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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def astra_data(astra_geom, datatype, data=None, ndim=2, allow_copy=False):
 """Create an ASTRA data object. Parameters astra_geom : dict ASTRA geometry object for the data creator, must correspond to the given ``datatype``. datatype : {'volume', 'projection'} Type of the data container. data : `DiscreteLpElement` or `numpy.ndarray`, optional Data for the initialization of the data object. If ``None``, an ASTRA data object filled with zeros is created. ndim : {2, 3}, optional Dimension of the data. If ``data`` is provided, this parameter has no effect. allow_copy : `bool`, optional If ``True``, allow copying of ``data``. This means that anything written by ASTRA to the returned object will not be written to ``data``. Returns ------- id : int Handle for the new ASTRA internal data object. """

    if data is not None:
        if isinstance(data, (DiscreteLpElement, np.ndarray)):
            ndim = data.ndim
        else:
            raise TypeError('`data` {!r} is neither DiscreteLpElement '
                            'instance nor a `numpy.ndarray`'.format(data))
    else:
        ndim = int(ndim)

    if datatype == 'volume':
        astra_dtype_str = '-vol'
    elif datatype == 'projection':
        astra_dtype_str = '-sino'
    else:
        raise ValueError('`datatype` {!r} not understood'.format(datatype))

    # Get the functions from the correct module
    if ndim == 2:
        link = astra.data2d.link
        create = astra.data2d.create
    elif ndim == 3:
        link = astra.data3d.link
        create = astra.data3d.create
    else:
        raise ValueError('{}-dimensional data not supported'
                         ''.format(ndim))

    # ASTRA checks if data is c-contiguous and aligned
    if data is not None:
        if allow_copy:
            data_array = np.asarray(data, dtype='float32', order='C')
            return link(astra_dtype_str, astra_geom, data_array)
        else:
            if isinstance(data, np.ndarray):
                return link(astra_dtype_str, astra_geom, data)
            elif data.tensor.impl == 'numpy':
                return link(astra_dtype_str, astra_geom, data.asarray())
            else:
                # Something else than NumPy data representation
                raise NotImplementedError('ASTRA supports data wrapping only '
                                          'for `numpy.ndarray` instances, got '
                                          '{!r}'.format(data))
    else:
        return create(astra_dtype_str, astra_geom)