def adaptive_regularization_weights_from_pixel_signals(inner_coefficient,
    outer_coefficient, pixel_signals):
    """Compute the regularization weights, which are the effective regularization coefficient of every     pixel. They are computed using the (hyper) pixel-signal of each pixel.

    Two regularization coefficients are used, corresponding to the:

    1) (pixel_signals) - pixels with a high pixel-signal (i.e. where the signal is located in the pixelization).
    2) (1.0 - pixel_signals) - pixels with a low pixel-signal (i.e. where the signal is not located in the      pixelization).

    Parameters
    ----------
    coefficients : (float, float)
        The regularization coefficients which controls the degree of smoothing of the inversion reconstruction.
    pixel_signals : ndarray
        The estimated signal in every pixelization pixel, used to change the regularization weighting of high signal         and low signal pixelizations.
    """
    return (inner_coefficient * pixel_signals + outer_coefficient * (1.0 -
        pixel_signals)) ** 2.0
