proptest/strategy/unions.rs
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//-
// 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 crate::std_facade::{fmt, Arc, Vec};
use core::cmp::{max, min};
use core::u32;
#[cfg(not(feature = "std"))]
use num_traits::float::FloatCore;
use crate::num::sample_uniform;
use crate::strategy::{lazy::LazyValueTree, traits::*};
use crate::test_runner::*;
/// A **relative** `weight` of a particular `Strategy` corresponding to `T`
/// coupled with `T` itself. The weight is currently given in `u32`.
pub type W<T> = (u32, T);
/// A **relative** `weight` of a particular `Strategy` corresponding to `T`
/// coupled with `Arc<T>`. The weight is currently given in `u32`.
pub type WA<T> = (u32, Arc<T>);
/// A `Strategy` which picks from one of several delegate `Stragegy`s.
///
/// See `Strategy::prop_union()`.
#[derive(Clone, Debug)]
#[must_use = "strategies do nothing unless used"]
pub struct Union<T: Strategy> {
// In principle T could be any `Strategy + Clone`, but that isn't possible
// for BC reasons with the 0.9 series.
options: Vec<WA<T>>,
}
impl<T: Strategy> Union<T> {
/// Create a strategy which selects uniformly from the given delegate
/// strategies.
///
/// When shrinking, after maximal simplification of the chosen element, the
/// strategy will move to earlier options and continue simplification with
/// those.
///
/// ## Panics
///
/// Panics if `options` is empty.
pub fn new(options: impl IntoIterator<Item = T>) -> Self {
let options: Vec<WA<T>> =
options.into_iter().map(|v| (1, Arc::new(v))).collect();
assert!(!options.is_empty());
Self { options }
}
pub(crate) fn try_new<E>(
it: impl Iterator<Item = Result<T, E>>,
) -> Result<Self, E> {
let options: Vec<WA<T>> = it
.map(|r| r.map(|v| (1, Arc::new(v))))
.collect::<Result<_, _>>()?;
assert!(!options.is_empty());
Ok(Self { options })
}
/// Create a strategy which selects from the given delegate strategies.
///
/// Each strategy is assigned a non-zero weight which determines how
/// frequently that strategy is chosen. For example, a strategy with a
/// weight of 2 will be chosen twice as frequently as one with a weight of
/// 1\.
///
/// ## Panics
///
/// Panics if `options` is empty or any element has a weight of 0.
///
/// Panics if the sum of the weights overflows a `u32`.
pub fn new_weighted(options: Vec<W<T>>) -> Self {
assert!(!options.is_empty());
assert!(
!options.iter().any(|&(w, _)| 0 == w),
"Union option has a weight of 0"
);
assert!(
options.iter().map(|&(w, _)| u64::from(w)).sum::<u64>()
<= u64::from(u32::MAX),
"Union weights overflow u32"
);
let options =
options.into_iter().map(|(w, v)| (w, Arc::new(v))).collect();
Self { options }
}
/// Add `other` as an additional alternate strategy with weight 1.
pub fn or(mut self, other: T) -> Self {
self.options.push((1, Arc::new(other)));
self
}
}
fn pick_weighted<I: Iterator<Item = u32>>(
runner: &mut TestRunner,
weights1: I,
weights2: I,
) -> usize {
let sum = weights1.map(u64::from).sum();
let weighted_pick = sample_uniform(runner, 0, sum);
weights2
.scan(0u64, |state, w| {
*state += u64::from(w);
Some(*state)
})
.filter(|&v| v <= weighted_pick)
.count()
}
impl<T: Strategy> Strategy for Union<T> {
type Tree = UnionValueTree<T>;
type Value = T::Value;
fn new_tree(&self, runner: &mut TestRunner) -> NewTree<Self> {
fn extract_weight<V>(&(w, _): &WA<V>) -> u32 {
w
}
let pick = pick_weighted(
runner,
self.options.iter().map(extract_weight::<T>),
self.options.iter().map(extract_weight::<T>),
);
let mut options = Vec::with_capacity(pick);
// Delay initialization for all options less than pick.
for option in &self.options[0..pick] {
options.push(LazyValueTree::new(Arc::clone(&option.1), runner));
}
// Initialize the tree at pick so at least one value is available. Note
// that if generation for the value at pick fails, the entire strategy
// will fail. This seems like the right call.
options.push(LazyValueTree::new_initialized(
self.options[pick].1.new_tree(runner)?,
));
Ok(UnionValueTree {
options,
pick,
min_pick: 0,
prev_pick: None,
})
}
}
macro_rules! access_vec {
([$($muta:tt)*] $dst:ident = $this:expr, $ix:expr, $body:block) => {{
let $dst = &$($muta)* $this.options[$ix];
$body
}}
}
/// `ValueTree` corresponding to `Union`.
pub struct UnionValueTree<T: Strategy> {
options: Vec<LazyValueTree<T>>,
// This struct maintains the invariant that between function calls,
// `pick` and `prev_pick` (if Some) always point to initialized
// trees.
pick: usize,
min_pick: usize,
prev_pick: Option<usize>,
}
macro_rules! lazy_union_value_tree_body {
($typ:ty, $access:ident) => {
type Value = $typ;
fn current(&self) -> Self::Value {
$access!([] opt = self, self.pick, {
opt.as_inner().unwrap_or_else(||
panic!(
"value tree at self.pick = {} must be initialized",
self.pick,
)
).current()
})
}
fn simplify(&mut self) -> bool {
let orig_pick = self.pick;
if $access!([mut] opt = self, orig_pick, {
opt.as_inner_mut().unwrap_or_else(||
panic!(
"value tree at self.pick = {} must be initialized",
orig_pick,
)
).simplify()
}) {
self.prev_pick = None;
return true;
}
assert!(
self.pick >= self.min_pick,
"self.pick = {} should never go below self.min_pick = {}",
self.pick,
self.min_pick,
);
if self.pick == self.min_pick {
// No more simplification to be done.
return false;
}
// self.prev_pick is always a valid pick.
self.prev_pick = Some(self.pick);
let mut next_pick = self.pick;
while next_pick > self.min_pick {
next_pick -= 1;
let initialized = $access!([mut] opt = self, next_pick, {
opt.maybe_init();
opt.is_initialized()
});
if initialized {
// next_pick was correctly initialized above.
self.pick = next_pick;
return true;
}
}
false
}
fn complicate(&mut self) -> bool {
if let Some(pick) = self.prev_pick {
// simplify() ensures that the previous pick was initialized.
self.pick = pick;
self.min_pick = pick;
self.prev_pick = None;
true
} else {
let pick = self.pick;
$access!([mut] opt = self, pick, {
opt.as_inner_mut().unwrap_or_else(||
panic!(
"value tree at self.pick = {} must be initialized",
pick,
)
).complicate()
})
}
}
}
}
impl<T: Strategy> ValueTree for UnionValueTree<T> {
lazy_union_value_tree_body!(T::Value, access_vec);
}
impl<T: Strategy> Clone for UnionValueTree<T>
where
T::Tree: Clone,
{
fn clone(&self) -> Self {
Self {
options: self.options.clone(),
pick: self.pick,
min_pick: self.min_pick,
prev_pick: self.prev_pick,
}
}
}
impl<T: Strategy> fmt::Debug for UnionValueTree<T>
where
T::Tree: fmt::Debug,
{
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
f.debug_struct("UnionValueTree")
.field("options", &self.options)
.field("pick", &self.pick)
.field("min_pick", &self.min_pick)
.field("prev_pick", &self.prev_pick)
.finish()
}
}
macro_rules! def_access_tuple {
($b:tt $name:ident, $($n:tt)*) => {
macro_rules! $name {
([$b($b muta:tt)*] $b dst:ident = $b this:expr,
$b ix:expr, $b body:block) => {
match $b ix {
0 => {
let $b dst = &$b($b muta)* $b this.options.0;
$b body
},
$(
$n => {
if let Some(ref $b($b muta)* $b dst) =
$b this.options.$n
{
$b body
} else {
panic!("TupleUnion tried to access \
uninitialised slot {}", $n)
}
},
)*
_ => panic!("TupleUnion tried to access out-of-range \
slot {}", $b ix),
}
}
}
}
}
def_access_tuple!($ access_tuple2, 1);
def_access_tuple!($ access_tuple3, 1 2);
def_access_tuple!($ access_tuple4, 1 2 3);
def_access_tuple!($ access_tuple5, 1 2 3 4);
def_access_tuple!($ access_tuple6, 1 2 3 4 5);
def_access_tuple!($ access_tuple7, 1 2 3 4 5 6);
def_access_tuple!($ access_tuple8, 1 2 3 4 5 6 7);
def_access_tuple!($ access_tuple9, 1 2 3 4 5 6 7 8);
def_access_tuple!($ access_tupleA, 1 2 3 4 5 6 7 8 9);
/// Similar to `Union`, but internally uses a tuple to hold the strategies.
///
/// This allows better performance than vanilla `Union` since one does not need
/// to resort to boxing and dynamic dispatch to handle heterogeneous
/// strategies.
///
/// The difference between this and `TupleUnion` is that with this, value trees
/// for variants that aren't picked at first are generated lazily.
#[must_use = "strategies do nothing unless used"]
#[derive(Clone, Copy, Debug)]
pub struct TupleUnion<T>(T);
impl<T> TupleUnion<T> {
/// Wrap `tuple` in a `TupleUnion`.
///
/// The struct definition allows any `T` for `tuple`, but to be useful, it
/// must be a 2- to 10-tuple of `(u32, Arc<impl Strategy>)` pairs where all
/// strategies ultimately produce the same value. Each `u32` indicates the
/// relative weight of its corresponding strategy.
/// You may use `WA<S>` as an alias for `(u32, Arc<S>)`.
///
/// Using this constructor directly is discouraged; prefer to use
/// `prop_oneof!` since it is generally clearer.
pub fn new(tuple: T) -> Self {
TupleUnion(tuple)
}
}
macro_rules! tuple_union {
($($gen:ident $ix:tt)*) => {
impl<A : Strategy, $($gen: Strategy<Value = A::Value>),*>
Strategy for TupleUnion<(WA<A>, $(WA<$gen>),*)> {
type Tree = TupleUnionValueTree<
(LazyValueTree<A>, $(Option<LazyValueTree<$gen>>),*)>;
type Value = A::Value;
fn new_tree(&self, runner: &mut TestRunner) -> NewTree<Self> {
let weights = [((self.0).0).0, $(((self.0).$ix).0),*];
let pick = pick_weighted(runner, weights.iter().cloned(),
weights.iter().cloned());
Ok(TupleUnionValueTree {
options: (
if 0 == pick {
LazyValueTree::new_initialized(
((self.0).0).1.new_tree(runner)?)
} else {
LazyValueTree::new(
Arc::clone(&((self.0).0).1), runner)
},
$(
if $ix == pick {
Some(LazyValueTree::new_initialized(
((self.0).$ix).1.new_tree(runner)?))
} else if $ix < pick {
Some(LazyValueTree::new(
Arc::clone(&((self.0).$ix).1), runner))
} else {
None
}),*),
pick: pick,
min_pick: 0,
prev_pick: None,
})
}
}
}
}
tuple_union!(B 1);
tuple_union!(B 1 C 2);
tuple_union!(B 1 C 2 D 3);
tuple_union!(B 1 C 2 D 3 E 4);
tuple_union!(B 1 C 2 D 3 E 4 F 5);
tuple_union!(B 1 C 2 D 3 E 4 F 5 G 6);
tuple_union!(B 1 C 2 D 3 E 4 F 5 G 6 H 7);
tuple_union!(B 1 C 2 D 3 E 4 F 5 G 6 H 7 I 8);
tuple_union!(B 1 C 2 D 3 E 4 F 5 G 6 H 7 I 8 J 9);
/// `ValueTree` type produced by `TupleUnion`.
#[derive(Clone, Copy, Debug)]
pub struct TupleUnionValueTree<T> {
options: T,
pick: usize,
min_pick: usize,
prev_pick: Option<usize>,
}
macro_rules! value_tree_tuple {
($access:ident, $($gen:ident)*) => {
impl<A : Strategy, $($gen: Strategy<Value = A::Value>),*> ValueTree
for TupleUnionValueTree<
(LazyValueTree<A>, $(Option<LazyValueTree<$gen>>),*)
> {
lazy_union_value_tree_body!(A::Value, $access);
}
}
}
value_tree_tuple!(access_tuple2, B);
value_tree_tuple!(access_tuple3, B C);
value_tree_tuple!(access_tuple4, B C D);
value_tree_tuple!(access_tuple5, B C D E);
value_tree_tuple!(access_tuple6, B C D E F);
value_tree_tuple!(access_tuple7, B C D E F G);
value_tree_tuple!(access_tuple8, B C D E F G H);
value_tree_tuple!(access_tuple9, B C D E F G H I);
value_tree_tuple!(access_tupleA, B C D E F G H I J);
const WEIGHT_BASE: u32 = 0x8000_0000;
/// Convert a floating-point weight in the range (0.0,1.0) to a pair of weights
/// that can be used with `Union` and similar.
///
/// The first return value is the weight corresponding to `f`; the second
/// return value is the weight corresponding to `1.0 - f`.
///
/// This call does not make any guarantees as to what range of weights it may
/// produce, except that adding the two return values will never overflow a
/// `u32`. As such, it is generally not meaningful to combine any other weights
/// with the two returned.
///
/// ## Panics
///
/// Panics if `f` is not a real number between 0.0 and 1.0, both exclusive.
pub fn float_to_weight(f: f64) -> (u32, u32) {
assert!(f > 0.0 && f < 1.0, "Invalid probability: {}", f);
// Clamp to 1..WEIGHT_BASE-1 so that we never produce a weight of 0.
let pos = max(
1,
min(WEIGHT_BASE - 1, (f * f64::from(WEIGHT_BASE)).round() as u32),
);
let neg = WEIGHT_BASE - pos;
(pos, neg)
}
#[cfg(test)]
mod test {
use super::*;
use crate::strategy::just::Just;
// FIXME(2018-06-01): figure out a way to run this test on no_std.
// The problem is that the default seed is fixed and does not produce
// enough passed tests. We need some universal source of non-determinism
// for the seed, which is unlikely.
#[cfg(feature = "std")]
#[test]
fn test_union() {
let input = (10u32..20u32).prop_union(30u32..40u32);
// Expect that 25% of cases pass (left input happens to be < 15, and
// left is chosen as initial value). Of the 75% that fail, 50% should
// converge to 15 and 50% to 30 (the latter because the left is beneath
// the passing threshold).
let mut passed = 0;
let mut converged_low = 0;
let mut converged_high = 0;
let mut runner = TestRunner::deterministic();
for _ in 0..256 {
let case = input.new_tree(&mut runner).unwrap();
let result = runner.run_one(case, |v| {
prop_assert!(v < 15);
Ok(())
});
match result {
Ok(true) => passed += 1,
Err(TestError::Fail(_, 15)) => converged_low += 1,
Err(TestError::Fail(_, 30)) => converged_high += 1,
e => panic!("Unexpected result: {:?}", e),
}
}
assert!(passed >= 32 && passed <= 96, "Bad passed count: {}", passed);
assert!(
converged_low >= 32 && converged_low <= 160,
"Bad converged_low count: {}",
converged_low
);
assert!(
converged_high >= 32 && converged_high <= 160,
"Bad converged_high count: {}",
converged_high
);
}
#[test]
fn test_union_weighted() {
let input = Union::new_weighted(vec![
(1, Just(0usize)),
(2, Just(1usize)),
(1, Just(2usize)),
]);
let mut counts = [0, 0, 0];
let mut runner = TestRunner::deterministic();
for _ in 0..65536 {
counts[input.new_tree(&mut runner).unwrap().current()] += 1;
}
println!("{:?}", counts);
assert!(counts[0] > 0);
assert!(counts[2] > 0);
assert!(counts[1] > counts[0] * 3 / 2);
assert!(counts[1] > counts[2] * 3 / 2);
}
#[test]
fn test_union_sanity() {
check_strategy_sanity(
Union::new_weighted(vec![
(1, 0i32..100),
(2, 200i32..300),
(1, 400i32..500),
]),
None,
);
}
// FIXME(2018-06-01): See note on `test_union`.
#[cfg(feature = "std")]
#[test]
fn test_tuple_union() {
let input = TupleUnion::new((
(1, Arc::new(10u32..20u32)),
(1, Arc::new(30u32..40u32)),
));
// Expect that 25% of cases pass (left input happens to be < 15, and
// left is chosen as initial value). Of the 75% that fail, 50% should
// converge to 15 and 50% to 30 (the latter because the left is beneath
// the passing threshold).
let mut passed = 0;
let mut converged_low = 0;
let mut converged_high = 0;
let mut runner = TestRunner::deterministic();
for _ in 0..256 {
let case = input.new_tree(&mut runner).unwrap();
let result = runner.run_one(case, |v| {
prop_assert!(v < 15);
Ok(())
});
match result {
Ok(true) => passed += 1,
Err(TestError::Fail(_, 15)) => converged_low += 1,
Err(TestError::Fail(_, 30)) => converged_high += 1,
e => panic!("Unexpected result: {:?}", e),
}
}
assert!(passed >= 32 && passed <= 96, "Bad passed count: {}", passed);
assert!(
converged_low >= 32 && converged_low <= 160,
"Bad converged_low count: {}",
converged_low
);
assert!(
converged_high >= 32 && converged_high <= 160,
"Bad converged_high count: {}",
converged_high
);
}
#[test]
fn test_tuple_union_weighting() {
let input = TupleUnion::new((
(1, Arc::new(Just(0usize))),
(2, Arc::new(Just(1usize))),
(1, Arc::new(Just(2usize))),
));
let mut counts = [0, 0, 0];
let mut runner = TestRunner::deterministic();
for _ in 0..65536 {
counts[input.new_tree(&mut runner).unwrap().current()] += 1;
}
println!("{:?}", counts);
assert!(counts[0] > 0);
assert!(counts[2] > 0);
assert!(counts[1] > counts[0] * 3 / 2);
assert!(counts[1] > counts[2] * 3 / 2);
}
#[test]
fn test_tuple_union_all_sizes() {
let mut runner = TestRunner::deterministic();
let r = Arc::new(1i32..10);
macro_rules! test {
($($part:expr),*) => {{
let input = TupleUnion::new((
$((1, $part.clone())),*,
(1, Arc::new(Just(0i32)))
));
let mut pass = false;
for _ in 0..1024 {
if 0 == input.new_tree(&mut runner).unwrap().current() {
pass = true;
break;
}
}
assert!(pass);
}}
}
test!(r); // 2
test!(r, r); // 3
test!(r, r, r); // 4
test!(r, r, r, r); // 5
test!(r, r, r, r, r); // 6
test!(r, r, r, r, r, r); // 7
test!(r, r, r, r, r, r, r); // 8
test!(r, r, r, r, r, r, r, r); // 9
test!(r, r, r, r, r, r, r, r, r); // 10
}
#[test]
fn test_tuple_union_sanity() {
check_strategy_sanity(
TupleUnion::new((
(1, Arc::new(0i32..100i32)),
(1, Arc::new(200i32..1000i32)),
(1, Arc::new(2000i32..3000i32)),
)),
None,
);
}
/// Test that unions work even if local filtering causes errors.
#[test]
fn test_filter_union_sanity() {
let filter_strategy = (0u32..256).prop_filter("!%5", |&v| 0 != v % 5);
check_strategy_sanity(
Union::new(vec![filter_strategy; 8]),
Some(filter_sanity_options()),
);
}
/// Test that tuple unions work even if local filtering causes errors.
#[test]
fn test_filter_tuple_union_sanity() {
let filter_strategy = (0u32..256).prop_filter("!%5", |&v| 0 != v % 5);
check_strategy_sanity(
TupleUnion::new((
(1, Arc::new(filter_strategy.clone())),
(1, Arc::new(filter_strategy.clone())),
(1, Arc::new(filter_strategy.clone())),
(1, Arc::new(filter_strategy.clone())),
)),
Some(filter_sanity_options()),
);
}
fn filter_sanity_options() -> CheckStrategySanityOptions {
CheckStrategySanityOptions {
// Due to internal rejection sampling, `simplify()` can
// converge back to what `complicate()` would do.
strict_complicate_after_simplify: false,
// Make failed filters return errors to test edge cases.
error_on_local_rejects: true,
..CheckStrategySanityOptions::default()
}
}
}