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t/AI-Pathfinding-SMAstar.t  view on Meta::CPAN

	use_ok('AI::Pathfinding::SMAstar::Examples::Phrase');
};

#########################

# 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.

my $dictionary_file;
my $min_letters;
my $caching;
my @words;
my @words_w_cands;
my @word_objs;
my $num_word_objs;
my @rev_word_objs;
my $num_words;
my $sparsity;
my $max_states_in_queue;
my %letter_freq;
my $max_word_length = 0;

my $MAX_COST = 99;

#my $collisions_per_length = PalUtils::collisions_per_length("ocid", "abo gad abalones rot abdicators enol aba dagoba");
#print "collisions: $collisions_per_length\n";
#exit;


$dictionary_file = 't/test8.lst';
$min_letters = 4;
$sparsity = 2;
$max_states_in_queue = 4;
  
diag("\ncreating AVL trees");

# create trees of WordObj objects, so that we can use
# WordObj::compare_up_to(), the 'relaxed' comparison function
my $avltree = Tree::AVL->new(
     fcompare => \&AI::Pathfinding::SMAstar::Examples::WordObj::compare,
     fget_key => \&AI::Pathfinding::SMAstar::Examples::WordObj::word,
     fget_data => \&AI::Pathfinding::SMAstar::Examples::WordObj::word,
    );

my $avltree_rev = Tree::AVL->new(
    fcompare => \&AI::Pathfinding::SMAstar::Examples::WordObj::compare,
    fget_key => \&AI::Pathfinding::SMAstar::Examples::WordObj::word,
    fget_data => \&AI::Pathfinding::SMAstar::Examples::WordObj::word,
    );


print STDERR "-" x 80 . "\n";
print STDERR "-" x 80 . "\n";


diag("reading dictionary '$dictionary_file'");
eval{

    ($num_words, @words) = AI::Pathfinding::SMAstar::Examples::PalUtils::read_dictionary_filter_by_density($dictionary_file, $sparsity);
};
is( $@, '', '$@ is not set after object insert' );

diag("loaded words: '$num_words'");
isnt( $num_words, undef, 'num_words is $num_words');



%letter_freq = AI::Pathfinding::SMAstar::Examples::PalUtils::find_letter_frequencies(@words);


foreach my $w (@words){
    my $length = length($w);
    if($length > $max_word_length){
	$max_word_length = $length;
    }
}


$num_words_filtered = @words;
diag("$num_words words in the currently loaded dictionary.  Minimum letters specified = $min_letters");
diag("$num_words_filtered words that meet the initial sparsity constraint max_sparsity = $sparsity.");

if(!@words){
    print STDERR "no words to process.  exiting\n";
    exit;
}

@word_objs = AI::Pathfinding::SMAstar::Examples::PalUtils::process_words_by_density(\@words, $sparsity);
@rev_word_objs = AI::Pathfinding::SMAstar::Examples::PalUtils::process_rev_words_by_density(\@words, $sparsity);
if(!@word_objs){ 
    print STDERR "no words achieve density specified by max sparsity $sparsity\n"; 
    exit;
}
$num_word_objs = @word_objs;


diag("loading avl trees.");
for (my $i = 0; $i < @word_objs; $i++) {
    show_progress($i/$num_words); 
    
    my $word = $word_objs[$i]->{_word};
    my $rev_word = $rev_word_objs[$i]->{_word};
 
    $avltree->insert($word_objs[$i]);    
    $avltree_rev->insert($rev_word_objs[$i]);
}
show_progress(1);
print STDERR "\n";


#
# Build the words-with-candidates list.   This will be used for phrases that are
# palindromes with a space in the middle position.   The descendants of these
# types of palindromes are found by sort-of starting all over again... any word becomes
# a candidate for the extension of the palindrome-  any word that has candidates,
# that is.   By building a list of only the words that have candidates, 
# the search time is greatly reduced.
#
my $i = 0;
diag("building words_w_cands_list.");
foreach my $w (@words){