A simple and fast no_std library to get the frequency spectrum of a digital signal (e.g. audio) using FFT.
It follows the KISS principle and consists of simple building blocks/optional features.
I'm not an expert on digital signal processing. Code contributions are highly welcome! :)
```rust use spectrumanalyzer::{samplesffttospectrum, FrequencyLimit}; use spectrumanalyzer::windows::hannwindow;
fn main() {
// This lib also works in no_std environments!
let samples: &[f32] = getsamples(); // TODO implement
// apply hann window for smoothing; length must be a power of 2 for the FFT
let hannwindow = hannwindow(&samples[0..4096]);
// calc spectrum
let spectrumhannwindow = samplesffttospectrum(
// (windowed) samples
&hann_window,
// sample rate
44100,
// optional frequency limit: e.g. only interested in frequencies 50 <= f <= 150?
FrequencyLimit::All,
// optional per element scaling function, e.g. 20 * log10(x); see doc comments
None,
// optional total scaling at the end; see doc comments
None,
);
for (fr, fr_val) in spectrum_hamming_window.raw_data().iter() {
println!("{}Hz => {}", fr, fr_val)
}
} ```
rust
// e.g. like this
fn get_scale_to_one_fn_factory() -> SpectrumTotalScaleFunctionFactory{
Box::new(
move |min: f32, max: f32, average: f32, median: f32| {
Box::new(
move |x| x/max
)
}
)
}
fn main() {
// ...
let spectrum_hann_window = samples_fft_to_spectrum(
&hann_window,
44100,
FrequencyLimit::All,
None,
// optional total scaling at the end; see doc comments
Some(get_scale_to_one_fn_factory()),
);
}
Measurements taken on i7-8650U @ 3 Ghz (Single-Core) with optimized build
| Operation | Time | | --------------------------------------------- | ------:| | Hann Window with 4096 samples | ≈70µs | | Hamming Window with 4096 samples | ≈10µs | | Hann Window with 16384 samples | ≈175µs | | Hamming Window with 16384 samples | ≈44µs | | FFT to spectrum with 4096 samples @ 44100Hz | ≈240µs | | FFT to spectrum with 16384 samples @ 44100Hz | ≈740µs |
In the following example you can see a basic visualization of frequencies 0 to 4000Hz for
a layered signal of sine waves of 50, 1000, and 3777Hz @ 41000Hz sample rate. The peaks for the
given frequencies are clearly visible. Each calculation was done with 2048 samples, i.e. ≈46ms.
The noise (wrong peaks) also comes from clipping of the added sine waves!
Peaks (50, 1000, 3777 Hz) are clearly visible but also noise.
Peaks (50, 1000, 3777 Hz) are clearly visible and overall noise is much smaller, but a few noisy peaks.
Peaks (50, 1000, 3777 Hz) are clearly visible and overall noise is smaller.
I tested f64 but the additional accuracy doesn't pay out the ~40% calculation overhead (on x86_64).
Apply a window function, like Hann window or Hamming window. But I'm not an expert on this.