Lower precision of tests where required

rand_distr/src/cauchy.rs

@@ -160,7 +160,7 @@ mod test {
         let expected = [15.023088, -5.446413, 3.7092876, 3.112482];
         for (a, b) in buf.iter().zip(expected.iter()) {
             let (a, b) = (*a, *b);
-            assert!((a - b).abs() < 1e-6, "expected: {} = {}", a, b);
+            assert!((a - b).abs() < 1e-5, "expected: {} = {}", a, b);
         }
     }
 }

rand_distr/src/normal.rs

@@ -345,7 +345,8 @@ mod tests {
         assert_almost_eq!(lnorm.norm.std_dev, 1.0, 2e-16);
 
         let lnorm = LogNormal::from_mean_cv(e.powf(1.5), (e - 1.0).sqrt()).unwrap();
-        assert_eq!((lnorm.norm.mean, lnorm.norm.std_dev), (1.0, 1.0));
+        assert!((lnorm.norm.mean - 1.0).abs() < 1e-15);
+        assert_eq!(lnorm.norm.std_dev, 1.0);
     }
     #[test]
     fn test_log_normal_invalid_sd() {

rand_distr/src/pareto.rs

@@ -87,6 +87,7 @@ where F: Float, OpenClosed01: Distribution<F>
 #[cfg(test)]
 mod tests {
     use super::*;
+    use core::fmt::{Debug, Display};
 
     #[test]
     #[should_panic]
@@ -108,21 +109,20 @@ mod tests {
 
     #[test]
     fn value_stability() {
-        fn test_samples<F: Float + core::fmt::Debug, D: Distribution<F>>(
-            distr: D, zero: F, expected: &[F],
+        fn test_samples<F: Float + Debug + Display, D: Distribution<F>>(
+            distr: D, thresh: F, expected: &[F],
         ) {
             let mut rng = crate::test::rng(213);
-            let mut buf = [zero; 4];
-            for x in &mut buf {
-                *x = rng.sample(&distr);
+            for v in expected {
+                let x = rng.sample(&distr);
+                assert!((x - *v).abs() < thresh, "not approx eq: {}, {}", x, *v);
             }
-            assert_eq!(buf, expected);
         }
 
-        test_samples(Pareto::new(1.0, 1.0).unwrap(), 0f32, &[
+        test_samples(Pareto::new(1f32, 1.0).unwrap(), 1e-6, &[
             1.0423688, 2.1235929, 4.132709, 1.4679428,
         ]);
-        test_samples(Pareto::new(2.0, 0.5).unwrap(), 0f64, &[
+        test_samples(Pareto::new(2.0, 0.5).unwrap(), 1e-14, &[
             9.019295276219136,
             4.3097126018270595,
             6.837815045397157,

rand_distr/tests/value_stability.rs

@@ -6,7 +6,9 @@
 // option. This file may not be copied, modified, or distributed
 // except according to those terms.
 
-use core::{fmt::Debug, cmp::PartialEq};
+use core::fmt::{Debug, Display};
+use core::cmp::PartialEq;
+use num_traits::Float;
 use rand::Rng;
 use rand_distr::*;
 
@@ -26,6 +28,16 @@ fn test_samples<F: Debug + Copy + PartialEq, D: Distribution<F>>(
     }
 }
 
+fn test_samples_approx<F: Float + Display + Copy + PartialEq, D: Distribution<F>>(
+    seed: u64, distr: D, thresh: F, expected: &[F],
+) {
+    let mut rng = get_rng(seed);
+    for &val in expected {
+        let x = rng.sample(&distr);
+        assert!((x - val).abs() < thresh, "not approx eq: {}, {}", x, val);
+    }
+}
+
 #[test]
 fn binominal_stability() {
     // We have multiple code paths: np < 10, p > 0.5
@@ -95,7 +107,7 @@ fn pareto_stability() {
     test_samples(213, Pareto::new(1.0, 1.0).unwrap(), &[
         1.0423688f32, 2.1235929, 4.132709, 1.4679428,
     ]);
-    test_samples(213, Pareto::new(2.0, 0.5).unwrap(), &[
+    test_samples_approx(213, Pareto::new(2.0, 0.5).unwrap(), 1e-14, &[
         9.019295276219136f64,
         4.3097126018270595,
         6.837815045397157,
@@ -184,7 +196,7 @@ fn gamma_stability() {
         0.5013580219361969,
         0.1457735613733489,
     ]);
-    test_samples(223, ChiSquared::new(0.1).unwrap(), &[
+    test_samples_approx(223, ChiSquared::new(0.1).unwrap(), 1e-15, &[
         0.014824404726978617f64,
         0.021602123937134326,
         0.0000003431429746851693,
@@ -201,7 +213,7 @@ fn gamma_stability() {
     test_samples(223, FisherF::new(1.0, 1.0).unwrap(), &[
         0.29925257f32, 3.4392934, 9.567652, 0.020074,
     ]);
-    test_samples(223, FisherF::new(0.7, 13.5).unwrap(), &[
+    test_samples_approx(223, FisherF::new(0.7, 13.5).unwrap(), 1e-14, &[
         3.3196593155045124f64,
         0.3409169916262829,
         0.03377989856426519,
@@ -285,7 +297,7 @@ fn normal_stability() {
     test_samples(213, LogNormal::new(0.0, 1.0).unwrap(), &[
         0.88830346f32, 2.1844804, 1.0678421, 0.30322206,
     ]);
-    test_samples(213, LogNormal::new(2.0, 0.5).unwrap(), &[
+    test_samples_approx(213, LogNormal::new(2.0, 0.5).unwrap(), 1e-14, &[
         6.964174338639032f64,
         10.921015733601452,
         7.6355881556915906,
@@ -339,6 +351,6 @@ fn cauchy_stability() {
     let expected = [15.023088, -5.446413, 3.7092876, 3.112482];
     for &a in expected.iter() {
         let b = rng.sample(&distr);
-        assert!((a - b).abs() < 1e-6, "expected: {} = {}", a, b);
+        assert!((a - b).abs() < 1e-5, "expected: {} = {}", a, b);
     }
 }