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Thomas Forgione 2018-02-16 18:24:29 +01:00
parent 14455d3693
commit 2d0ec8ceae
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7 changed files with 363 additions and 17 deletions

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@ -4,6 +4,7 @@ version = "0.1.0"
authors = ["Thomas Forgione <thomas@tforgione.fr>"]
[dependencies]
rand = "*"
[[bin]]
name = "example"

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plot/centers.dat Normal file
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plot/plot.gpi Normal file
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@ -0,0 +1,11 @@
set terminal png size 1280,720 enhanced font "Sans,15"
set output "diagram.png"
set pointsize 3
set xrange [0:10]
set yrange [0:10]
plot "< awk '{if($3 == \"red\") print}' dat.dat" u 1:2 t "red" pt 4, \
"< awk '{if($3 == \"green\") print}' dat.dat" u 1:2 t "green" pt 4, \
"< awk '{if($3 == \"blue\") print}' dat.dat" u 1:2 t "blue" pt 4, \
"< awk '{if($3 == \"red\") print}' centers.dat" u 1:2 t "red" pt 7, \
"< awk '{if($3 == \"green\") print}' centers.dat" u 1:2 t "green" pt 7, \
"< awk '{if($3 == \"blue\") print}' centers.dat" u 1:2 t "blue" pt 7

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plot/regen.sh Executable file
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@ -0,0 +1,5 @@
#!/usr/bin/env bash
cd ..
cargo run --release --bin example
cd plot
gnuplot plot.gpi

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@ -1,10 +1,13 @@
extern crate rand;
extern crate generic_kmeans;
use std::fmt::{Display, Formatter, Result};
use std::fs::File;
use rand::distributions::Range;
use rand::distributions::normal::Normal;
use generic_kmeans::{kmeans, Clusterable};
#[derive(PartialEq, Clone)]
#[derive(PartialEq, Copy, Clone)]
struct Vector2<T> {
pub x: T,
pub y: T,
@ -54,29 +57,52 @@ impl Clusterable for Vector2<f64> {
fn main() {
let elements = vec![
Vector2::new(8.0, 3.0),
Vector2::new(9.0, 3.0),
Vector2::new(9.0, 2.0),
Vector2::new(1.0, 8.0),
Vector2::new(2.0, 9.0),
Vector2::new(3.0, 8.0),
use rand::distributions::IndependentSample;
let colors = vec![
"blue",
"red",
"green",
];
let initial = vec![
Vector2::new(1.0, 10.0),
Vector2::new(10.0, 0.0),
];
let range = Range::new(0.0, 10.0);
let mut rng = rand::thread_rng();
let cluster_number = 3;
let (clusters, nb_iterations) = kmeans(initial, elements, 1000).ok().unwrap();
let mut centers = vec![];
for _ in 0..cluster_number {
let center = Vector2::new(range.ind_sample(&mut rng), range.ind_sample(&mut rng));
centers.push((center, Normal::new(center.x, 0.5), Normal::new(center.y, 0.5)));
}
let mut elements = vec![];
for &mut (_, x_rng, y_rng) in centers.iter_mut() {
for _ in 0..100 {
elements.push(Vector2::new(x_rng.ind_sample(&mut rng), y_rng.ind_sample(&mut rng)));
}
}
let (clusters, nb_iterations) = kmeans(
centers.iter().map(|x| x.clone().0).collect::<Vec<_>>(), elements, 100000).ok().unwrap();
println!("{}", nb_iterations);
for (index, cluster) in clusters.iter().enumerate() {
println!("CLUSTER {}", index);
let mut output = File::create("plot/dat.dat").unwrap();
for (cluster, color) in clusters.iter().zip(&colors) {
for element in cluster {
println!("\t{}", element);
use std::io::Write;
writeln!(output, "{} {} {}", element.x, element.y, color).unwrap();
}
}
let mut center_file = File::create("plot/centers.dat").unwrap();
for (&(center, _, _), color) in centers.iter().zip(&colors) {
use std::io::Write;
writeln!(center_file, "{} {} {}", center.x, center.y, color).unwrap();
}
}