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Matching MATLAB’s resample function in Python

It is rather annoying that a fast implementation of MATLAB’s resample function does not exist in Python with minimal theoretical knowledge of signal processing. This post aims to provide a simple implementation of MATLAB’s resample function in Python. With, you guessed it, zero context and therefore no theoretical knowledge of signal processing. The function ha been tested against MATLAB’s resample function using a simple example. I might include that later. I had originally answered this on StackExchange, but it is lost because the question was deleted.

import numpy as np
from scipy.signal import resample_poly
from math import gcd
def matlab_resample(x, resample_rate, orig_sample_rate):
    """
    Resample a signal by a rational factor (p/q) to match MATLAB's `resample` function.

    Parameters:
        x (array-like): Input signal.
        p (int): Upsampling factor.
        q (int): Downsampling factor.

    Returns:
        array-like: Resampled signal.
    """
    p = resample_rate
    q = orig_sample_rate
    factor_gcd = gcd(int(p), int(q))
    p = int(p // factor_gcd)
    q = int(q // factor_gcd)

    # Ensure input is a numpy array
    x = np.asarray(x)

    # Use resample_poly to perform efficient polyphase filtering
    y = resample_poly(x, p, q, window=('kaiser', 5.0))

    # Match MATLAB's output length behavior
    output_length = int(np.ceil(len(x) * p / q))
    y = y[:output_length]

    return y