digital_filter/
lib.rs

1//! # Digital Filter
2//!
3//! This crate will provide an interface to a digital FIR filter implementation for no-std
4//! environments that cannot depend on a heap being present. By passing in the filter weights and a
5//! matching empty buffer, this crate will instantiate a digital filter that will accept a stream
6//! of inputs and produce a stream of filtered outputs.
7//!
8//! This crate is effectively an implementation of the `lfilter` function in SciPy. The goal of
9//! this crate is to be a self-contained way to apply a digital filter in an embedded system. It
10//! doesn't perform filter design, so you'll need an external tool to design the filter weights for
11//! input. SciPy and Matlab both have excellent tools for this (`scipy.signal.firwin` for SciPy).
12#![no_std]
13#![allow(unused_imports)]
14
15#[macro_use]
16extern crate generic_array;
17extern crate heapless;
18extern crate typenum;
19
20use heapless::spsc::Queue;
21use generic_array::{GenericArray, ArrayLength};
22
23type FilterItem = f32;
24type FilterBuf<N> = GenericArray<FilterItem, N>;
25type FilterRing<N> = Queue<FilterItem, N>;
26
27pub struct DigitalFilter<N>
28where
29    N: ArrayLength<FilterItem> + heapless::ArrayLength<FilterItem>,
30{
31    coeffs: FilterBuf<N>,
32    buffer: FilterRing<N>
33}
34
35impl<N> DigitalFilter<N>
36where
37    N: ArrayLength<FilterItem> + heapless::ArrayLength<FilterItem>,
38{
39    pub fn new(coeffs: FilterBuf<N>) -> Self {
40        let num_taps = coeffs.len();
41        let mut buffer: FilterRing<N> = Queue::new();
42        for _idx in 0..num_taps {
43            buffer.enqueue(0.).unwrap();
44        }
45        DigitalFilter { coeffs, buffer }
46    }
47
48
49    pub fn filter(&mut self, input: f32) -> f32 {
50        let _ = self.buffer.dequeue();
51        self.buffer.enqueue(input).unwrap();
52        let mut output: f32 = 0_f32;
53        let mut c_idx = self.coeffs.len();
54        for el in self.buffer.iter() {
55            c_idx -= 1;
56            output += el * self.coeffs[c_idx];
57        }
58        output
59    }
60}
61
62
63#[cfg(test)]
64mod tests {
65    use DigitalFilter;
66
67    #[test]
68    fn basic_filter_test() {
69        let coeffs = arr![f32; 1., 1., 1.];
70        let mut filter = DigitalFilter::new(coeffs);
71        let inputs = [4., 8., 15., 16., 23., 42.];
72        let expected_output = [4., 12., 27., 39., 54., 81.];
73        let mut actual_output = [0.; 6];
74        for (idx, input) in inputs.iter().enumerate() {
75            actual_output[idx] = filter.filter(*input);
76        }
77        assert_eq!(expected_output, actual_output);
78    }
79
80    #[test]
81    fn varying_weight_filter_test() {
82        let coeffs = arr![f32; 1., 2., 3.];
83        let mut filter = DigitalFilter::new(coeffs);
84        let inputs = [4., 8., 15., 16., 23., 42.];
85        let expected_output = [4., 16., 43., 70., 100., 136.];
86        let mut actual_output = [0.; 6];
87        for (idx, input) in inputs.iter().enumerate() {
88            actual_output[idx] = filter.filter(*input);
89        }
90        assert_eq!(expected_output, actual_output);
91    }
92}
digital_filter/lib.rs

digital_filter/
lib.rs
