Module sparse_fft 

Sparse Fast Fourier Transform Implementation

This module provides implementations of Sparse FFT algorithms, which are efficient for signals that have a sparse representation in the frequency domain. These algorithms can achieve sub-linear runtime when the signal has only a few significant frequency components.

Module Organization

• config - Configuration types and enums for sparse FFT
• algorithms - Core sparse FFT algorithm implementations
• windowing - Window function utilities
• estimation - Sparsity estimation methods
• reconstruction - Spectrum reconstruction utilities

Examples

use scirs2_fft::sparse_fft::{sparse_fft, SparseFFTConfig, SparsityEstimationMethod};

// Create a sparse signal
let signal = vec![1.0, 0.0, 0.0, 0.5, 0.0, 0.0, 0.25, 0.0];

// Compute sparse FFT with 4 components
let result = sparse_fft(&signal, 4, None, None).unwrap();

println!("Found {} sparse components", result.values.len());

Re-exports

pub use algorithms::SparseFFT;

pub use algorithms::SparseFFTResult;

pub use config::SparseFFTAlgorithm;

pub use config::SparseFFTConfig;

pub use config::SparsityEstimationMethod;

pub use config::WindowFunction;

pub use algorithms::adaptive_sparse_fft;

pub use algorithms::frequency_pruning_sparse_fft;

pub use algorithms::sparse_fft;

pub use algorithms::sparse_fft2;

pub use algorithms::sparse_fftn;

pub use algorithms::spectral_flatness_sparse_fft;

pub use reconstruction::reconstruct_filtered;

pub use reconstruction::reconstruct_high_resolution;

pub use reconstruction::reconstruct_spectrum;

pub use reconstruction::reconstruct_time_domain;

pub use config::try_as_complex;

Modules

algorithms

Core sparse FFT algorithm implementations

config

Configuration types and utilities for Sparse FFT algorithms

estimation

Sparsity estimation methods for Sparse FFT

reconstruction

Spectrum reconstruction utilities for Sparse FFT

windowing

Window function implementations for Sparse FFT