Update dependencies

Cargo.toml

@@ -23,7 +23,7 @@ harness = false
 name = "kurtosis"
 
 [dependencies]
-num-traits = "0.1"
+num-traits = "0.2"
 num-integer = "0.1"
 quickersort = "3"
 
@@ -38,6 +38,6 @@ version = "1"
 
 [dev-dependencies]
 bencher = "0.1"
-rand = "0.3"
+rand = "0.5"
 serde_json = "1"
-streaming-stats = "0.1"
+streaming-stats = "0.2"

tests/histogram.rs

@@ -4,7 +4,8 @@ extern crate core;
 extern crate rand;
 
 use core::iter::Iterator;
-use rand::distributions::IndependentSample;
+use rand::distributions::Distribution;
+use rand::FromEntropy;
 
 use average::Histogram;
 
@@ -188,9 +189,9 @@ fn mul() {
 fn variance() {
     let mut h = Histogram10::with_const_width(-3., 3.);
     let normal = rand::distributions::Normal::new(0., 1.);
-    let mut rng = rand::weak_rng();
+    let mut rng = rand::rngs::SmallRng::from_entropy();
     for _ in 0..1000000 {
-        let _ = h.add(normal.ind_sample(&mut rng));
+        let _ = h.add(normal.sample(&mut rng));
     }
     println!("{:?}", h);
     let sum: u64 = h.bins().iter().sum();

tests/random.rs

@@ -4,15 +4,17 @@
 
 extern crate rand;
 
+use rand::distributions::Distribution;
+
 use average::{Kurtosis, Estimate};
 
 #[test]
 fn normal_distribution() {
-    use rand::distributions::{Normal, IndependentSample};
+    use rand::distributions::Normal;
     let normal = Normal::new(2.0, 3.0);
     let mut a = Kurtosis::new();
     for _ in 0..1_000_000 {
-        a.add(normal.ind_sample(&mut ::rand::thread_rng()));
+        a.add(normal.sample(&mut ::rand::thread_rng()));
     }
     assert_almost_eq!(a.mean(), 2.0, 1e-2);
     assert_almost_eq!(a.sample_variance().sqrt(), 3.0, 1e-2);
@@ -24,12 +26,12 @@ fn normal_distribution() {
 
 #[test]
 fn exponential_distribution() {
-    use rand::distributions::{Exp, IndependentSample};
+    use rand::distributions::Exp;
     let lambda = 2.0;
     let normal = Exp::new(lambda);
     let mut a = Kurtosis::new();
     for _ in 0..6_000_000 {
-        a.add(normal.ind_sample(&mut ::rand::thread_rng()));
+        a.add(normal.sample(&mut ::rand::thread_rng()));
     }
     assert_almost_eq!(a.mean(), 1./lambda, 1e-2);
     assert_almost_eq!(a.sample_variance().sqrt(), 1./lambda, 1e-2);

tests/streaming_stats.rs

@@ -7,13 +7,14 @@ extern crate stats;
 
 /// Create a random vector by sampling from a normal distribution.
 fn initialize_vec(size: usize) -> Vec<f64> {
-    use rand::distributions::{Normal, IndependentSample};
+    use rand::distributions::{Normal, Distribution};
     use rand::{XorShiftRng, SeedableRng};
     let normal = Normal::new(2.0, 3.0);
     let mut values = Vec::with_capacity(size);
-    let mut rng = XorShiftRng::from_seed([1, 2, 3, 4]);
+    let mut rng = XorShiftRng::from_seed(
+        [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]);
     for _ in 0..size {
-        values.push(normal.ind_sample(&mut rng));
+        values.push(normal.sample(&mut rng));
     }
     values
 }
@@ -33,5 +34,5 @@ fn average_vs_streaming_stats_large() {
     let a: average::MeanWithError = values.iter().collect();
     let b: stats::OnlineStats = values.iter().map(|x| *x).collect();
     assert_almost_eq!(a.mean(), b.mean(), 1e-16);
-    assert_almost_eq!(a.population_variance(), b.variance(), 1e-13);
+    assert_almost_eq!(a.population_variance(), b.variance(), 1e-12);
 }