refactor: add native tests from test.pmf.js

anandkaranubc · anandkaranubc · commit 7e4dedad14da · 2025-01-05T10:00:04.000-08:00
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diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/pmf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/pmf/test/test.native.js
@@ -25,6 +25,9 @@ var tape = require( 'tape' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
 
 
 // VARIABLES //
@@ -35,85 +38,145 @@ var opts = {
 };
 
 
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
 // TESTS //
 
-tape('main export is a function', opts, function test(t) {
-	t.ok(true, __filename);
-	t.strictEqual(typeof pmf, 'function', 'main export is a function');
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof pmf, 'function', 'main export is a function' );
 	t.end();
 });
 
-tape('if provided `NaN` for any parameter, the function returns `NaN`', opts, function test(t) {
-	var v;
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
+	var y = pmf( NaN, 10, 10, 5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = pmf( 0.0, NaN, 10, 5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = pmf( 0.0, 10, NaN, 5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = pmf( 0.0, 10, 10, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	t.end();
+});
 
-	v = pmf(NaN, 10, 5, 2);
-	t.equal(isnan(v), true, 'returns NaN');
+tape( 'if provided an integer `x` greater than `min( n, K )`, the function returns `0` (provided all parameters are valid)', opts, function test( t ) {
+	var y = pmf( PINF, 20, 20, 10 );
+	t.equal( y, 0.0, 'returns 0' );
 
-	v = pmf(2, NaN, 5, 2);
-	t.equal(isnan(v), true, 'returns NaN');
+	y = pmf( 11, 20, 20, 10 );
+	t.equal( y, 0.0, 'returns 0' );
 
-	v = pmf(2, 10, NaN, 2);
-	t.equal(isnan(v), true, 'returns NaN');
+	y = pmf( 100, 20, 20, 10 );
+	t.equal( y, 0.0, 'returns 0' );
 
-	v = pmf(2, 10, 5, NaN);
-	t.equal(isnan(v), true, 'returns NaN');
+	t.end();
+});
+
+tape( 'if provided an integer for `x` smaller than `max( 0, n + K - N )`, the function returns `0`', opts, function test( t ) {
+	var y = pmf( NINF, 40, 20, 10 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pmf( -1.0, 40, 20, 10 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pmf( -2.0, 30, 20, 20 );
+	t.equal( y, 0.0, 'returns 0' );
 
 	t.end();
 });
 
-tape('if provided invalid inputs, the function returns `NaN`', opts, function test(t) {
-	var v;
+tape( 'if provided an `N` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = pmf( 2.0, 30.5, 20, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pmf( 2.0, -2, 20, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pmf( 2.0, -1, 20, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
 
-	v = pmf(2, -10, 5, 2);
-	t.equal(isnan(v), true, 'returns NaN');
+	y = pmf( 0.0, 20.5, 20, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
 
-	v = pmf(2, 10.5, 5, 2);
-	t.equal(isnan(v), true, 'returns NaN');
+	y = pmf( 0.0, PINF, 20, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
 
-	v = pmf(2, 10, -5, 2);
-	t.equal(isnan(v), true, 'returns NaN');
+	t.end();
+});
+
+tape( 'if provided a `K` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = pmf( 2.0, 20, 3.5, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
 
-	v = pmf(2, 10, 5.5, 2);
-	t.equal(isnan(v), true, 'returns NaN');
+	y = pmf( 2.0, 20, -2, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
 
-	v = pmf(2, 10, 5, -2);
-	t.equal(isnan(v), true, 'returns NaN');
+	y = pmf( 2.0, 20, -1, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
 
-	v = pmf(2, 10, 5, 2.5);
-	t.equal(isnan(v), true, 'returns NaN');
+	y = pmf( 0.0, 20, 2.5, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pmf( 0.0, 20, PINF, 10 );
+	t.equal( isnan( y ), true, 'returns NaN' );
 
 	t.end();
 });
 
-tape('the function evaluates the PMF for a hypergeometric distribution', opts, function test(t) {
-	var testCases = [{
-		'x': 1.0,
-		'N': 8,
-		'K': 4,
-		'n': 2,
-		'expected': 0.571
-	},
-	{
-		'x': 2.0,
-		'N': 8,
-		'K': 4,
-		'n': 2,
-		'expected': 0.214
-	},
-	{
-		'x': 0.0,
-		'N': 8,
-		'K': 4,
-		'n': 2,
-		'expected': 0.214
-	}];
-	var tol = 1e-3;
-
-	testCases.forEach(function evaluateTestCase(testCase) {
-		var computedPMF = pmf(testCase.x, testCase.N, testCase.K, testCase.n);
-		var delta = abs(computedPMF - testCase.expected);
-		t.ok(delta <= tol, 'within tolerance. x: ' + testCase.x + ', N: ' + testCase.N + ', K: ' + testCase.K + ', n: ' + testCase.n + ', y: ' + computedPMF + ', expected: ' + testCase.expected + ', Δ: ' + delta + ', tol: ' + tol);
-	});
+tape( 'if provided an `n` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = pmf( 2.0, 40, 20, 3.5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pmf( 2.0, 40, 20, -2 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pmf( 2.0, 40, 20, -1 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pmf( 0.0, 40, 20, 2.5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pmf( 0.0, 40, 20, PINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
 
+tape( 'the function evaluates the pmf for `x`', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var x;
+	var N;
+	var K;
+	var n;
+	var y;
+	var i;
+
+	expected = data.expected;
+	x = data.x;
+	N = data.N;
+	K = data.K;
+	n = data.n;
+	for ( i = 0; i < x.length; i++ ) {
+		y = pmf( x[i], N[i], K[i], n[i] );
+		if ( y === expected[i] ) {
+			t.equal( y, expected[i], 'x: '+x[i]+', N: '+N[i]+', K: '+K[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1040.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. N: '+N[i]+'. K: '+K[i]+'. n: '+n[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
 	t.end();
 });
