _stats.size(); i < size; ++i )
{
s += _stats[i]->className() + "\n";
}
s += "\n";
s += "Updaters\n";
for ( unsigned int i = 0; i < _updaters.size(); ++i )
{
s += _updaters[i]->className() + "\n";
}
s += "\n";
s += "Monitors\n";
for ( unsigned int i = 0; i < _monitors.size(); ++i )
{
s += _monitors[i]->className() + "\n";
}
s += "\n";
s += "Continuators\n";
for ( unsigned int i = 0, size = _continuators.size(); i < size; ++i )
{
s += _continuators[i]->className() + "\n";
}
s += "\n";
return s;
}
private:
std::vector< edoContinue< D >* > _continuators;
std::vector< edoStatBase< D >* > _stats;
std::vector< eoMonitor* > _monitors;
std::vector< eoUpdater* > _updaters;
};
#endif // !_edoCheckPoint_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (c) Marc Schoenauer, Maarten Keijzer and GeNeura Team, 2001
Copyright (C) 2010 Thales group
*/
/*
Authors:
todos@geneura.ugr.es
Marc Schoenauer <Marc.Schoenauer@polytechnique.fr>
Martin Keijzer <mkeijzer@dhi.dk>
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#include <cstdlib>
#include <iostream>
#include <fstream>
#include <stdexcept>
#include <utils/edoFileSnapshot.h>
#include <utils/compatibility.h>
#include <utils/eoParam.h>
edoFileSnapshot::edoFileSnapshot(std::string dirname,
unsigned int frequency /*= 1*/,
std::string filename /*= "gen"*/,
std::string delim /*= " "*/,
unsigned int counter /*= 0*/,
bool rmFiles /*= true*/,
bool saveFilenames /*= true*/)
: _dirname(dirname), _frequency(frequency),
_filename(filename), _delim(delim),
_counter(counter), _saveFilenames(saveFilenames),
_descOfFiles( NULL ), _boolChanged(true)
{
std::string s = "test -d " + _dirname;
int res = system(s.c_str());
// test for (unlikely) errors
if ( (res == -1) || (res == 127) )
{
throw std::runtime_error("Problem executing test of dir in eoFileSnapshot");
}
// now make sure there is a dir without any genXXX file in it
if (res) // no dir present
{
s = std::string("mkdir ") + _dirname;
}
else if (!res && rmFiles)
{
s = std::string("/bin/rm -f ") + _dirname+ "/" + _filename + "*";
}
else
{
s = " ";
}
int dummy;
dummy = system(s.c_str());
// all done
_descOfFiles = new std::ofstream( std::string(dirname + "/list_of_files.txt").c_str() );
}
edoFileSnapshot::~edoFileSnapshot()
{
delete _descOfFiles;
}
void edoFileSnapshot::setCurrentFileName()
{
std::ostringstream oscount;
oscount << _counter;
_currentFileName = _dirname + "/" + _filename + oscount.str();
}
eoMonitor& edoFileSnapshot::operator()(void)
{
if (_counter % _frequency)
{
_boolChanged = false; // subclass with gnuplot will do nothing
_counter++;
return (*this);
}
_counter++;
_boolChanged = true;
setCurrentFileName();
std::ofstream os(_currentFileName.c_str());
if (!os)
{
std::string str = "edoFileSnapshot: Could not open " + _currentFileName;
throw std::runtime_error(str);
}
if ( _saveFilenames )
{
*_descOfFiles << _currentFileName.c_str() << std::endl;
}
return operator()(os);
}
eoMonitor& edoFileSnapshot::operator()(std::ostream& os)
{
iterator it = vec.begin();
os << (*it)->getValue();
for ( ++it; it != vec.end(); ++it )
{
os << _delim.c_str() << (*it)->getValue();
}
os << '\n';
return *this;
}

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (c) Marc Schoenauer, Maarten Keijzer and GeNeura Team, 2001
Copyright (C) 2010 Thales group
*/
/*
Authors:
todos@geneura.ugr.es
Marc Schoenauer <Marc.Schoenauer@polytechnique.fr>
Martin Keijzer <mkeijzer@dhi.dk>
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoFileSnapshot_h
#define _edoFileSnapshot_h
#include <string>
#include <fstream>
#include <stdexcept>
#include "utils/eoMonitor.h"
class edoFileSnapshot : public eoMonitor
{
public:
edoFileSnapshot(std::string dirname,
unsigned int frequency = 1,
std::string filename = "gen",
std::string delim = " ",
unsigned int counter = 0,
bool rmFiles = true,
bool saveFilenames = true);
virtual ~edoFileSnapshot();
virtual bool hasChanged() {return _boolChanged;}
virtual std::string getDirName() { return _dirname; }
virtual unsigned int getCounter() { return _counter; }
virtual const std::string baseFileName() { return _filename;}
std::string getFileName() {return _currentFileName;}
void setCurrentFileName();
virtual eoMonitor& operator()(void);
virtual eoMonitor& operator()(std::ostream& os);
private :
std::string _dirname;
unsigned int _frequency;
std::string _filename;
std::string _delim;
std::string _currentFileName;
unsigned int _counter;
bool _saveFilenames;
std::ofstream* _descOfFiles;
bool _boolChanged;
};
#endif // !_edoFileSnapshot

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoHyperVolume_h
#define _edoHyperVolume_h
template < typename EOT >
class edoHyperVolume
{
public:
typedef typename EOT::AtomType AtomType;
edoHyperVolume() : _hv(1) {}
void update(AtomType v)
{
_hv *= ::sqrt( v );
assert( _hv <= std::numeric_limits< AtomType >::max() );
}
AtomType get_hypervolume() const { return _hv; }
protected:
AtomType _hv;
};
#endif // !_edoHyperVolume_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (c) Marc Schoenauer, Maarten Keijzer and GeNeura Team, 2001
Copyright (C) 2010 Thales group
*/
/*
Authors:
todos@geneura.ugr.es
Marc Schoenauer <Marc.Schoenauer@polytechnique.fr>
Martin Keijzer <mkeijzer@dhi.dk>
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoPopStat_h
#define _edoPopStat_h
#include <utils/eoStat.h>
/** Thanks to MS/VC++, eoParam mechanism is unable to handle std::vectors of stats.
This snippet is a workaround:
This class will "print" a whole population into a std::string - that you can later
send to any stream
This is the plain version - see eoPopString for the Sorted version
Note: this Stat should probably be used only within eoStdOutMonitor, and not
inside an eoFileMonitor, as the eoState construct will work much better there.
*/
template <class EOT>
class edoPopStat : public eoStat<EOT, std::string>
{
public:
using eoStat<EOT, std::string>::value;
/** default Ctor, void std::string by default, as it appears
on the description line once at beginning of evolution. and
is meaningless there. _howMany defaults to 0, that is, the whole
population*/
edoPopStat(std::string _desc ="")
: eoStat<EOT, std::string>("", _desc) {}
/** Fills the value() of the eoParam with the dump of the population. */
void operator()(const eoPop<EOT>& _pop)
{
std::ostringstream os;
os << _pop;
value() = os.str();
}
};
#endif // !_edoPopStat_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoStat_h
#define _edoStat_h
#include <eoFunctor.h>
template < typename D >
class edoStatBase : public eoUF< const D&, void >
{
public:
// virtual void operator()( const D& ) = 0 (provided by eoUF< A1, R >)
virtual void lastCall( const D& ) {}
virtual std::string className() const { return "edoStatBase"; }
};
template < typename D > class edoCheckPoint;
template < typename D, typename T >
class edoStat : public eoValueParam< T >, public edoStatBase< D >
{
public:
edoStat(T value, std::string description)
: eoValueParam< T >(value, description)
{}
virtual std::string className(void) const { return "edoStat"; }
edoStat< D, T >& addTo(edoCheckPoint< D >& cp) { cp.add(*this); return *this; }
// TODO: edoStat< D, T >& addTo(eoMonitor& mon) { mon.add(*this); return *this; }
};
//! A parent class for any kind of distribution to dump parameter to std::string type
template < typename D >
class edoDistribStat : public edoStat< D, std::string >
{
public:
using edoStat< D, std::string >::value;
edoDistribStat(std::string desc)
: edoStat< D, std::string >("", desc)
{}
};
#endif // !_edoStat_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoStatNormalMono_h
#define _edoStatNormalMono_h
#include "edoStat.h"
#include "edoNormalMono.h"
template < typename EOT >
class edoStatNormalMono : public edoDistribStat< edoNormalMono< EOT > >
{
public:
using edoDistribStat< edoNormalMono< EOT > >::value;
edoStatNormalMono( std::string desc = "" )
: edoDistribStat< edoNormalMono< EOT > >( desc )
{}
void operator()( const edoNormalMono< EOT >& distrib )
{
value() = "\n# ====== mono normal distribution dump =====\n";
std::ostringstream os;
os << distrib.mean() << " " << distrib.variance() << std::endl;
value() += os.str();
}
};
#endif // !_edoStatNormalMono_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoStatNormalMulti_h
#define _edoStatNormalMulti_h
#include <boost/numeric/ublas/io.hpp>
#include "edoStat.h"
#include "edoNormalMulti.h"
template < typename EOT >
class edoStatNormalMulti : public edoDistribStat< edoNormalMulti< EOT > >
{
public:
typedef typename EOT::AtomType AtomType;
using edoDistribStat< edoNormalMulti< EOT > >::value;
edoStatNormalMulti( std::string desc = "" )
: edoDistribStat< edoNormalMulti< EOT > >( desc )
{}
void operator()( const edoNormalMulti< EOT >& distrib )
{
value() = "\n# ====== multi normal distribution dump =====\n";
std::ostringstream os;
os << distrib.mean() << " " << distrib.varcovar() << std::endl;
// ublas::vector< AtomType > mean = distrib.mean();
// std::copy(mean.begin(), mean.end(), std::ostream_iterator< std::string >( os, " " ));
// ublas::symmetric_matrix< AtomType, ublas::lower > varcovar = distrib.varcovar();
// std::copy(varcovar.begin(), varcovar.end(), std::ostream_iterator< std::string >( os, " " ));
// os << std::endl;
value() += os.str();
}
};
#endif // !_edoStatNormalMulti_h

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#ifndef _edoStatUniform_h
#define _edoStatUniform_h
#include "edoStat.h"
#include "edoUniform.h"
template < typename EOT >
class edoStatUniform : public edoDistribStat< edoUniform< EOT > >
{
public:
using edoDistribStat< edoUniform< EOT > >::value;
edoStatUniform( std::string desc = "" )
: edoDistribStat< edoUniform< EOT > >( desc )
{}
void operator()( const edoUniform< EOT >& distrib )
{
value() = "\n# ====== uniform distribution dump =====\n";
std::ostringstream os;
os << distrib.min() << " " << distrib.max() << std::endl;
value() += os.str();
}
};
#endif // !_edoStatUniform_h

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###############################################################################
##
## CMakeLists file for unit test
##
###############################################################################
######################################################################################
### 1) Include the sources
######################################################################################
######################################################################################
######################################################################################
### 2) Specify where CMake can find the libraries
######################################################################################
######################################################################################
######################################################################################
### 3) Define your targets and link the librairies
######################################################################################
FIND_PACKAGE(Boost 1.33.0)
INCLUDE_DIRECTORIES(${CMAKE_CURRENT_SOURCE_DIR})
INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS})
LINK_DIRECTORIES(${Boost_LIBRARY_DIRS})
INCLUDE_DIRECTORIES(${CMAKE_SOURCE_DIR}/application/common)
SET(SOURCES
t-edoEstimatorNormalMulti
t-mean-distance
t-bounderno
t-uniform
t-continue
)
FOREACH(current ${SOURCES})
ADD_EXECUTABLE(${current} ${current}.cpp)
ADD_TEST(${current} ${current})
TARGET_LINK_LIBRARIES(${current} edo edoutils ${EO_LIBRARIES} ${MO_LIBRARIES} ${Boost_LIBRARIES})
INSTALL(TARGETS ${current} RUNTIME DESTINATION share/edo/test COMPONENT test)
ENDFOREACH()
######################################################################################

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#!/usr/bin/env python
from pylab import *
FILE_LOCATIONS = 'means_distances_results/files_description.txt'
data = []
locations = [ line.split()[0] for line in open( FILE_LOCATIONS ) ]
for cur_file in locations:
data.append( [ float(line.split()[7]) for line in open( cur_file ).readlines() ] )
print locations
#print data
boxplot( data )
show()

40
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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#include <eo>
#include <edo>
#include "Rosenbrock.h"
typedef eoReal< eoMinimizingFitness > EOT;
int main(void)
{
edoBounderNo< EOT > bounder;
return 0;
}

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#include <eo>
#include <edo>
#include "Rosenbrock.h"
typedef eoReal< eoMinimizingFitness > EOT;
typedef edoUniform< EOT > Distrib;
int main(void)
{
eoState state;
edoContinue< Distrib >* continuator = new edoDummyContinue< Distrib >();
state.storeFunctor(continuator);
return 0;
}

267
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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#include <sstream>
#include <iomanip>
#include <eo>
#include <mo>
#include <utils/eoLogger.h>
#include <utils/eoParserLogger.h>
#include <edo>
#include "Rosenbrock.h"
#include "Sphere.h"
typedef eoReal< eoMinimizingFitness > EOT;
typedef edoNormalMulti< EOT > Distrib;
typedef EOT::AtomType AtomType;
int main(int ac, char** av)
{
//-----------------------------------------------------
// (0) parser + eo routines
//-----------------------------------------------------
eoParserLogger parser(ac, av);
std::string section("Algorithm parameters");
unsigned int p_size = parser.createParam((unsigned int)100, "popSize", "Population Size", 'P', section).value(); // P
unsigned int s_size = parser.createParam((unsigned int)2, "dimension-size", "Dimension size", 'd', section).value(); // d
AtomType mean_value = parser.createParam((AtomType)0, "mean", "Mean value", 'm', section).value(); // m
AtomType covar1_value = parser.createParam((AtomType)1.0, "covar1", "Covar value 1", '1', section).value();
AtomType covar2_value = parser.createParam((AtomType)0.5, "covar2", "Covar value 2", '2', section).value();
AtomType covar3_value = parser.createParam((AtomType)1.0, "covar3", "Covar value 3", '3', section).value();
std::ostringstream ss;
ss << p_size << "_" << std::fixed << std::setprecision(1)
<< mean_value << "_" << covar1_value << "_" << covar2_value << "_"
<< covar3_value << "_gen";
std::string gen_filename = ss.str();
if (parser.userNeedsHelp())
{
parser.printHelp(std::cout);
exit(1);
}
make_verbose(parser);
make_help(parser);
assert(p_size > 0);
assert(s_size > 0);
eoState state;
//-----------------------------------------------------
//-----------------------------------------------------
// (1) Population init and sampler
//-----------------------------------------------------
eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5);
state.storeFunctor(gen);
eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( s_size, *gen );
state.storeFunctor(init);
// create an empty pop and let the state handle the memory
// fill population thanks to eoInit instance
eoPop< EOT >& pop = state.takeOwnership( eoPop< EOT >( p_size, *init ) );
//-----------------------------------------------------
//-----------------------------------------------------------------------------
// (2) distribution initial parameters
//-----------------------------------------------------------------------------
ublas::vector< AtomType > mean( s_size );
for (unsigned int i = 0; i < s_size; ++i) { mean( i ) = mean_value; }
ublas::symmetric_matrix< AtomType, ublas::lower > varcovar( s_size, s_size );
varcovar( 0, 0 ) = covar1_value;
varcovar( 0, 1 ) = covar2_value;
varcovar( 1, 1 ) = covar3_value;
Distrib distrib( mean, varcovar );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (3a) distribution output preparation
//-----------------------------------------------------------------------------
edoDummyContinue< Distrib >* distrib_dummy_continue = new edoDummyContinue< Distrib >();
state.storeFunctor(distrib_dummy_continue);
edoCheckPoint< Distrib >* distrib_continue = new edoCheckPoint< Distrib >( *distrib_dummy_continue );
state.storeFunctor(distrib_continue);
edoDistribStat< Distrib >* distrib_stat = new edoStatNormalMulti< EOT >();
state.storeFunctor(distrib_stat);
distrib_continue->add( *distrib_stat );
edoFileSnapshot* distrib_file_snapshot = new edoFileSnapshot( "TestResDistrib", 1, gen_filename );
state.storeFunctor(distrib_file_snapshot);
distrib_file_snapshot->add(*distrib_stat);
distrib_continue->add(*distrib_file_snapshot);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (3b) distribution output
//-----------------------------------------------------------------------------
(*distrib_continue)( distrib );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare bounder class to set bounds of sampling.
// This is used by edoSampler.
//-----------------------------------------------------------------------------
edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5),
EOT(pop[0].size(), 5),
*gen);
state.storeFunctor(bounder);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare sampler class with a specific distribution
//-----------------------------------------------------------------------------
edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder );
state.storeFunctor(sampler);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (4) sampling phase
//-----------------------------------------------------------------------------
pop.clear();
for (unsigned int i = 0; i < p_size; ++i)
{
EOT candidate_solution = (*sampler)( distrib );
pop.push_back( candidate_solution );
}
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (5) population output
//-----------------------------------------------------------------------------
eoContinue< EOT >* pop_cont = new eoGenContinue< EOT >( 2 ); // never reached fitness
state.storeFunctor(pop_cont);
eoCheckPoint< EOT >* pop_continue = new eoCheckPoint< EOT >( *pop_cont );
state.storeFunctor(pop_continue);
edoPopStat< EOT >* pop_stat = new edoPopStat<EOT>;
state.storeFunctor(pop_stat);
pop_continue->add(*pop_stat);
edoFileSnapshot* pop_file_snapshot = new edoFileSnapshot( "TestResPop", 1, gen_filename );
state.storeFunctor(pop_file_snapshot);
pop_file_snapshot->add(*pop_stat);
pop_continue->add(*pop_file_snapshot);
(*pop_continue)( pop );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (6) estimation phase
//-----------------------------------------------------------------------------
edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >();
state.storeFunctor(estimator);
distrib = (*estimator)( pop );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (7) distribution output
//-----------------------------------------------------------------------------
(*distrib_continue)( distrib );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (8) euclidianne distance estimation
//-----------------------------------------------------------------------------
ublas::vector< AtomType > new_mean = distrib.mean();
ublas::symmetric_matrix< AtomType, ublas::lower > new_varcovar = distrib.varcovar();
AtomType distance = 0;
for ( unsigned int d = 0; d < s_size; ++d )
{
distance += pow( mean[ d ] - new_mean[ d ], 2 );
}
distance = sqrt( distance );
eo::log << eo::logging
<< "mean: " << mean << std::endl
<< "new mean: " << new_mean << std::endl
<< "distance: " << distance << std::endl
;
//-----------------------------------------------------------------------------
return 0;
}

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#include <sys/stat.h>
#include <sys/types.h>
#include <sstream>
#include <iomanip>
#include <fstream>
#include <eo>
#include <mo>
#include <utils/eoLogger.h>
#include <utils/eoParserLogger.h>
#include <edo>
#include <boost/numeric/ublas/vector.hpp>
#include <boost/numeric/ublas/symmetric_matrix.hpp>
#include "Rosenbrock.h"
#include "Sphere.h"
typedef eoReal< eoMinimizingFitness > EOT;
typedef edoNormalMulti< EOT > Distrib;
typedef EOT::AtomType AtomType;
int main(int ac, char** av)
{
//-----------------------------------------------------
// (0) parser + eo routines
//-----------------------------------------------------
eoParserLogger parser(ac, av);
std::string section("Algorithm parameters");
unsigned int r_max = parser.createParam((unsigned int)100, "run-number", "Number of run", 'r', section).value(); // r
unsigned int p_min = parser.createParam((unsigned int)10, "population-min", "Population min", 'p', section).value(); // p
unsigned int p_max = parser.createParam((unsigned int)1000, "population-max", "Population max", 'P', section).value(); // P
unsigned int p_step = parser.createParam((unsigned int)50, "population-step", "Population step", 't', section).value(); // t
unsigned int s_size = parser.createParam((unsigned int)2, "dimension-size", "Dimension size", 'd', section).value(); // d
AtomType mean_value = parser.createParam((AtomType)0, "mean", "Mean value", 'm', section).value(); // m
AtomType covar1_value = parser.createParam((AtomType)1.0, "covar1", "Covar value 1", '1', section).value(); // 1
AtomType covar2_value = parser.createParam((AtomType)0.5, "covar2", "Covar value 2", '2', section).value(); // 2
AtomType covar3_value = parser.createParam((AtomType)1.0, "covar3", "Covar value 3", '3', section).value(); // 3
std::string results_directory = parser.createParam((std::string)"means_distances_results", "results-directory", "Results directory", 'R', section).value(); // R
std::string files_description = parser.createParam((std::string)"files_description.txt", "files-description", "Files description", 'F', section).value(); // F
if (parser.userNeedsHelp())
{
parser.printHelp(std::cout);
exit(1);
}
make_verbose(parser);
make_help(parser);
//-----------------------------------------------------
assert(r_max >= 1);
assert(s_size >= 2);
eo::log << eo::quiet;
::mkdir( results_directory.c_str(), 0755 );
for ( unsigned int p_size = p_min; p_size <= p_max; p_size += p_step )
{
assert(p_size >= p_min);
std::ostringstream desc_file;
desc_file << results_directory << "/" << files_description;
std::ostringstream cur_file;
cur_file << results_directory << "/pop_" << p_size << ".txt";
eo::log << eo::file( desc_file.str() ) << cur_file.str().c_str() << std::endl;
eo::log << eo::file( cur_file.str() );
eo::log << eo::logging << "run_number p_size s_size mean(0) mean(1) new-mean(0) new-mean(1) distance" << std::endl;
eo::log << eo::quiet;
for ( unsigned int r = 1; r <= r_max; ++r)
{
eoState state;
//-----------------------------------------------------
// (1) Population init and sampler
//-----------------------------------------------------
eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5);
state.storeFunctor(gen);
eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( s_size, *gen );
state.storeFunctor(init);
// create an empty pop and let the state handle the memory
// fill population thanks to eoInit instance
eoPop< EOT >& pop = state.takeOwnership( eoPop< EOT >( p_size, *init ) );
//-----------------------------------------------------
//-----------------------------------------------------------------------------
// (2) distribution initial parameters
//-----------------------------------------------------------------------------
ublas::vector< AtomType > mean( s_size, mean_value );
ublas::symmetric_matrix< AtomType, ublas::lower > varcovar( s_size, s_size );
varcovar( 0, 0 ) = covar1_value;
varcovar( 0, 1 ) = covar2_value;
varcovar( 1, 1 ) = covar3_value;
Distrib distrib( mean, varcovar );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare bounder class to set bounds of sampling.
// This is used by edoSampler.
//-----------------------------------------------------------------------------
edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5),
EOT(pop[0].size(), 5),
*gen);
state.storeFunctor(bounder);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// Prepare sampler class with a specific distribution
//-----------------------------------------------------------------------------
edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder );
state.storeFunctor(sampler);
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (4) sampling phase
//-----------------------------------------------------------------------------
pop.clear();
for (unsigned int i = 0; i < p_size; ++i)
{
EOT candidate_solution = (*sampler)( distrib );
pop.push_back( candidate_solution );
}
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (6) estimation phase
//-----------------------------------------------------------------------------
edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >();
state.storeFunctor(estimator);
distrib = (*estimator)( pop );
//-----------------------------------------------------------------------------
//-----------------------------------------------------------------------------
// (8) euclidianne distance estimation
//-----------------------------------------------------------------------------
ublas::vector< AtomType > new_mean = distrib.mean();
ublas::symmetric_matrix< AtomType, ublas::lower > new_varcovar = distrib.varcovar();
AtomType distance = 0;
for ( unsigned int d = 0; d < s_size; ++d )
{
distance += pow( mean[ d ] - new_mean[ d ], 2 );
}
distance = sqrt( distance );
eo::log << r << " " << p_size << " " << s_size << " "
<< mean(0) << " " << mean(1) << " "
<< new_mean(0) << " " << new_mean(1) << " "
<< distance << std::endl
;
//-----------------------------------------------------------------------------
}
}
return 0;
}

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/*
The Evolving Distribution Objects framework (EDO) is a template-based,
ANSI-C++ evolutionary computation library which helps you to write your
own estimation of distribution algorithms.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Copyright (C) 2010 Thales group
*/
/*
Authors:
Johann Dréo <johann.dreo@thalesgroup.com>
Caner Candan <caner.candan@thalesgroup.com>
*/
#include <eo>
#include <edo>
#include "Rosenbrock.h"
typedef eoReal< eoMinimizingFitness > EOT;
int main(void)
{
eoState state;
edoUniform< EOT >* distrib = new edoUniform< EOT >( EOT(3, -1), EOT(3, 1) );
state.storeFunctor(distrib);
return 0;
}

18
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#!/usr/bin/env python
PSIZE = 10000
MEAN = 0
CMD = "./test/t-edoEstimatorNormalMulti -P=%s -m=%.1f -1=%.1f -2=%.1f -3=%.1f && ./gplot.py -r TestResPop -p -w 5 -u -g %s -G results_for_test_cov_parameters -f %s_gen1"
from os import system
from numpy import arange
if __name__ == '__main__':
for p1 in list(arange(0.1, 1.1, 0.1)):
for p2 in list(arange(-1., 0., 0.1)) + list(arange(0., 1.1, 0.1)):
for p3 in list(arange(0.1, 1.1, 0.1)):
gen = '%d_%.1f_%.1f_%.1f_%.1f' % (PSIZE, MEAN, p1, p2, p3)
cmd = CMD % ( PSIZE, MEAN, p1, p2, p3, gen, gen )
print cmd
system( cmd )