From 7797a5c03914b8828dfbd6890a333f0595a09b98 Mon Sep 17 00:00:00 2001 From: Martin Geisler Date: Sun, 26 Jul 2020 15:39:32 +0200 Subject: [PATCH] Update rand dependency to latest version and get rid of rand_derive --- Cargo.toml | 4 +-- src/lib.rs | 66 ++++++++++++++++++++++++--------------------- tests/complexity.rs | 5 ++-- 3 files changed, 40 insertions(+), 35 deletions(-) diff --git a/Cargo.toml b/Cargo.toml index 39019f9..8469a1b 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -21,8 +21,8 @@ codecov = { repository = "mgeisler/smawk" } [dependencies] ndarray = "0.10" num-traits = "0.1" -rand = "0.3" -rand_derive = "0.3" +rand = "0.7" [dev-dependencies] version-sync = "0.8" +rand_chacha = "0.2" diff --git a/src/lib.rs b/src/lib.rs index 6eaf9ba..a9372ee 100644 --- a/src/lib.rs +++ b/src/lib.rs @@ -96,8 +96,8 @@ use ndarray::{s, Array2, ArrayView1, ArrayView2, Axis, Si}; use num_traits::{PrimInt, WrappingAdd}; -use rand::{Rand, Rng}; -use rand_derive::Rand; +use rand::distributions::{Distribution, Standard}; +use rand::Rng; /// Compute lane minimum by brute force. /// @@ -473,7 +473,7 @@ pub fn is_monge(matrix: &Array2) -> bool { /// A Monge matrix can be decomposed into one of these primitive /// building blocks. -#[derive(Rand)] +#[derive(Copy, Clone)] enum MongePrim { ConstantRows, ConstantCols, @@ -483,7 +483,10 @@ enum MongePrim { impl MongePrim { /// Generate a Monge matrix from a primitive. - fn to_matrix(&self, m: usize, n: usize, rng: &mut R) -> Array2 { + fn to_matrix(&self, m: usize, n: usize, rng: &mut R) -> Array2 + where + Standard: Distribution, + { let mut matrix = Array2::from_elem((m, n), T::zero()); // Avoid panic in UpperRightOnes and LowerLeftOnes below. if m == 0 || n == 0 { @@ -518,13 +521,13 @@ impl MongePrim { } /// Generate a random Monge matrix. -pub fn random_monge_matrix(m: usize, n: usize, rng: &mut R) -> Array2 +pub fn random_monge_matrix(m: usize, n: usize, rng: &mut R) -> Array2 where - T: Rand + PrimInt, + Standard: Distribution, { let mut matrix = Array2::from_elem((m, n), T::zero()); for _ in 0..(m + n) { - let monge = if rng.gen() { + let monge = if rng.gen::() { MongePrim::LowerLeftOnes } else { MongePrim::UpperRightOnes @@ -538,7 +541,8 @@ where mod tests { use super::*; use ndarray::arr2; - use rand::XorShiftRng; + use rand::SeedableRng; + use rand_chacha::ChaCha20Rng; #[test] fn is_monge_handles_overflow() { @@ -554,47 +558,47 @@ mod tests { #[test] fn monge_constant_rows() { - let mut rng = XorShiftRng::new_unseeded(); + let mut rng = ChaCha20Rng::seed_from_u64(0); assert_eq!( MongePrim::ConstantRows.to_matrix(5, 4, &mut rng), arr2(&[ - [15u8, 15, 15, 15], - [132, 132, 132, 132], - [11, 11, 11, 11], - [140, 140, 140, 140], - [67, 67, 67, 67] + [178u8, 178, 178, 178], + [214, 214, 214, 214], + [168, 168, 168, 168], + [126, 126, 126, 126], + [192, 192, 192, 192], ]) ); } #[test] fn monge_constant_cols() { - let mut rng = XorShiftRng::new_unseeded(); - let matrix = MongePrim::ConstantCols.to_matrix(5, 4, &mut rng); + let mut rng = ChaCha20Rng::seed_from_u64(0); + let matrix: Array2 = MongePrim::ConstantCols.to_matrix(5, 4, &mut rng); assert!(is_monge(&matrix)); assert_eq!( matrix, arr2(&[ - [15u8, 132, 11, 140], - [15, 132, 11, 140], - [15, 132, 11, 140], - [15, 132, 11, 140], - [15, 132, 11, 140] + [178, 214, 168, 126], + [178, 214, 168, 126], + [178, 214, 168, 126], + [178, 214, 168, 126], + [178, 214, 168, 126] ]) ); } #[test] fn monge_upper_right_ones() { - let mut rng = XorShiftRng::new_unseeded(); + let mut rng = ChaCha20Rng::seed_from_u64(1); let matrix = MongePrim::UpperRightOnes.to_matrix(5, 4, &mut rng); assert!(is_monge(&matrix)); assert_eq!( matrix, arr2(&[ - [0, 0, 0, 1], - [0, 0, 0, 1], - [0, 0, 0, 0], + [0, 0, 1, 1], + [0, 0, 1, 1], + [0, 0, 1, 1], [0, 0, 0, 0], [0, 0, 0, 0] ]) @@ -603,7 +607,7 @@ mod tests { #[test] fn monge_lower_left_ones() { - let mut rng = XorShiftRng::new_unseeded(); + let mut rng = ChaCha20Rng::seed_from_u64(1); let matrix = MongePrim::LowerLeftOnes.to_matrix(5, 4, &mut rng); assert!(is_monge(&matrix)); assert_eq!( @@ -611,9 +615,9 @@ mod tests { arr2(&[ [0, 0, 0, 0], [0, 0, 0, 0], - [0, 0, 0, 0], - [1, 0, 0, 0], - [1, 0, 0, 0] + [1, 1, 0, 0], + [1, 1, 0, 0], + [1, 1, 0, 0] ]) ); } @@ -810,7 +814,7 @@ mod tests { #[test] fn implementations_agree() { let sizes = vec![1, 2, 3, 4, 5, 10, 15, 20, 30]; - let mut rng = XorShiftRng::new_unseeded(); + let mut rng = ChaCha20Rng::seed_from_u64(0); for _ in 0..4 { for m in sizes.clone().iter() { for n in sizes.clone().iter() { @@ -909,7 +913,7 @@ mod tests { #[test] fn online_agree() { let sizes = vec![1, 2, 3, 4, 5, 10, 15, 20, 30, 50]; - let mut rng = XorShiftRng::new_unseeded(); + let mut rng = ChaCha20Rng::seed_from_u64(0); for _ in 0..5 { for &size in &sizes { // Random totally monotone square matrix of the diff --git a/tests/complexity.rs b/tests/complexity.rs index 4034363..1642f7b 100644 --- a/tests/complexity.rs +++ b/tests/complexity.rs @@ -1,5 +1,6 @@ use ndarray::{Array1, Array2, Axis, LinalgScalar}; -use rand::XorShiftRng; +use rand::SeedableRng; +use rand_chacha::ChaCha20Rng; use smawk::{online_column_minima, random_monge_matrix}; use std::borrow::Borrow; @@ -56,7 +57,7 @@ fn linear_regression(values: &[(usize, i32)]) -> LinRegression { /// grows as O(*n*) for *n* ✕ *n* matrix. #[test] fn online_linear_complexity() { - let mut rng = XorShiftRng::new_unseeded(); + let mut rng = ChaCha20Rng::seed_from_u64(0); let mut data = vec![]; for &size in &[1, 2, 3, 4, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100] {