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Merge pull request #1039 from Andlon/remove-proptest-patch 

Remove redundant proptest patch in `nalgebra-sparse`
This commit is contained in:
Sébastien Crozet 2021-12-01 13:54:36 +01:00 committed by GitHub
parent 77b9263319 6e10efe862
commit 56a4835b71
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2 changed files with 4 additions and 161 deletions
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19
nalgebra-sparse/src/proptest.rs
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@ -5,11 +5,6 @@
//! The strategies provided here are generally expected to be able to generate the entire range //! The strategies provided here are generally expected to be able to generate the entire range
//! of possible outputs given the constraints on dimensions and values. However, there are no //! of possible outputs given the constraints on dimensions and values. However, there are no
//! particular guarantees on the distribution of possible values. //! particular guarantees on the distribution of possible values.
// Contains some patched code from proptest that we can remove in the (hopefully near) future.
// See docs in file for more details.
mod proptest_patched;
use crate::coo::CooMatrix; use crate::coo::CooMatrix;
use crate::csc::CscMatrix; use crate::csc::CscMatrix;
use crate::csr::CsrMatrix; use crate::csr::CsrMatrix;
@ -31,16 +26,10 @@ fn dense_row_major_coord_strategy(
let mut booleans = vec![true; nnz]; let mut booleans = vec![true; nnz];
booleans.append(&mut vec![false; (nrows * ncols) - nnz]); booleans.append(&mut vec![false; (nrows * ncols) - nnz]);
// Make sure that exactly `nnz` of the booleans are true // Make sure that exactly `nnz` of the booleans are true
Just(booleans)
// TODO: We cannot use the below code because of a bug in proptest, see // Need to shuffle to make sure they are randomly distributed
// https://github.com/AltSysrq/proptest/pull/217 .prop_shuffle()
// so for now we're using a patched version of the Shuffle adapter .prop_map(move |booleans| {
// (see also docs in `proptest_patched`
// Just(booleans)
// // Need to shuffle to make sure they are randomly distributed
// .prop_shuffle()
proptest_patched::Shuffle(Just(booleans)).prop_map(move |booleans| {
booleans booleans
.into_iter() .into_iter()
.enumerate() .enumerate()

146
nalgebra-sparse/src/proptest/proptest_patched.rs
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@ -1,146 +0,0 @@
//! Contains a modified implementation of `proptest::strategy::Shuffle`.
//!
//! The current implementation in `proptest` does not generate all permutations, which is
//! problematic for our proptest generators. The issue has been fixed in
//! https://github.com/AltSysrq/proptest/pull/217
//! but it has yet to be merged and released. As soon as this fix makes it into a new release,
//! the modified code here can be removed.
//!
/*!
This code has been copied and adapted from
https://github.com/AltSysrq/proptest/blob/master/proptest/src/strategy/shuffle.rs
The original licensing text is:
//-
// Copyright 2017 Jason Lingle
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
*/
use proptest::num;
use proptest::prelude::Rng;
use proptest::strategy::{NewTree, Shuffleable, Strategy, ValueTree};
use proptest::test_runner::{TestRng, TestRunner};
use std::cell::Cell;
#[derive(Clone, Debug)]
#[must_use = "strategies do nothing unless used"]
pub struct Shuffle<S>(pub(super) S);
impl<S: Strategy> Strategy for Shuffle<S>
where
S::Value: Shuffleable,
{
type Tree = ShuffleValueTree<S::Tree>;
type Value = S::Value;
fn new_tree(&self, runner: &mut TestRunner) -> NewTree<Self> {
let rng = runner.new_rng();
self.0.new_tree(runner).map(|inner| ShuffleValueTree {
inner,
rng,
dist: Cell::new(None),
simplifying_inner: false,
})
}
}
#[derive(Clone, Debug)]
pub struct ShuffleValueTree<V> {
inner: V,
rng: TestRng,
dist: Cell<Option<num::usize::BinarySearch>>,
simplifying_inner: bool,
}
impl<V: ValueTree> ShuffleValueTree<V>
where
V::Value: Shuffleable,
{
fn init_dist(&self, dflt: usize) -> usize {
if self.dist.get().is_none() {
self.dist.set(Some(num::usize::BinarySearch::new(dflt)));
}
self.dist.get().unwrap().current()
}
fn force_init_dist(&self) {
if self.dist.get().is_none() {
let _ = self.init_dist(self.current().shuffle_len());
}
}
}
impl<V: ValueTree> ValueTree for ShuffleValueTree<V>
where
V::Value: Shuffleable,
{
type Value = V::Value;
fn current(&self) -> V::Value {
let mut value = self.inner.current();
let len = value.shuffle_len();
// The maximum distance to swap elements. This could be larger than
// `value` if `value` has reduced size during shrinking; that's OK,
// since we only use this to filter swaps.
let max_swap = self.init_dist(len);
// If empty collection or all swaps will be filtered out, there's
// nothing to shuffle.
if 0 == len || 0 == max_swap {
return value;
}
let mut rng = self.rng.clone();
for start_index in 0..len - 1 {
// Determine the other index to be swapped, then skip the swap if
// it is too far. This ordering is critical, as it ensures that we
// generate the same sequence of random numbers every time.
// NOTE: The below line is the whole reason for the existence of this adapted code
// We need to be able to swap with the same element, so that some elements remain in
// place rather being swapped
// let end_index = rng.gen_range(start_index + 1..len);
let end_index = rng.gen_range(start_index..len);
if end_index - start_index <= max_swap {
value.shuffle_swap(start_index, end_index);
}
}
value
}
fn simplify(&mut self) -> bool {
if self.simplifying_inner {
self.inner.simplify()
} else {
// Ensure that we've initialised `dist` to *something* to give
// consistent non-panicking behaviour even if called in an
// unexpected sequence.
self.force_init_dist();
if self.dist.get_mut().as_mut().unwrap().simplify() {
true
} else {
self.simplifying_inner = true;
self.inner.simplify()
}
}
}
fn complicate(&mut self) -> bool {
if self.simplifying_inner {
self.inner.complicate()
} else {
self.force_init_dist();
self.dist.get_mut().as_mut().unwrap().complicate()
}
}
}