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Add IFFT

Benchmarks (Intel Core i5-6300U @ 4x 3GHz, 16GB RAM):
```
dft         time:   [49.610 ms 50.141 ms 50.861 ms]
idft        time:   [49.531 ms 49.938 ms 50.412 ms]
fft         time:   [848.62 us 853.68 us 859.08 us]
ifft        time:   [849.98 us 852.73 us 856.13 us]
```
main
arnaucube 4 years ago
parent
commit
2aab0a81b2
3 changed files with 104 additions and 10 deletions
  1. +19
    -0
      README.md
  2. +3
    -0
      benches/bench_fft.rs
  3. +82
    -10
      src/lib.rs

+ 19
- 0
README.md

@ -4,3 +4,22 @@ Fast Fourier Transform implementation in Rust.
https://en.wikipedia.org/wiki/Fast_Fourier_transform & [DFT](https://en.wikipedia.org/wiki/Discrete_Fourier_transform)
## Usage
```rust
let values: Vec<f64> = vec![0.2, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8];
// compute the FFT (Fast Fourier Transform)
let fft_res = fft(&values);
// compute the IFFT (Inverse Fast Fourier Transform)
let ifft_res = ifft(&fft_res);
// Also, available directly (and slower) DFT & IDFT:
// compute the DFT (Discrete Fourier Transform)
let dft_res = dft(&values);
// compute the IDFT (Inverse Discrete Fourier Transform)
let idft_res = idft(&dft_res);
```

+ 3
- 0
benches/bench_fft.rs

@ -12,10 +12,13 @@ fn criterion_benchmark(c: &mut Criterion) {
.sample_iter(rand::distributions::Standard)
.take(1024)
.collect();
let f = fft_rs::fft(&values);
c.bench_function("dft", |b| b.iter(|| fft_rs::dft(&values)));
c.bench_function("idft", |b| b.iter(|| fft_rs::idft(&f)));
c.bench_function("fft", |b| b.iter(|| fft_rs::fft(&values)));
c.bench_function("ifft", |b| b.iter(|| fft_rs::ifft(&f)));
}
criterion_group!(benches, criterion_benchmark);

+ 82
- 10
src/lib.rs

@ -3,15 +3,23 @@ use std::f64::consts::PI;
// fft computes the Fast Fourier Transform
pub fn fft(x: &Vec<f64>) -> Vec<Complex64> {
let mut x_compl: Vec<Complex64> = vec![Complex::new(0_f64, 0_f64); x.len()];
for i in 0..x.len() {
x_compl[i] = Complex::new(x[i], 0_f64);
}
fft_compl(x_compl)
}
fn fft_compl(x: Vec<Complex64>) -> Vec<Complex64> {
let N = x.len();
if N % 2 > 0 {
panic!("not a power of 2");
} else if N <= 2 {
return dft(x);
return dft_compl(x);
}
let mut x_even: Vec<f64> = Vec::new();
let mut x_odd: Vec<f64> = Vec::new();
let mut x_even: Vec<Complex64> = Vec::new();
let mut x_odd: Vec<Complex64> = Vec::new();
for i in 0..x.len() {
if i % 2 == 0 {
x_even.push(x[i]);
@ -19,8 +27,8 @@ pub fn fft(x: &Vec) -> Vec {
x_odd.push(x[i]);
}
}
let mut x_even_cmplx = fft(&x_even);
let mut x_odd_cmplx = fft(&x_odd);
let mut x_even_cmplx = fft_compl(x_even);
let mut x_odd_cmplx = fft_compl(x_odd);
let mut w = Complex::new(0_f64, 2_f64 * PI / N as f64);
let mut f_k: Vec<Complex64> = Vec::new();
@ -44,18 +52,46 @@ pub fn fft(x: &Vec) -> Vec {
r
}
// ifft computes the Inverse Fast Fourier Transform
pub fn ifft(x: &Vec<Complex64>) -> Vec<f64> {
// use the IFFT method of computing conjugates, then FFT, then conjugate again, and then divide
// by N
let mut x_conj: Vec<Complex64> = Vec::new();
for i in 0..x.len() {
x_conj.push(x[i].conj());
}
let x_res = fft_compl(x_conj);
let mut r: Vec<Complex64> = Vec::new();
for i in 0..x_res.len() {
r.push(x_res[i].conj());
}
let n = x.len() as f64;
let mut rr: Vec<f64> = Vec::new();
for i in 0..r.len() {
r[i] = r[i] / Complex::new(n, 0_f64);
rr.push(r[i].re);
}
rr
}
// dft computes the Discrete Fourier Transform
pub fn dft(x: &Vec<f64>) -> Vec<Complex64> {
let mut x_compl: Vec<Complex64> = vec![Complex::new(0_f64, 0_f64); x.len()];
for i in 0..x.len() {
x_compl[i] = Complex::new(x[i], 0_f64);
}
dft_compl(x_compl)
}
fn dft_compl(x: Vec<Complex64>) -> Vec<Complex64> {
let mut w = Complex::new(0_f64, -2_f64 * PI / x.len() as f64);
// f_k = SUM{n=0, N-1} f_n * e^(-j2pi*k*n)/N
// f_k (dft_matrix) = SUM{n=0, N-1} f_n * e^(-j2pi*k*n)/N
// https://en.wikipedia.org/wiki/Discrete_Fourier_transform
let mut f: Vec<Vec<Complex64>> = Vec::new();
let mut dft_matrix: Vec<Vec<Complex64>> = Vec::new();
for i in 0..x.len() {
let mut f_k: Vec<Complex64> = Vec::new();
for j in 0..x.len() {
@ -64,9 +100,9 @@ pub fn dft(x: &Vec) -> Vec {
let fe = (w * i_compl * j_compl).exp();
f_k.push(fe);
}
f.push(f_k.clone());
dft_matrix.push(f_k.clone());
}
let r = mul_mv(f, x_compl);
let r = mul_mv(dft_matrix, x);
r
}
@ -74,7 +110,7 @@ pub fn dft(x: &Vec) -> Vec {
pub fn idft(x: &Vec<Complex64>) -> Vec<f64> {
let mut w = Complex::new(0_f64, 2_f64 * PI / x.len() as f64);
// f_k = (SUM{n=0, N-1} f_n * e^(j2pi*k*n)/N)/N
// f_k (dft_matrix) = (SUM{n=0, N-1} f_n * e^(j2pi*k*n)/N)/N
let mut dft_matrix: Vec<Vec<Complex64>> = Vec::new();
for i in 0..x.len() {
let mut f_k: Vec<Complex64> = Vec::new();
@ -143,6 +179,8 @@ fn mul_vv_el(a: Vec, b: Vec) -> Vec {
#[cfg(test)]
mod tests {
use super::*;
extern crate rand;
use rand::Rng;
#[test]
fn test_dft_simple_values() {
@ -180,5 +218,39 @@ mod tests {
assert_eq!(format!("{:.2}", r[2]), "-0.30-0.40i");
assert_eq!(format!("{:.2}", r[3]), "-0.30-0.17i");
assert_eq!(format!("{:.2}", r[4]), "-0.30+0.00i");
// expect result similar to initial values
let o = ifft(&r);
println!("{:?}", o);
assert_eq!(format!("{:.1}", o[0]), "0.2");
assert_eq!(format!("{:.1}", o[1]), "0.2");
assert_eq!(format!("{:.1}", o[2]), "0.3");
assert_eq!(format!("{:.1}", o[3]), "0.4");
assert_eq!(format!("{:.1}", o[4]), "0.5");
assert_eq!(format!("{:.1}", o[5]), "0.6");
assert_eq!(format!("{:.1}", o[6]), "0.7");
assert_eq!(format!("{:.1}", o[7]), "0.8");
}
#[test]
fn test_dft_random_values() {
let values: Vec<f64> = rand::thread_rng()
.sample_iter(rand::distributions::Standard)
.take(1024)
.collect();
let r = dft(&values);
println!("{:?}", r.len());
let o = idft(&r);
}
#[test]
fn test_fft_random_values() {
let values: Vec<f64> = rand::thread_rng()
.sample_iter(rand::distributions::Standard)
.take(1024)
.collect();
let r = fft(&values);
println!("{:?}", r.len());
let o = ifft(&r);
}
}

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