Made the bin argument a kwarg

    nzs = pxy > 0 # Only non-zero pxy values contribute to the sum

    return np.sum(pxy[nzs] * np.log(pxy[nzs] / px_py[nzs]))

def mutual_information_match(d_template, s_image, subpixel_size=3, bins=100,

def mutual_information_match(d_template, s_image, subpixel_size=3,

                             func=None, **kwargs):

    """

    Applys the mutual information matcher function over a search image using a

        for j in range(x_diff+1):

            sub_image = s_image[i:i+template_size[1],  # y

                                j:j+template_size[0]]  # x

            corr = func(sub_image, d_template, bins=bins, **kwargs)

            corr = func(sub_image, d_template, **kwargs)

            if corr > max_corr:

                max_corr = corr

                max_i = i