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|
#!/usr/bin/perl
use strict;
use warnings;
use Test::More tests => 21209;
use_ok('Math::Vector::Real::kdTree');
use Sort::Key::Top qw(nhead);
use Math::Vector::Real;
use Math::Vector::Real::Test qw(eq_vector);
sub find_in_ball_bruteforce {
my ($vs, $ix, $d) = @_;
my $d2 = $d * $d;
grep { $ix <=> $_ and $vs->[$ix]->dist2($vs->[$_]) <= $d2 } 0..$#$vs;
}
sub nearest_vectors_bruteforce {
my ($bottom, $top) = Math::Vector::Real->box(@_);
my $box = $top - $bottom;
my $v = [map $_ - $bottom, @_];
my $ixs = [0..$#_];
my $dist2 = [($box->abs2 * 10 + 1) x @_];
my $neighbors = [(undef) x @_];
_nearest_vectors_bruteforce($v, $ixs, $dist2, $neighbors, $box, 0);
return @$neighbors;
}
sub _nearest_vectors_bruteforce {
my ($v, $ixs, $dist2, $neighbors) = @_;
my $ixix = 0;
for my $i (@$ixs) {
$ixix++;
my $v0 = $v->[$i];
for my $j (@$ixs[$ixix..$#$ixs]) {
my $d2 = $v0->dist2($v->[$j]);
if ($dist2->[$i] > $d2) {
$dist2->[$i] = $d2;
$neighbors->[$i] = $j;
}
if ($dist2->[$j] > $d2) {
$dist2->[$j] = $d2;
$neighbors->[$j] = $i;
}
}
}
}
sub farthest_vectors_bruteforce {
my @best_ix;
my @best_d2 = ((-1) x @_);
for my $i (1..$#_) {
my $v = $_[$i];
for my $j (0..$i - 1) {
my $d2 = Math::Vector::Real::dist2($v, $_[$j]);
if ($d2 > $best_d2[$i]) {
$best_d2[$i] = $d2;
$best_ix[$i] = $j;
}
if ($d2 > $best_d2[$j]) {
$best_d2[$j] = $d2;
$best_ix[$j] = $i;
}
}
}
return @best_ix;
}
sub find_two_nearest_vectors_bruteforce {
my @best_ix = (undef, undef);
my $best_d2 = 'inf' + 0;
for my $i (1..$#_) {
my $v = $_[$i];
for my $j (0..$i - 1) {
my $d2 = Math::Vector::Real::dist2($v, $_[$j]);
if ($d2 < $best_d2) {
$best_d2 = $d2;
@best_ix = ($i, $j);
}
}
}
(@best_ix, sqrt($best_d2))
}
sub test_neighbors {
unshift @_, $_[0];
goto &test_neighbors_indirect;
}
sub test_neighbors_indirect {
my ($o1, $o2, $n1, $n2, $msg) = @_;
my (@d1, @d2);
for my $ix (0..$#$o1) {
my $eo = $o1->[$ix];
my $ixn1 = $n1->[$ix];
defined $ixn1 or do {
fail($msg);
diag("expected index for element $ix is undefined");
goto break_me;
};
my $ixn2 = $n2->[$ix];
defined $ixn2 or do {
fail($msg);
diag("template index for element $ix is undefined");
goto break_me;
};
$ixn1 < @$o2 or do {
fail($msg);
diag("expected index $ixn1 out of range");
goto break_me;
};
$ixn2 < @$o2 or do {
fail($msg);
diag("template index $ixn1 out of range");
goto break_me;
};
my $en1 = $o2->[$ixn1];
my $en2 = $o2->[$ixn2];
push @d1, $eo->dist2($en1);
push @d2, $eo->dist2($en2);
}
is "@d1", "@d2", $msg and return 1;
break_me:
diag "break me!";
0;
}
my %gen = ( num => sub { rand },
int => sub { int rand(10) } );
#srand 318275924;
diag "srand: " . srand;
for my $g (keys %gen) {
for my $d (1, 2, 3, 10) {
for my $n (2, 10, 50, 250, 500) {
# for my $n ((2) x 100) {
my $id = "gen: $g, d: $d, n: $n";
my @o = map V(map $gen{$g}->(), 1..$d), 1..$n;
my @nbf = nearest_vectors_bruteforce(@o);
my $t = Math::Vector::Real::kdTree->new(@o);
my @n = map scalar($t->find_nearest_vector_internal($_)), 0..$#o;
is ($#n, $#o, "count find_nearest_vector_internal - build - $id");
test_neighbors(\@o, \@n, \@nbf, "find_nearest_vector_internal - build - $id");
is_deeply([map $t->at($_), 0..$#o], \@o , "at - build - after find_nearest_vector_internal - $id");
@n = $t->find_nearest_vector_all_internal;
is ($#n, $#o, "count find_nearest_vector_all_internal - build - $id");
test_neighbors(\@o, \@n, \@nbf, "find_nearest_vector_all_internal - build - $id");
is_deeply([map $t->at($_), 0..$#o], \@o , "at - build - after find_nearest_vector_all_internal - $id");
$t = Math::Vector::Real::kdTree->new;
for my $ix (0..$#o) {
$t->insert($o[$ix]);
my @obp = $t->ordered_by_proximity;
is ($ix, $#obp, "ordered_by_proxymity - count - $id, ix: $ix");
}
is_deeply([map $t->at($_), 0..$#o], \@o , "at - insert - after insert - $id");
@n = map scalar($t->find_nearest_vector_internal($_)), 0..$#o;
test_neighbors(\@o, \@n, \@nbf, "find_nearest_vector_internal - insert - $id");
is_deeply([map $t->at($_), 0..$#o], \@o , "at - insert - after find_nearest_vector_internal - $id");
@n = $t->find_nearest_vector_all_internal;
test_neighbors(\@o, \@n, \@nbf, "find_nearest_vector_all_internal - insert - $id");
is_deeply([map $t->at($_), 0..$#o], \@o , "at - insert - after find_nearest_vector_all_internal - $id");
my @fbf = farthest_vectors_bruteforce(@o);
@n = map scalar($t->find_farthest_vector_internal($_)), 0..$#o;
test_neighbors(\@o, \@n, \@fbf, "find_farthest_vector_internal - insert - $id");
is_deeply([map $t->at($_), 0..$#o], \@o , "at - insert - after find_farthest_vector_internal - $id");
my ($b1, $b2, $min_d2) = $t->find_two_nearest_vectors;
my ($b1bf, $b2bf, $min_d2_bf) = find_two_nearest_vectors_bruteforce(@o);
is($min_d2, $min_d2_bf, "nearest_two_vectors") or do {
diag "values differ: $min_d2 $min_d2_bf best: $b1, $b2, best_bf: $b1bf, $b2bf\n";
diag $t->dump_to_string(pole_id => 1, remark => [$b1, $b2, $b1bf, $b2bf]);
};
my %seed_errs = (k_means_seed => [1], k_means_seed_pp => [1, 0.9, 0.5]);
my $k;
for ($k = 1; $k < @n; $k *= 2) {
for my $seed_method (qw(k_means_seed)) { # k_means_seed_pp)) {
for my $err (@{$seed_errs{$seed_method}}) {
no warnings 'once';
local $Math::Vector::Real::kdTree::k_means_seed_pp_test = sub {
my ($t, $err, $kmvs, $ws) = @_;
# use Data::Dumper;
# diag Dumper $ws;
# diag Dumper $kmvs;
my @error;
for my $ix (0..$#o) {
my $w = nhead map { $o[$ix]->dist2($_) } @$kmvs;
# diag "checking element $ix, o: $o[$ix] ws: $ws->[$ix], w: $w";
if ($ws->[$ix] + 0.0001 < $w * $err or $ws->[$ix] * $err > $w + 0.0001) {
push @error, "weight calculation failed for ix $ix: precise: $w, estimated: $ws->[$ix], err: $err"
}
}
ok(@error == 0, "k_means_seed_pp_test, k: $k, err: $err, $id");
diag $_ for @error;
};
my @kms = $t->$seed_method($k, $err);
my $k_gen = scalar(@kms);
if ($seed_method eq 'k_means_seed') {
is ($k_gen, $k, "$seed_method generates $k results - err: $err, $id");
}
else {
ok(1, "keep number of tests unchanged") for $k_gen..$k-1;
ok($k_gen >= 1, "$seed_method generates at least one result");
ok($k_gen <= $k, "$seed_method generates $k or less results");
}
my @km = $t->k_means_loop(@kms);
is (scalar(@km), $k_gen, "k_means_loop generates $k_gen results - err: $err, $id")
or do {
diag "break me 2";
};
my @kma = $t->k_means_assign(@km);
my $t1 = Math::Vector::Real::kdTree->new(@km);
my @n = map scalar($t1->find_nearest_vector($_)), @o;
test_neighbors_indirect(\@o, \@km, \@kma, \@n, "k_means_assign - err: $err, k: $k, $id");
my @sum = map V((0) x $d), 1..$k_gen;
my @count = ((0) x $k_gen);
for my $ix (0..$#kma) {
my $cluster = $kma[$ix];
$count[$cluster]++;
$sum[$cluster] += $o[$ix];
}
for my $cluster (0..$#sum) {
if ($count[$cluster]) {
$sum[$cluster] /= $count[$cluster];
}
else {
$sum[$cluster] = $km[$cluster];
}
eq_vector($sum[$cluster], $km[$cluster], "cluster centroid - $cluster - k: $k, $id");
}
ok (1, "keep number of tests unchanged") for $#sum..$k-1;
}
}
}
for my $ix (0..$#o) {
my $r = 0.0001 + rand(1);
my @bix = sort { $a <=> $b } $t->find_in_ball($o[$ix], $r, $ix);
my @bixbf = find_in_ball_bruteforce(\@o, $ix, $r);
is_deeply (\@bix, \@bixbf, "find_in_ball - $ix - $id") or
do {;
diag "break me 3";
}
}
}
}
}
|
