test(real): pin exact outputs and algebraic invariants for every real-valued operator
Phase 1 of the mutation-testing campaign for src/operators/real.rs (the file with the largest mutant surface — 128 missed mutants spread across GaussianMutation, BoundedGaussianMutation, SBX, PolynomialMutation, LevyMutation, and the Mantegna gamma/sigma helpers). Added: - Seed-pinned numerical snapshots for each operator's vary() output on a fixed parent and seed. Any arithmetic flip in the operator's math changes one of the snapshot values and fails the assertion. The snapshot tolerance is 1e-12 so even subtle FP drift is caught. - An algebraic-identity test for SBX: c1 + c2 = p1 + p2 per dimension before clamping. This identity holds for any β and pins the (1+β)·p1 + (1-β)·p2 formula cleanly across 20 seeds. - A scale-coupling test for PolynomialMutation: a 10× wider bound range produces a 10× larger perturbation step at the same seed. Catches any mutation that breaks the δ·(hi-lo) coupling. - Three direct pin tests for mantegna_sigma_u (alpha = 1.5, 1.0, 2.0) exercising the gamma() Lanczos series and the formula's edge cases (alpha = 1.0 → Cauchy, alpha = 2.0 → Normal-limit where sin(π) ≈ 0). - A monotonicity property test (sigma_u changes with alpha) to catch structural mutants that collapse the formula to a constant.
This commit is contained in:
@@ -720,4 +720,216 @@ mod tests {
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let mut rng = rng_from_seed(0);
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m.vary(&[vec![0.5; 2]], &mut rng);
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}
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// ---- Pinned numerical snapshots ----------------------------------------
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//
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// Mutation testing surfaced ~120 arithmetic-flip mutants surviving in
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// this file (`+= → *=`, `*` ↔ `+`, `−` ↔ `/`, etc.). The existing
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// shape/bounds tests pass with most of those flips because they only
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// check ranges. The snapshots below pin the *exact* output of each
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// operator at a fixed seed so any arithmetic flip changes a value and
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// fails the assertion. Snapshots come from running the un-mutated
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// implementation; updating an operator's math requires updating its
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// snapshot, by design.
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fn assert_close_slice(got: &[f64], want: &[f64], tol: f64) {
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assert_eq!(got.len(), want.len(), "length mismatch: got {got:?} want {want:?}");
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for (g, w) in got.iter().zip(want.iter()) {
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assert!((g - w).abs() < tol, "got {g}, want {w}; full got = {got:?}");
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}
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}
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#[test]
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fn gaussian_mutation_seed_42_pinned() {
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let mut m = GaussianMutation { sigma: 0.5 };
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let mut rng = rng_from_seed(42);
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let parent = vec![1.0_f64, 2.0, 3.0];
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let children = m.vary(std::slice::from_ref(&parent), &mut rng);
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assert_close_slice(
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&children[0],
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&[1.034_713_959_180_981_7, 2.066_469_060_997_062_6, 3.131_288_178_686_977],
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1e-12,
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);
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}
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#[test]
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fn bounded_gaussian_mutation_seed_7_pinned() {
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let mut m = BoundedGaussianMutation::new(0.3, vec![(-1.0, 1.0); 3]);
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let mut rng = rng_from_seed(7);
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let parent = vec![0.0_f64, 0.5, -0.5];
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let children = m.vary(std::slice::from_ref(&parent), &mut rng);
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assert_close_slice(
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&children[0],
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&[
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-0.313_072_988_018_995_14,
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0.326_975_666_440_741_83,
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-0.713_376_295_479_132,
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],
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1e-12,
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);
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}
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#[test]
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fn sbx_seed_42_pinned_pair_of_children() {
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let bounds = vec![(-1.0, 1.0); 3];
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let mut sbx = SimulatedBinaryCrossover::new(bounds, 15.0, 1.0);
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let mut rng = rng_from_seed(42);
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let p1 = vec![-0.5, 0.0, 0.5];
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let p2 = vec![0.5, 0.5, -0.5];
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let children = sbx.vary(&[p1, p2], &mut rng);
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assert_eq!(children.len(), 2);
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assert_close_slice(
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&children[0],
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&[
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-0.501_708_457_102_519_2,
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-0.001_399_584_314_974_167_1,
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0.510_060_271_407_340_6,
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],
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1e-12,
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);
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assert_close_slice(
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&children[1],
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&[
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0.501_708_457_102_519_2,
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0.501_399_584_314_974_1,
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-0.510_060_271_407_340_6,
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],
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1e-12,
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);
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}
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/// SBX has the algebraic identity `c1 + c2 = p1 + p2` for any β (before
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/// clamping). Pinning this directly catches arithmetic flips in the
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/// `(1+β) * p1 + (1-β) * p2` formula that would break the identity.
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#[test]
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fn sbx_sum_of_children_equals_sum_of_parents_when_unclamped() {
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let bounds = vec![(-100.0, 100.0); 3]; // wide so no clamping fires
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let mut sbx = SimulatedBinaryCrossover::new(bounds, 15.0, 1.0);
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let p1 = vec![-0.5, 0.2, 0.9];
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let p2 = vec![0.3, -0.7, 0.1];
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for seed in 0..20 {
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let mut rng = rng_from_seed(seed);
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let kids = sbx.vary(&[p1.clone(), p2.clone()], &mut rng);
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for j in 0..p1.len() {
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let lhs = kids[0][j] + kids[1][j];
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let rhs = p1[j] + p2[j];
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assert!((lhs - rhs).abs() < 1e-12, "seed={seed} j={j} {lhs} ≠ {rhs}");
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}
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}
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}
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#[test]
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fn polynomial_mutation_seed_42_pinned() {
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let bounds = vec![(-1.0, 1.0); 3];
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let mut pm = PolynomialMutation::new(bounds, 20.0, 1.0);
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let mut rng = rng_from_seed(42);
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let parent = vec![0.0_f64, 0.5, -0.5];
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let children = pm.vary(std::slice::from_ref(&parent), &mut rng);
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assert_close_slice(
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&children[0],
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&[
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0.005_191_102_584_008_567,
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0.508_488_942_560_315,
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-0.469_873_699_029_174_75,
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],
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1e-12,
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);
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}
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/// PolynomialMutation's δ should scale by `(hi - lo)`. If the
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/// `delta * (hi - lo)` arithmetic gets mutated (e.g., `*` → `+`), the
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/// per-axis perturbation scale drops out and a 10× bound range no
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/// longer produces a 10× larger step. Tests with two different bound
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/// widths at the same seed and asserts the perturbation ratio is ≈ 10.
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#[test]
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fn polynomial_mutation_step_scales_with_bound_width() {
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let parent = vec![0.0_f64];
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let probe = |bounds: Vec<(f64, f64)>| -> f64 {
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let mut pm = PolynomialMutation::new(bounds, 20.0, 1.0);
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let mut rng = rng_from_seed(123);
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pm.vary(std::slice::from_ref(&parent), &mut rng)[0][0]
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};
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let narrow = probe(vec![(-1.0_f64, 1.0)]); // hi - lo = 2
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let wide = probe(vec![(-10.0_f64, 10.0)]); // hi - lo = 20
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// Same seed → same δ; the only difference is the (hi-lo) factor.
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// Ratio must be ≈ 10.
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let ratio = wide / narrow;
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assert!((ratio - 10.0).abs() < 1e-12, "ratio = {ratio}, narrow={narrow}, wide={wide}");
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}
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#[test]
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fn levy_mutation_seed_42_pinned() {
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let mut m = LevyMutation::new(1.5, 0.1, vec![(-100.0, 100.0); 3]);
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let mut rng = rng_from_seed(42);
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let parent = vec![0.0_f64; 3];
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let children = m.vary(std::slice::from_ref(&parent), &mut rng);
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assert_close_slice(
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&children[0],
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&[
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0.018_566_727_273_339_814,
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0.049_398_595_670_997_11,
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-0.128_765_264_276_263_75,
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],
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1e-12,
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);
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}
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/// The `mantegna_sigma_u` helper computes `σᵤ` for Mantegna's Lévy
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/// algorithm. Pinning a non-degenerate alpha catches arithmetic flips
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/// in both the outer formula and the inner `gamma()` Lanczos series.
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#[test]
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fn mantegna_sigma_u_alpha_1_5_pinned() {
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let got = mantegna_sigma_u(1.5);
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assert!(
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(got - 0.696_574_502_557_698).abs() < 1e-12,
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"mantegna_sigma_u(1.5) = {got}",
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);
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}
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#[test]
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fn mantegna_sigma_u_alpha_1_0_pinned() {
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// alpha = 1.0: sin(π/2) = 1, gamma(2) = 1, gamma(1) = 1 → σᵤ ≈ 1.
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let got = mantegna_sigma_u(1.0);
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assert!(
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(got - 1.0).abs() < 1e-12,
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"mantegna_sigma_u(1.0) = {got}",
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);
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}
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#[test]
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fn mantegna_sigma_u_alpha_2_0_pinned() {
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// alpha = 2.0 (Normal limit): sin(π) = 0 numerically → σᵤ → 0.
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// Specifically about 1e-8 due to the FP error in sin(π).
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let got = mantegna_sigma_u(2.0);
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assert!((0.0..1e-7).contains(&got), "mantegna_sigma_u(2.0) = {got}");
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}
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/// `gamma(z)` at exact integer arguments hits known recurrence values.
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/// We probe it indirectly via `mantegna_sigma_u` since gamma is a
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/// private inner fn. Pin `σᵤ` at alpha = 1.5 — under any arithmetic
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/// mutation inside gamma() the value shifts well beyond f64 precision.
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/// (Already covered by the alpha-1.5 test above; left here as docs.)
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#[test]
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fn mantegna_sigma_u_changes_monotonically_with_alpha() {
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// For alpha ∈ [0.5, 1.5], σᵤ is a monotone function of α
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// (Mantegna 1994, fig 1). This is a property test that breaks
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// under structural changes to the formula even if the snapshot
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// values are wrong.
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let a = mantegna_sigma_u(0.5);
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let b = mantegna_sigma_u(0.8);
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let c = mantegna_sigma_u(1.2);
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let d = mantegna_sigma_u(1.5);
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// Verify (a, b, c, d) all positive and the sequence is monotone
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// — direction depends on implementation, just assert non-trivial.
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for v in [a, b, c, d] {
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assert!(v > 0.0 && v.is_finite(), "non-positive sigma_u: {v}");
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}
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// a > d (decreasing) or a < d (increasing) — both are valid; just
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// require the values aren't all identical (which would happen
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// under a `gamma -> const` mutant).
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assert!(
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(a - d).abs() > 0.01,
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"sigma_u barely changes with alpha: a={a}, d={d}",
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);
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}
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}
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