AI-ANN
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_Inline/build/AI/ANN/Neuron_6185/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/_Inline/build/benchmark_pl_03a5/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/_Inline/build/benchmark_pl_3d06/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/_Inline/build/benchmark_pl_6dc1/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/_Inline/build/benchmark_pl_ac1b/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/_Inline/build/benchmark_pl_b832/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/_Inline/build/benchmark_pl_b905/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/_Inline/build/benchmark_pl_c51b/Makefile view on Meta::CPAN
ci :
$(PERLRUN) "-MExtUtils::Manifest=maniread" \
-e "@all = keys %{ maniread() };" \
-e "print(qq{Executing $(CI) @all\n}); system(qq{$(CI) @all});" \
-e "print(qq{Executing $(RCS_LABEL) ...\n}); system(qq{$(RCS_LABEL) @all});"
# --- MakeMaker distmeta section:
distmeta : create_distdir metafile
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{META.yml} => q{Module meta-data (added by MakeMaker)}}) } ' \
-e ' or print "Could not add META.yml to MANIFEST: $${'\''@'\''}\n"' --
# --- MakeMaker distsignature section:
distsignature : create_distdir
$(NOECHO) cd $(DISTVNAME) && $(ABSPERLRUN) -MExtUtils::Manifest=maniadd -e 'eval { maniadd({q{SIGNATURE} => q{Public-key signature (added by MakeMaker)}}) } ' \
-e ' or print "Could not add SIGNATURE to MANIFEST: $${'\''@'\''}\n"' --
$(NOECHO) cd $(DISTVNAME) && $(TOUCH) SIGNATURE
cd $(DISTVNAME) && cpansign -s
examples/benchmark.pl view on Meta::CPAN
#!/usr/bin/perl
use strict;
use warnings;
use Benchmark qw(:all);
use AI::ANN::Neuron;
my %data = (id => 1, inputs => [ 4*rand()-2, 4*rand()-2, 4*rand()-2,
4*rand()-2, 4*rand()-2 ],
neurons => [ 4*rand()-2, 4*rand()-2, 4*rand()-2,
4*rand()-2, 4*rand()-2 ]);
my $object1 = new AI::ANN::Neuron ( %data, inline_c => 0 );
my $object2 = new AI::ANN::Neuron ( %data, inline_c => 1 );
my @data = ( [ 4*rand()-2, 4*rand()-2, 4*rand()-2, 4*rand()-2, 4*rand()-2 ],
[ 4*rand()-2, 4*rand()-2, 4*rand()-2, 4*rand()-2, 4*rand()-2 ]);
cmpthese( -1, { 'pure_perl' => sub{$object1->execute(@data)},
'inline_c' => sub{$object2->execute(@data)} });
use Math::Libm qw(erf M_PI);
use Inline C => <<'END_C';
#include <math.h>
double afunc[4001];
double dafunc[4001];
void generate_globals() {
int i;
for (i=0;i<=4000;i++) {
afunc[i] = 2 * (erf(i/1000.0-2));
The "Corresponding Source" for a work in object code form means all
the source code needed to generate, install, and (for an executable
work) run the object code and to modify the work, including scripts to
control those activities. However, it does not include the work's
System Libraries, or general-purpose tools or generally available free
programs which are used unmodified in performing those activities but
which are not part of the work. For example, Corresponding Source
includes interface definition files associated with source files for
the work, and the source code for shared libraries and dynamically
linked subprograms that the work is specifically designed to require,
such as by intimate data communication or control flow between those
subprograms and other parts of the work.
The Corresponding Source need not include anything that users
can regenerate automatically from other parts of the Corresponding
Source.
The Corresponding Source for a work in source code form is that
same work.
2. Basic Permissions.
lib/AI/ANN.pm view on Meta::CPAN
has 'rawpotentials' => (is => 'ro', isa => 'ArrayRef[Int]');
has 'minvalue' => (is => 'rw', isa => 'Int', default => 0);
has 'maxvalue' => (is => 'rw', isa => 'Int', default => 1);
has 'afunc' => (is => 'rw', isa => 'CodeRef', default => sub {sub {shift}});
has 'dafunc' => (is => 'rw', isa => 'CodeRef', default => sub {sub {1}});
has 'backprop_eta' => (is => 'rw', isa => 'Num', default => 0.1);
around BUILDARGS => sub {
my $orig = shift;
my $class = shift;
my %data;
if ( @_ == 1 && ref $_[0] eq 'HASH' ) {
%data = %{$_[0]};
} else {
%data = @_;
}
if (exists $data{'inputs'} && not exists $data{'input_count'}) {
$data{'input_count'} = $data{'inputs'};
delete $data{'inputs'}; # inputs is used later for the actual
# values of the inputs.
}
my $neuronlist = $data{'data'};
$data{'outputneurons'} = [];
$data{'network'} = [];
for (my $i = 0; $i <= $#{$neuronlist} ; $i++) {
push @{$data{'outputneurons'}}, $i
if $neuronlist->[$i]->{'iamanoutput'};
my @pass = (
$i,
$neuronlist->[$i]->{'inputs'},
$neuronlist->[$i]->{'neurons'} );
push @pass, $neuronlist->[$i]->{'eta_inputs'},
$neuronlist->[$i]->{'eta_neurons'}
if defined $neuronlist->[$i]->{'eta_neurons'};
$data{'network'}->[$i]->{'object'} =
new AI::ANN::Neuron( @pass );
}
delete $data{'data'};
return $class->$orig(%data);
};
sub execute {
my $self = shift;
my $inputs = $self->{'inputs'} = shift;
# Don't bother dereferencing $inputs only to rereference a lot
my $net = $self->{'network'}; # For less typing
my $lastneuron = $#{$net};
my @neurons = ();
lib/AI/ANN/Evolver.pm view on Meta::CPAN
has 'mutation_amount' => (is => 'rw', isa => 'CodeRef', default => sub{sub{2 * rand() - 1}});
has 'add_link_chance' => (is => 'rw', isa => 'Num', default => 0);
has 'kill_link_chance' => (is => 'rw', isa => 'Num', default => 0);
has 'sub_crossover_chance' => (is => 'rw', isa => 'Num', default => 0);
has 'gaussian_tau' => (is => 'rw', isa => 'CodeRef', default => sub{sub{1/sqrt(2*sqrt(shift))}});
has 'gaussian_tau_prime' => (is => 'rw', isa => 'CodeRef', default => sub{sub{1/sqrt(2*shift)}});
around BUILDARGS => sub {
my $orig = shift;
my $class = shift;
my %data;
if ( @_ == 1 && ref $_[0] eq 'HASH' ) {
%data = %{$_[0]};
} else {
%data = @_;
}
if ((not (ref $data{'mutation_amount'})) || ref $data{'mutation_amount'} ne 'CODE') {
my $range = $data{'mutation_amount'};
$data{'mutation_amount'} = sub { $range * (rand() * 2 - 1) };
}
return $class->$orig(%data);
};
sub crossover {
my $self = shift;
my $network1 = shift;
my $network2 = shift;
my $class = ref($network1);
my $inputcount = $network1->input_count();
my $minvalue = $network1->minvalue();
my $maxvalue = $network1->maxvalue();
my $afunc = $network1->afunc();
my $dafunc = $network1->dafunc();
# They better have the same number of inputs
$inputcount == $network2->input_count() || return -1;
my $networkdata1 = $network1->get_internals();
my $networkdata2 = $network2->get_internals();
my $neuroncount = $#{$networkdata1};
# They better also have the same number of neurons
$neuroncount == $#{$networkdata2} || return -1;
my $networkdata3 = [];
for (my $i = 0; $i <= $neuroncount; $i++) {
if (rand() < $self->{'sub_crossover_chance'}) {
$networkdata3->[$i] = { 'inputs' => [], 'neurons' => [] };
$networkdata3->[$i]->{'iamanoutput'} =
$networkdata1->[$i]->{'iamanoutput'};
for (my $j = 0; $j < $inputcount; $j++) {
$networkdata3->[$i]->{'inputs'}->[$j] =
(rand() > 0.5) ?
$networkdata1->[$i]->{'inputs'}->[$j] :
$networkdata2->[$i]->{'inputs'}->[$j];
# Note to self: Don't get any silly ideas about dclone()ing
# these, that's a good way to waste half an hour debugging.
}
for (my $j = 0; $j <= $neuroncount; $j++) {
$networkdata3->[$i]->{'neurons'}->[$j] =
(rand() > 0.5) ?
$networkdata1->[$i]->{'neurons'}->[$j] :
$networkdata2->[$i]->{'neurons'}->[$j];
}
} else {
$networkdata3->[$i] = dclone(
(rand() > 0.5) ?
$networkdata1->[$i] :
$networkdata2->[$i] );
}
}
my $network3 = $class->new ( 'inputs' => $inputcount,
'data' => $networkdata3,
'minvalue' => $minvalue,
'maxvalue' => $maxvalue,
'afunc' => $afunc,
'dafunc' => $dafunc);
return $network3;
}
sub mutate {
my $self = shift;
my $network = shift;
my $class = ref($network);
my $networkdata = $network->get_internals();
my $inputcount = $network->input_count();
my $minvalue = $network->minvalue();
my $maxvalue = $network->maxvalue();
my $afunc = $network->afunc();
my $dafunc = $network->dafunc();
my $neuroncount = $#{$networkdata}; # BTW did you notice that this
# isn't what it says it is?
$networkdata = dclone($networkdata); # For safety.
for (my $i = 0; $i <= $neuroncount; $i++) {
# First each input/neuron pair
for (my $j = 0; $j < $inputcount; $j++) {
my $weight = $networkdata->[$i]->{'inputs'}->[$j];
if (defined $weight && $weight != 0) {
if (rand() < $self->{'mutation_chance'}) {
$weight += (rand() * 2 - 1) * $self->{'mutation_amount'};
if ($weight > $self->{'max_value'}) {
$weight = $self->{'max_value'};
}
if ($weight < $self->{'min_value'}) {
$weight = $self->{'min_value'} + 0.000001;
}
}
lib/AI/ANN/Neuron.pm view on Meta::CPAN
has 'id' => (is => 'rw', isa => 'Int');
has 'inputs' => (is => 'rw', isa => 'ArrayRef', required => 1);
has 'neurons' => (is => 'rw', isa => 'ArrayRef', required => 1);
has 'eta_inputs' => (is => 'rw', isa => 'ArrayRef');
has 'eta_neurons' => (is => 'rw', isa => 'ArrayRef');
has 'inline_c' => (is => 'ro', isa => 'Int', required => 1, default => 1);
around BUILDARGS => sub {
my $orig = shift;
my $class = shift;
my %data;
if ( @_ >= 2 && ref $_[0] && ref $_[1]) {
%data = ('inputs' => $_[0], 'neurons' => $_[1]);
$data{'eta_inputs'} = $_[2] if defined $_[2];
$data{'eta_neurons'} = $_[3] if defined $_[3];
} elsif ( @_ >= 3 && ref $_[1] && ref $_[2]) {
%data = ('id' => $_[0], 'inputs' => $_[1], 'neurons' => $_[2]);
$data{'eta_inputs'} = $_[3] if defined $_[3];
$data{'eta_neurons'} = $_[4] if defined $_[4];
} elsif ( @_ == 1 && ref $_[0] eq 'HASH' ) {
%data = %{$_[0]};
} else {
%data = @_;
}
if (ref $data{'inputs'} eq 'HASH') {
my @temparray;
foreach my $i (keys %{$data{'inputs'}}) {
if (defined $data{'inputs'}->{$i} && $data{'inputs'}->{$i} != 0) {
$temparray[$i]=$data{'inputs'}->{$i};
}
}
$data{'inputs'}=\@temparray;
}
if (ref $data{'neurons'} eq 'HASH') {
my @temparray;
foreach my $i (keys %{$data{'neurons'}}) {
if (defined $data{'neurons'}->{$i} && $data{'neurons'}->{$i} != 0) {
$temparray[$i]=$data{'neurons'}->{$i};
}
}
$data{'neurons'}=\@temparray;
}
if (defined $data{'eta_inputs'} && ref $data{'eta_inputs'} eq 'HASH') {
my @temparray;
foreach my $i (keys %{$data{'eta_inputs'}}) {
if (defined $data{'eta_inputs'}->{$i} && $data{'eta_inputs'}->{$i} != 0) {
$temparray[$i]=$data{'eta_inputs'}->{$i};
}
}
$data{'eta_inputs'}=\@temparray;
}
if (defined $data{'eta_neurons'} && ref $data{'eta_neurons'} eq 'HASH') {
my @temparray;
foreach my $i (keys %{$data{'eta_neurons'}}) {
if (defined $data{'eta_neurons'}->{$i} && $data{'eta_neurons'}->{$i} != 0) {
$temparray[$i]=$data{'eta_neurons'}->{$i};
}
}
$data{'eta_neurons'}=\@temparray;
}
foreach my $i (0..$#{$data{'inputs'}}) {
$data{'inputs'}->[$i] ||= 0;
}
foreach my $i (0..$#{$data{'neurons'}}) {
$data{'neurons'}->[$i] ||= 0;
}
foreach my $i (0..$#{$data{'eta_inputs'}}) {
$data{'eta_inputs'}->[$i] ||= 0;
}
foreach my $i (0..$#{$data{'eta_neurons'}}) {
$data{'eta_neurons'}->[$i] ||= 0;
}
return $class->$orig(%data);
};
sub ready {
my $self = shift;
my $inputs = shift;
my $neurons = shift;
if (ref $neurons eq 'HASH') {
my @temparray;
foreach my $i (keys %$neurons) {
t/00_initialize.t view on Meta::CPAN
use Test::More tests => 9;
BEGIN { use_ok('AI::ANN');
use_ok('AI::ANN::Neuron');
use_ok('AI::ANN::Evolver'); };
#########################
# Insert your test code below, the Test::More module is use()ed here so read
# its man page ( perldoc Test::More ) for help writing this test script.
$network=new AI::ANN ('inputs' => 1, 'data' => [{ iamanoutput => 1, inputs => {0 => 1}, neurons => {}}]);
ok(defined $network, "new() works");
ok($network->isa("AI::ANN"), "Right class");
$neuron=new AI::ANN::Neuron (0, {0 => 1}, {});
ok(defined $neuron, "new() works");
ok($neuron->isa("AI::ANN::Neuron"), "Right class");
$evolver=new AI::ANN::Evolver ();
t/02_network_basic.t view on Meta::CPAN
use Test::More tests => 25;
BEGIN { use_ok('AI::ANN');
use_ok('AI::ANN::Neuron'); };
#########################
# Insert your test code below, the Test::More module is use()ed here so read
# its man page ( perldoc Test::More ) for help writing this test script.
$network=new AI::ANN ('inputs'=>1, 'data'=>[{ iamanoutput => 1, inputs => {0 => 1}, neurons => {}}], 'maxvalue' => 10);
ok(defined $network, "new() works");
ok($network->isa("AI::ANN"), "Right class");
ok($out=$network->execute([1]), "executed and still alive");
is($#{$out}, 0, "execute() output for a single neuron is the right length");
is($out->[0], 1, "execute() output for a single neuron has the correct value");
($inputs, $neurons, $outputs) = $network->get_state();
is($#{$inputs}, 0, "get_state inputs is correct length");
is($inputs->[0], 1, "get_state inputs returns correct element 0");
is($#{$neurons}, 0, "get_state neurons is correct length");
is($neurons->[0], 1, "get_state neurons returns correct element 0");
is($#{$outputs}, 0, "get_state outputs is correct length");
is($outputs->[0], 1, "get_state outputs returns correct element 0");
$network=new AI::ANN ('inputs'=>1, 'data'=>[{ iamanoutput => 0, inputs => {0 => 2}, neurons => {}},
{ iamanoutput => 1, inputs => {}, neurons => {0 => 2}}], 'maxvalue' => 10);
ok(defined $network, "new() works");
ok($network->isa("AI::ANN"), "Right class");
ok($out=$network->execute([1]), "executed and still alive");
is($#{$out}, 0, "execute() output for two neurons is the right length");
is($out->[0], 4, "execute() output for two neurons has the correct value");
t/03_evolver_basic.t view on Meta::CPAN
BEGIN { use_ok('AI::ANN');
use_ok('AI::ANN::Evolver'); };
#########################
# Insert your test code below, the Test::More module is use()ed here so read
# its man page ( perldoc Test::More ) for help writing this test script.
# This test basically works by crossing a network with itself and making sure nothing changes
$network1=new AI::ANN ('inputs'=>1, 'data'=>[{ iamanoutput => 1, inputs => {0 => 1}, neurons => {}}]);
$network2=new AI::ANN ('inputs'=>1, 'data'=>[{ iamanoutput => 1, inputs => {0 => 1}, neurons => {}}]);
ok(defined $network1, "new() works");
ok($network1->isa("AI::ANN"), "Right class");
ok(defined $network2, "new() works");
ok($network2->isa("AI::ANN"), "Right class");
ok($out=$network1->execute([1]), "executed and still alive");
is($#{$out}, 0, "execute() output for a single neuron is the right length before crossover");
is($out->[0], 1, "execute() output for a single neuron has the correct value before crossover");
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