Trait valence::rand::prelude::IteratorRandom
source Β· pub trait IteratorRandom: Sized + Iterator {
// Provided methods
fn choose<R>(self, rng: &mut R) -> Option<Self::Item>
where R: Rng + ?Sized { ... }
fn choose_stable<R>(self, rng: &mut R) -> Option<Self::Item>
where R: Rng + ?Sized { ... }
fn choose_multiple_fill<R>(
self,
rng: &mut R,
buf: &mut [Self::Item],
) -> usize
where R: Rng + ?Sized { ... }
fn choose_multiple<R>(self, rng: &mut R, amount: usize) -> Vec<Self::Item>
where R: Rng + ?Sized { ... }
}
Expand description
Extension trait on iterators, providing random sampling methods.
This trait is implemented on all iterators I
where I: Iterator + Sized
and provides methods for
choosing one or more elements. You must use
this trait:
use rand::seq::IteratorRandom;
let mut rng = rand::thread_rng();
let faces = "πππππ π’";
println!("I am {}!", faces.chars().choose(&mut rng).unwrap());
Example output (non-deterministic):
I am π!
Provided Methods§
sourcefn choose<R>(self, rng: &mut R) -> Option<Self::Item>
fn choose<R>(self, rng: &mut R) -> Option<Self::Item>
Choose one element at random from the iterator.
Returns None
if and only if the iterator is empty.
This method uses Iterator::size_hint
for optimisation. With an
accurate hint and where Iterator::nth
is a constant-time operation
this method can offer O(1)
performance. Where no size hint is
available, complexity is O(n)
where n
is the iterator length.
Partial hints (where lower > 0
) also improve performance.
Note that the output values and the number of RNG samples used
depends on size hints. In particular, Iterator
combinators that donβt
change the values yielded but change the size hints may result in
choose
returning different elements. If you want consistent results
and RNG usage consider using IteratorRandom::choose_stable
.
sourcefn choose_stable<R>(self, rng: &mut R) -> Option<Self::Item>
fn choose_stable<R>(self, rng: &mut R) -> Option<Self::Item>
Choose one element at random from the iterator.
Returns None
if and only if the iterator is empty.
This method is very similar to choose
except that the result
only depends on the length of the iterator and the values produced by
rng
. Notably for any iterator of a given length this will make the
same requests to rng
and if the same sequence of values are produced
the same index will be selected from self
. This may be useful if you
need consistent results no matter what type of iterator you are working
with. If you do not need this stability prefer choose
.
Note that this method still uses Iterator::size_hint
to skip
constructing elements where possible, however the selection and rng
calls are the same in the face of this optimization. If you want to
force every element to be created regardless call .inspect(|e| ())
.
sourcefn choose_multiple_fill<R>(self, rng: &mut R, buf: &mut [Self::Item]) -> usize
fn choose_multiple_fill<R>(self, rng: &mut R, buf: &mut [Self::Item]) -> usize
Collects values at random from the iterator into a supplied buffer until that buffer is filled.
Although the elements are selected randomly, the order of elements in the buffer is neither stable nor fully random. If random ordering is desired, shuffle the result.
Returns the number of elements added to the buffer. This equals the length of the buffer unless the iterator contains insufficient elements, in which case this equals the number of elements available.
Complexity is O(n)
where n
is the length of the iterator.
For slices, prefer SliceRandom::choose_multiple
.
sourcefn choose_multiple<R>(self, rng: &mut R, amount: usize) -> Vec<Self::Item>
fn choose_multiple<R>(self, rng: &mut R, amount: usize) -> Vec<Self::Item>
Collects amount
values at random from the iterator into a vector.
This is equivalent to choose_multiple_fill
except for the result type.
Although the elements are selected randomly, the order of elements in the buffer is neither stable nor fully random. If random ordering is desired, shuffle the result.
The length of the returned vector equals amount
unless the iterator
contains insufficient elements, in which case it equals the number of
elements available.
Complexity is O(n)
where n
is the length of the iterator.
For slices, prefer SliceRandom::choose_multiple
.