:dep ndarray = "0.15.6"
-:dep linfa = { version = "0.6.1" }
-// clustering is a separate crate
-:dep linfa-clustering = { version = "0.6.1" }
-// apt install libfontconfig-dev on Ubuntu 22.04 LTS
-:dep plotters = { version = "^0.3.4", default_features = false, features = ["evcxr", "all_series"] }
-extern crate plotters;
-// Import all the plotters prelude functions
-use plotters::prelude::*;
-:dep rand = "0.8.5"
-// Import the linfa prelude and KMeans algorithm
-use linfa::prelude::*;
-use linfa_clustering::Dbscan;
-// We'll build our dataset on our own using ndarray and rand
-use ndarray::prelude::*;
-// Import the plotters crate to create the scatter plot
-use plotters::prelude::*;
-use rand::prelude::*;
-use std::f32;
-// Creates random points contained in an approximately square area
-pub fn create_square(center_point: [f32; 2], edge_length: f32, num_points: usize) -> Array2<f32> {
- // We
- let mut data: Array2<f32> = Array2::zeros((num_points, 2));
- let mut rng = rand::thread_rng();
- for i in 0..num_points {
- let x = rng.gen_range(-edge_length * 0.5..edge_length * 0.5); // generates a float between 0 and 1
- let y = rng.gen_range(-edge_length * 0.5..edge_length * 0.5);
- data[[i, 0]] = center_point[0] + x;
- data[[i, 1]] = center_point[1] + y;
- }
-
- data
-}
-// Creates a circle of random points
-pub fn create_circle(center_point: [f32; 2], radius: f32, num_points: usize) -> Array2<f32> {
- let mut data: Array2<f32> = Array2::zeros((num_points, 2));
- let mut rng = rand::thread_rng();
- for i in 0..num_points {
- let theta = rng.gen_range(0.0..2.0 * f32::consts::PI);
- let r = rng.gen_range(0.0..radius);
- let x = r * f32::cos(theta);
- let y = r * f32::sin(theta);
-
- data[[i, 0]] = center_point[0] + x;
- data[[i, 1]] = center_point[1] + y;
- }
-
- data
-}
-// Creates a line y = m*x + b with some noise
-pub fn create_line(m: f64, b: f64, num_points: usize, min_max: [f64; 2]) -> Array2<f64> {
- let mut data: Array2<f64> = Array2::zeros((num_points, 2));
-
- let mut rng = rand::thread_rng();
- for i in 0..num_points {
- let var_y = rng.gen_range(-0.5..0.5f64);
- data[[i, 0]] = rng.gen_range(min_max[0]..min_max[1]);
- data[[i, 1]] = (m * data[[i, 0]]) + b + var_y;
- }
-
- data
-}
-// Creates a quadratic y = m*x^2 + b with some noise
-pub fn create_curve(m: f64, pow: f64, b: f64, num_points: usize, min_max: [f64; 2]) -> Array2<f64> {
- let mut data: Array2<f64> = Array2::zeros((num_points, 2));
-
- let mut rng = rand::thread_rng();
- for i in 0..num_points {
- let var_y = rng.gen_range(-0.5..0.5f64);
- data[[i, 0]] = rng.gen_range(min_max[0]..min_max[1]);
- data[[i, 1]] = (m * data[[i, 0]].powf(pow)) + b + var_y;
- }
-
- data
-}
-// Creates a hollow circle of random points with a specified inner and outer diameter
-pub fn create_hollow_circle(
- center_point: [f32; 2],
- radius: [f32; 2],
- num_points: usize,
-) -> Array2<f32> {
- assert!(radius[0] < radius[1]);
- let mut data: Array2<f32> = Array2::zeros((num_points, 2));
- let mut rng = rand::thread_rng();
- for i in 0..num_points {
- let theta = rng.gen_range(0.0..2.0 * f32::consts::PI);
- let r = rng.gen_range(radius[0]..radius[1]);
- let x = r * f32::cos(theta);
- let y = r * f32::sin(theta);
-
- data[[i, 0]] = center_point[0] + x;
- data[[i, 1]] = center_point[1] + y;
- }
-
- data
-}
-// Check the array has the correct shape for plotting (Two-dimensional, with 2 columns)
-pub fn check_array_for_plotting(arr: &Array2<f32>) -> bool {
- if (arr.shape().len() != 2) || (arr.shape()[1] != 2) {
- panic!(
- "Array shape of {:?} is incorrect for 2D plotting!",
- arr.shape()
- );
- // false
- } else {
- true
- }
-}
-// The goal is to be able to find each of these as distinct, and exclude some of the noise
-let circle: Array2<f32> = create_circle([5.0, 5.0], 1.0, 100); // Cluster 0
-let donut_1: Array2<f32> = create_hollow_circle([5.0, 5.0], [2.0, 3.0], 400); // Cluster 1
-let donut_2: Array2<f32> = create_hollow_circle([5.0, 5.0], [4.5, 4.75], 1000); // Cluster 2
-let noise: Array2<f32> = create_square([5.0, 5.0], 10.0, 100); // Random noise
-
-
-let data = ndarray::concatenate(
- Axis(0),
- &[circle.view(), donut_1.view(), donut_2.view(), noise.view()],
- )
- .expect("An error occurred while stacking the dataset");
-evcxr_figure((640, 240), |root| {
-
- root.fill(&WHITE).unwrap();
-
- let x_lim = 0.0..10.0f32;
- let y_lim = 0.0..10.0f32;
-
- let mut ctx = ChartBuilder::on(&root)
- .set_label_area_size(LabelAreaPosition::Left, 40) // Put in some margins
- .set_label_area_size(LabelAreaPosition::Right, 40)
- .set_label_area_size(LabelAreaPosition::Bottom, 40)
- .caption("DBSCAN", ("sans-serif", 25)) // Set a caption and font
- .build_cartesian_2d(x_lim, y_lim)
- .expect("Couldn't build our ChartBuilder");
-
- let circle: Array2<f32> = create_circle([5.0, 5.0], 1.0, 100); // Cluster 0
- let donut_1: Array2<f32> = create_hollow_circle([5.0, 5.0], [2.0, 3.0], 400); // Cluster 1
- let donut_2: Array2<f32> = create_hollow_circle([5.0, 5.0], [4.5, 4.75], 1000); // Cluster 2
- let noise: Array2<f32> = create_square([5.0, 5.0], 10.0, 100); // Random noise
-
- let data = ndarray::concatenate(
- Axis(0),
- &[circle.view(), donut_1.view(), donut_2.view(), noise.view()],
- )
- .expect("An error occurred while stacking the dataset");
-
- // Compared to linfa's KMeans algorithm, the DBSCAN implementation can operate
- // directly on an ndarray `Array2` data structure, so there's no need to convert it
- // into the linfa-native `Dataset` first.
- let min_points = 20;
- let clusters = Dbscan::params(min_points)
- .tolerance(0.6)
- .transform(&data)
- .unwrap();
- // println!("{:#?}", clusters);
-
-
- let x_lim = 0.0..10.0f32;
- let y_lim = 0.0..10.0f32;
-
-
- ctx.configure_mesh().draw().unwrap();
- let root_area = ctx.plotting_area();
- // ANCHOR_END: configure_chart
-
- // ANCHOR: run_check_for_plotting;
- // check_array_for_plotting(dataset: &Array2<f32>) -> bool {}
- check_array_for_plotting(&circle); // Panics if that's not true
- // ANCHOR_END: run_check_for_plotting
-
- // ANCHOR: plot_points
- for i in 0..data.shape()[0] {
- let coordinates = data.slice(s![i, 0..2]);
-
- let point = match clusters[i] {
- Some(0) => Circle::new(
- (coordinates[0], coordinates[1]),
- 3,
- ShapeStyle::from(&RED).filled(),
- ),
- Some(1) => Circle::new(
- (coordinates[0], coordinates[1]),
- 3,
- ShapeStyle::from(&GREEN).filled(),
- ),
- Some(2) => Circle::new(
- (coordinates[0], coordinates[1]),
- 3,
- ShapeStyle::from(&BLUE).filled(),
- ),
- // Making sure our pattern-matching is exhaustive
- // Note that we can define a custom color using RGB
- _ => Circle::new(
- (coordinates[0], coordinates[1]),
- 3,
- ShapeStyle::from(&RGBColor(255, 255, 255)).filled(),
- ),
- };
-
- root_area
- .draw(&point)
- .expect("An error occurred while drawing the point!");
- }
-
- Ok(())
-}).style("width:90%")
-extern crate plotters;
-use plotters::prelude::*;
-evcxr_figure((640, 240), |root| {
- // The following code will create a chart context
- let mut chart = ChartBuilder::on(&root)
- .caption("Hello Plotters Chart Context!", ("Arial", 20).into_font())
- .build_cartesian_2d(0f32..1f32, 0f32..1f32)?;
- // Then we can draw a series on it!
- chart.draw_series((1..10).map(|x|{
- let x = x as f32/10.0;
- Circle::new((x,x), 5, &RED)
- }))?;
- Ok(())
-}).style("width:60%")
-
-