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# Source code for astropy.nddata.mixins.ndslicing

    # Licensed under a 3-clause BSD style license - see LICENSE.rst
    # This module implements the Slicing mixin to the NDData class.

    from astropy import log
    from astropy.wcs.wcsapi import (
        BaseHighLevelWCS,
        BaseLowLevelWCS,
        HighLevelWCSWrapper,
        SlicedLowLevelWCS,
    )

    __all__ = ["NDSlicingMixin"]

    class NDSlicingMixin:
        """Mixin to provide slicing on objects using the `NDData`
        interface.

        The ``data``, ``mask``, ``uncertainty`` and ``wcs`` will be sliced, if
        set and sliceable. The ``unit`` and ``meta`` will be untouched. The return
        will be a reference and not a copy, if possible.

        Examples
        --------
        Using this Mixin with `~astropy.nddata.NDData`:

            >>> from astropy.nddata import NDData, NDSlicingMixin
            >>> class NDDataSliceable(NDSlicingMixin, NDData):
            ...     pass

        Slicing an instance containing data::

            >>> nd = NDDataSliceable([1,2,3,4,5])
            >>> nd[1:3]
            NDDataSliceable([2, 3])

        Also the other attributes are sliced for example the ``mask``::

            >>> import numpy as np
            >>> mask = np.array([True, False, True, True, False])
            >>> nd2 = NDDataSliceable(nd, mask=mask)
            >>> nd2slc = nd2[1:3]
            >>> nd2slc[nd2slc.mask]
            NDDataSliceable([3])

        Be aware that changing values of the sliced instance will change the values
        of the original::

            >>> nd3 = nd2[1:3]
            >>> nd3.data[0] = 100
            >>> nd2
            NDDataSliceable([  1, 100,   3,   4,   5])

        See also
        --------
        NDDataRef
        NDDataArray
        """

        def __getitem__(self, item):
            # Abort slicing if the data is a single scalar.
            if self.data.shape == ():
                raise TypeError("scalars cannot be sliced.")

            # Let the other methods handle slicing.
            kwargs = self._slice(item)
            return self.__class__(**kwargs)

        def _slice(self, item):
            """Collects the sliced attributes and passes them back as `dict`.

            It passes uncertainty, mask and wcs to their appropriate ``_slice_*``
            method, while ``meta`` and ``unit`` are simply taken from the original.
            The data is assumed to be sliceable and is sliced directly.

            When possible the return should *not* be a copy of the data but a
            reference.

            Parameters
            ----------
            item : slice
                The slice passed to ``__getitem__``.

            Returns
            -------
            dict :
                Containing all the attributes after slicing - ready to
                use them to create ``self.__class__.__init__(**kwargs)`` in
                ``__getitem__``.
            """
            kwargs = {}
            kwargs["data"] = self.data[item]
            # Try to slice some attributes
            kwargs["uncertainty"] = self._slice_uncertainty(item)
            kwargs["mask"] = self._slice_mask(item)
            kwargs["wcs"] = self._slice_wcs(item)
            # Attributes which are copied and not intended to be sliced
            kwargs["unit"] = self.unit
            kwargs["meta"] = self.meta
            return kwargs

        def _slice_uncertainty(self, item):
            if self.uncertainty is None:
                return None
            try:
                return self.uncertainty[item]
            except TypeError:
                # Catching TypeError in case the object has no __getitem__ method.
                # But let IndexError raise.
                log.info("uncertainty cannot be sliced.")
            return self.uncertainty

        def _slice_mask(self, item):
            if self.mask is None:
                return None
            try:
                return self.mask[item]
            except TypeError:
                log.info("mask cannot be sliced.")
            return self.mask

        def _slice_wcs(self, item):
            if self.wcs is None:
                return None

            try:
                llwcs = SlicedLowLevelWCS(self.wcs.low_level_wcs, item)
                return HighLevelWCSWrapper(llwcs)
            except Exception as err:
                self._handle_wcs_slicing_error(err, item)

        # Implement this in a method to allow subclasses to customise the error.
        def _handle_wcs_slicing_error(self, err, item):
            raise ValueError(
                f"Slicing the WCS object with the slice '{item}' "
                "failed, if you want to slice the NDData object without the WCS, you "
                "can remove by setting `NDData.wcs = None` and then retry."
            ) from err