commit eb6f22be87d59a57d8fd95be4435ca0071bf871e
Author: Sebastian <sebastian@sebastians-site.de>
Date:   Sun Jun 18 14:43:04 2023 +0200

    First working filter

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..ea8c4bf
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+/target
diff --git a/Cargo.lock b/Cargo.lock
new file mode 100644
index 0000000..544e8cc
--- /dev/null
+++ b/Cargo.lock
@@ -0,0 +1,192 @@
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+# It is not intended for manual editing.
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diff --git a/Cargo.toml b/Cargo.toml
new file mode 100644
index 0000000..a1c50e8
--- /dev/null
+++ b/Cargo.toml
@@ -0,0 +1,9 @@
+[package]
+name = "firls-rs"
+version = "0.1.0"
+edition = "2021"
+
+# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
+
+[dependencies]
+nalgebra = "0.32.2"
diff --git a/src/main.rs b/src/main.rs
new file mode 100644
index 0000000..ce5e3f7
--- /dev/null
+++ b/src/main.rs
@@ -0,0 +1,89 @@
+use std::println;
+
+use nalgebra::base::{DMatrix, DVector};
+
+fn main() {
+    let num_coeffs = 6;
+
+    let response = generate_frequency_response(
+        8000.0,
+        &vec![(0.0, 1.0), (1900.0, 1.0), (3000.0, 0.0), (4000.0, 0.0)],
+        128,
+    );
+    println!("{:?}", response);
+
+    let matrix = generate_design_matrix(num_coeffs, 128);
+
+    println!("{} {}", matrix.ncols(), matrix.nrows());
+
+    let pseudo_inverse = matrix.pseudo_inverse(0.0).unwrap();
+
+    println!("{} {}", pseudo_inverse.ncols(), pseudo_inverse.nrows());
+    println!("{} {}", response.ncols(), response.nrows());
+
+    let coeffs = pseudo_inverse * response;
+
+    println!("[");
+    for i in 1..num_coeffs {
+        println!("{},", coeffs[num_coeffs - i])
+    }
+    for i in 0..num_coeffs {
+        println!("{},", coeffs[i])
+    }
+    println!("]");
+}
+
+fn generate_frequency_response(
+    f_samp: f32,
+    points: &Vec<(f32, f32)>,
+    num_points: usize,
+) -> DVector<f32> {
+    let step_size = f_samp / 2.0 / (num_points - 1) as f32;
+    println!("Step size is {}Hz", step_size);
+
+    let mut response = DVector::<f32>::zeros(num_points);
+
+    for step in 0..num_points {
+        let step_freq = step as f32 * step_size;
+
+        response[step] = interpolate_between_points(step_freq, &points)
+    }
+
+    response
+}
+
+fn interpolate_between_points(input: f32, points: &Vec<(f32, f32)>) -> f32 {
+    if input <= points.first().unwrap().0 {
+        return points.first().unwrap().1;
+    };
+    if input >= points.last().unwrap().0 {
+        return points.last().unwrap().1;
+    };
+
+    let mut result = f32::NAN;
+    for idx in 0..points.len() {
+        if input >= points[idx].0 && points[idx + 1].0 > input {
+            let slope = (points[idx + 1].1 - points[idx].1) / (points[idx + 1].0 - points[idx].0);
+            result = points[idx].1 + (input - points[idx].0) * slope;
+            break;
+        }
+    }
+
+    result
+}
+
+fn generate_design_matrix(num_coeffs: usize, num_freqs: usize) -> DMatrix<f32> {
+    let step_size = 1.0 / 2.0 / (num_freqs - 1) as f32;
+
+    let mut result = DMatrix::<f32>::zeros(num_freqs, num_coeffs);
+    result.fill_column(0, 1.0);
+
+    for row_idx in 0..num_freqs {
+        let omega = row_idx as f32 * step_size * 2.0 * std::f32::consts::PI;
+        for col_idx in 1..num_coeffs {
+            result[(row_idx, col_idx)] = 2.0 * (omega * col_idx as f32).cos()
+        }
+    }
+
+    result
+}
diff --git a/test.py b/test.py
new file mode 100644
index 0000000..e7142d9
--- /dev/null
+++ b/test.py
@@ -0,0 +1,35 @@
+#!/usr/bin/env python3
+
+from scipy import signal
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def main():
+    fs = 8000.0
+
+    coeffs = [
+            -0.0047233836,
+            0.04476544,
+            -0.038443737,
+            -0.0911246,
+            0.2894902,
+            0.6123418,
+            0.2894902,
+            -0.0911246,
+            -0.038443737,
+            0.04476544,
+            -0.0047233836,
+        ]
+
+    freq_space = np.linspace(-fs/2 / (fs/2)*np.pi, fs/2 / (fs/2)*np.pi, 512)
+    freqs, response = signal.freqz(coeffs, worN=freq_space)
+    response = 10 * np.log(abs(response))
+    plt.plot(fs/2*freqs/(np.pi), response)
+    plt.grid()
+    plt.show()
+
+ 
+
+if __name__ == '__main__':
+    main()
\ No newline at end of file