def psf_configure_simple(psf_type="GAUSSIAN", fwhm=1, kernelsize=11, deltaPix=1, truncate=6, kernel=None):
    """
    this routine generates keyword arguments to initialize a PSF() class in lenstronomy. Have a look at the PSF class
    documentation to see the full possibilities.

    :param psf_type: string, type of PSF model
    :param fwhm: Full width at half maximum of PSF (if GAUSSIAN psf)
    :param kernelsize: size in pixel of kernel (use odd numbers), only applicable for PIXEL kernels
    :param deltaPix: pixel size in angular units (only needed for GAUSSIAN kernel
    :param truncate: how many sigmas out is the truncation happening
    :param kernel: 2d numpy arra centered PSF (odd number per axis)
    :return: keyword arguments
    """

    if psf_type == 'GAUSSIAN':
        sigma = util.fwhm2sigma(fwhm)
        sigma_axis = sigma
        gaussian = Gaussian()
        x_grid, y_grid = util.make_grid(kernelsize, deltaPix)
        kernel_large = gaussian.function(x_grid, y_grid, amp=1., sigma_x=sigma_axis, sigma_y=sigma_axis, center_x=0, center_y=0)
        kernel_large /= np.sum(kernel_large)
        kernel_large = util.array2image(kernel_large)
        kernel_pixel = kernel_util.pixel_kernel(kernel_large)
        kwargs_psf = {'psf_type': psf_type, 'fwhm': fwhm, 'truncation': truncate*fwhm, 'kernel_point_source': kernel_large, 'kernel_pixel': kernel_pixel, 'pixel_size': deltaPix}
    elif psf_type == 'PIXEL':
        kernel_large = copy.deepcopy(kernel)
        kernel_large = kernel_util.cut_psf(kernel_large, psf_size=kernelsize)
        kwargs_psf = {'psf_type': "PIXEL", 'kernel_point_source': kernel_large}
    elif psf_type == 'NONE':
        kwargs_psf = {'psf_type': 'NONE'}
    else:
        raise ValueError("psf type %s not supported!" % psf_type)
    return kwargs_psf