rao

用 Rust 编写的自适应光学工具

lib.rs:

rao

rao - Rust 中的自适应光学工具 - 是一套快速且鲁棒的自适应光学实用工具。当前 rao 的范围是用于自适应光学中的大矩阵计算，用于实时自适应光学配置和控制。具体来说，我们旨在提供快速、可扩展且可靠的 API，用于生成

• rao::IMat - 测量和执行器之间的相互作用矩阵，
• rao::CovMat - 测量之间的协方差矩阵。

这两个矩阵通常是实时控制 (RTC) 配置中的最大计算负担，也是 RTC 中性能最敏感的部分。

示例

构建一个交互矩阵和平方网格 SH-WFS

use crate::rao::Matrix;
const N_SUBX: i32 = 8;  // 8 x 8 subapertures
const PITCH: f64 = 0.2;  // 0.2 metres gap between actuators
const COUPLING: f64 = 0.5;  // actuator cross-coupling

// build list of measurements
let mut measurements = vec![];
for i in 0..N_SUBX {
    for j in 0..N_SUBX {
        let x0 = ((j-N_SUBX/2) as f64 + 0.5)*PITCH;
        let y0 = ((i-N_SUBX/2) as f64 + 0.5)*PITCH;
        let xz = 0.0;  // angular x-component (radians)
        let yz = 0.0;  // angular y-compenent (radians)
        // define the optical axis of subaperture
        let line = rao::Line::new(x0,xz,y0,yz);
        // slope-style measurement
        // x-slope
        measurements.push(rao::Measurement::SlopeTwoEdge{
            central_line: line.clone(),
            edge_separation: PITCH,
            edge_length: PITCH,
            npoints: 5,
            gradient_axis: rao::Vec2D::x_unit(),
        });
        // y-slope
        measurements.push(rao::Measurement::SlopeTwoEdge{
            central_line: line.clone(),
            edge_separation: PITCH,
            edge_length: PITCH,
            npoints: 5,
            gradient_axis: rao::Vec2D::y_unit(),
        });
    }
}

// build list of actuators
let mut actuators = vec![];
for i in 0..(N_SUBX+1) {
    for j in 0..(N_SUBX+1) {
        let x = ((j-N_SUBX/2) as f64)*PITCH;
        let y = ((i-N_SUBX/2) as f64)*PITCH;
        actuators.push(
            // Gaussian influence functions
            rao::Actuator::Gaussian{
                // std defined by coupling and pitch
                sigma: rao::coupling_to_sigma(COUPLING, PITCH),
                // position of actuator in 3D (z=altitude)
                position: rao::Vec3D::new(x, y, 0.0),
            }
        );
    }
}

// instanciate imat from (actu,meas)
let imat = rao::IMat::new(&measurements, &actuators);
// serialise imat for saving
let data: Vec<f64> = imat.flattened_array();