implement an lms filter from scratch to perform active noise cancellation from a live audio feed in python. implement the lms filter by scratch in python

main.py
import numpy as np
import sounddevice as sd
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main.py
def lms_filter(input_signal, desired_signal, filter_length, step_size):
    filter_coefficients = np.zeros(filter_length)  # Initialize filter coefficients
    filtered_output = np.zeros(len(input_signal))  # Initialize filtered output
    for n in range(filter_length, len(input_signal)):
        x = input_signal[n : n - filter_length : -1]  # Select current input samples
        y = np.dot(filter_coefficients, x)  # Estimate the output
        e = desired_signal[n] - y  # Calculate the error
        filter_coefficients = filter_coefficients + step_size * e * x  # Update the filter coefficients
        filtered_output[n] = y  # Store the filtered output
    return filtered_output
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main.py
# Define the desired noise signal and step size
desired_noise = sd.rec(int(10 * fs), samplerate=fs, channels=1)[:, 0]  # Use sounddevice library to record desired noise
step_size = 0.1  # Adjust step size according to requirements

# Run the active noise cancellation
fs = 44100  # Sample rate
duration = 10  # Duration in seconds
input_signal = sd.rec(int(duration * fs), samplerate=fs, channels=1)[:, 0]  # Use sounddevice library to record input audio
filtered_output = lms_filter(input_signal, desired_noise, filter_length=128, step_size=step_size)

# Play the filtered output
sd.play(filtered_output, samplerate=fs, blocking=True)
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