def create_matching_kernel(source_psf, target_psf, window=None):
    """
    Create a kernel to match 2D point spread functions (PSF) using the
    ratio of Fourier transforms.

    Parameters
    ----------
    source_psf : 2D `~numpy.ndarray`
        The source PSF.  The source PSF should have higher resolution
        (i.e. narrower) than the target PSF.  ``source_psf`` and
        ``target_psf`` must have the same shape and pixel scale.

    target_psf : 2D `~numpy.ndarray`
        The target PSF.  The target PSF should have lower resolution
        (i.e. broader) than the source PSF.  ``source_psf`` and
        ``target_psf`` must have the same shape and pixel scale.

    window : callable, optional
        The window (or taper) function or callable class instance used
        to remove high frequency noise from the PSF matching kernel.
        Some examples include:

        * `~photutils.psf.matching.HanningWindow`
        * `~photutils.psf.matching.TukeyWindow`
        * `~photutils.psf.matching.CosineBellWindow`
        * `~photutils.psf.matching.SplitCosineBellWindow`
        * `~photutils.psf.matching.TopHatWindow`

        For more information on window functions and example usage, see
        :ref:`psf_matching`.

    Returns
    -------
    kernel : 2D `~numpy.ndarray`
        The matching kernel to go from ``source_psf`` to ``target_psf``.
        The output matching kernel is normalized such that it sums to 1.
    """

    # inputs are copied so that they are not changed when normalizing
    source_psf = np.copy(np.asanyarray(source_psf))
    target_psf = np.copy(np.asanyarray(target_psf))

    if source_psf.shape != target_psf.shape:
        raise ValueError('source_psf and target_psf must have the same shape '
                         '(i.e. registered with the same pixel scale).')

    # ensure input PSFs are normalized
    source_psf /= source_psf.sum()
    target_psf /= target_psf.sum()

    source_otf = fftshift(fft2(source_psf))
    target_otf = fftshift(fft2(target_psf))
    ratio = target_otf / source_otf

    # apply a window function in frequency space
    if window is not None:
        ratio *= window(target_psf.shape)

    kernel = np.real(fftshift((ifft2(ifftshift(ratio)))))
    return kernel / kernel.sum()
Create a kernel to match 2D point spread functions (PSF) using the
    ratio of Fourier transforms.

    Parameters
    ----------
    source_psf : 2D `~numpy.ndarray`
        The source PSF.  The source PSF should have higher resolution
        (i.e. narrower) than the target PSF.  ``source_psf`` and
        ``target_psf`` must have the same shape and pixel scale.

    target_psf : 2D `~numpy.ndarray`
        The target PSF.  The target PSF should have lower resolution
        (i.e. broader) than the source PSF.  ``source_psf`` and
        ``target_psf`` must have the same shape and pixel scale.

    window : callable, optional
        The window (or taper) function or callable class instance used
        to remove high frequency noise from the PSF matching kernel.
        Some examples include:

        * `~photutils.psf.matching.HanningWindow`
        * `~photutils.psf.matching.TukeyWindow`
        * `~photutils.psf.matching.CosineBellWindow`
        * `~photutils.psf.matching.SplitCosineBellWindow`
        * `~photutils.psf.matching.TopHatWindow`

        For more information on window functions and example usage, see
        :ref:`psf_matching`.

    Returns
    -------
    kernel : 2D `~numpy.ndarray`
        The matching kernel to go from ``source_psf`` to ``target_psf``.
        The output matching kernel is normalized such that it sums to 1.