AI-NeuralNet-FastSOM

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Changes  view on Meta::CPAN

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        - added original AI::NN::SOM test suite (and it works!)
 
0.04  Sat Jul 18 16:45:27 2009
        - removed dependence on Inline::C
        - minor refactor
 
0.03  Sat Jul 18 09:30:08 2009
        - created wrappers for most c-level stuff
 
0.02  Wed Jul 15 18:56:13 2009
        - moved data structures into C structs
 
0.01  Thu Jul  2 09:07:01 2009
        - original version; created by h2xs 1.23 with options
                -AXn AI::NeuralNet::FastSOM

FastSOM.h  view on Meta::CPAN

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 *                              +---Vector---+---NV
 *                              |             \--NV
 *                               \--Vector---+---NV
 *                                            \--NV
 * 
 * References
 * ==========
 * 
 * Each of Rect, Map, Array, and Vector contains a member 'ref' which is
 * an SV* pointing to an RV. The RV can be returned directly to perl-land
 * after being blessed into its respective class.
 * 
 * The RV references an SV containing an IV. The IV is set to the base
 * address of its component structure. This is so the class code can know
 * which instance of the class is being referred to on callback.
 * 
 * The reference count of the SV has its initial reference count set to one,
 * representing its parents ownership. If a parent dies or a perl-land
 * reference is taken of any componenet, its reference count should
 * be adjusted accordingly.
 * 
 * When the count reaches zero perl will call the classes DESTROY method,
 * at which point we can decrease the reference count on each child and
 * free the component structure.
 * 
 * The intent of all this reference count tom-foolery is to keep the
 * component structures from disappearing from underneath perl-land
 * references to them. As a bonus, we get a neat destruction mechanism
 * without having to reimplement OOP in C.
 */
 
/*
 * SOM_Vector : holds Z NVs
 *
 * should be allocated:
 *      sizeof(SOM_Vector) + sizeof(NV)*(Z-1)
 *

FastSOM.h  view on Meta::CPAN

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        NV element;
} SOM_Vector;
 
/*
 * SOM_Array : holds Y ptrs to SOM_Vector thingys
 *
 * should be allocated:
 *      sizeof(SOM_Array) + sizeof(SOM_Vector*)*(Y-1)
 *
 * 'ref' and 'vector' elements similar in functionality to the 'ref' and
 * 'element' members, respectively, of the SOM_Vector struct.
 *
 * 'Y' is the number of SOM_Vector pointers in the 'vector' array.
 *
 * 'Z' is provided here only for propogation down the line in creating
 * the SOM_Vectors.
 */
typedef struct {
        SV *ref;
        IV Y;
        IV Z;
        SOM_Vector *vector;
} SOM_Array;
 
/*
 * SOM_Map : holds X ptrs to SOM_Array thingys
 *
 * should be allocated:
 *      sizeof(SOM_Map) + sizeof(SOM_Array*)*(X-1)
 *
 * 'ref' and 'array' are similar in functionality to the 'ref' and 'element'
 * members, respectively, of the SOM_Vector struct.
 *
 * 'X' is the number of SOM_Array pointers in the 'array' array.
 *
 * 'Y' and 'Z' are provided here only for propagation down the line in
 * creation of SOM_Array and SOM_Vector structs.
 */
typedef struct {
        SV *ref;
        IV X;
        IV Y;

META.json  view on Meta::CPAN

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   },
   "name" : "AI-NeuralNet-FastSOM",
   "no_index" : {
      "directory" : [
         "t",
         "inc"
      ]
   },
   "prereqs" : {
      "build" : {
         "requires" : {
            "ExtUtils::MakeMaker" : "0"
         }
      },
      "configure" : {
         "requires" : {
            "ExtUtils::MakeMaker" : "0"
         }
      },
      "runtime" : {
         "requires" : {
            "Storable" : "0"
         }
      }
   },
   "release_status" : "stable",
   "version" : "0.19",
   "x_serialization_backend" : "JSON::PP version 2.27300"
}

META.yml  view on Meta::CPAN

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---
abstract: 'Perl extension for fast Kohonen Maps'
author:
  - 'Rick Myers <jrm@cpan.org>'
build_requires:
  ExtUtils::MakeMaker: '0'
configure_requires:
  ExtUtils::MakeMaker: '0'
dynamic_config: 1
generated_by: 'ExtUtils::MakeMaker version 7.1, CPAN::Meta::Converter version 2.150005'
license: perl
meta-spec:
  url: http://module-build.sourceforge.net/META-spec-v1.4.html
  version: '1.4'
name: AI-NeuralNet-FastSOM
no_index:
  directory:
    - t
    - inc
requires:
  Storable: '0'
version: '0.19'
x_serialization_backend: 'CPAN::Meta::YAML version 0.012'

examples/eigenvector_initialization.pl  view on Meta::CPAN

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sub _find_num {
    my $v = shift;
    my $l = shift;
    for my $i (0..$#$l) {
        return $i if $v == $l->[$i];
    }
    return undef;
}
 
        for (@es_idx) {                                                  # from the highest values downwards, take the index
            push @training_vectors, [ list $E->dice($_) ] ;              # get the corresponding vector
        }
    }
 
    $nn->initialize (@training_vectors[0..0]);                           # take only the biggest ones (the eigenvalues are big, actually)
#warn $nn->as_string;
    my @mes = $nn->train ($epochs, @vs);
    warn "eigen:    length until error is < $epsilon ". scalar (grep { $_ >= $epsilon } @mes);
}
 
__END__

examples/load_save.pl  view on Meta::CPAN

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sub _find_num {
    my $v = shift;
    my $l = shift;
    for my $i (0..$#$l) {
        return $i if $v == $l->[$i];
    }
    return undef;
}
 
        for (@es_idx) {                                                  # from the highest values downwards, take the index
            push @training_vectors, [ list $E->dice($_) ] ;              # get the corresponding vector
        }
    }
 
    $nn->initialize (@training_vectors[0..0]);                           # take only the biggest ones (the eigenvalues are big, actually)
#warn $nn->as_string;
    my @mes = $nn->train ($epochs, @vs);
    warn "eigen:    length until error is < $epsilon ". scalar (grep { $_ >= $epsilon } @mes);
}
 
__END__

lib/AI/NeuralNet/FastSOM/Hexa.pm  view on Meta::CPAN

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Example:
 
   my $m = $nn->map;
   for my $x (0 .. $nn->diameter -1) {
       for my $y (0 .. $nn->diameter -1){
           warn "vector at $x, $y: ". Dumper $m->[$x]->[$y];
       }
   }
 
This array represents a hexagon like this (ASCII drawing is so cool):
 
               <0,0>
           <0,1>   <1,0>
       <0,2>   <1,1>   <2,0>
   <0,3>   <1,2>   <2,1>   <3,0>
  ...............................
 
 
=item I<as_string>

lib/AI/NeuralNet/FastSOM/Rect.pm  view on Meta::CPAN

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=head2 Methods
 
=over
 
=item I<map>
 
I<$m> = I<$nn>->map
 
This method returns the 2-dimensional array of vectors in the grid
(as a reference to an array of references to arrays of vectors). The
representation of the 2-dimensional array is straightforward.
 
Example:
 
   my $m = $nn->map;
   for my $x (0 .. 5) {
       for my $y (0 .. 4){
           warn "vector at $x, $y: ". Dumper $m->[$x]->[$y];
       }
   }

t/rect.t  view on Meta::CPAN

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    my $v2 = $nn3->map->[0]->[0];
    is( $v, $v2, 'vector eq' );
 
    my $v3 = $nn2->map->[0][0];
    is( $v, $v3, 'vector shorter' );
 
    my $m = $nn->map;
    $m->[0][0][0] = 3.245;
    is( $m->[0][0][0], 3.245, 'element set' );
    $m->[0][0][0] = 1.25;
    is( $m->[0][0][0], 1.25, 'element reset' );
    $m->[0][0][1] = 4.8;
    is( $m->[0][0][1], 4.8, 'element set z' );
    $m->[0][0][1] = 2.6;
    is( $m->[0][0][1], 2.6, 'element reset z' );
    $m->[0][1][0] = 8.9;
    is( $m->[0][1][0], 8.9, 'element set y' );
    $m->[0][1][0] = 1.2;
    is( $m->[0][1][0], 1.2, 'element reset y' );
    $m->[1][0][0] = 5.4;
    is( $m->[1][0][0], 5.4, 'element set z' );
    $m->[1][0][0] = 3.23;
    is( $m->[1][0][0], 3.23, 'element reset z');
 
    $m->[4][5][2] = 2.29;
    is( $m->[4][5][2], 2.29, 'last element set' );
    is( $m->[-1][5][2], 2.29, 'negative x' );
    is( $m->[4][-1][2], 2.29, 'negative y' );
    is( $m->[4][5][-1], 2.29, 'negative z' );
    is( $m->[-1][-1][-1], 2.29, 'negative all' );
}
 
{