AI-FuzzyEngine

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lib/AI/FuzzyEngine.pm  view on Meta::CPAN

    # TODO: Rapid return if @_ == 1 (isa piddle)
    # TODO: join "-", ndims -> Schnellcheck auf gleiche Dim.

    # All elements must get piddles
    my @pdls  = map { PDL::Core::topdl($_) } @vals;

    # Get size of wrapping piddle (using a trick)
    # applying valid expansion rules for element wise operations
    my $zeros = PDL->pdl(0);
    #        v-- does not work due to threading mechanisms :-((
    # $zeros += $_ for @pdls;
    # Avoid threading!
    for my $p (@pdls) {
        croak "Empty piddles are not allowed" if $p->isempty();
        eval { $zeros = $zeros + $p->zeros(); 1
            } or croak q{Can't expand piddles to same size};
    }

    # Now, cat 'em by expanding them on the fly
    my $vals = PDL::cat( map {$_ + $zeros} @pdls );
    return $vals;
};

lib/AI/FuzzyEngine.pm  view on Meta::CPAN

    $green->ok(       $saturation->crit() );
    $green->increase( $saturation->over() );

    # All sets provide their respective membership degrees: 
    my $saturation_is_over = $saturation->over(); # This is no defuzzification!
    my $green_is_ok        = $green->ok();

    # Defuzzification ( is a matter of the fuzzy variable )
    my $delta_green = $green->defuzzify(); # -5 ... 5

=head2 Using PDL and its threading capability

    use PDL;
    use AI::FuzzyEngine;

    # (Probably a stupide example)
    my $fe        = AI::FuzzyEngine->new();

    # Declare variables as usual
    my $severity  = $fe->new_variable( 0 => 10,
                          low  => [0, 1, 3, 1, 5, 0       ],

lib/AI/FuzzyEngine.pm  view on Meta::CPAN

    $problem->no( $fe->not( $problem->yes )  );

    # Fuzzy results are represented by the membership degrees of sets 
    print 'Problem yes: ', $problem->yes,  "\n";
    # [
    #  [         0 0.33333333 0.33333333 0.33333333]
    #  [         0        0.5          1          1]
    # ]

    # Defuzzify the output variables
    # Caveat: This includes some non-threadable operations up to now
    my $problem_ratings = $problem->defuzzify();
    print 'Problems rated: ', $problem_ratings;
    # [
    #  [         0 0.60952381 0.60952381 0.60952381]
    #  [         0       0.75          1          1]
    # ]

=head1 EXPORT

Nothing is exported or exportable.

lib/AI/FuzzyEngine.pm  view on Meta::CPAN

calculation goes as follows:

    # Get the common dimensions
    my $zeros = PDL->pdl(0);
    # Note: $zeros += $_->zeros() for @pdls does not work here
    $zeros = $zeros + $_->zeros() for @pdls;

    # Expand all piddles
    @pdls = map {$_ + $zeros} @pdls;

Defuzzification uses some heavy non-threading code,
so there might be a performance penalty for big piddles. 

=head2 Todos

=over 2

=item Add optional alternative implementations of fuzzy operations

=item More checks on input arguments and allowed method calls

=item PDL awareness: Use threading in C<< $variable->defuzzify >>

=item Divide tests into API tests and test of internal functions

=back

=head1 CAVEATS / BUGS

This is my first module.
I'm happy about feedback that helps me to learn
and improve my contributions to the Perl ecosystem.

t/02-fuzzyEngine-pdl_aware.t  view on Meta::CPAN

    $problem->yes( $severity->high,  $threshold->low );
    $problem->no( $fe->not( $problem->yes )  );

#    print 'Problem yes: ', $problem->yes,  "\n";
    # [
    #  [         0 0.33333333 0.33333333 0.33333333]
    #  [         0        0.5          1          1]
    # ]

    # Defuzzify the output variables
    # Caveat: This includes some non-threadable operations up to now
    my $problem_ratings = $problem->defuzzify();
#    print 'Problems rated: ', $problem_ratings;
    # [
    #  [         0 0.60952381 0.60952381 0.60952381]
    #  [         0       0.75          1          1]
    # ]

    ok( 1, 'POD synopsis' );
};