+ test/t-doEstimatorNormalMulti
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Caner Candan
parent
f410026068
commit
e70464630e
5 changed files with 228 additions and 24 deletions
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@ -39,6 +39,7 @@ def logger(level_name, filename='plot.log'):
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def parser(parser=optparse.OptionParser()):
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parser.add_option('-v', '--verbose', choices=LEVELS.keys(), default='warning', help='set a verbose level')
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parser.add_option('-f', '--files', help='give some input sample files separated by comma (cf. gen1,gen2,...)', default='')
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parser.add_option('-r', '--respop', help='define the population results containing folder', default='./ResPop')
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parser.add_option('-o', '--output', help='give an output filename for logging', default='plot.log')
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parser.add_option('-d', '--dimension', help='give a dimension size', default=2)
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parser.add_option('-m', '--multiplot', action="store_true", help='plot all graphics in one window', dest="multiplot", default=True)
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@ -252,6 +253,7 @@ def main():
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n = int(options.dimension)
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w = int(options.windowid)
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r = options.respop
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if options.multiplot:
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g = Gnuplot.Gnuplot()
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@ -270,56 +272,56 @@ def main():
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g('set origin 0.0, 0.5')
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if n >= 1:
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plotXPointYFitness('./ResPop', state=gstate, g=g)
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plotXPointYFitness(r, state=gstate, g=g)
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g('set size 0.5, 0.5')
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g('set origin 0.0, 0.0')
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if n >= 2:
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plotXPointYFitness('./ResPop', '4:1', state=gstate, g=g)
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plotXPointYFitness(r, '4:1', state=gstate, g=g)
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g('set size 0.5, 0.5')
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g('set origin 0.5, 0.5')
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if n >= 2:
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plotXYPointZFitness('./ResPop', state=gstate, g=g)
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plotXYPointZFitness(r, state=gstate, g=g)
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g('set size 0.5, 0.5')
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g('set origin 0.5, 0.0')
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if n >= 2:
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plotXYPoint('./ResPop', state=gstate, g=g)
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plotXYPoint(r, state=gstate, g=g)
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elif n >= 3:
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plotXYZPoint('./ResPop', state=gstate, g=g)
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plotXYZPoint(r, state=gstate, g=g)
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g('set nomultiplot')
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else:
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if n >= 1 and w in [0, 1]:
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plotXPointYFitness('./ResPop', state=gstate)
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plotXPointYFitness(r, state=gstate)
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if n >= 2 and w in [0, 2]:
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plotXPointYFitness('./ResPop', '4:1', state=gstate)
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plotXPointYFitness(r, '4:1', state=gstate)
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if n >= 2 and w in [0, 3]:
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plotXYPointZFitness('./ResPop', state=gstate)
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plotXYPointZFitness(r, state=gstate)
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if n >= 3 and w in [0, 4]:
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plotXYZPoint('./ResPop', state=gstate)
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plotXYZPoint(r, state=gstate)
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if n >= 2 and w in [0, 5]:
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plotXYPoint('./ResPop', state=gstate)
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plotXYPoint(r, state=gstate)
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# if n >= 1:
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# plotParams('./ResParams.txt', state=gstate)
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# if n >= 2:
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# plot2DRectFromFiles('./ResBounds', state=gstate)
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# plotXYPoint('./ResPop', state=gstate)
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# plotXYPoint(r, state=gstate)
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# g = plot2DRectFromFiles('./ResBounds', state=gstate, plot=False)
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# plotXYPoint('./ResPop', g=g)
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# plotXYPoint(r, g=g)
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wait(prompt='Press return to end the plot.\n')
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@ -154,7 +154,7 @@ int main(int ac, char** av)
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//-----------------------------------------------------------------------------
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// general output
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// population output
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//-----------------------------------------------------------------------------
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eoCheckPoint< EOT >& pop_continue = do_make_checkpoint(parser, state, eval, eo_continue);
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@ -171,14 +171,6 @@ int main(int ac, char** av)
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// population output
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// distribution output
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//-----------------------------------------------------------------------------
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@ -9,7 +9,7 @@
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#define _doEstimatorNormalMulti_h
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#include "doEstimator.h"
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#include "doUniform.h"
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#include "doNormalMulti.h"
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template < typename EOT >
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class doEstimatorNormalMulti : public doEstimator< doNormalMulti< EOT > >
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@ -23,13 +23,24 @@
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### 3) Define your targets and link the librairies
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######################################################################################
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FIND_PACKAGE(Boost 1.33.0)
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INCLUDE_DIRECTORIES(${CMAKE_CURRENT_SOURCE_DIR})
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INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS})
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LINK_DIRECTORIES(${Boost_LIBRARY_DIRS})
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INCLUDE_DIRECTORIES(${CMAKE_SOURCE_DIR}/application/eda_sa)
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SET(SOURCES
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t-doEstimatorNormalMulti
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)
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FOREACH(current ${SOURCES})
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ADD_EXECUTABLE(${current} ${current}.cpp)
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TARGET_LINK_LIBRARIES(${current} ${PROJECT_NAME} ${EO_LIBRARIES})
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ADD_CURRENT(${current} ${current})
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ADD_TEST(${current} ${current})
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TARGET_LINK_LIBRARIES(${current} do doutils ${EO_LIBRARIES} ${MO_LIBRARIES} ${Boost_LIBRARIES})
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INSTALL(TARGETS ${current} RUNTIME DESTINATION share/do/test COMPONENT test)
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ENDFOREACH()
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######################################################################################
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199
test/t-doEstimatorNormalMulti.cpp
Normal file
199
test/t-doEstimatorNormalMulti.cpp
Normal file
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@ -0,0 +1,199 @@
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#include <eo>
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#include <mo>
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#include <utils/eoLogger.h>
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#include <utils/eoParserLogger.h>
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#include <do>
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#include "Rosenbrock.h"
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#include "Sphere.h"
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typedef eoReal< eoMinimizingFitness > EOT;
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typedef doNormalMulti< EOT > Distrib;
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typedef EOT::AtomType AtomType;
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int main(int ac, char** av)
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{
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//-----------------------------------------------------
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// (0) parser + eo routines
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//-----------------------------------------------------
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eoParserLogger parser(ac, av);
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std::string section("Algorithm parameters");
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unsigned int p_size = parser.createParam((unsigned int)100, "popSize", "Population Size", 'P', section).value(); // P
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unsigned int s_size = parser.createParam((unsigned int)2, "dimension-size", "Dimension size", 'd', section).value(); // d
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AtomType mean_value = parser.createParam((AtomType)0, "mean", "Mean value", 'm', section).value(); // m
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AtomType covar1_value = parser.createParam((AtomType)1, "covar1", "Covar value 1", '1', section).value();
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AtomType covar2_value = parser.createParam((AtomType)0.5, "covar2", "Covar value 2", '2', section).value();
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AtomType covar3_value = parser.createParam((AtomType)1, "covar3", "Covar value 3", '3', section).value();
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if (parser.userNeedsHelp())
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{
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parser.printHelp(std::cout);
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exit(1);
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}
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make_verbose(parser);
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make_help(parser);
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assert(p_size > 0);
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assert(s_size > 0);
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eoState state;
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//-----------------------------------------------------
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//-----------------------------------------------------
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// (1) Population init and sampler
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//-----------------------------------------------------
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eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5);
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state.storeFunctor(gen);
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eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( s_size, *gen );
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state.storeFunctor(init);
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// create an empty pop and let the state handle the memory
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// fill population thanks to eoInit instance
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eoPop< EOT >& pop = state.takeOwnership( eoPop< EOT >( p_size, *init ) );
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//-----------------------------------------------------
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//-----------------------------------------------------------------------------
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// (2) distribution initial parameters
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//-----------------------------------------------------------------------------
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ublas::vector< AtomType > mean( s_size, mean_value );
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ublas::symmetric_matrix< AtomType, ublas::lower > varcovar( s_size, s_size );
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varcovar( 0, 0 ) = covar1_value;
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varcovar( 0, 1 ) = covar2_value;
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varcovar( 1, 1 ) = covar3_value;
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Distrib distrib( mean, varcovar );
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// (3) distribution output
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//-----------------------------------------------------------------------------
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doDummyContinue< Distrib >* dummy_continue = new doDummyContinue< Distrib >();
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state.storeFunctor(dummy_continue);
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doCheckPoint< Distrib >* distribution_continue = new doCheckPoint< Distrib >( *dummy_continue );
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state.storeFunctor(distribution_continue);
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doDistribStat< Distrib >* distrib_stat = new doStatNormalMulti< EOT >();
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state.storeFunctor(distrib_stat);
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distribution_continue->add( *distrib_stat );
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eoMonitor* stdout_monitor = new eoStdoutMonitor();
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state.storeFunctor(stdout_monitor);
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stdout_monitor->add(*distrib_stat);
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distribution_continue->add( *stdout_monitor );
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(*distribution_continue)( distrib );
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// Prepare bounder class to set bounds of sampling.
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// This is used by doSampler.
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//-----------------------------------------------------------------------------
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doBounder< EOT >* bounder = new doBounderRng< EOT >(EOT(pop[0].size(), -5),
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EOT(pop[0].size(), 5),
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*gen);
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state.storeFunctor(bounder);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// Prepare sampler class with a specific distribution
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//-----------------------------------------------------------------------------
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doSampler< Distrib >* sampler = new doSamplerNormalMulti< EOT >( *bounder );
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state.storeFunctor(sampler);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// (4) sampling phase
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//-----------------------------------------------------------------------------
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pop.clear();
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for (unsigned int i = 0; i < p_size; ++i)
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{
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EOT candidate_solution = (*sampler)( distrib );
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pop.push_back( candidate_solution );
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}
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// pop.sort();
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// (5) population output
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//-----------------------------------------------------------------------------
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eoContinue< EOT >* cont = new eoGenContinue< EOT >( 2 ); // never reached fitness
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state.storeFunctor(cont);
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eoCheckPoint< EOT >* pop_continue = new eoCheckPoint< EOT >( *cont );
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state.storeFunctor(pop_continue);
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doPopStat< EOT >* popStat = new doPopStat<EOT>;
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state.storeFunctor(popStat);
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pop_continue->add(*popStat);
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doFileSnapshot* fileSnapshot = new doFileSnapshot("TestResPop");
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state.storeFunctor(fileSnapshot);
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fileSnapshot->add(*popStat);
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pop_continue->add(*fileSnapshot);
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(*pop_continue)( pop );
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// (6) estimation phase
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//-----------------------------------------------------------------------------
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doEstimator< Distrib >* estimator = new doEstimatorNormalMulti< EOT >();
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state.storeFunctor(estimator);
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distrib = (*estimator)( pop );
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// (7) distribution output
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//-----------------------------------------------------------------------------
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(*distribution_continue)( distrib );
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//-----------------------------------------------------------------------------
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return 0;
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}
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