Merge pull request #4 from promised-ai/feature/from-parameters

Add Parameterized trait and test macro for ConjugatePrior

Cargo.toml

@@ -46,7 +46,6 @@ rand_xoshiro = "0.6"
 serde1 = ["serde", "nalgebra/serde-serialize"]
 arraydist = ["nalgebra"]
 process = ["serde", "nalgebra/serde-serialize", "argmin", "argmin-math", "arraydist"]
-datum = []
 experimental = ["rand_xoshiro"]
 
 [package.metadata.docs.rs]

src/data/mod.rs

@@ -2,12 +2,6 @@
 mod partition;
 mod stat;
 
-#[cfg(feature = "datum")]
-mod datum;
-
-#[cfg(feature = "datum")]
-pub use datum::Datum;
-
 pub use partition::Partition;
 pub use stat::BernoulliSuffStat;
 pub use stat::BetaSuffStat;

src/dist/bernoulli.rs

@@ -40,6 +40,18 @@ pub struct Bernoulli {
     p: f64,
 }
 
+impl Parameterized for Bernoulli {
+    type Parameters = f64;
+
+    fn emit_params(&self) -> Self::Parameters {
+        self.p()
+    }
+
+    fn from_params(params: Self::Parameters) -> Self {
+        Self::new_unchecked(params)
+    }
+}
+
 #[derive(Debug, Clone, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 #[cfg_attr(feature = "serde1", serde(rename_all = "snake_case"))]
@@ -373,7 +385,7 @@ mod tests {
     const N_TRIES: usize = 5;
     const X2_PVAL: f64 = 0.2;
 
-    test_basic_impls!([binary] Bernoulli::default());
+    test_basic_impls!(bool, Bernoulli, Bernoulli::default());
 
     #[test]
     fn new() {
@@ -658,7 +670,7 @@ mod tests {
     }
 
     #[test]
-    fn unifrom_entropy() {
+    fn uniform_entropy() {
         let b = Bernoulli::uniform();
         assert::close(b.entropy(), f64::consts::LN_2, TOL);
     }

src/dist/beta.rs

@@ -53,6 +53,26 @@ pub struct Beta {
     ln_beta_ab: OnceLock<f64>,
 }
 
+pub struct BetaParameters {
+    pub alpha: f64,
+    pub beta: f64,
+}
+
+impl Parameterized for Beta {
+    type Parameters = BetaParameters;
+
+    fn emit_params(&self) -> Self::Parameters {
+        Self::Parameters {
+            alpha: self.alpha(),
+            beta: self.beta(),
+        }
+    }
+
+    fn from_params(params: Self::Parameters) -> Self {
+        Self::new_unchecked(params.alpha, params.beta)
+    }
+}
+
 impl PartialEq for Beta {
     fn eq(&self, other: &Beta) -> bool {
         self.alpha == other.alpha && self.beta == other.beta
@@ -454,7 +474,7 @@ mod tests {
     const KS_PVAL: f64 = 0.2;
     const N_TRIES: usize = 5;
 
-    test_basic_impls!([continuous] Beta::jeffreys());
+    test_basic_impls!(f64, Beta, Beta::jeffreys());
 
     #[test]
     fn new() {
@@ -578,7 +598,7 @@ mod tests {
     }
 
     #[test]
-    fn draw_should_resturn_values_within_0_to_1() {
+    fn draw_should_return_values_within_0_to_1() {
         let mut rng = rand::thread_rng();
         let beta = Beta::jeffreys();
         for _ in 0..100 {

src/dist/beta/bernoulli_prior.rs

@@ -84,9 +84,12 @@ impl<X: Booleable> ConjugatePrior<X, Bernoulli> for Beta {
 #[cfg(test)]
 mod tests {
     use super::*;
+    use crate::test_conjugate_prior;
 
     const TOL: f64 = 1E-12;
 
+    test_conjugate_prior!(bool, Bernoulli, Beta, Beta::new(0.5, 1.2).unwrap());
+
     #[test]
     fn posterior_from_data_bool() {
         let data = vec![false, true, false, true, true];
@@ -108,29 +111,4 @@ mod tests {
         assert::close(posterior.alpha(), 4.0, TOL);
         assert::close(posterior.beta(), 3.0, TOL);
     }
-
-    #[test]
-    fn bern_bayes_law() {
-        let mut rng = rand::thread_rng();
-
-        // Prior
-        let prior = Beta::new(5.0, 2.0).unwrap();
-        let par: f64 = prior.draw(&mut rng);
-        let prior_f = prior.f(&par);
-
-        // Likelihood
-        let lik = Bernoulli::new(par).unwrap();
-        let lik_data: bool = lik.draw(&mut rng);
-        let lik_f = lik.f(&lik_data);
-
-        // Evidence
-        let ev = prior.m(&DataOrSuffStat::Data(&[lik_data]));
-
-        // Posterior
-        let post = prior.posterior(&DataOrSuffStat::Data(&[lik_data]));
-        let post_f = post.f(&par);
-
-        // Bayes' law
-        assert::close(post_f, prior_f * lik_f / ev, 1e-12);
-    }
 }

src/dist/beta_binom.rs

@@ -66,6 +66,28 @@ pub struct BetaBinomial {
     ln_beta_ab: OnceLock<f64>,
 }
 
+pub struct BetaBinomialParameters {
+    pub n: u32,
+    pub alpha: f64,
+    pub beta: f64,
+}
+
+impl Parameterized for BetaBinomial {
+    type Parameters = BetaBinomialParameters;
+
+    fn emit_params(&self) -> Self::Parameters {
+        Self::Parameters {
+            n: self.n(),
+            alpha: self.alpha(),
+            beta: self.beta(),
+        }
+    }
+
+    fn from_params(params: Self::Parameters) -> Self {
+        Self::new_unchecked(params.n, params.alpha, params.beta)
+    }
+}
+
 impl PartialEq for BetaBinomial {
     fn eq(&self, other: &BetaBinomial) -> bool {
         self.n == other.n
@@ -427,7 +449,11 @@ mod tests {
 
     const TOL: f64 = 1E-12;
 
-    test_basic_impls!([count] BetaBinomial::new(10, 0.2, 0.7).unwrap());
+    test_basic_impls!(
+        u32,
+        BetaBinomial,
+        BetaBinomial::new(10, 0.2, 0.7).unwrap()
+    );
 
     #[test]
     fn new() {