normxcorr.py

def normxcorr1(template, search_window):
    """
    Normlized cross-correlation using scipy - contributed by d-chambers.

    :type template: :class:`numpy.ndarray`
    :param template: 1D numpy array to use as template
    :type search_window: :class: `numpy.ndarray`
    :param search_window: 1D numpy array to search for the template within.

    :rtype: :class: `numpy.ndarray`
    :returns: Normalized cross-correlation vector.
    """
    # cast to float 32
    template = template.astype(np.float32)
    search_window = search_window.astype(np.float32)
    # switch t and s if t is larger than s
    if len(template) > len(search_window):
        template, search_window = search_window, template
    n = len(template)
    nt = (template - np.mean(template)) / (np.std(template) * n)
    a = bottleneck.move_mean(search_window, n)[n - 1:]
    b = bottleneck.move_std(search_window, n)[n - 1:]
    c = fftconvolve(nt[::-1], search_window, mode="valid")
    result = (c - nt.sum() * a) / b
    return result