Struct Uniform 

pub struct Uniform { /* private fields */ }

The struct representing an uniform distribution.

Given a range, it generates a vector of uniform distributed input sizes.

Implementations

impl Uniform

pub fn new(range: RangeInclusive<usize>) -> Self

Creates a new uniform distribution.

Arguments

• range - The range of the distribution.

Examples found in repository

examples/search/main.rs (line 22)

fn main() {
    // Create a distribution for the length of the vectors
    // Here we use an uniform distribution with a minimum of 10 and a maximum of 100_000
    let length_distribution = Uniform::new(10..=100_000);

    // Create the builder for the vectors
    // Here we choose to use the fast generator method in order to generate ordered vectors
    let vector_builder = InputBuilder::new(length_distribution, Generator::Fast);

    // Build 200 vectors
    let vectors = vector_builder.build(200);

    // Create a slice of the algorithms we want to measure
    let algorithms: &[(fn(&input::SearchInput) -> Option<usize>, &str); 2] = &[
        (linear_search_input, "Linear search"),
        (binary_search_input, "Binary search"),
    ];

    // Measure the algorithms on the vectors, given a relative error of 0.001
    let results = measure(&vectors, algorithms, 0.001);

    let file_name = "results/search.svg";

    // Here we print the linear regression of the log-log scale of the results
    for result in results.clone().measurements {
        let log_linear_regression = result.log_log_scale().linear_regression();
        println!(
            "{}: {} * x + {}",
            result.algorithm_name, log_linear_regression.0, log_linear_regression.1
        )
    }

    let config = PlotConfig::default()
        .with_title("Search in an ordered vector")
        .with_caption("The time plot of searching algorithms in an ordered vector");

    // Plot the results
    time_plot(file_name, results, &config);
}

pub fn set_gen_type(&mut self, gen_type: GenerationType)

Sets the generation type of the exponential distribution. The generation type can be either fixed intervals or random.

Arguments

• gen_type - The generation type.

Trait Implementations

impl Clone for Uniform

fn clone(&self) -> Uniform

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Uniform

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl ProbabilityDistribution for Uniform

fn inverse_cdf(&self, u: f64) -> f64

This function takes a value x in [0,1] uniformly distributed and returns a value that is distributed according to the probability distribution chosen.

fn get_gen_type(&self) -> &GenerationType

Returns the generation type of the distribution.