AI-ParticleSwarmOptimization-Pmap
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1.007 Mon, 09 Jan 2023 22:08:55 +0100
- First release with Dist::Zilla.
1.006 Thu, 05 Jan 2023 11:16:26 +0100
- Fix: MANIFEST
1.005 Mon, 17 Oct 2022 18:51:37 +0200
- Fix in a range of randomness. Thanks to Mario Roy :-)
1.004 Sun, 16 Oct 2022 16:19:22 +0200
- Fix of testing set.
1.003 Sun, 16 Oct 2022 16:13:19 +0200
- Fix of testing set.
1.002 Fri, 07 Oct 2022 18:19:01 +0200
- Fix of version number.
1.001 Fri, 07 Oct 2022 14:12:56 +0200
- Fix in a POD.
1.000 Fri, 07 Oct 2022 10:33:30 +0200
- First release.
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Makefile.PL view on Meta::CPAN
},
"DISTNAME" => "AI-ParticleSwarmOptimization-Pmap",
"LICENSE" => "lgpl",
"NAME" => "AI::ParticleSwarmOptimization::Pmap",
"PREREQ_PM" => {
"AI::ParticleSwarmOptimization" => "1.006",
"List::Util" => 0,
"Parallel::parallel_map" => "0.02"
},
"VERSION" => "1.008",
"test" => {
"TESTS" => "t/*.t"
}
);
my %FallbackPrereqs = (
"AI::ParticleSwarmOptimization" => "1.006",
"List::Util" => 0,
"Parallel::parallel_map" => "0.02"
);
-posMin: number, optional
Minimum coordinate value for any dimension in the hyper space.
Defaults to --posMax (if -posMax is negative -posMin should be set
more negative).
-randSeed: number, optional
Seed for the random number generator. Useful if you want to rerun
an optimization, perhaps for benchmarking or test purposes.
-randStartVelocity: boolean, optional
Set true to initialize particles with a random velocity. Otherwise
particle velocity is set to 0 on initalization.
A range based on 1/100th of --posMax - -posMin is used for the
initial speed in each dimension of the velocity vector if a random
start velocity is used.
lib/AI/ParticleSwarmOptimization/Pmap.pm view on Meta::CPAN
Maximum coordinate value for any dimension in the hyper space. Defaults to 100.
=item I<-posMin>: number, optional
Minimum coordinate value for any dimension in the hyper space. Defaults to
-I<-posMax> (if I<-posMax> is negative I<-posMin> should be set more negative).
=item I<-randSeed>: number, optional
Seed for the random number generator. Useful if you want to rerun an
optimization, perhaps for benchmarking or test purposes.
=item I<-randStartVelocity>: boolean, optional
Set true to initialize particles with a random velocity. Otherwise particle
velocity is set to 0 on initalization.
A range based on 1/100th of -I<-posMax> - I<-posMin> is used for the initial
speed in each dimension of the velocity vector if a random start velocity is
used.
t/01_pso_multi.t view on Meta::CPAN
#!/usr/bin/perl
use strict;
use warnings;
use Test::More;
use lib '../lib'; # For development testing
use AI::ParticleSwarmOptimization::Pmap;
=head1 NAME
AI::ParticleSwarmOptimization::Pmap test suite
=head1 DESCRIPTION
Test AI::ParticleSwarmOptimization::Pmap
=cut
plan (tests => 1);
# Calculation tests.
my $pso = AI::ParticleSwarmOptimization::Pmap->new (
-fitFunc => \&calcFit,
-dimensions => 10,
-iterations => 10,
-numParticles => 1000,
# only for many-core version # the best if == $#cores of your system
# selecting best value if undefined
-workers => 4,
);
( run in 1.196 second using v1.01-cache-2.11-cpan-87723dcf8b7 )