imgal 0.2.0

A fast and open-source scientific image processing and algorithm library.
Documentation 
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use std::f64::consts::LN_2;

use crate::distribution::normalized_gaussian;

/// Create a 1-dimensional Gaussian instrument response function (IRF).
///
/// # Description
///
/// Creates a Gaussian IRF by converting "full width at half maximum" (FWHM)
/// parameters into a normalized Gaussian distribution. The FWHM is converted to
/// standard deviation using the relationship:
///
/// ```text
/// σ = FWHM / (2 × √(2 × ln(2)))
/// ```
///
/// Where `ln(2) ≈ 0.693147` is the natural logarithm of `2`.
///
/// # Arguments
///
/// * `bins`: The number of discrete points to sample the Gaussian distribution.
/// * `time_range`: The total time range over which to simulate the IRF.
/// * `irf_center`: The temporal position of the IRF peak within the time range.
/// * `irf_width`: The full width at half maximum (FWHM) of the IRF.
///
/// # Returns
///
/// * `Vec<f64>`: The simulated 1-dimensional IRF curve.
pub fn gaussian_irf_1d(bins: usize, time_range: f64, irf_center: f64, irf_width: f64) -> Vec<f64> {
    let sigma = irf_width / (2.0 * (2.0 * LN_2).sqrt());

    normalized_gaussian(sigma, bins, time_range, irf_center)
}