view release on metacpan or  search on metacpan

t/90-cli-commands.t  view on Meta::CPAN

# --- 2. fit (a known-good command) --------------------------------------
subtest 'fit produces a model' => sub {
	my $out = `$^X -Ilib $bin fit -i $train_csv -o $model -n 30 -m 16 -s 42 2>&1`;
	is( $?, 0, 'fit exits 0' );
	ok( -s $model, 'model.json was written' );
};

# --- 3. info ------------------------------------------------------------
subtest 'info dumps model metadata' => sub {
	my $out = `$^X -Ilib $bin info -m $model 2>&1`;
	is( $?, 0, 'info exits 0' );
	like( $out, qr/n_trees\s+30/,           'info reports n_trees=30' );
	like( $out, qr/n_features\s+3/,         'info reports n_features=3' );
	like( $out, qr/mode\s+axis/,            'info reports mode=axis' );
	like( $out, qr/tree_total_nodes\s+\d+/, 'info reports a tree_total_nodes count' );
};

subtest 'info --json emits parseable JSON' => sub {
	my $out = `$^X -Ilib $bin info -m $model --json 2>&1`;
	is( $?, 0, 'info --json exits 0' );
	require JSON::PP;
	my $obj = eval { JSON::PP->new->decode($out) };
	ok( !$@, 'output parses as JSON' ) or diag("error: $@");
	is( $obj->{n_trees}, 30,     'JSON n_trees matches' ) if $obj;
	is( $obj->{mode},    'axis', 'JSON mode matches' )    if $obj;
};

# --- 3b. info reports feature-name tags --------------------------------
subtest 'info displays tag info' => sub {
	# The baseline model was fit without -t, so it is untagged.
	my $out = `$^X -Ilib $bin info -m $model 2>&1`;
	like( $out, qr/tagged\s+0/, 'untagged model reports tagged=0' );
	unlike( $out, qr/feature_names/, 'untagged model omits the feature_names block' );

	# Fit a tagged model over the same 3-feature CSV.
	my $tagged = "$tmp/tagged.json";
	my $fit    = `$^X -Ilib $bin fit -i $train_csv -o $tagged -n 30 -m 16 -s 42 -t cpu -t mem -t disk 2>&1`;
	is( $?, 0, 'tagged fit exits 0' ) or diag($fit);

	my $t = `$^X -Ilib $bin info -m $tagged 2>&1`;
	is( $?, 0, 'info on tagged model exits 0' );
	like( $t, qr/tagged\s+1/,                     'reports tagged=1' );
	like( $t, qr/feature_names\s+cpu, mem, disk/, 'lists the joined tags' );
	like( $t, qr/\[0\]\s+cpu/,                    'lists tag [0] cpu' );
	like( $t, qr/\[1\]\s+mem/,                    'lists tag [1] mem' );
	like( $t, qr/\[2\]\s+disk/,                   'lists tag [2] disk' );

	# --json carries the same info in machine-readable form.
	my $j = `$^X -Ilib $bin info -m $tagged --json 2>&1`;
	require JSON::PP;
	my $obj = eval { JSON::PP->new->decode($j) };
	ok( !$@, 'tagged --json parses' ) or diag("error: $@");
	if ($obj) {
		is( $obj->{tagged}, 1, 'JSON tagged=1' );
		is_deeply( $obj->{feature_names}, [qw(cpu mem disk)], 'JSON feature_names matches tags' );
	}
}; ## end 'info displays tag info' => sub

# --- 4. bench -----------------------------------------------------------
subtest 'bench reports per-method ops/s' => sub {
	# Short --secs so the bench finishes quickly in CI.
	my $out = `$^X -Ilib $bin bench -m $model -i $query_csv --secs 0.3 2>&1`;
	is( $?, 0, 'bench exits 0' );
	like( $out, qr/score_samples\b/,       'mentions score_samples' );
	like( $out, qr/predict\b/,             'mentions predict' );
	like( $out, qr/score_predict_split\b/, 'mentions score_predict_split' );
	like( $out, qr/path_lengths\b/,        'mentions path_lengths' );
	like( $out, qr/ops\/s/,                'has ops/s column header' );
}; ## end 'bench reports per-method ops/s' => sub

# --- 5. pack + packed predict ------------------------------------------
SKIP: {
	skip 'pack requires Inline::C backend', 4
		unless $Algorithm::Classifier::IsolationForest::HAS_C;

	subtest 'pack writes a .iforest-packed file' => sub {
		my $out = `$^X -Ilib $bin pack -m $model -i $query_csv -o $packed 2>&1`;
		is( $?, 0, 'pack exits 0' );
		ok( -s $packed, 'packed file written' );

		# Verify magic bytes.
		open my $fh, '<:raw', $packed or die $!;
		my $magic;
		read( $fh, $magic, 8 );
		close $fh;
		is( $magic, "IFPKD\0\0\0", 'magic bytes match' );
	}; ## end 'pack writes a .iforest-packed file' => sub

	subtest 'predict consumes a packed input' => sub {
		my $out = `$^X -Ilib $bin predict -m $model -i $packed -o $pred_csv 2>&1`;
		is( $?, 0, 'predict (packed input) exits 0' );
		ok( -s $pred_csv, 'output prediction file written' );

		my @lines = do { open my $fh, '<', $pred_csv; <$fh> };
		is( scalar @lines, 7, 'predict emitted one row per query point (7)' );
		like( $lines[0], qr/^[\d.eE+-]+,[01]\s*$/, 'first row matches "score,label"' );
	};

	subtest 'predict on packed input agrees with CSV input' => sub {
		# Run predict against the raw CSV too and check the labels match.
		my $out = `$^X -Ilib $bin predict -m $model -i $query_csv -o $pred2_csv 2>&1`;
		is( $?, 0, 'predict (CSV input) exits 0' );

		my @a = do { open my $fh, '<', $pred_csv;  <$fh> };
		my @b = do { open my $fh, '<', $pred2_csv; <$fh> };
		is( scalar @a, scalar @b, 'same row count' );

		my $diffs = 0;
		for my $i ( 0 .. $#a ) {
			chomp( my $la = $a[$i] );
			chomp( my $lb = $b[$i] );
			my ( $sa, $ya ) = split /,/, $la;
			my ( $sb, $yb ) = split /,/, $lb;
			$diffs++ if abs( $sa - $sb ) > 1e-9;
			$diffs++ if $ya != $yb;
		}
		is( $diffs, 0, 'packed-input scores and labels match CSV-input output' );
	}; ## end 'predict on packed input agrees with CSV input' => sub

	subtest 'predict with -d works on packed input' => sub {
		my $out = `$^X -Ilib $bin predict -m $model -i $packed -d 2>&1`;
		is( $?, 0, 'predict -d (packed) exits 0' );