build: make rand an optional dependency

Author: FreezyLemon

Cargo.toml

@@ -22,21 +22,26 @@ path = "src/lib.rs"
 [[bench]]
 name = "order_statistics"
 harness = false
+required-features = ["rand"]
 
 [features]
-default = ["nalgebra"]
+default = ["nalgebra", "rand"]
 nalgebra = ["dep:nalgebra"]
+rand = ["dep:rand", "nalgebra?/rand"]
 
 [dependencies]
-rand = "0.8"
 approx = "0.5.0"
 num-traits = "0.2.14"
 
+[dependencies.rand]
+version = "0.8"
+optional = true
+
 [dependencies.nalgebra]
 version = "0.32"
 optional = true
 default-features = false
-features = ["rand", "std"]
+features = ["std"]
 
 [dev-dependencies]
 criterion = "0.5"

benches/order_statistics.rs

@@ -1,4 +1,3 @@
-extern crate rand;
 extern crate statrs;
 use criterion::{black_box, criterion_group, criterion_main, BatchSize, Criterion};
 use rand::prelude::*;

src/distribution/bernoulli.rs

@@ -1,6 +1,5 @@
 use crate::distribution::{Binomial, BinomialError, Discrete, DiscreteCDF};
 use crate::statistics::*;
-use rand::Rng;
 
 /// Implements the
 /// [Bernoulli](https://en.wikipedia.org/wiki/Bernoulli_distribution)
@@ -85,8 +84,9 @@ impl std::fmt::Display for Bernoulli {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for Bernoulli {
-    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         rng.gen_bool(self.p()) as u8 as f64
     }
 }

src/distribution/beta.rs

@@ -1,7 +1,6 @@
 use crate::distribution::{Continuous, ContinuousCDF};
 use crate::function::{beta, gamma};
 use crate::statistics::*;
-use rand::Rng;
 
 /// Implements the [Beta](https://en.wikipedia.org/wiki/Beta_distribution)
 /// distribution
@@ -121,8 +120,9 @@ impl std::fmt::Display for Beta {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for Beta {
-    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         // Generated by sampling two gamma distributions and normalizing.
         let x = super::gamma::sample_unchecked(rng, self.shape_a, 1.0);
         let y = super::gamma::sample_unchecked(rng, self.shape_b, 1.0);

src/distribution/binomial.rs

@@ -1,7 +1,6 @@
 use crate::distribution::{Discrete, DiscreteCDF};
 use crate::function::{beta, factorial};
 use crate::statistics::*;
-use rand::Rng;
 use std::f64;
 
 /// Implements the
@@ -110,8 +109,9 @@ impl std::fmt::Display for Binomial {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for Binomial {
-    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         (0..self.n).fold(0.0, |acc, _| {
             let n: f64 = rng.gen();
             if n < self.p {

src/distribution/categorical.rs

@@ -1,6 +1,5 @@
 use crate::distribution::{Discrete, DiscreteCDF};
 use crate::statistics::*;
-use rand::Rng;
 use std::f64;
 
 /// Implements the
@@ -124,8 +123,9 @@ impl std::fmt::Display for Categorical {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for Categorical {
-    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         sample_unchecked(rng, &self.cdf)
     }
 }
@@ -322,7 +322,8 @@ impl Discrete<u64, f64> for Categorical {
 
 /// Draws a sample from the categorical distribution described by `cdf`
 /// without doing any bounds checking
-pub fn sample_unchecked<R: Rng + ?Sized>(rng: &mut R, cdf: &[f64]) -> f64 {
+#[cfg(feature = "rand")]
+pub fn sample_unchecked<R: ::rand::Rng + ?Sized>(rng: &mut R, cdf: &[f64]) -> f64 {
     let draw = rng.gen::<f64>() * cdf.last().unwrap();
     cdf.iter()
         .enumerate()

src/distribution/cauchy.rs

@@ -1,6 +1,5 @@
 use crate::distribution::{Continuous, ContinuousCDF};
 use crate::statistics::*;
-use rand::Rng;
 use std::f64;
 
 /// Implements the [Cauchy](https://en.wikipedia.org/wiki/Cauchy_distribution)
@@ -111,8 +110,9 @@ impl std::fmt::Display for Cauchy {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for Cauchy {
-    fn sample<R: Rng + ?Sized>(&self, r: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> f64 {
         self.location + self.scale * (f64::consts::PI * (r.gen::<f64>() - 0.5)).tan()
     }
 }

src/distribution/chi.rs

@@ -1,7 +1,6 @@
 use crate::distribution::{Continuous, ContinuousCDF};
 use crate::function::gamma;
 use crate::statistics::*;
-use rand::Rng;
 use std::f64;
 
 /// Implements the [Chi](https://en.wikipedia.org/wiki/Chi_distribution)
@@ -94,8 +93,9 @@ impl std::fmt::Display for Chi {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for Chi {
-    fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         (0..self.freedom as i64)
             .fold(0.0, |acc, _| {
                 acc + super::normal::sample_unchecked(rng, 0.0, 1.0).powf(2.0)

src/distribution/chi_squared.rs

@@ -1,6 +1,5 @@
 use crate::distribution::{Continuous, ContinuousCDF, Gamma, GammaError};
 use crate::statistics::*;
-use rand::Rng;
 use std::f64;
 
 /// Implements the
@@ -101,8 +100,9 @@ impl std::fmt::Display for ChiSquared {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for ChiSquared {
-    fn sample<R: Rng + ?Sized>(&self, r: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> f64 {
         ::rand::distributions::Distribution::sample(&self.g, r)
     }
 }

src/distribution/dirac.rs

@@ -1,6 +1,5 @@
 use crate::distribution::ContinuousCDF;
 use crate::statistics::*;
-use rand::Rng;
 
 /// Implements the [Dirac Delta](https://en.wikipedia.org/wiki/Dirac_delta_function#As_a_distribution)
 /// distribution
@@ -69,8 +68,9 @@ impl std::fmt::Display for Dirac {
     }
 }
 
+#[cfg(feature = "rand")]
 impl ::rand::distributions::Distribution<f64> for Dirac {
-    fn sample<R: Rng + ?Sized>(&self, _: &mut R) -> f64 {
+    fn sample<R: ::rand::Rng + ?Sized>(&self, _: &mut R) -> f64 {
         self.0
     }
 }