Update dependencies
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@ -38,8 +38,9 @@ version = "0.3"
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[dev-dependencies]
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bencher = "0.1"
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rand = "0.6"
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rand_xoshiro = "0.1"
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rand = "0.7"
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rand_xoshiro = "0.3"
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rand_distr = "0.2"
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serde_json = "1"
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streaming-stats = "0.2"
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quantiles = "0.7"
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@ -2,6 +2,8 @@
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extern crate core;
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extern crate rand;
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extern crate rand_xoshiro;
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extern crate rand_distr;
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#[cfg(feature = "serde1")]
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#[macro_use] extern crate serde_derive;
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#[cfg(feature = "serde1")]
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@ -10,8 +12,8 @@ extern crate serde_json;
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#[macro_use] extern crate serde_big_array;
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use core::iter::Iterator;
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use rand::distributions::Distribution;
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use rand::FromEntropy;
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use rand::SeedableRng;
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use rand_distr::Distribution;
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use average::{Histogram, Merge};
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@ -197,8 +199,8 @@ fn mul() {
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#[test]
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fn variance() {
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let mut h = Histogram10::with_const_width(-3., 3.);
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let normal = rand::distributions::Normal::new(0., 1.);
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let mut rng = rand::rngs::SmallRng::from_entropy();
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let normal = rand_distr::Normal::new(0., 1.).unwrap();
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let mut rng = rand_xoshiro::Xoshiro256StarStar::from_entropy();
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for _ in 0..1000000 {
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let _ = h.add(normal.sample(&mut rng));
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}
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@ -3,15 +3,15 @@
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#[macro_use] extern crate average;
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extern crate rand;
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extern crate rand_distr;
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use rand::distributions::Distribution;
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use rand_distr::Distribution;
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use average::{Kurtosis, Estimate};
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#[test]
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fn normal_distribution() {
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use rand::distributions::Normal;
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let normal = Normal::new(2.0, 3.0);
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let normal = rand_distr::Normal::new(2.0, 3.0).unwrap();
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let mut a = Kurtosis::new();
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for _ in 0..1_000_000 {
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a.add(normal.sample(&mut ::rand::thread_rng()));
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@ -26,9 +26,8 @@ fn normal_distribution() {
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#[test]
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fn exponential_distribution() {
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use rand::distributions::Exp;
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let lambda = 2.0;
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let normal = Exp::new(lambda);
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let normal = rand_distr::Exp::new(lambda).unwrap();
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let mut a = Kurtosis::new();
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for _ in 0..6_000_000 {
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a.add(normal.sample(&mut ::rand::thread_rng()));
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@ -3,17 +3,18 @@
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#[macro_use] extern crate average;
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extern crate rand;
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extern crate rand_xoshiro;
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extern crate rand_distr;
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extern crate stats;
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/// Create a random vector by sampling from a normal distribution.
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fn initialize_vec(size: usize) -> Vec<f64> {
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use rand::distributions::{Normal, Distribution};
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use rand_distr::{Normal, Distribution};
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use rand_xoshiro::Xoshiro256StarStar;
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use rand::SeedableRng;
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use rand::rngs::SmallRng;
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let normal = Normal::new(2.0, 3.0);
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let normal = Normal::new(2.0, 3.0).unwrap();
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let mut values = Vec::with_capacity(size);
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let mut rng = SmallRng::from_seed(
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[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]);
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let mut rng = Xoshiro256StarStar::seed_from_u64(42);
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for _ in 0..size {
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values.push(normal.sample(&mut rng));
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}
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