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* New tree configuration of the project:

Browse source 
.../
   ...           + -- EO
   |             |
   |             |
   +-- src ----- + -- EDO
   |             |
   |             |
   +-- test      + -- MO
   |             |
   |             |
   +-- tutorial  + -- MOEO
   |             |
   |             |
   +-- doc       + -- SMP
   |             |
   |             |
   ...           + -- EOMPI
                 |
                 |
                 + -- EOSERIAL

Question for current maintainers: ./README: new release?

Also:

* Moving out eompi & eoserial modules (issue #2).

* Correction of the errors when executing "make doc" command.

* Adding a solution for the conflicting headers problem (see the two CMake Cache
 Values: PROJECT_TAG & PROJECT_HRS_INSTALL_SUBPATH) (issue #1)

* Header inclusions:
        ** src: changing absolute paths into relative paths ('#include <...>' -> '#include "..."')
        ** test, tutorial: changing relative paths into absolute paths ('#include "..."' -> '#include <...>')

* Moving out some scripts from EDO -> to the root

* Add a new script for compilation and installation (see build_gcc_linux_install)

* Compilation with uBLAS library or EDO module: now ok

* Minor modifications on README & INSTALL files

* Comment eompi failed tests with no end

*** TODO: CPack (debian (DEB) & RedHat (RPM) packages) (issues #6 & #7) ***
This commit is contained in:
Adèle Harrissart 2014-08-04 13:40:28 +02:00
commit 490e837f7a
2359 changed files with 7688 additions and 16329 deletions
Download patch file Download diff file Expand all files Collapse all files

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######################################################################################
### 1) Where do we go now ?!?
######################################################################################
include_directories(
#${CMAKE_CURRENT_SOURCE_DIR}/common
)
include_directories(${EIGEN3_INCLUDE_DIR})
add_subdirectory(common) # Rosenbrock and Sphere
#add_subdirectory(eda_sa)
if(EIGEN3_FOUND) # see edoNormalAdaptive
add_subdirectory(eda)
add_subdirectory(cmaes)
endif()
######################################################################################

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project(cmaes)
#find_package(Eigen3 REQUIRED)
#include_directories(EIGEN3_INCLUDE_DIR)
include_directories( ${EIGEN3_INCLUDE_DIR} )
#message( "MESSAGE:" ${EIGEN3_INCLUDE_DIR} )
#find_package(Boost 1.33.0)
#include_directories(${Boost_INCLUDE_DIRS})
link_directories(${Boost_LIBRARY_DIRS})
#include_directories(${CMAKE_CURRENT_SOURCE_DIR})
#include_directories(${EO_SRC_DIR}/src)
#include_directories(${EDO_SRC_DIR}/src)
#link_directories(${EO_BIN_DIRS}/${LIB})
#link_directories(${EDO_BIN_DIRS}/${LIB})
# set(RESOURCES
# ${PROJECT_NAME}.param
# )
#
# foreach(file ${RESOURCES})
# execute_process(
# COMMAND ${CMAKE_COMMAND} -E copy_if_different
# ${CMAKE_CURRENT_SOURCE_DIR}/${file}
# ${EDO_BIN_DIR}/${file}
# )
# endforeach(file)
#file(GLOB SOURCES *.cpp)
set(EXECUTABLE_OUTPUT_PATH ${EDO_BIN_DIR})
add_executable(${PROJECT_NAME} main.cpp)
target_link_libraries(${PROJECT_NAME} eo eoutils edoutils ${Boost_LIBRARIES})

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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 <paradiseo/eo.h>
//#include <paradiseo/mo.h>
#include <paradiseo/eo/eoEvalFuncCounterBounder.h>
#include <paradiseo/eo/do/make_pop.h>
#include <paradiseo/eo/do/make_run.h>
#include <paradiseo/eo/do/make_continue.h>
#include <paradiseo/eo/do/make_checkpoint.h>
#include <paradiseo/edo.h>
#include "../common/Rosenbrock.h"
#include "../common/Sphere.h"
typedef eoReal<eoMinimizingFitness> RealVec;
typedef edoNormalAdaptive< RealVec > Distrib;
int main(int ac, char** av)
{
eoParser parser(ac, av);
eoState state;
// Letters used by the following declarations:
unsigned long max_eval = parser.getORcreateParam((unsigned long)0, "maxEval", "Maximum number of evaluations (0 = none)", 'E', "Stopping criterion").value(); // E
unsigned int dim = parser.createParam((unsigned int)10, "dimension-size", "Dimension size", 'd', "Problem").value(); // d
double mu = dim / 2;
edoNormalAdaptive<RealVec> distribution(dim);
eoSelect< RealVec >* selector = new eoRankMuSelect< RealVec >( mu );
state.storeFunctor(selector);
edoEstimator< Distrib >* estimator = new edoEstimatorNormalAdaptive<RealVec>( distribution );
state.storeFunctor(estimator);
eoEvalFunc< RealVec >* plainEval = new Rosenbrock< RealVec >();
state.storeFunctor(plainEval);
eoEvalFuncCounterBounder< RealVec > eval(*plainEval, max_eval);
eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5);
state.storeFunctor(gen);
eoInitFixedLength< RealVec >* init = new eoInitFixedLength< RealVec >( dim, *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 edoUniform).
eoPop< RealVec >& 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 edoSampler.
edoBounder< RealVec >* bounder =
new edoBounderRng< RealVec >( RealVec(dim, -5), RealVec(dim, 5), *gen); // FIXME do not use hard-coded bounds
state.storeFunctor(bounder);
// Prepare sampler class with a specific distribution
edoSampler< Distrib >* sampler = new edoSamplerNormalAdaptive< RealVec >( *bounder );
state.storeFunctor(sampler);
// stopping criteria
// ... and creates the parameter letters: C E g G s T
eoContinue< RealVec >& eo_continue = do_make_continue(parser, state, eval);
// population output
eoCheckPoint< RealVec >& pop_continue = do_make_checkpoint(parser, state, eval, eo_continue);
// keep the best solution found so far in an eoStat
// thus, if the population's best individual fitness decreases during the search, we could
// still keep the best found since the beginning, while avoiding the bias of elitism on the sample
eoBestIndividualStat<RealVec> best_indiv;
pop_continue.add( best_indiv );
// 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);
eoReplacement< RealVec >* replacor = new eoCommaReplacement< RealVec >();
state.storeFunctor(replacor);
// Help + Verbose routines
make_verbose(parser);
make_help(parser);
// Some stuff to display helper when we are using -h option
if (parser.userNeedsHelp())
{
parser.printHelp(std::cout);
exit(1);
}
eoPopLoopEval<RealVec> popEval( eval );
// CMA-ES algorithm configuration
edoAlgo< Distrib >* algo = new edoAlgoAdaptive< Distrib >
(distribution, popEval, *selector, *estimator, *sampler, *replacor,
pop_continue, *distribution_continue );
// Use the best solution of the random first pop to start the search
// That is, center the distribution's mean on it.
distribution.mean( pop.best_element() );
// Beginning of the algorithm call
try {
eo::log << eo::progress << "Best solution after random init: " << pop.best_element().fitness() << std::endl;
do_run(*algo, pop);
} catch (eoEvalFuncCounterBounderException& e) {
eo::log << eo::warnings << "warning: " << e.what() << std::endl;
}
// use the stat instead of the pop, to get the best solution of the whole search
std::cout << best_indiv.value() << std::endl;
return 0;
}

15
tutorial/edo/common/CMakeLists.txt Executable file
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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}
${EDO_BIN_DIR}/${file}
)
ENDFOREACH(file)

42
tutorial/edo/common/Rosenbrock.h Executable file
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#ifndef _Rosenbrock_h
#define _Rosenbrock_h
#include <paradiseo/eo.h>
#include <paradiseo/eo/es.h>
#include <paradiseo/eo/es/eoRealInitBounded.h>
#include <paradiseo/eo/es/eoRealOp.h>
#include <paradiseo/eo/es/eoEsChromInit.h>
#include <paradiseo/eo/es/eoRealOp.h>
#include <paradiseo/eo/es/make_real.h>
#include <paradiseo/eo/apply.h>
#include <paradiseo/eo/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

42
tutorial/edo/common/Sphere.h Executable file
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#ifndef _Sphere_h
#define _Sphere_h
#include <paradiseo/eo.h>
#include <paradiseo/eo/es.h>
#include <paradiseo/eo/es/eoRealInitBounded.h>
#include <paradiseo/eo/es/eoRealOp.h>
#include <paradiseo/eo/es/eoEsChromInit.h>
#include <paradiseo/eo/es/eoRealOp.h>
#include <paradiseo/eo/es/make_real.h>
#include <paradiseo/eo/apply.h>
#include <paradiseo/eo/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

36
tutorial/edo/common/boxplot_eda_n_edasa.py Executable file
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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()

68
tutorial/edo/common/ggobi.py Executable file
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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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tutorial/edo/common/gplot.py Executable file
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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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tutorial/edo/eda/CMakeLists.txt Executable file
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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(${Boost_LIBRARY_DIRS})
#include_directories(${EO_SRC_DIR}/src)
link_directories(${EO_BIN_DIR}/${LIB})
#include_directories(${EDO_SRC_DIR}/src)
link_directories(${EDO_BIN_DIR}/${LIB})
set(RESOURCES
${PROJECT_NAME}.param
)
foreach(FILE ${RESOURCES})
execute_process(
COMMAND ${CMAKE_COMMAND} -E copy_if_different
${CMAKE_CURRENT_SOURCE_DIR}/${FILE}
${EDO_BIN_DIR}/${FILE}
)
endforeach(FILE)
file(GLOB SOURCES *.cpp)
set(EXECUTABLE_OUTPUT_PATH ${EDO_BIN_DIR})
add_executable(${PROJECT_NAME} ${SOURCES})
target_link_libraries(${PROJECT_NAME} eo eoutils edoutils ${Boost_LIBRARIES})

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tutorial/edo/eda/eda.param Executable file
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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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tutorial/edo/eda/main.cpp Executable file
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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 <paradiseo/eo.h>
// #include <mo>
#include <paradiseo/eo/eoEvalFuncCounterBounder.h>
#include <paradiseo/eo/do/make_pop.h>
#include <paradiseo/eo/do/make_run.h>
#include <paradiseo/eo/do/make_continue.h>
#include <paradiseo/eo/do/make_checkpoint.h>
#include <paradiseo/edo.h>
#include "../common/Rosenbrock.h"
#include "../common/Sphere.h"
typedef eoReal<eoMinimizingFitness> EOT;
typedef edoNormalMulti< EOT > Distrib;
int main(int ac, char** av)
{
eoParser parser(ac, av);
// Letters used by the following declarations:
// a d i p t
std::string section("Algorithm parameters");
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);
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 edoUniform).
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 edoSampler.
edoBounder< EOT >* bounder =
new edoBounderRng< EOT >( EOT(dimension_size, -5), EOT(dimension_size, 5), *gen); // FIXME do not use hard-coded bounds
state.storeFunctor(bounder);
// Prepare sampler class with a specific distribution
edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder );
state.storeFunctor(sampler);
// 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());
state.storeFunctor(replacor);
// Help + Verbose routines
make_verbose(parser);
make_help(parser);
// Some stuff to display helper when we are using -h option
if (parser.userNeedsHelp())
{
parser.printHelp(std::cout);
exit(1);
}
// population output (after helper)
//
// FIXME: theses objects are instanciated 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("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 );
eoPopLoopEval<EOT> popEval( eval );
// EDA algorithm configuration
edoAlgo< Distrib >* algo = new edoAlgoStateless< Distrib >
(popEval, *selector, *estimator, *sampler, *replacor,
pop_continue, *distribution_continue );
// 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;
}

27
tutorial/edo/eda_sa/CMakeLists.txt Executable file
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@ -0,0 +1,27 @@
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}
${EDO_BIN_DIR}/${file}
)
ENDFOREACH(file)
FILE(GLOB SOURCES *.cpp)
SET(EXECUTABLE_OUTPUT_PATH ${EDO_BIN_DIR})
ADD_EXECUTABLE(${PROJECT_NAME} ${SOURCES})
TARGET_LINK_LIBRARIES(${PROJECT_NAME} edo edoutils ${EO_LIBRARIES} ${MO_LIBRARIES} ${Boost_LIBRARIES})

7
tutorial/edo/eda_sa/eda_sa.param Executable file
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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

284
tutorial/edo/eda_sa/main.cpp Executable file
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#include <paradiseo/eo.h>
#include <paradiseo/mo.h>
#include <paradiseo/eo/eoEvalFuncCounterBounder.h>
#include <paradiseo/eo/do/make_pop.h>
#include <paradiseo/eo/do/make_run.h>
#include <paradiseo/eo/do/make_continue.h>
#include <paradiseo/eo/do/make_checkpoint.h>
#include <paradiseo/edo.h>
#include "../common/Rosenbrock.h"
#include "../common/Sphere.h"
typedef eoReal<eoMinimizingFitness> EOT;
typedef edoNormalMulti< EOT > Distrib;
int main(int ac, char** av)
{
eoParser 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;
}