rand: Update ndarray-rand to rand 0.8

Also edit docs and links in docs. Remove some instances of versioned
links (we can't have too many places where we need to update the version
for each new version of rand).

Update ndarray-rand quickcheck after rand update

(quickcheck is still on rand 0.7, but the rest of the crate uses rand 0.8)

Update numeric-tests to rand 0.8

Author: bluss

ndarray-rand/Cargo.toml

@@ -15,15 +15,15 @@ keywords = ["multidimensional", "matrix", "rand", "ndarray"]
 
 [dependencies]
 ndarray = { version = "0.14", path = ".." }
-rand_distr = "0.3.0"
+rand_distr = "0.4.0"
 quickcheck = { version = "0.9", default-features = false, optional = true }
 
 [dependencies.rand]
-version = "0.7.0"
+version = "0.8.0"
 features = ["small_rng"]
 
 [dev-dependencies]
-rand_isaac = "0.2.0"
+rand_isaac = "0.3.0"
 quickcheck = { version = "0.9", default-features = false }
 
 [package.metadata.release]

ndarray-rand/src/lib.rs

@@ -12,16 +12,16 @@
 //!
 //! ## Note
 //!
-//! `ndarray-rand` depends on [`rand` 0.7][rand].
+//! `ndarray-rand` depends on [`rand` 0.8][rand].
 //!
 //! [`rand`][rand] and [`rand_distr`][rand_distr]
 //! are re-exported as sub-modules, [`ndarray_rand::rand`](rand/index.html)
 //! and [`ndarray_rand::rand_distr`](rand_distr/index.html) respectively.
 //! You can use these submodules for guaranteed version compatibility or
 //! convenience.
 //!
-//! [rand]: https://docs.rs/rand/0.7
-//! [rand_distr]: https://docs.rs/rand_distr/0.3
+//! [rand]: https://docs.rs/rand/0.8
+//! [rand_distr]: https://docs.rs/rand_distr/0.4
 //!
 //! If you want to use a random number generator or distribution from another crate
 //! with `ndarray-rand`, you need to make sure that the other crate also depends on the
@@ -39,12 +39,12 @@ use ndarray::{ArrayBase, DataOwned, Dimension};
 #[cfg(feature = "quickcheck")]
 use quickcheck::{Arbitrary, Gen};
 
-/// [`rand`](https://docs.rs/rand/0.7), re-exported for convenience and version-compatibility.
+/// `rand`, re-exported for convenience and version-compatibility.
 pub mod rand {
     pub use rand::*;
 }
 
-/// [`rand-distr`](https://docs.rs/rand_distr/0.3), re-exported for convenience and version-compatibility.
+/// `rand-distr`, re-exported for convenience and version-compatibility.
 pub mod rand_distr {
     pub use rand_distr::*;
 }
@@ -55,8 +55,7 @@ pub mod rand_distr {
 /// for other types.
 ///
 /// The default RNG is a fast automatically seeded rng (currently
-/// [`rand::rngs::SmallRng`](https://docs.rs/rand/0.7/rand/rngs/struct.SmallRng.html)
-/// seeded from [`rand::thread_rng`](https://docs.rs/rand/0.7/rand/fn.thread_rng.html)).
+/// [`rand::rngs::SmallRng`], seeded from [`rand::thread_rng`]).
 ///
 /// Note that `SmallRng` is cheap to initialize and fast, but it may generate
 /// low-quality random numbers, and reproducibility is not guaranteed. See its
@@ -298,7 +297,7 @@ pub enum SamplingStrategy {
 #[cfg(feature = "quickcheck")]
 impl Arbitrary for SamplingStrategy {
     fn arbitrary<G: Gen>(g: &mut G) -> Self {
-        if g.gen_bool(0.5) {
+        if bool::arbitrary(g) {
             SamplingStrategy::WithReplacement
         } else {
             SamplingStrategy::WithoutReplacement

numeric-tests/Cargo.toml

@@ -8,10 +8,10 @@ publish = false
 approx = "0.4"
 ndarray = { path = "..", features = ["approx"] }
 ndarray-rand = { path = "../ndarray-rand/" }
-rand_distr = "0.3"
+rand_distr = "0.4"
 
 [dependencies.rand]
-version = "0.7.0"
+version = "0.8.0"
 features = ["small_rng"]
 
 [lib]

numeric-tests/tests/accuracy.rs

@@ -76,8 +76,8 @@ fn accurate_eye_f32() {
     // pick a few random sizes
     let mut rng = SmallRng::from_entropy();
     for _ in 0..10 {
-        let i = rng.gen_range(15, 512);
-        let j = rng.gen_range(15, 512);
+        let i = rng.gen_range(15..512);
+        let j = rng.gen_range(15..512);
         println!("Testing size {} by {}", i, j);
         let a = gen(Ix2(i, j));
         let eye = Array::eye(i);
@@ -104,8 +104,8 @@ fn accurate_eye_f64() {
     // pick a few random sizes
     let mut rng = SmallRng::from_entropy();
     for _ in 0..10 {
-        let i = rng.gen_range(15, 512);
-        let j = rng.gen_range(15, 512);
+        let i = rng.gen_range(15..512);
+        let j = rng.gen_range(15..512);
         println!("Testing size {} by {}", i, j);
         let a = gen_f64(Ix2(i, j));
         let eye = Array::eye(i);
@@ -121,9 +121,9 @@ fn accurate_mul_f32() {
     // pick a few random sizes
     let mut rng = SmallRng::from_entropy();
     for i in 0..20 {
-        let m = rng.gen_range(15, 512);
-        let k = rng.gen_range(15, 512);
-        let n = rng.gen_range(15, 1560);
+        let m = rng.gen_range(15..512);
+        let k = rng.gen_range(15..512);
+        let n = rng.gen_range(15..1560);
         let a = gen(Ix2(m, k));
         let b = gen(Ix2(n, k));
         let b = b.t();
@@ -145,9 +145,9 @@ fn accurate_mul_f32_general() {
     // pick a few random sizes
     let mut rng = SmallRng::from_entropy();
     for i in 0..20 {
-        let m = rng.gen_range(15, 512);
-        let k = rng.gen_range(15, 512);
-        let n = rng.gen_range(15, 1560);
+        let m = rng.gen_range(15..512);
+        let k = rng.gen_range(15..512);
+        let n = rng.gen_range(15..1560);
         let a = gen(Ix2(m, k));
         let b = gen(Ix2(n, k));
         let mut c = gen(Ix2(m, n));
@@ -171,9 +171,9 @@ fn accurate_mul_f64() {
     // pick a few random sizes
     let mut rng = SmallRng::from_entropy();
     for i in 0..20 {
-        let m = rng.gen_range(15, 512);
-        let k = rng.gen_range(15, 512);
-        let n = rng.gen_range(15, 1560);
+        let m = rng.gen_range(15..512);
+        let k = rng.gen_range(15..512);
+        let n = rng.gen_range(15..1560);
         let a = gen_f64(Ix2(m, k));
         let b = gen_f64(Ix2(n, k));
         let b = b.t();
@@ -195,9 +195,9 @@ fn accurate_mul_f64_general() {
     // pick a few random sizes
     let mut rng = SmallRng::from_entropy();
     for i in 0..20 {
-        let m = rng.gen_range(15, 512);
-        let k = rng.gen_range(15, 512);
-        let n = rng.gen_range(15, 1560);
+        let m = rng.gen_range(15..512);
+        let k = rng.gen_range(15..512);
+        let n = rng.gen_range(15..1560);
         let a = gen_f64(Ix2(m, k));
         let b = gen_f64(Ix2(n, k));
         let mut c = gen_f64(Ix2(m, n));
@@ -221,8 +221,8 @@ fn accurate_mul_with_column_f64() {
     // pick a few random sizes
     let mut rng = SmallRng::from_entropy();
     for i in 0..10 {
-        let m = rng.gen_range(1, 350);
-        let k = rng.gen_range(1, 350);
+        let m = rng.gen_range(1..350);
+        let k = rng.gen_range(1..350);
         let a = gen_f64(Ix2(m, k));
         let b_owner = gen_f64(Ix2(k, k));
         let b_row_col;