def GaussianFilter()

in src/smclarify/util/__init__.py [0:0]

• 9 lines of code
• 2 McCabe index (conditional complexity)

def GaussianFilter(input_array: np.ndarray, sigma: int = 1) -> np.ndarray:
    """
    :param input_array: array which Gaussian Filter is applied to
    :param sigma: integer which indicates standard deviation of the desired Gaussian distribution
    :return: smoothed array
    """

    if len(input_array) == 0:
        raise ValueError("input array is empty")

    def GaussianKernel(x: float, sigma: int) -> float:

        return np.exp(-((x**2) / (2 * (sigma**2)))) * 1 / (np.sqrt(2 * np.pi) * sigma)

    x = np.linspace(1, len(input_array), len(input_array))
    centered_x = x - np.mean(x)

    gauss_filter = GaussianKernel(centered_x, sigma)
    return np.convolve(input_array, gauss_filter, "same")