pub fn add_f32(src_a: &[f32], src_b: &[f32], dst: &mut [f32])Examples found in repository?
examples/basic_usage.rs (line 12)
5fn main() {
6 println!("=== embedded-dsp Basic Usage Example ===");
7
8 // 1. Vector Operations
9 let a = [1.0f32, 2.0, 3.0, 4.0];
10 let b = [10.0f32, 20.0, 30.0, 40.0];
11 let mut vec_out = [0.0f32; 4];
12 add_f32(&a, &b, &mut vec_out);
13 println!("Vector Add: {:?}", vec_out);
14
15 let dot = dot_prod_f32(&a, &b);
16 println!("Vector Dot Product: {}", dot);
17
18 // 2. Q15 Fixed-Point Saturating Math
19 let q15_a = [20000i16, 25000];
20 let q15_b = [15000i16, 10000];
21 let mut q15_out = [0i16; 2];
22 add_q15(&q15_a, &q15_b, &mut q15_out);
23 println!("Q15 Saturating Add (clamped at 32767): {:?}", q15_out);
24
25 // 3. FIR Filtering
26 let coeffs = [0.25f32, 0.5, 0.25]; // 3-tap moving average filter
27 let mut state = [0.0f32; 3 + 4 - 1];
28 let mut fir = FirInstanceF32::init(3, &coeffs, &mut state);
29
30 let input_signal = [1.0f32, 2.0, 3.0, 4.0];
31 let mut filtered_signal = [0.0f32; 4];
32 fir_f32(&mut fir, &input_signal, &mut filtered_signal);
33 println!("FIR Filter Output: {:?}", filtered_signal);
34
35 // 4. PID Motor Controller
36 let mut pid = PidInstanceF32::new(2.0, 0.1, 0.05);
37 let control_output = pid.process(10.0);
38 println!("PID Control Signal: {}", control_output);
39
40 // 5. 64-Point Complex FFT
41 let mut fft_data = [0.0f32; 128]; // 64 complex pairs [re, im, ...]
42 for i in 0..64 {
43 fft_data[2 * i] = (i as f32 * 0.1).sin();
44 }
45 cfft_f32(&mut fft_data, 64, 0, 1);
46 println!("64-Point Complex FFT processed successfully!");
47
48 // 6. 1D Conditional Median Filtering (Impulse / Spike Rejection)
49 let spiky_signal = [1.0f32, 1.1, 1.0, 100.0, 1.2, 1.1, 1.0];
50 let mut clean_signal = [0.0f32; 7];
51 median_filter_1d_f32(&spiky_signal, &mut clean_signal, 3, 5.0);
52 println!("Conditional Median Filter Out: {:?}", clean_signal);
53
54 // 7. Welch's Method Power Spectral Density (PSD)
55 let mut psd_out = [0.0f32; 32];
56 let mut sine_wave = [0.0f32; 128];
57 for (i, val) in sine_wave.iter_mut().enumerate() {
58 *val = (2.0 * core::f32::consts::PI * 100.0 * (i as f32) / 1000.0).sin();
59 }
60 welch_psd_f32(
61 &sine_wave,
62 &mut psd_out,
63 64,
64 32,
65 1000.0,
66 WelchWindow::Hamming,
67 true,
68 );
69 println!("Welch PSD (dB) at bin 6: {:.2} dB", psd_out[6]);
70
71 // 8. 2D Spatial Processing (2D DCT & Sobel Edge Detection)
72 let img_4x4 = [
73 0.0f32, 0.0, 10.0, 10.0, 0.0, 0.0, 10.0, 10.0, 0.0, 0.0, 10.0, 10.0, 0.0, 0.0, 10.0, 10.0,
74 ];
75 let mut edges = [0.0f32; 16];
76 sobel_edge_detection_f32(&img_4x4, &mut edges, 4, 4, 15.0);
77 println!("2D Sobel Edge Output (4x4): {:?}", edges);
78
79 // 9. Weighted Polynomial Least-Squares Sensor Calibration
80 let x_cal = [0.0f32, 1.0, 2.0, 3.0, 4.0];
81 let y_cal = [2.0f32, 5.0, 8.0, 11.0, 14.0]; // y = 2 + 3x
82 let mut cal_coeffs = [0.0f32; 2];
83 polynomial_least_squares_fit(&x_cal, &y_cal, None, 1, &mut cal_coeffs);
84 println!(
85 "Fitted Sensor Calibration: y = {:.2} + {:.2}*x",
86 cal_coeffs[0], cal_coeffs[1]
87 );
88}