scirs2_fft/compressed_sensing/
types.rs

1//! Types for compressed sensing via FFT-based measurements.
2
3/// Configuration for compressed sensing recovery algorithms.
4#[derive(Debug, Clone)]
5pub struct CsConfig {
6    /// Target sparsity (number of non-zero coefficients).
7    pub sparsity: usize,
8    /// Maximum number of iterations.
9    pub max_iter: usize,
10    /// Convergence tolerance.
11    pub tol: f64,
12}
13
14impl Default for CsConfig {
15    fn default() -> Self {
16        Self {
17            sparsity: 5,
18            max_iter: 100,
19            tol: 1e-6,
20        }
21    }
22}
23
24/// Sparse frequency-domain measurements (partial DFT observations).
25///
26/// Represents y = A·x where A is a partial DFT matrix built from `indices`.
27#[derive(Debug, Clone)]
28pub struct Measurement {
29    /// Which frequency bins were observed (row indices of the DFT matrix).
30    pub indices: Vec<usize>,
31    /// Observed values: real and imaginary parts interleaved as `[re0, im0, re1, im1, …]`.
32    pub values: Vec<f64>,
33}
34
35/// Result of a compressed sensing recovery.
36#[derive(Debug, Clone)]
37pub struct CsResult {
38    /// Recovered time-domain signal of length N.
39    pub recovered: Vec<f64>,
40    /// Number of iterations performed.
41    pub iterations: usize,
42    /// Final residual ‖y − A·x‖₂.
43    pub residual: f64,
44}
45
46/// Recovery algorithm to use.
47#[non_exhaustive]
48#[derive(Debug, Clone, Copy, PartialEq, Eq)]
49pub enum RecoveryMethod {
50    /// Orthogonal Matching Pursuit.
51    Omp,
52    /// Iterative Shrinkage / Thresholding (ISTA / FISTA).
53    Ista,
54    /// Alternating Direction Method of Multipliers.
55    Admm,
56    /// Compressive Sampling Matching Pursuit.
57    CoSaMP,
58}
scirs2_fft/compressed_sensing/types.rs

scirs2_fft/compressed_sensing/
types.rs
