diff options
Diffstat (limited to 'rand/src/distributions/gamma.rs')
| -rw-r--r-- | rand/src/distributions/gamma.rs | 90 |
1 files changed, 24 insertions, 66 deletions
diff --git a/rand/src/distributions/gamma.rs b/rand/src/distributions/gamma.rs index 43ac2bc..b5a97f5 100644 --- a/rand/src/distributions/gamma.rs +++ b/rand/src/distributions/gamma.rs @@ -8,13 +8,14 @@ // except according to those terms. //! The Gamma and derived distributions. +#![allow(deprecated)] use self::GammaRepr::*; use self::ChiSquaredRepr::*; -use Rng; -use distributions::normal::StandardNormal; -use distributions::{Distribution, Exp, Open01}; +use crate::Rng; +use crate::distributions::normal::StandardNormal; +use crate::distributions::{Distribution, Exp, Open01}; /// The Gamma distribution `Gamma(shape, scale)` distribution. /// @@ -32,20 +33,11 @@ use distributions::{Distribution, Exp, Open01}; /// == 1`, and using the boosting technique described in that paper for /// `shape < 1`. /// -/// # Example -/// -/// ``` -/// use rand::distributions::{Distribution, Gamma}; -/// -/// let gamma = Gamma::new(2.0, 5.0); -/// let v = gamma.sample(&mut rand::thread_rng()); -/// println!("{} is from a Gamma(2, 5) distribution", v); -/// ``` -/// /// [^1]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple Method for /// 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) +#[deprecated(since="0.7.0", note="moved to rand_distr crate")] #[derive(Clone, Copy, Debug)] pub struct Gamma { repr: GammaRepr, @@ -174,16 +166,7 @@ impl Distribution<f64> for GammaLargeShape { /// of `k` independent standard normal random variables. For other /// `k`, this uses the equivalent characterisation /// `χ²(k) = Gamma(k/2, 2)`. -/// -/// # Example -/// -/// ``` -/// use rand::distributions::{ChiSquared, Distribution}; -/// -/// let chi = ChiSquared::new(11.0); -/// let v = chi.sample(&mut rand::thread_rng()); -/// println!("{} is from a χ²(11) distribution", v) -/// ``` +#[deprecated(since="0.7.0", note="moved to rand_distr crate")] #[derive(Clone, Copy, Debug)] pub struct ChiSquared { repr: ChiSquaredRepr, @@ -229,16 +212,7 @@ impl Distribution<f64> for ChiSquared { /// This distribution is equivalent to the ratio of two normalised /// chi-squared distributions, that is, `F(m,n) = (χ²(m)/m) / /// (χ²(n)/n)`. -/// -/// # Example -/// -/// ``` -/// use rand::distributions::{FisherF, Distribution}; -/// -/// let f = FisherF::new(2.0, 32.0); -/// let v = f.sample(&mut rand::thread_rng()); -/// println!("{} is from an F(2, 32) distribution", v) -/// ``` +#[deprecated(since="0.7.0", note="moved to rand_distr crate")] #[derive(Clone, Copy, Debug)] pub struct FisherF { numer: ChiSquared, @@ -270,16 +244,7 @@ impl Distribution<f64> for FisherF { /// The Student t distribution, `t(nu)`, where `nu` is the degrees of /// freedom. -/// -/// # Example -/// -/// ``` -/// use rand::distributions::{StudentT, Distribution}; -/// -/// let t = StudentT::new(11.0); -/// let v = t.sample(&mut rand::thread_rng()); -/// println!("{} is from a t(11) distribution", v) -/// ``` +#[deprecated(since="0.7.0", note="moved to rand_distr crate")] #[derive(Clone, Copy, Debug)] pub struct StudentT { chi: ChiSquared, @@ -305,16 +270,7 @@ impl Distribution<f64> for StudentT { } /// The Beta distribution with shape parameters `alpha` and `beta`. -/// -/// # Example -/// -/// ``` -/// use rand::distributions::{Distribution, Beta}; -/// -/// let beta = Beta::new(2.0, 5.0); -/// let v = beta.sample(&mut rand::thread_rng()); -/// println!("{} is from a Beta(2, 5) distribution", v); -/// ``` +#[deprecated(since="0.7.0", note="moved to rand_distr crate")] #[derive(Clone, Copy, Debug)] pub struct Beta { gamma_a: Gamma, @@ -345,30 +301,32 @@ impl Distribution<f64> for Beta { #[cfg(test)] mod test { - use distributions::Distribution; + use crate::distributions::Distribution; use super::{Beta, ChiSquared, StudentT, FisherF}; + const N: u32 = 100; + #[test] fn test_chi_squared_one() { let chi = ChiSquared::new(1.0); - let mut rng = ::test::rng(201); - for _ in 0..1000 { + let mut rng = crate::test::rng(201); + for _ in 0..N { chi.sample(&mut rng); } } #[test] fn test_chi_squared_small() { let chi = ChiSquared::new(0.5); - let mut rng = ::test::rng(202); - for _ in 0..1000 { + let mut rng = crate::test::rng(202); + for _ in 0..N { chi.sample(&mut rng); } } #[test] fn test_chi_squared_large() { let chi = ChiSquared::new(30.0); - let mut rng = ::test::rng(203); - for _ in 0..1000 { + let mut rng = crate::test::rng(203); + for _ in 0..N { chi.sample(&mut rng); } } @@ -381,8 +339,8 @@ mod test { #[test] fn test_f() { let f = FisherF::new(2.0, 32.0); - let mut rng = ::test::rng(204); - for _ in 0..1000 { + let mut rng = crate::test::rng(204); + for _ in 0..N { f.sample(&mut rng); } } @@ -390,8 +348,8 @@ mod test { #[test] fn test_t() { let t = StudentT::new(11.0); - let mut rng = ::test::rng(205); - for _ in 0..1000 { + let mut rng = crate::test::rng(205); + for _ in 0..N { t.sample(&mut rng); } } @@ -399,8 +357,8 @@ mod test { #[test] fn test_beta() { let beta = Beta::new(1.0, 2.0); - let mut rng = ::test::rng(201); - for _ in 0..1000 { + let mut rng = crate::test::rng(201); + for _ in 0..N { beta.sample(&mut rng); } } |