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t/41-mungers.t  view on Meta::CPAN

		n_trees       => 40,
		sample_size   => 64,
		contamination => 0.05,
		feature_names => [@TAGS],
		mungers       => mungers(),
	);
	$f->fit_tagged( raw_rows(200) );
	my $before = $f->score_sample_tagged( {%WEIRD} );

	my $path = "$dir/munged_model.json";
	$f->save($path);

	my $re = $batch_class->load($path);
	is_deeply( $re->{mungers}, mungers(), 'munger spec survived the round trip' );
	is(
		$re->{munger_module_version},
		$Algorithm::ToNumberMunger::VERSION,
		'munger module version recorded with the model'
	);
	ok( !$re->{_munger_plan}, 'plan is not compiled at load time (lazy)' );

	my $after = $re->score_sample_tagged( {%WEIRD} );
	cmp_ok( abs( $after - $before ), '<', 1e-12, 'reloaded model munges and scores identically' );
	ok( $re->{_munger_plan}, 'plan compiled lazily on first tagged use' );

	# A spec naming a munger the installed module lacks croaks lazily,
	# with a message naming it -- the stale-module failure mode.
	my $broken = $batch_class->load($path);
	$broken->{mungers}{method}{munger} = 'bogus_from_the_future';
	ok( !eval { $broken->score_sample_tagged( {%WEIRD} ); 1 }, 'unknown munger in a loaded model croaks' );
	like( $@, qr/unknown munger 'bogus_from_the_future'/, 'error names the unknown munger' );
}; ## end 'persistence round trip (batch)' => sub

subtest 'Online: learn_tagged batches, prequential scoring, persistence' => sub {
	my $dir = tempdir( CLEANUP => 1 );
	srand(10);
	my $m = $online_class->new(
		seed             => 42,
		n_trees          => 40,
		window_size      => 128,
		max_leaf_samples => 16,
		feature_names    => [@TAGS],
		mungers          => mungers(),
	);

	my $ret = $m->learn_tagged( raw_rows(200) );
	is( $ret,     $m,  'learn_tagged (batch form) chains' );
	is( $m->seen, 200, 'batch form learned every row' );
	$m->learn_tagged( { method => 'GET', path => '/one.html', host => 'www.example.com', bytes => 640 } );
	is( $m->seen, 201, 'single-hashref form still works' );

	my $normal = $m->score_sample_tagged( {%NORMAL} );
	my $weird  = $m->score_learn_tagged( {%WEIRD} );
	cmp_ok( $weird, '>', $normal, 'raw anomalous row scores above a normal one prequentially' );

	my $path = "$dir/oiforest_munged.json";
	$m->save($path);

	# Parent-class load dispatches AND keeps the munger spec.
	my $re = Algorithm::Classifier::IsolationForest->load($path);
	isa_ok( $re, $online_class, 'parent load() returns the online model' );
	is_deeply( $re->{mungers}, mungers(), 'munger spec survived the online round trip' );

	my $s1 = $m->score_sample_tagged( {%WEIRD} );
	my $s2 = $re->score_sample_tagged( {%WEIRD} );
	cmp_ok( abs( $s2 - $s1 ), '<', 1e-12, 'reloaded online model munges and scores identically' );
}; ## end 'Online: learn_tagged batches, prequential scoring, persistence' => sub

done_testing;