Function malachite_base::vecs::random::random_unique_vecs
source · pub fn random_unique_vecs<I: Iterator>(
seed: Seed,
xs_gen: &dyn Fn(Seed) -> I,
mean_length_numerator: u64,
mean_length_denominator: u64
) -> RandomUniqueVecs<I::Item, GeometricRandomNaturalValues<u64>, I> ⓘwhere
I::Item: Eq + Hash,
Expand description
Generates random Vec
s using elements from an iterator, where the Vec
s have no repeated
elements.
The lengths of the Vec
s are sampled from a geometric distribution with a specified mean
$m$, equal to mean_length_numerator / mean_length_denominator
. $m$ must be greater than 0.
Strictly speaking, the input iterator must generate infinitely many distinct elements. In
practice it only needs to generate $k$ distinct elements, where $k$ is the largest length
actually sampled from the geometric distribution. For example, if
mean_length_numerator / mean_length_denominator
is significantly lower than 256, then it’s
ok to use random_unsigneds::<u8>
.
xs_gen
must be infinite.
Panics
Panics if mean_length_numerator
or mean_length_denominator
are zero, or, if after being
reduced to lowest terms, their sum is greater than or equal to $2^{64}$.
Examples
use itertools::Itertools;
use malachite_base::num::random::random_primitive_ints;
use malachite_base::random::EXAMPLE_SEED;
use malachite_base::vecs::random::random_unique_vecs;
let xs = random_unique_vecs(EXAMPLE_SEED, &random_primitive_ints::<u8>, 4, 1);
let values = xs.take(20).collect_vec();
assert_eq!(
values.iter().map(Vec::as_slice).collect_vec().as_slice(),
&[
&[][..],
&[85, 11, 136, 200, 235, 134, 203, 223, 38, 217, 177, 162, 32, 166],
&[234, 30, 218, 90],
&[106, 9, 216, 204],
&[151],
&[],
&[213, 97, 253, 78, 91],
&[39, 191],
&[175, 170, 232, 233],
&[],
&[2, 35, 22, 217, 198, 114],
&[],
&[],
&[17, 32, 173, 114, 65, 121, 222, 25, 144, 148, 79],
&[115, 52, 73, 69, 137, 91, 153, 178],
&[],
&[112, 34, 95],
&[],
&[106, 167, 197, 130, 168],
&[122, 207, 172, 177, 86, 150, 221, 218, 101]
]
);