doc: add doc(cfg(feature = "...'))

This will add a note "Available on crate feature <...> only."
to feature-gated structs, impls etc.

Cargo.toml

@@ -56,3 +56,7 @@ features = ["macros"]
 level = "warn"
 # Set by cargo-llvm-cov when running on nightly
 check-cfg = ['cfg(coverage_nightly)']
+
+[package.metadata.docs.rs]
+all-features = true
+rustdoc-args = ["--cfg", "docsrs"]

src/distribution/bernoulli.rs

@@ -85,6 +85,7 @@ impl std::fmt::Display for Bernoulli {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Bernoulli {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         rng.gen_bool(self.p()) as u8 as f64

src/distribution/beta.rs

@@ -121,6 +121,7 @@ impl std::fmt::Display for Beta {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Beta {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         // Generated by sampling two gamma distributions and normalizing.

src/distribution/binomial.rs

@@ -110,6 +110,7 @@ impl std::fmt::Display for Binomial {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Binomial {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         (0..self.n).fold(0.0, |acc, _| {

src/distribution/categorical.rs

@@ -124,6 +124,7 @@ impl std::fmt::Display for Categorical {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Categorical {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         sample_unchecked(rng, &self.cdf)
@@ -323,6 +324,7 @@ impl Discrete<u64, f64> for Categorical {
 /// Draws a sample from the categorical distribution described by `cdf`
 /// without doing any bounds checking
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(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()

src/distribution/cauchy.rs

@@ -111,6 +111,7 @@ impl std::fmt::Display for Cauchy {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Cauchy {
     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

@@ -94,6 +94,7 @@ impl std::fmt::Display for Chi {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Chi {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         (0..self.freedom as i64)

src/distribution/chi_squared.rs

@@ -101,6 +101,7 @@ impl std::fmt::Display for ChiSquared {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for ChiSquared {
     fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> f64 {
         ::rand::distributions::Distribution::sample(&self.g, r)

src/distribution/dirac.rs

@@ -69,6 +69,7 @@ impl std::fmt::Display for Dirac {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Dirac {
     fn sample<R: ::rand::Rng + ?Sized>(&self, _: &mut R) -> f64 {
         self.0

src/distribution/dirichlet.rs

@@ -192,6 +192,7 @@ where
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl<D> ::rand::distributions::Distribution<OVector<f64, D>> for Dirichlet<D>
 where
     D: Dim,

src/distribution/discrete_uniform.rs

@@ -75,6 +75,7 @@ impl std::fmt::Display for DiscreteUniform {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for DiscreteUniform {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         rng.gen_range(self.min..=self.max) as f64

src/distribution/empirical.rs

@@ -175,6 +175,7 @@ impl std::fmt::Display for Empirical {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Empirical {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         use crate::distribution::Uniform;

src/distribution/erlang.rs

@@ -83,6 +83,7 @@ impl std::fmt::Display for Erlang {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Erlang {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         ::rand::distributions::Distribution::sample(&self.g, rng)

src/distribution/exponential.rs

@@ -91,6 +91,7 @@ impl std::fmt::Display for Exp {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Exp {
     fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> f64 {
         use crate::distribution::ziggurat;

src/distribution/fisher_snedecor.rs

@@ -124,6 +124,7 @@ impl std::fmt::Display for FisherSnedecor {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for FisherSnedecor {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         (super::gamma::sample_unchecked(rng, self.freedom_1 / 2.0, 0.5) * self.freedom_2)

src/distribution/gamma.rs

@@ -122,6 +122,7 @@ impl std::fmt::Display for Gamma {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Gamma {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         sample_unchecked(rng, self.shape, self.rate)
@@ -401,6 +402,7 @@ impl Continuous<f64, f64> for Gamma {
 /// ACM Transactions on Mathematical Software, Vol. 26, No. 3, September 2000,
 /// Pages 363-372
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 pub fn sample_unchecked<R: ::rand::Rng + ?Sized>(rng: &mut R, shape: f64, rate: f64) -> f64 {
     let mut a = shape;
     let mut afix = 1.0;

src/distribution/geometric.rs

@@ -91,6 +91,7 @@ impl std::fmt::Display for Geometric {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Geometric {
     fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> f64 {
         use ::rand::distributions::OpenClosed01;

src/distribution/hypergeometric.rs

@@ -146,6 +146,7 @@ impl std::fmt::Display for Hypergeometric {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Hypergeometric {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         let mut population = self.population as f64;

src/distribution/inverse_gamma.rs

@@ -119,6 +119,7 @@ impl std::fmt::Display for InverseGamma {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for InverseGamma {
     fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> f64 {
         1.0 / super::gamma::sample_unchecked(r, self.shape, self.rate)

src/distribution/laplace.rs

@@ -111,6 +111,7 @@ impl std::fmt::Display for Laplace {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Laplace {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         let x: f64 = rng.gen_range(-0.5..0.5);

src/distribution/log_normal.rs

@@ -88,6 +88,7 @@ impl std::fmt::Display for LogNormal {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for LogNormal {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         super::normal::sample_unchecked(rng, self.location, self.scale).exp()

src/distribution/mod.rs

@@ -51,6 +51,7 @@ mod chi;
 mod chi_squared;
 mod dirac;
 #[cfg(feature = "nalgebra")]
+#[cfg_attr(docsrs, doc(cfg(feature = "nalgebra")))]
 mod dirichlet;
 mod discrete_uniform;
 mod empirical;
@@ -67,10 +68,13 @@ mod inverse_gamma;
 mod laplace;
 mod log_normal;
 #[cfg(feature = "nalgebra")]
+#[cfg_attr(docsrs, doc(cfg(feature = "nalgebra")))]
 mod multinomial;
 #[cfg(feature = "nalgebra")]
+#[cfg_attr(docsrs, doc(cfg(feature = "nalgebra")))]
 mod multivariate_normal;
 #[cfg(feature = "nalgebra")]
+#[cfg_attr(docsrs, doc(cfg(feature = "nalgebra")))]
 mod multivariate_students_t;
 mod negative_binomial;
 mod normal;
@@ -81,8 +85,10 @@ mod triangular;
 mod uniform;
 mod weibull;
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 mod ziggurat;
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 mod ziggurat_tables;
 
 /// The `ContinuousCDF` trait is used to specify an interface for univariate

src/distribution/multinomial.rs

@@ -160,6 +160,7 @@ where
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl<D> ::rand::distributions::Distribution<OVector<f64, D>> for Multinomial<D>
 where
     D: Dim,

src/distribution/multivariate_normal.rs

@@ -239,6 +239,7 @@ where
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl<D> ::rand::distributions::Distribution<OVector<f64, D>> for MultivariateNormal<D>
 where
     D: Dim,

src/distribution/multivariate_students_t.rs

@@ -197,6 +197,7 @@ where
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl<D> ::rand::distributions::Distribution<OVector<f64, D>> for MultivariateStudent<D>
 where
     D: Dim,

src/distribution/negative_binomial.rs

@@ -136,6 +136,7 @@ impl std::fmt::Display for NegativeBinomial {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<u64> for NegativeBinomial {
     fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> u64 {
         use crate::distribution::{gamma, poisson};

src/distribution/normal.rs

@@ -106,6 +106,7 @@ impl std::fmt::Display for Normal {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Normal {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         sample_unchecked(rng, self.mean, self.std_dev)
@@ -348,6 +349,7 @@ pub fn ln_pdf_unchecked(x: f64, mean: f64, std_dev: f64) -> f64 {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 /// draws a sample from a normal distribution using the Box-Muller algorithm
 pub fn sample_unchecked<R: ::rand::Rng + ?Sized>(rng: &mut R, mean: f64, std_dev: f64) -> f64 {
     use crate::distribution::ziggurat;

src/distribution/pareto.rs

@@ -113,6 +113,7 @@ impl std::fmt::Display for Pareto {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Pareto {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         use rand::distributions::OpenClosed01;

src/distribution/poisson.rs

@@ -90,6 +90,7 @@ impl std::fmt::Display for Poisson {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Poisson {
     /// Generates one sample from the Poisson distribution either by
     /// Knuth's method if lambda < 30.0 or Rejection method PA by
@@ -284,6 +285,7 @@ impl Discrete<u64, f64> for Poisson {
 /// Series C (Applied Statistics) Vol. 28 No. 1. (1979) pp. 29 - 35
 /// otherwise
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 pub fn sample_unchecked<R: ::rand::Rng + ?Sized>(rng: &mut R, lambda: f64) -> f64 {
     if lambda < 30.0 {
         let limit = (-lambda).exp();

src/distribution/students_t.rs

@@ -143,6 +143,7 @@ impl std::fmt::Display for StudentsT {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for StudentsT {
     fn sample<R: ::rand::Rng + ?Sized>(&self, r: &mut R) -> f64 {
         // based on method 2, section 5 in chapter 9 of L. Devroye's

src/distribution/triangular.rs

@@ -112,6 +112,7 @@ impl std::fmt::Display for Triangular {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Triangular {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         sample_unchecked(rng, self.min, self.max, self.mode)
@@ -383,6 +384,7 @@ impl Continuous<f64, f64> for Triangular {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 fn sample_unchecked<R: ::rand::Rng + ?Sized>(rng: &mut R, min: f64, max: f64, mode: f64) -> f64 {
     let f: f64 = rng.gen();
     if f < (mode - min) / (max - min) {

src/distribution/uniform.rs

@@ -120,6 +120,7 @@ impl std::fmt::Display for Uniform {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Uniform {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         let d = rand::distributions::Uniform::new_inclusive(self.min, self.max);
@@ -495,6 +496,7 @@ mod tests {
     }
 
     #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
     #[test]
     fn test_samples_in_range() {
         use rand::rngs::StdRng;

src/distribution/weibull.rs

@@ -121,6 +121,7 @@ impl std::fmt::Display for Weibull {
 }
 
 #[cfg(feature = "rand")]
+#[cfg_attr(docsrs, doc(cfg(feature = "rand")))]
 impl ::rand::distributions::Distribution<f64> for Weibull {
     fn sample<R: ::rand::Rng + ?Sized>(&self, rng: &mut R) -> f64 {
         let x: f64 = rng.gen();

src/lib.rs

@@ -50,6 +50,7 @@
 #![allow(clippy::many_single_char_names)]
 #![forbid(unsafe_code)]
 #![cfg_attr(coverage_nightly, feature(coverage_attribute))]
+#![cfg_attr(docsrs, feature(doc_cfg))]
 
 #[macro_use]
 extern crate approx;