11_clusterdistance.t

这是一个关于c-cluster的技术文章,它详细地介绍了cluster的一些技术分类及算法等,是学习聚类的入门好教程.

my ($last_test,$loaded);

######################### We start with some black magic to print on failure.
use lib '../blib/lib','../blib/arch';

BEGIN { $last_test = 7; $| = 1; print "1..$last_test\n"; }
END   { print "not ok 1  Can't load Algorithm::Cluster\n" unless $loaded; }

use Algorithm::Cluster;
no  warnings 'Algorithm::Cluster';

$loaded = 1;
print "ok 1\n";

######################### End of black magic.

sub test;  # Predeclare the test function (defined below)

my $tcounter = 1;
my $want     = '';


#------------------------------------------------------
# Data for Tests
# 

#----------
# dataset 1
#
my $weight1 =  [ 1,1,1,1,1 ];
my $data1   =  [
        [  1.1, 2.2, 3.3, 4.4, 5.5, ], 
        [  3.1, 3.2, 1.3, 2.4, 1.5, ], 
        [  4.1, 2.2, 0.3, 5.4, 0.5, ], 
        [ 12.1, 2.0, 0.0, 5.0, 0.0, ], 
];
my $mask1 =  [
        [ 1, 1, 1, 1, 1, ], 
        [ 1, 1, 1, 1, 1, ], 
        [ 1, 1, 1, 1, 1, ], 
        [ 1, 1, 1, 1, 1, ], 
];
my $data1_c1 = [ 0 ];
my $data1_c2 = [ 1,2 ];
my $data1_c3 = [ 3 ];


#----------
# dataset 2
#
my $weight2 =  [ 1,1 ];
my $data2   =  [
	[ 1.1, 1.2 ],
	[ 1.4, 1.3 ],
	[ 1.1, 1.5 ],
	[ 2.0, 1.5 ],
	[ 1.7, 1.9 ],
	[ 1.7, 1.9 ],
	[ 5.7, 5.9 ],
	[ 5.7, 5.9 ],
	[ 3.1, 3.3 ],
	[ 5.4, 5.3 ],
	[ 5.1, 5.5 ],
	[ 5.0, 5.5 ],
	[ 5.1, 5.2 ],
];
my $mask2 =  [
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
	[ 1, 1 ],
];
my $data2_c1 = [ 0, 1, 2, 3 ];
my $data2_c2 = [ 4, 5, 6, 7 ];
my $data2_c3 = [ 8 ];


#------------------------------------------------------
# Tests
# 
my $distance;

#----------
# test dataset 1
#
my %params = (

	transpose =>         0,
	method    =>       'a',
	dist      =>       'e',
	data      =>    $data1,
	mask      =>    $mask1,
	weight    =>  $weight1,
	cluster1  => $data1_c1,
	cluster2  => $data1_c2,
);

$distance = Algorithm::Cluster::clusterdistance(\%params);
$want = '  6.650';       test q( sprintf "%7.3f", $distance );

$params{cluster1} = $data1_c1;
$params{cluster2} = $data1_c3;
$distance = Algorithm::Cluster::clusterdistance(\%params);
$want = ' 32.508';       test q( sprintf "%7.3f", $distance );

$params{cluster1} = $data1_c2;
$params{cluster2} = $data1_c3;
$distance = Algorithm::Cluster::clusterdistance(\%params);
$want = ' 15.118';       test q( sprintf "%7.3f", $distance );

#----------
# test dataset 2
#
%params = (

	transpose =>         0,
	method    =>       'a',
	dist      =>       'e',
	data      =>    $data2,
	mask      =>    $mask2,
	weight    =>  $weight2,
	cluster1  => $data2_c1,
	cluster2  => $data2_c2,
);
$distance = Algorithm::Cluster::clusterdistance(\%params);
$want = '  5.833';       test q( sprintf "%7.3f", $distance );

$params{cluster1} = $data2_c1;
$params{cluster2} = $data2_c3;
$distance = Algorithm::Cluster::clusterdistance(\%params);
$want = '  3.298';       test q( sprintf "%7.3f", $distance );

$params{cluster1} = $data2_c2;
$params{cluster2} = $data2_c3;
$distance = Algorithm::Cluster::clusterdistance(\%params);
$want = '  0.360';       test q( sprintf "%7.3f", $distance );



#------------------------------------------------------
# Test function
# 
sub test {
	$tcounter++;

	my $string = shift;
	my $ret = eval $string;
	$ret = 'undef' if not defined $ret;

	if("$ret" =~ /^$want$/sm) {

		print "ok $tcounter\n";

	} else {
		print "not ok $tcounter\n",
		"   -- '$string' returned '$ret'\n", 
		"   -- expected =~ /$want/\n"
	}
}

__END__