feat!: Gaussian's EP operations stop wearing arithmetic's clothes
`Gaussian` publicly implemented `Mul`, `Div`, `Add` and `Sub`. They were
the EP product, cavity and variance-space convolutions, and every one of
them lies to a reader who takes the operator at face value:
a = N(10, 2) b = N(4, 3) c = N(1, 1)
a * b N(8.15, 1.66) not 40
a - b sigma GREW, 2 -> sqrt(4 + 9)
a * N(1, 0) mu = NaN "multiply by one"
a / c pi = -0.75 mu() prints a confident 0
The last is this crate's signature defect on a public operator. `Div` is
the cavity and can legitimately leave a negative precision, which is not
a distribution — and `mu()`/`sigma()` guard `pi <= 0` and report `0.0`
and `inf`, so it comes back as a plausible number with no panic, no
`Debug` marker and nothing to test against.
The four impls are now `pub(crate)` inherent methods that say what they
do: `ep_product`, `cavity`, `convolve`, `convolve_diff`, plus `scale`
for the one operation that genuinely is arithmetic. Nothing in a user's
workflow needed operator syntax; inference did, and it still has it.
`pi()` and `tau()` follow. Storing natural parameters is a performance
decision — it makes message passing two adds — not a contract. The
public surface is now exactly: `from_ms`, `from_mv`, `mu`, `sigma`,
`variance`, `probability_below`, `probability_above`. `from_mv` and
`variance` are promoted from `pub(crate)`; they are the honest pair for
callers who already hold a variance and should not pay a round trip
through the square root.
Four integration tests asserted bit-identity on `(pi, tau)`. They assert
it on `(mu, variance)` instead — still `assert_eq!`, still exact, and
`1/pi` and `tau/pi` are deterministic, so bit-equal natural parameters
give bit-equal moments. `a_nan_sigma_passes_through_from_ms` drops its
`|| g.pi().is_nan()` half: `sigma()` substitutes for `pi <= 0` and
`pi == inf`, so NaN survives to it only from a NaN precision.
`benches/gaussian.rs` is deleted. It timed two f64 additions through the
public operators, and keeping those public solely to feed it is the same
thing #73 objected to when a benchmark was dictating five public types.
The paths it covered are exercised by `batch` and `history_converge`
through the real call chain.
Closes #71.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011hcFjNDmHXZF8URGLku5zZ
This commit is contained in:
@@ -64,8 +64,11 @@ fn members_matches_the_typed_path_exactly() {
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for key in ["player", "layout_7"] {
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let a = typed.current_skill(&key).unwrap();
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let b = fluent.current_skill(&key).unwrap();
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assert_eq!(a.pi(), b.pi(), "{key} pi");
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assert_eq!(a.tau(), b.tau(), "{key} tau");
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// Exact equality, on the public moments rather than the natural
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// parameters: `mu` and `variance` are `tau/pi` and `1/pi`, so
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// bit-equal natural parameters give bit-equal moments.
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assert_eq!(a.mu(), b.mu(), "{key} mu");
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assert_eq!(a.variance(), b.variance(), "{key} variance");
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}
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}
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@@ -87,8 +87,8 @@ fn a_joint_answers_exactly_what_the_one_shot_call_does() {
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let terms = [(&a, 1.0), (&b, -1.0)];
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let one_shot = h.posterior_of(&terms).unwrap();
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let cached = joint.posterior_of(&terms).unwrap();
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assert_eq!(one_shot.pi(), cached.pi(), "{a} - {b}");
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assert_eq!(one_shot.tau(), cached.tau(), "{a} - {b}");
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assert_eq!(one_shot.mu(), cached.mu(), "{a} - {b}");
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assert_eq!(one_shot.variance(), cached.variance(), "{a} - {b}");
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}
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}
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@@ -104,8 +104,8 @@ fn a_joint_agrees_at_a_pinned_time_too() {
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let cached = joint.posterior_of_at(time, &terms);
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match (one_shot, cached) {
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(Ok(x), Ok(y)) => {
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assert_eq!(x.pi(), y.pi(), "t={time} {a} - {b}");
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assert_eq!(x.tau(), y.tau(), "t={time} {a} - {b}");
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assert_eq!(x.mu(), y.mu(), "t={time} {a} - {b}");
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assert_eq!(x.variance(), y.variance(), "t={time} {a} - {b}");
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}
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(Err(x), Err(y)) => assert_eq!(x, y, "t={time} {a} - {b}"),
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(x, y) => panic!("t={time} {a} - {b}: disagreed on success: {x:?} vs {y:?}"),
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@@ -262,8 +262,8 @@ fn unseen_competitors_match_the_one_shot_path() {
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let terms = [(&a, 1.0), (&z, -1.0)];
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let one_shot = h.posterior_of(&terms).unwrap();
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let cached = joint.posterior_of(&terms).unwrap();
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assert_eq!(one_shot.pi(), cached.pi());
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assert_eq!(one_shot.tau(), cached.tau());
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assert_eq!(one_shot.mu(), cached.mu());
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assert_eq!(one_shot.variance(), cached.variance());
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}
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/// A drift too small to represent must collapse, not corrupt the matrix.
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@@ -94,8 +94,8 @@ fn registering_matches_configuring_on_the_first_event() {
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};
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for ((k, a), (_, b)) in skills(&configured).into_iter().zip(skills(®istered)) {
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assert_eq!(a.pi(), b.pi(), "{k} pi");
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assert_eq!(a.tau(), b.tau(), "{k} tau");
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assert_eq!(a.mu(), b.mu(), "{k} mu");
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assert_eq!(a.variance(), b.variance(), "{k} variance");
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}
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}
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@@ -225,8 +225,8 @@ fn registration_makes_the_fit_order_independent() {
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let forward = build(false);
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let backward = build(true);
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for ((k, a), (_, b)) in skills(&forward).into_iter().zip(skills(&backward)) {
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assert_eq!(a.pi(), b.pi(), "{k} pi");
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assert_eq!(a.tau(), b.tau(), "{k} tau");
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assert_eq!(a.mu(), b.mu(), "{k} mu");
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assert_eq!(a.variance(), b.variance(), "{k} variance");
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}
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}
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@@ -246,8 +246,8 @@ fn rating_reads_back_what_was_stored() {
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.unwrap();
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let r = h.rating(&"layout").unwrap();
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assert_eq!(r.drift_scale(), 0.25);
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assert_eq!(r.prior().pi(), PINNED.pi());
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assert_eq!(r.prior().tau(), PINNED.tau());
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assert_eq!(r.prior().mu(), PINNED.mu());
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assert_eq!(r.prior().variance(), PINNED.variance());
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// A competitor created by an event reports the history defaults.
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h.record_winner(&"player", &"layout", 1).unwrap();
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+10
-3
@@ -248,9 +248,13 @@ mod builder_parameters {
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};
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let zero = fit(0.0);
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let positive = fit(25.0 / 6.0);
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assert!(zero.pi().is_finite() && zero.pi() > 0.0);
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// `variance` rather than `pi`: the natural parameters are the crate's
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// internal representation and no longer public. It is the same
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// quantity inverted, so a finite positive precision is a finite
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// positive variance.
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assert!(zero.variance().is_finite() && zero.variance() > 0.0);
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assert!(
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(zero.pi() - positive.pi()).abs() > 1e-6,
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(zero.variance() - positive.variance()).abs() > 1e-6,
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"zero beta must not merely be ignored: {zero:?} vs {positive:?}"
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);
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}
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@@ -280,7 +284,10 @@ mod constructor_parameters {
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#[test]
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fn a_nan_sigma_passes_through_from_ms() {
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let g = Gaussian::from_ms(25.0, f64::NAN);
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assert!(g.sigma().is_nan() || g.pi().is_nan());
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// `sigma()` is NaN exactly when the precision is: it guards `pi <= 0`
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// (reporting `inf`) and `pi == inf` (reporting `0.0`), so NaN survives
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// only from a NaN precision.
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assert!(g.sigma().is_nan());
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}
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#[test]
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