AI-FuzzyEngine
view release on metacpan or search on metacpan
Tests re-factored
requires perl 5.8.9
POD improved, PDL sections added
0.2.1 2013-02-14
Bug in test fixed (use PDL removed)
versioning of Set and Variable adapted
0.2.2 2013-02-27
Declaring a version with version->declare() instead of qw()
A variable can change its sets' membership functions
(e.g. within optimisation routines)
Providing $fe->true() and $fe->false()
lib/AI/FuzzyEngine.pm view on Meta::CPAN
ok => [ -2, 0 0, 1, 2, 0 ],
increase => [ 0, 0, 2, 1, 5, 1],
);
# Reset FuzzyEngine (resets all variables)
$fe->reset();
# Reset a fuzzy variable directly
$flow->reset;
# Membership functions can be changed via the set's variable.
# This might be useful during parameter identification algorithms
# Changing a function resets the respective variable.
$flow->change_set( med => [500, 0, 1000, 1, 1500, 0] );
# Fuzzification of input variables
$flow->fuzzify( 600 );
$cap->fuzzify( 1000 );
# Membership degrees of the respective sets are now available:
my $flow_is_small = $flow->small(); # 0.8
my $flow_is_med = $flow->med(); # 0.2
my $flow_is_huge = $flow->huge(); # 0.0
lib/AI/FuzzyEngine.pm view on Meta::CPAN
The fuzzy engine C<$fe> has all variables registered
that have been created by its C<new_variable> method.
A variable can be defuzzified:
my $out_value = $var->defuzzify();
Membership functions can be replaced via a set's variable:
$var->change_set( $name_of_set => [$x11n, $y11n, $x12n, $y12n, ... ] );
The variable will be reset when replacing a membership function
of any of its sets.
Interdependencies with other variables are not checked
(it might happen that the results of any rules are no longer valid,
so it needs some recalculations).
Sometimes internal variables are used that need neither fuzzification
nor defuzzification.
They can be created by a simplified call to C<new_variable>:
lib/AI/FuzzyEngine.pm view on Meta::CPAN
This is my first module.
I'm happy about feedback that helps me to learn
and improve my contributions to the Perl ecosystem.
Please report any bugs or feature requests to
C<bug-ai-fuzzyengine at rt.cpan.org>, or through
the web interface at
L<http://rt.cpan.org/NoAuth/ReportBug.html?Queue=AI-FuzzyEngine>.
I will be notified, and then you'll
automatically be notified of progress on your bug as I make changes.
=head1 SUPPORT
You can find documentation for this module with the perldoc command.
perldoc AI::FuzzyEngine
=head1 AUTHOR
Juergen Mueck, jmueck@cpan.org
lib/AI/FuzzyEngine/Set.pm view on Meta::CPAN
};
$fun->[0] = \@x;
$fun->[1] = \@y;
return $fun;
}
sub synchronize_funs {
my ($class, $funA, $funB) = @_;
# change $funA, $funB directly, use their references
# \@x and \@y as part of $fun will be replaced nevertheless
my @xA = _x_of $funA;
my @yA = _y_of $funA;
my @xB = _x_of $funB;
my @yB = _y_of $funB;
croak '$funA is empty' unless @xA;
croak '$funB is empty' unless @xB;
lib/AI/FuzzyEngine/Set.pm view on Meta::CPAN
$y[$ix] = $max;
};
return @y;
}
sub _minmax_of_pair_of_funs {
my ($class, $factor, $funA, $funB) = @_;
# $factor > 0: 'max' operation
# $factor < 0: 'min' operation
# synchronize interpolation points (original functions are changed)
$class->synchronize_funs( $funA, $funB );
my @x = _x_of $funA;
my @yA = _y_of $funA;
my @yB = _y_of $funB;
# my @y = List::MoreUtils::pairwise { $a*$factor > $b*$factor ?
# $a : $b
# } @yA, @yB;
my @y = _max_of( $factor, \@yA, \@yB ); # faster than pairwise
lib/AI/FuzzyEngine/Set.pm view on Meta::CPAN
return $self->{degree} = $self->_interpol( $fun => $val );
}
sub reset {
my ($self) = @_;
$self->{degree} = 0;
$self;
}
# Replace a membership function
# To be called by variable->change_set( 'setname' => $new_fun );
sub replace_memb_fun {
my ($self, $new_fun) = @_;
$self->{memb_fun} = $new_fun;
return;
}
1;
=pod
lib/AI/FuzzyEngine/Variable.pm view on Meta::CPAN
} @funs, @degrees;
return \@clipped;
}
sub reset {
my ($self) = @_;
$_->reset() for values %{$self->sets};
return $self;
}
sub change_set {
my ($self, $setname, $new_memb_fun) = @_;
my $set = $self->set( $setname );
# Some checks
croak "Set $setname does not exist" unless defined $set;
croak 'Variable is internal' if $self->is_internal;
# Convert to internal representation
my $fun = $self->_curve_to_fun( $new_memb_fun );
lib/AI/FuzzyEngine/Variable.pm view on Meta::CPAN
# register the new method to $self (the fuzzy variable)
no strict 'refs';
*{ $set_name } = $method;
};
}
sub _non_is_a_piddle {
return List::MoreUtils::none {ref $_ eq 'PDL'} @_;
}
# Might change for Variables inherited from AI::FuzzyEngine::Variable:
sub _class_of_set { 'AI::FuzzyEngine::Set' }
sub _curve_to_fun {
# Convert input format for membership functions
# to internal representation:
# [$x11, $y11, $x12, $y12, ... ]
# --> [ $x11, $x12, ... ] => [$y11, $y12, ... ] ]
my ($class, $curve) = @_;
my %points = @$curve;
my @x = sort {$a<=>$b} keys %points;
t/01-fuzzyEngine.t view on Meta::CPAN
is( $degree, 0.1, 'and / or for degree of low work' );
my $w = $var_class->new( $fe,
0 => 2,
'low' => [0, 1],
'med' => [0, 0],
);
# $v and $w have a 'low' function.
# Are they independent with regard to degree?
is( $v->low, 0.1, 'degree for low unchanged from other variables' );
is( $w->low, 0, 'degree for low of the new variable is independent');
};
subtest "$var_class order of sets" => sub {
my @range = 0..99;
my @list_of_sets = map { ("s_$_" => [$_,1]) } @range;
my $x = $var_class->new( $fe, 0 => 1, @list_of_sets );
my @indexes = map {/(\d+)/} $x->set_names;
t/01-fuzzyEngine.t view on Meta::CPAN
[ [0, 10] => [0.5, 0.5] ],
'even if constant',
);
is_deeply( $v->sets->{high}->memb_fun(),
[ [0, 10] => [0.25, 0.75] ],
'... limits even when crossing edges',
);
};
subtest "$var_class change_set" => sub {
my $v = $var_class->new( $fe,
0 => 10,
'low' => [ 3, 1, 6, 0],
# becomes [ [0, 3, 6, 10] => [1, 1, 0, 0] ],
'high' => [ -5, 0, 15, 1],
);
$v->fuzzify( 5 ); # $v->low > 0 && $v->high > 0
my $new_memb_fun = [2, 1, 8, 0];
$v->change_set( low => $new_memb_fun );
is_deeply( $v->sets->{low}->memb_fun(),
[ [0, 2, 8, 10] => [1, 1, 0, 0] ],
'change_set works and adapts borders in x',
);
is_deeply( [$v->low, $v->high], [0, 0], 'change_set resets the variable' );
throws_ok { $v->change_set( 'wrong_set' )
} qr/set/i, 'change_set checks correct set name';
1;
};
subtest "$var_class fuzzification and defuzzification" => sub {
my $v = $var_class->new( $fe,
0 => 10,
'low' => [ 3, 1, 6, 0],
'med' => [ 5, 0.5],
t/01-fuzzyEngine.t view on Meta::CPAN
is( $degree, 0.1, 'and / or for degree of low work' );
$v->reset;
is( $v->low, 0, 'reset works' );
# Throw errors!
throws_ok { $v->fuzzify(0)
} qr/internal/, 'Checks illegal fuzzify call';
throws_ok { $v->defuzzify
} qr/internal/, 'Checks illegal defuzzify call';
throws_ok { $v->change_set( low => [[]=>[]] )
} qr/internal/i, 'Blocks change_set';
};
$fe = $class->new();
subtest "$class as factory" => sub {
my $v = $fe->new_variable( 0 => 10,
'low' => [0, 1, 10, 0],
'high' => [0, 0, 10, 1],
);
t/01-fuzzyEngine.t view on Meta::CPAN
$v->low( 0.1 );
$w->low( 0.2 );
my $v_resetted = $v->reset;
isa_ok( $v_resetted,
$var_class,
'What variable->reset returns',
) or exit;
is( $v->low, 0.0, 'Variable can be resetted' );
is( $w->low, 0.2, 'Other variables stay unchanged' );
my $fe_resetted = $fe->reset();
isa_ok( $fe_resetted,
$class,
'What fuzzyEngine->reset returns',
);
is( $w->low, 0.0, 'FuzzyEngine resets all variables' );
};
subtest 'synopsis' => sub {
t/01-fuzzyEngine.t view on Meta::CPAN
ok => [ -2, 0, 0, 1, 2, 0 ],
increase => [ 0, 0, 2, 1, 5, 1],
);
# Reset FuzzyEngine (resets all variables)
$fe->reset();
# Reset a fuzzy variable directly
$flow->reset;
# Membership functions can be changed via the set's variable.
# This might be useful during parameter identification algorithms
# Changing a function resets the respective variable.
$flow->change_set( med => [500, 0, 1000, 1, 1500, 0] );
# Fuzzification of input variables
$flow->fuzzify( 600 );
$cap->fuzzify( 1000 );
# Membership degrees of the respective sets are now available:
my $flow_is_small = $flow->small(); # 0.8
my $flow_is_med = $flow->med(); # 0.2
my $flow_is_huge = $flow->huge(); # 0.0
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