AI-Logic-AnswerSet

 view release on metacpan or  search on metacpan

lib/AI/Logic/AnswerSet.pm  view on Meta::CPAN

		        my @tmp = split(', ', $line);
			push @arr, @tmp;
		}

	}

	return @arr;
}

sub statistics {	# Return an array of hashes in which the statistics of every predicate of every answerSets are stored
			# If a condition of comparison is specified(number of predicates) it returns the answer sets that satisfy
			# that condition 

	my @as = @{$_[0]};
	my @pred = @{$_[1]};
	my @num = @{$_[2]};
	my @operators = @{$_[3]};

	my @sets;
	my @ans;
	
	my $countAS = 0;
	my @stat;

	my $countPred;

	foreach my $elem (@as) {

		if($elem =~ /(\w+).*\n/) {
			push @{$sets[$countAS]}, $elem;
			if(_existsPred($1,\@pred)) {
				$stat[$countAS]{$1} += 1;
				$countAS += 1;
			}
		}

		elsif($elem =~ /(\w+).*/) {
			push @{$sets[$countAS]}, $elem;
			if(_existsPred($1,\@pred)) {
				$stat[$countAS]{$1} += 1;
			}
		}
	}

	my $comparison = 0;
	if(@num and @operators) {
		$comparison = 1;
	}

lib/AI/Logic/AnswerSet.pm  view on Meta::CPAN

				if(_evaluate($t,$num[$i],$operators[$i])) {
					$countPred++;
				}
				else {
					$countPred = 0;
					break;
				}
			}

			if($countPred == $size) {
				push @ans , $sets[$j];
			}
			$countPred = 0;
		}
		return @ans;

	}

	return @stat;
}

lib/AI/Logic/AnswerSet.pm  view on Meta::CPAN

This method allows to get one of the results of C<iterativeExec>.

	my @outputs = AI::Logic::AnswerSet::iterativeExec("3col.txt","nodes.txt","./instances");
	my @out = AI::Logic::AnswerSet::selectOutput(\@outputs,0);

In this case the first output is selected.

=head3 getASFromFile

Parses the output of a DLV execution saved in a file and gather the answer sets.

	AI::Logic::AnswerSet::executeFromFileAndSave("outprog.txt","dlvprog.txt","");
	my @result = AI::Logic::AnswerSet::getASFromFile("outprog.txt");

=head3 getAS

Parses the output of a DLV execution and gather the answer sets.

	my @out = AI::Logic::AnswerSet::singleExec("3col.txt","nodes.txt","edges.txt","-nofacts");
	my @result = AI::Logic::AnswerSet::getAS(@out);

=head3 mapAS

Parses the new output in order to save and organize the results into a hashmap.

	my @out = AI::Logic::AnswerSet::singleExec("3col.txt","nodes.txt","edges.txt","-nofacts");
	my @result = AI::Logic::AnswerSet::getAS(@out);
	my @mappedAS = AI::Logic::AnswerSet::mapAS(@result);

The user can set some constraints on the data to be saved in the hashmap, such as predicates, or answer sets, or both.

	my @mappedAS = AI::Logic::AnswerSet::mapAS(@result,@predicates,@answerSets);

For instance, think about the 3-colorability problem: imagine to 
have the edges in the hashmap, and to print the edges contained in the third answer set
returned by DLV; this is an example of the print instruction, useful to understand how
the hashmap works:

	print "Edges: @{$mappedAS[2]{edge}}\n";

In this case, we are printing the array containing the predicate "edge".

=head3 getPred

Easily manage the hashmap and get the desired predicate(see the print example

lib/AI/Logic/AnswerSet.pm  view on Meta::CPAN

	my @edges = AI::Logic::AnswerSet::getPred(\@mappedAS,3,"edge");

=head3 getProjection

Returns the projection of the n-th term of a specified predicate.
Suppose that we have the predicate "person" C<person(Name,Surename);> and
that we just want the surenames of all the instances of "person":

	my @surenames = AI::Logic::AnswerSet::getProjection(\@mappedAS,3,"person",2);

The parameters are, respectively: hashmap, number of the answer set, name of the predicate,
position of the term.

=head3 statistics

This method returns an array of hashes with some stats of every predicate of every answer set,
namely the number of occurrences of the specified predicates of each answer set.
If a condition is specified(number of predicates), only the answer sets that satisfy
the condition are returned.

	my @res = AI::Logic::AnswerSet::getAS(@output);
	my @predicates = ("node","edge");
	my @stats = AI::Logic::AnswerSet::statistics(\@res,\@predicates);

In this case the data structure returned is the same as the one returned by C<mapAS()>.
Hence, for each answer set (each element of the array of hashes), the hashmap will appear 
like this:

	{
		node => 6
		edge => 9
	}

This means that for a particular answer set we have 6 nodes and 9 edges.
In addition, this method can be used with some constraints:

	my @res = AI::Logic::AnswerSet::getAS(@output);
	my @predicates = ("node,"edge");
	my @numbers = (4,15);
	my @operators = (">","<");
	my @stats = AI::Logic::AnswerSet::statistics(\@res,\@predicates,\@numbers,\@operators);

Now the functions returns the answer sets that satisfy the condition, i.e., an answer set
is returned only if the number of occurrences of the predicate "node" is higher than 4, and the number of occurrences of the predicate "edge" less than 15.

=head3 getFacts

Get the logic program facts from a file or a string.

	my @facts = AI::Logic::AnswerSet::getFacts($inputFile);

or