Making distributions comparable by deriving PartialEq

rand_distr/src/binomial.rs

@@ -30,7 +30,7 @@ use num_traits::Float;
 /// let v = bin.sample(&mut rand::thread_rng());
 /// println!("{} is from a binomial distribution", v);
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Binomial {
     /// Number of trials.
@@ -347,4 +347,9 @@ mod test {
     fn test_binomial_invalid_lambda_neg() {
         Binomial::new(20, -10.0).unwrap();
     }
+
+    #[test]
+    fn binomial_distributions_can_be_compared() {
+        assert_eq!(Binomial::new(1, 1.0), Binomial::new(1, 1.0));
+    }
 }

rand_distr/src/cauchy.rs

@@ -31,7 +31,7 @@ use core::fmt;
 /// let v = cau.sample(&mut rand::thread_rng());
 /// println!("{} is from a Cauchy(2, 5) distribution", v);
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Cauchy<F>
 where F: Float + FloatConst, Standard: Distribution<F>
@@ -164,4 +164,9 @@ mod test {
             assert_almost_eq!(*a, *b, 1e-5);
         }
     }
+
+    #[test]
+    fn cauchy_distributions_can_be_compared() {
+        assert_eq!(Cauchy::new(1.0, 2.0), Cauchy::new(1.0, 2.0));
+    }
 }

rand_distr/src/dirichlet.rs

@@ -32,7 +32,7 @@ use alloc::{boxed::Box, vec, vec::Vec};
 /// println!("{:?} is from a Dirichlet([1.0, 2.0, 3.0]) distribution", samples);
 /// ```
 #[cfg_attr(doc_cfg, doc(cfg(feature = "alloc")))]
-#[derive(Clone, Debug)]
+#[derive(Clone, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Dirichlet<F>
 where
@@ -183,4 +183,9 @@ mod test {
     fn test_dirichlet_invalid_alpha() {
         Dirichlet::new_with_size(0.0f64, 2).unwrap();
     }
+
+    #[test]
+    fn dirichlet_distributions_can_be_compared() {
+        assert_eq!(Dirichlet::new(&[1.0, 2.0]), Dirichlet::new(&[1.0, 2.0]));
+    }
 }

rand_distr/src/exponential.rs

@@ -91,7 +91,7 @@ impl Distribution<f64> for Exp1 {
 /// let v = exp.sample(&mut rand::thread_rng());
 /// println!("{} is from a Exp(2) distribution", v);
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Exp<F>
 where F: Float, Exp1: Distribution<F>
@@ -178,4 +178,9 @@ mod test {
     fn test_exp_invalid_lambda_nan() {
         Exp::new(f64::nan()).unwrap();
     }
+
+    #[test]
+    fn exponential_distributions_can_be_compared() {
+        assert_eq!(Exp::new(1.0), Exp::new(1.0));
+    }
 }

rand_distr/src/frechet.rs

@@ -27,7 +27,7 @@ use rand::Rng;
 /// let val: f64 = thread_rng().sample(Frechet::new(0.0, 1.0, 1.0).unwrap());
 /// println!("{}", val);
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Frechet<F>
 where
@@ -182,4 +182,9 @@ mod tests {
             .zip(&probabilities)
             .all(|(p_hat, p)| (p_hat - p).abs() < 0.003))
     }
+
+    #[test]
+    fn frechet_distributions_can_be_compared() {
+        assert_eq!(Frechet::new(1.0, 2.0, 3.0), Frechet::new(1.0, 2.0, 3.0));
+    }
 }

rand_distr/src/gamma.rs

@@ -54,7 +54,7 @@ use serde::{Serialize, Deserialize};
 ///       Generating Gamma Variables" *ACM Trans. Math. Softw.* 26, 3
 ///       (September 2000), 363-372.
 ///       DOI:[10.1145/358407.358414](https://doi.acm.org/10.1145/358407.358414)
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 pub struct Gamma<F>
 where
@@ -91,7 +91,7 @@ impl fmt::Display for Error {
 #[cfg_attr(doc_cfg, doc(cfg(feature = "std")))]
 impl std::error::Error for Error {}
 
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 enum GammaRepr<F>
 where
@@ -119,7 +119,7 @@ where
 ///
 /// See `Gamma` for sampling from a Gamma distribution with general
 /// shape parameters.
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 struct GammaSmallShape<F>
 where
@@ -135,7 +135,7 @@ where
 ///
 /// See `Gamma` for sampling from a Gamma distribution with general
 /// shape parameters.
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 struct GammaLargeShape<F>
 where
@@ -280,7 +280,7 @@ where
 /// let v = chi.sample(&mut rand::thread_rng());
 /// println!("{} is from a χ²(11) distribution", v)
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 pub struct ChiSquared<F>
 where
@@ -314,7 +314,7 @@ impl fmt::Display for ChiSquaredError {
 #[cfg_attr(doc_cfg, doc(cfg(feature = "std")))]
 impl std::error::Error for ChiSquaredError {}
 
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 enum ChiSquaredRepr<F>
 where
@@ -385,7 +385,7 @@ where
 /// let v = f.sample(&mut rand::thread_rng());
 /// println!("{} is from an F(2, 32) distribution", v)
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 pub struct FisherF<F>
 where
@@ -472,7 +472,7 @@ where
 /// let v = t.sample(&mut rand::thread_rng());
 /// println!("{} is from a t(11) distribution", v)
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 pub struct StudentT<F>
 where
@@ -522,15 +522,15 @@ where
 /// Generating beta variates with nonintegral shape parameters.
 /// Communications of the ACM 21, 317-322.
 /// https://doi.org/10.1145/359460.359482
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 enum BetaAlgorithm<N> {
     BB(BB<N>),
     BC(BC<N>),
 }
 
 /// Algorithm BB for `min(alpha, beta) > 1`.
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 struct BB<N> {
     alpha: N,
@@ -539,7 +539,7 @@ struct BB<N> {
 }
 
 /// Algorithm BC for `min(alpha, beta) <= 1`.
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 struct BC<N> {
     alpha: N,
@@ -560,7 +560,7 @@ struct BC<N> {
 /// let v = beta.sample(&mut rand::thread_rng());
 /// println!("{} is from a Beta(2, 5) distribution", v);
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
 pub struct Beta<F>
 where
@@ -811,4 +811,29 @@ mod test {
             assert!(!beta.sample(&mut rng).is_nan(), "failed at i={}", i);
         }
     }
+
+    #[test]
+    fn gamma_distributions_can_be_compared() {
+        assert_eq!(Gamma::new(1.0, 2.0), Gamma::new(1.0, 2.0));
+    }
+
+    #[test]
+    fn beta_distributions_can_be_compared() {
+        assert_eq!(Beta::new(1.0, 2.0), Beta::new(1.0, 2.0));
+    }
+
+    #[test]
+    fn chi_squared_distributions_can_be_compared() {
+        assert_eq!(ChiSquared::new(1.0), ChiSquared::new(1.0));
+    }
+
+    #[test]
+    fn fisher_f_distributions_can_be_compared() {
+        assert_eq!(FisherF::new(1.0, 2.0), FisherF::new(1.0, 2.0));
+    }
+
+    #[test]
+    fn student_t_distributions_can_be_compared() {
+        assert_eq!(StudentT::new(1.0), StudentT::new(1.0));
+    }
 }

rand_distr/src/geometric.rs

@@ -27,7 +27,7 @@ use num_traits::Float;
 /// let v = geo.sample(&mut rand::thread_rng());
 /// println!("{} is from a Geometric(0.25) distribution", v);
 /// ```
-#[derive(Copy, Clone, Debug)]
+#[derive(Copy, Clone, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Geometric
 {
@@ -235,4 +235,9 @@ mod test {
             results.iter().map(|x| (x - mean) * (x - mean)).sum::<f64>() / results.len() as f64;
         assert!((variance - expected_variance).abs() < expected_variance / 10.0);
     }
+
+    #[test]
+    fn geometric_distributions_can_be_compared() {
+        assert_eq!(Geometric::new(1.0), Geometric::new(1.0));
+    }
 }

rand_distr/src/gumbel.rs

@@ -27,7 +27,7 @@ use rand::Rng;
 /// let val: f64 = thread_rng().sample(Gumbel::new(0.0, 1.0).unwrap());
 /// println!("{}", val);
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Gumbel<F>
 where
@@ -152,4 +152,9 @@ mod tests {
             .zip(&probabilities)
             .all(|(p_hat, p)| (p_hat - p).abs() < 0.003))
     }
+
+    #[test]
+    fn gumbel_distributions_can_be_compared() {
+        assert_eq!(Gumbel::new(1.0, 2.0), Gumbel::new(1.0, 2.0));
+    }
 }

rand_distr/src/hypergeometric.rs

@@ -7,7 +7,7 @@ use core::fmt;
 #[allow(unused_imports)]
 use num_traits::Float;
 
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 enum SamplingMethod {
     InverseTransform{ initial_p: f64, initial_x: i64 },
@@ -45,7 +45,7 @@ enum SamplingMethod {
 /// let v = hypergeo.sample(&mut rand::thread_rng());
 /// println!("{} is from a hypergeometric distribution", v);
 /// ```
-#[derive(Copy, Clone, Debug)]
+#[derive(Copy, Clone, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Hypergeometric {
     n1: u64,
@@ -419,4 +419,9 @@ mod test {
         test_hypergeometric_mean_and_variance(10100, 10000, 1000, &mut rng);
         test_hypergeometric_mean_and_variance(100100, 100, 10000, &mut rng);
     }
+
+    #[test]
+    fn hypergeometric_distributions_can_be_compared() {
+        assert_eq!(Hypergeometric::new(1, 2, 3), Hypergeometric::new(1, 2, 3));
+    }
 }

rand_distr/src/inverse_gaussian.rs

@@ -26,7 +26,7 @@ impl fmt::Display for Error {
 impl std::error::Error for Error {}
 
 /// The [inverse Gaussian distribution](https://en.wikipedia.org/wiki/Inverse_Gaussian_distribution)
-#[derive(Debug, Clone, Copy)]
+#[derive(Debug, Clone, Copy, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct InverseGaussian<F>
 where
@@ -109,4 +109,9 @@ mod tests {
         assert!(InverseGaussian::new(1.0, -1.0).is_err());
         assert!(InverseGaussian::new(1.0, 1.0).is_ok());
     }
+
+    #[test]
+    fn inverse_gaussian_distributions_can_be_compared() {
+        assert_eq!(InverseGaussian::new(1.0, 2.0), InverseGaussian::new(1.0, 2.0));
+    }
 }

rand_distr/src/normal.rs

@@ -112,7 +112,7 @@ impl Distribution<f64> for StandardNormal {
 /// ```
 ///
 /// [`StandardNormal`]: crate::StandardNormal
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Normal<F>
 where F: Float, StandardNormal: Distribution<F>
@@ -227,7 +227,7 @@ where F: Float, StandardNormal: Distribution<F>
 /// let v = log_normal.sample(&mut rand::thread_rng());
 /// println!("{} is from an ln N(2, 9) distribution", v)
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct LogNormal<F>
 where F: Float, StandardNormal: Distribution<F>
@@ -368,4 +368,14 @@ mod tests {
         assert!(LogNormal::from_mean_cv(0.0, 1.0).is_err());
         assert!(LogNormal::from_mean_cv(1.0, -1.0).is_err());
     }
+
+    #[test]
+    fn normal_distributions_can_be_compared() {
+        assert_eq!(Normal::new(1.0, 2.0), Normal::new(1.0, 2.0));
+    }
+
+    #[test]
+    fn log_normal_distributions_can_be_compared() {
+        assert_eq!(LogNormal::new(1.0, 2.0), LogNormal::new(1.0, 2.0));
+    }
 }

rand_distr/src/normal_inverse_gaussian.rs

@@ -26,7 +26,7 @@ impl fmt::Display for Error {
 impl std::error::Error for Error {}
 
 /// The [normal-inverse Gaussian distribution](https://en.wikipedia.org/wiki/Normal-inverse_Gaussian_distribution)
-#[derive(Debug, Clone, Copy)]
+#[derive(Debug, Clone, Copy, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct NormalInverseGaussian<F>
 where
@@ -104,4 +104,9 @@ mod tests {
         assert!(NormalInverseGaussian::new(1.0, 2.0).is_err());
         assert!(NormalInverseGaussian::new(2.0, 1.0).is_ok());
     }
+
+    #[test]
+    fn normal_inverse_gaussian_distributions_can_be_compared() {
+        assert_eq!(NormalInverseGaussian::new(1.0, 2.0), NormalInverseGaussian::new(1.0, 2.0));
+    }
 }

rand_distr/src/pareto.rs

@@ -23,7 +23,7 @@ use core::fmt;
 /// let val: f64 = thread_rng().sample(Pareto::new(1., 2.).unwrap());
 /// println!("{}", val);
 /// ```
-#[derive(Clone, Copy, Debug)]
+#[derive(Clone, Copy, Debug, PartialEq)]
 #[cfg_attr(feature = "serde1", derive(serde::Serialize, serde::Deserialize))]
 pub struct Pareto<F>
 where F: Float, OpenClosed01: Distribution<F>
@@ -131,4 +131,9 @@ mod tests {
             105.8826669383772,
         ]);
     }
+
+    #[test]
+    fn pareto_distributions_can_be_compared() {
+        assert_eq!(Pareto::new(1.0, 2.0), Pareto::new(1.0, 2.0));
+    }
 }