core.py 文件源码

def create_background_image(ccd, profile_model, nsigma, separation):
    """Creates a background-only image

    Using a profile model and assuming the spectrum is misaligned only a little
    bit (i.e. a couple of pixels from end to end) with respect to the lines of
    the detector. The number of sigmas determines the width of the zone to be
    masked and the separation is an offset that is added.

    Args:
        ccd (object): A ccdproc.CCDData instance.
        profile_model (object): An astropy.modeling.Model instance. Describes
            the spatial profile of the target.
        nsigma (float): Number of sigmas. Used to calculate the width of the
            target zone to be masked.
        separation (float): Additional offset that adds to the width of the
            target zone.

    Returns:
        A ccdproc.CCDData instance with the spectrum masked.

    """
    background_ccd = ccd.copy()
    spatial_length, dispersion_length = background_ccd.data.shape
    target_profiles = []
    if 'CompoundModel' in profile_model.__class__.name:
        log_spec.debug(profile_model.submodel_names)
        for m in range(len(profile_model.submodel_names)):
            submodel_name = profile_model.submodel_names[m]

            target_profiles.append(profile_model[submodel_name])
    else:
        target_profiles.append(profile_model)

    for target in target_profiles:
        target_mean = target.mean.value
        target_stddev = target.stddev.value

        data_low_lim = np.int(np.max(
            [0, target_mean - (nsigma / 2. + separation) * target_stddev]))

        data_high_lim = np.int(np.min([spatial_length, int(
            target_mean + (nsigma / 2. + separation) * target_stddev)]))

        background_ccd.data[data_low_lim:data_high_lim, :] = 0

    if False:
        plt.title('Background Image')
        plt.imshow(background_ccd.data, clim=(0, 50))
        plt.show()

    return background_ccd