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#-*-CPerl-*-
#########################
use strict;
BEGIN { plan 'no_plan' };
use lib qw( lib ../lib ../../lib ); #Just in case we are testing it in-place
use Algorithm::Evolutionary qw( Individual::String Individual::BitString
Individual::Vector Individual::Tree
Fitness::ONEMAX);
#########################
# Insert your test code below, the Test module is use()ed here so read
# its man page ( perldoc Test ) for help writing this test script.
#String
print "Testing Individual objects...String \n";
is( ref Algorithm::Evolutionary::Individual::String->new(['a'..'z'],10), "Algorithm::Evolutionary::Individual::String", "Good ref" );
is( ref Algorithm::Evolutionary::Individual::Base::create( 'String', { chars => ['a'..'e'], length => 10 }), "Algorithm::Evolutionary::Individual::String", "Good ref" );
#Bitstring - 3 & 4
print "BitString...\n";
my $bs = Algorithm::Evolutionary::Individual::BitString->new(100);
is( ref $bs, "Algorithm::Evolutionary::Individual::BitString", , "Good ref" );
is( ref Algorithm::Evolutionary::Individual::Base::create( 'BitString', { length => 10 }), "Algorithm::Evolutionary::Individual::BitString", "Good ref" );
#Vector - 5..7
print "Vector...\n";
is( ref Algorithm::Evolutionary::Individual::Vector->new(10), "Algorithm::Evolutionary::Individual::Vector", "Good ref" );
is( ref Algorithm::Evolutionary::Individual::Base::create( 'Vector',
{ length => 20,
rangestart => -5,
rangeend => 5 }),
"Algorithm::Evolutionary::Individual::Vector", "Good ref" );
my $primitives = { sum => [2, -1, 1],
multiply => [2, -1, 1],
substract => [2, -1, 1],
divide => [2, -1, 1],
x => [0, -10, 10],
y => [0, -10, 10] };
is( ref Algorithm::Evolutionary::Individual::Tree->new( $primitives, 3 ), "Algorithm::Evolutionary::Individual::Tree", "Good ref" );
my $fitness = sub {
my $indi = shift;
return unpack("N", pack("B32", substr("0" x 32 . $indi->{'_str'}, -32)));
};
is( $bs->evaluate( $fitness ) > 0, 1, "Evaluation correct");
my $fitness_obj = new Algorithm::Evolutionary::Fitness::ONEMAX;
is( $bs->evaluate( $fitness_obj ) > 0, 1, "Evaluation object correct" );
my $bprime = new Algorithm::Evolutionary::Individual::String ['a'..'z'], 64;
print "Testing algorithms\n";
#test 33
my $m = new Algorithm::Evolutionary::Op::Bitflip; #Changes a single bit
my $initTemp = 2;
my $minTemp = 0.1;
my $freezer = new Algorithm::Evolutionary::Op::LinearFreezer( $initTemp );
my $numChanges = 7;
my $eval =
sub {
my $indi = shift;
my ( $x, $y ) = @{$indi->{_array}};
my $sqrt = sqrt( $x*$x+$y*$y);
return sin( $sqrt )/$sqrt;
};
my $sa = new Algorithm::Evolutionary::Op::SimulatedAnnealing( $eval, $m, $freezer, $initTemp, $minTemp, );
is( ref $sa, 'Algorithm::Evolutionary::Op::SimulatedAnnealing', "Good class" );
#test 34
my $c = new Algorithm::Evolutionary::Op::Crossover; #Classical 2-point crossover
my $replacementRate = 0.3; #Replacement rate
my $popSize = 20;
my $selector = new Algorithm::Evolutionary::Op::RouletteWheel $popSize; #One of the possible selectors
my $onemax = sub {
my $indi = shift;
my $total = 0;
my $len = $indi->size();
my $i = 0;
while ($i < $len ) {
$total += substr($indi->{'_str'}, $i, 1);
$i++;
}
return $total;
};
my @pop;
my $numBits = 20;
for ( 0..$popSize ) {
my $indi = new Algorithm::Evolutionary::Individual::BitString $numBits ; #Creates random individual
my $fitness = $onemax->( $indi );
$indi->Fitness( $fitness );
push( @pop, $indi );
}
#fitness
my $generation =
new Algorithm::Evolutionary::Op::GeneralGeneration( $onemax, $selector, [$m, $c], $replacementRate );
my @sortPop = sort { $b->Fitness() <=> $a->Fitness() } @pop;
my $bestIndi = $sortPop[0];
$generation->apply( \@sortPop );
is( $bestIndi->Fitness() <= $sortPop[0]->Fitness(), 1, "Fitness improvement" ); #fitness improves, but not always
# To be obsoleted
my $ggxml = $generation->asXML();
my $gprime = Algorithm::Evolutionary::Op::Base->fromXML( $ggxml );
is( $gprime->{_eval}( $pop[0] ) eq $generation->{_eval}( $pop[0] ) , 1, "XML" ); #Code snippets will never be exactly the same.
#Test 33 & 34
my $ez = new Algorithm::Evolutionary::Op::Easy $onemax;
my $ezxml = $ez->asXML();
my $ezprime = Algorithm::Evolutionary::Op::Base->fromXML( $ezxml );
is( $ezprime->{_eval}( $pop[0] ) eq $ez->{_eval}( $pop[0] ) , 1, "Code snippets" ); #Code snippets will never be exactly the same.
my $oldBestFitness = $bestIndi->Fitness();
$ez->apply( \@sortPop );
is( $sortPop[0]->Fitness() >= $oldBestFitness, 1, "Fitness improving");
#Test 35 & 36
my $g100 = new Algorithm::Evolutionary::Op::GenerationalTerm 10;
my $f = new Algorithm::Evolutionary::Op::FullAlgorithm $generation, $g100;
my $fxml = $f->asXML();
my $txml = $f->{_terminator}->asXML();
my $fprime = Algorithm::Evolutionary::Op::Base->fromXML( $fxml );
is( $txml eq $fprime->{_terminator}->asXML() , 1, "from XML" );
$oldBestFitness = $bestIndi->Fitness();
for ( @sortPop ) {
if ( !defined $_->Fitness() ) {
my $fitness = $onemax->( $_ );
$_->Fitness( $fitness );
}
}
$f->apply( \@sortPop );
is( $sortPop[0]->Fitness() >= $oldBestFitness, 1, "Improving fitness");
=head1 Copyright
This file is released under the GPL. See the LICENSE file included in this distribution,
CVS Info: $Date: 2010/09/24 08:39:07 $
$Header: /media/Backup/Repos/opeal/opeal/Algorithm-Evolutionary/t/general.t,v 3.1 2010/09/24 08:39:07 jmerelo Exp $
$Author: jmerelo $
$Revision: 3.1 $
$Name $
=cut