1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
|
mod config;
mod corpus;
mod layout;
use rayon::prelude::*;
use rand::prelude::*;
use rand_pcg::*;
use corpus::*;
use layout::*;
fn main() {
let corpus = Corpus::load("new.txt").unwrap();
println!("{}", corpus);
let starting_layout = Layout::from_verbose(
"
Y W F L M K P O , Q
U R S N H D T E A I
Z X C V J B G ' . /
",
)
.unwrap();
let mut rng = Pcg64::from_entropy();
type Fun = Vec<(Layout, u32)>;
let mut best = std::u32::MAX;
let mut layouts: Fun = (0..10)
.into_iter()
.map(|i| {
let layout;
if i >= 0 {
layout = Layout::new_random_from(&starting_layout, &mut rng);
} else {
layout = starting_layout;
}
return (layout, corpus.layout_fitness(&layout));
})
.collect();
loop {
let new_layouts = layouts
.iter()
.enumerate()
.map(|(i, (kbd, _))| {
if i > 0 {
Layout::new_random_from(kbd, &mut rng)
} else {
kbd.clone()
}
})
.collect::<Vec<Layout>>();
new_layouts
.par_iter()
.map(|layout| {
return (*layout, corpus.layout_fitness(layout));
})
.collect_into_vec(&mut layouts);
layouts.sort_by(|(_, lfit), (_, rfit)| lfit.cmp(rfit));
if layouts[0].1 < best {
best = layouts[0].1;
let evl = corpus.evaluate_layout(&layouts[0].0);
println!("");
println!("================================================================================\nLayout:\n{}",
layouts[0].0
);
println!("{}\n{}", evl, layouts[0].1);
}
}
}
|
