How do I generate a vector of 100 64-bit integer values in the range from 1 to 20, allowing duplicates?
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1Generate one and keep on going. /halfserious – Veedrac Jan 12 '18 at 02:04
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Like ' let secret_number = rand::thread_rng().gen_range(1, 101);'? I could make a closure out of it and map it to a vector for 1..100? – mrsteve Jan 12 '18 at 02:22
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Yeah, pretty much. – Veedrac Jan 12 '18 at 02:24
2 Answers
There are a few main pieces that you need here. First, how to create a vector of 100 calculated items? The easiest way is to create a range of 100 and map over those items. For instance you could do:
let vals: Vec<u64> = (0..100).map(|v| v + 1000).collect();
// [1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, ...
Splitting this up:
0..100creates an iterator for 0 through 99.mapprocesses each item in the iterator when the iterator is processed..collect()takes an iterator and converts it into any type that implementsFromIteratorwhich in your case isVec.
Expanding on this for your random values, you can adjust the .map function to generate a random value from 0 to 20 using the rand crate's gen_range function to create a numeric value within a given range.
use rand::Rng; // 0.6.5
fn main() {
let mut rng = rand::thread_rng();
let vals: Vec<u64> = (0..100).map(|_| rng.gen_range(0, 20)).collect();
println!("{:?}", vals);
}
You should also consider using the rand::distributions::Uniform type to create the range up front, which is is more efficient than calling gen_range multiple times, then pull samples from it 100 times:
use rand::{distributions::Uniform, Rng}; // 0.6.5
fn main() {
let mut rng = rand::thread_rng();
let range = Uniform::new(0, 20);
let vals: Vec<u64> = (0..100).map(|_| rng.sample(&range)).collect();
println!("{:?}", vals);
}
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TL;DR:
use rand::{distributions::Uniform, Rng}; // 0.8.0
fn main() {
let range = Uniform::from(0..20);
let values: Vec<u64> = rand::thread_rng().sample_iter(&range).take(100).collect();
println!("{:?}", values);
}
It's important to use rand::distributions::uniform::Uniform instead of simply performing the modulo of a uniform random number. See Why do people say there is modulo bias when using a random number generator? for more details.
Since we are generating multiple numbers from a range, it's more performant to create the Uniform once and reuse it. Creating the Uniform does some computation to avoid sampling bias.
We can use Rng::sample_iter to create an iterator of random values and then take some number of them, collecting into a Vec. collect will even make use of Iterator::size_hint to allocate exactly the right number of elements.
If you only needed a single random number in the range, you could use the shortcut Rng::gen_range:
use rand::Rng; // 0.8.0
fn main() {
let mut rng = rand::thread_rng();
let value: u64 = rng.gen_range(0..20);
}
If you needed a vector of random values without limiting to a range, you can use the Standard distribution:
use rand::{distributions::Standard, Rng}; // 0.8.0
fn main() {
let values: Vec<u64> = rand::thread_rng().sample_iter(Standard).take(100).collect();
println!("{:?}", values);
}
- 388,571
- 95
- 1,107
- 1,366
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Could be `rng.gen_iter::
().take(100).map(|n| n % 20 + 1).collect();` with only std. – Stargateur Jan 12 '18 at 09:52 -
1@Stargateur You might at least note that `% 20` is not the same as `gen_range(0, 20)` - and I'd really advise against "cheating" on this level, even if for specific use cases it might not matter. – Stefan Jan 12 '18 at 10:12
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@Stefan What do you mean, I'm not cheating, this is how all ranges are implemented, https://doc.rust-lang.org/rand/src/rand/distributions/range.rs.html#127. This is very classic. – Stargateur Jan 12 '18 at 10:30
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@Stargateur Just read the comment and the `accept_zone` condition above the line you just linked to see the difference. – Stefan Jan 12 '18 at 10:35
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2The `accept_zone` calculation is the reason why you should allocate [`Range`](https://doc.rust-lang.org/rand/rand/distributions/range/struct.Range.html) once and reuse it, instead of calling [`gen_range`](https://doc.rust-lang.org/rand/rand/trait.Rng.html#method.gen_range) in a loop. – Stefan Jan 12 '18 at 10:39