How to use the plonk._logging.logger.error function in plonk

Returns
    -------
    Snap
        The Snap object.
    """
    if data_source not in _data_sources:
        raise ValueError(
            f'Unknown data source. Available data sources:\n{_data_sources}'
        )

    if data_source == 'Phantom':
        try:
            return read_phantom(filename)
        except FileNotFoundError as e:
            logger.error(f'File not found: {filename}')
            raise e
        except OSError as e:
            # Catch errors raised by h5py due to file corruption
            logger.error(f'File likely corrupted: {filename}')
            raise e
    raise RuntimeError('Cannot load snap')

----------
    interpolated_data_cartesian
        The interpolated data on a Cartesian grid.
    extent_cartesian
        The extent in Cartesian space as (xmin, xmax, ymin, ymax). It
        must be square.

    Returns
    -------
    interpolated_data_polar
        The interpolated data on a polar grid (R, phi).
    extent_polar
        The extent on a polar grid (0, Rmax, 0, 2π).
    """
    if transform is None:
        logger.error(
            'cartesian_to_polar requires skimage (scikit-image) which is unavailable\n'
            'try pip install skimage --or-- conda install skimage'
        )
    data, extent = interpolated_data_cartesian, extent_cartesian

    if not np.allclose(extent[1] - extent[0], extent[3] - extent[2]):
        raise ValueError('Bad polar plot: x and y have different scales')

    number_of_pixels = data.shape
    radius_pix = 0.5 * data.shape[0]

    data = transform.warp_polar(data, radius=radius_pix)

    radius = 0.5 * (extent[1] - extent[0])
    extent_polar = (0, radius, 0, 2 * np.pi)

array: ndarray = self.snap[array_name]
            if array.ndim == 1:
                self._profiles[name] = self.particles_to_binned_quantity(
                    aggregation, array
                )
                return self._profiles[name]
            raise ValueError(
                'Requested profile has array dimension > 1.\nTo access x-, y-, or '
                'z-components, or magnitude of vector quantities,\ntry, for '
                'example, prof["velocity_x"] or prof["momentum_magnitude"].\nTo '
                'access dust profiles, try, for example, prof["stopping_time_001"] '
                'or\nprof["dust_mass_sum"].'
            )
        except ValueError:
            if self.snap._extra_quantities:
                logger.error('Profile unavailable.')
            else:
                logger.error(
                    'Profile unavailable. Try calling extra_quantities method on Snap.'
                )

self._profiles[name] = self.particles_to_binned_quantity(
                    aggregation, array
                )
                return self._profiles[name]
            raise ValueError(
                'Requested profile has array dimension > 1.\nTo access x-, y-, or '
                'z-components, or magnitude of vector quantities,\ntry, for '
                'example, prof["velocity_x"] or prof["momentum_magnitude"].\nTo '
                'access dust profiles, try, for example, prof["stopping_time_001"] '
                'or\nprof["dust_mass_sum"].'
            )
        except ValueError:
            if self.snap._extra_quantities:
                logger.error('Profile unavailable.')
            else:
                logger.error(
                    'Profile unavailable. Try calling extra_quantities method on Snap.'
                )

| (particle_type == istar)
        | (particle_type == idarkmatter)
        | (particle_type == ibulge)
    ] = 0
    sub_type[particle_type == iboundary] = 0
    idust = _get_dataset('idust', 'header')(snap)
    ndustlarge = _get_dataset('ndustlarge', 'header')(snap)
    for idx in range(idust, idust + ndustlarge):
        sub_type[particle_type == idx] = idx - idust + 1
    try:
        idustbound = _get_dataset('idustbound', 'header')(snap)
        for idx in range(idustbound, idustbound + ndustlarge):
            sub_type[particle_type == idx] = idx - idustbound + 1
    except KeyError:
        if np.any(particle_type >= idust + ndustlarge):
            logger.error('Cannot determine dust boundary particles')
    return sub_type

# Dark matter |                                     5 | 5
    # Bulge       |                                     6 | 6
    idust = _get_dataset('idust', 'header')(snap)
    ndustlarge = _get_dataset('ndustlarge', 'header')(snap)
    particle_type = np.abs(_get_dataset('itype', 'particles')(snap))
    particle_type[
        (particle_type >= idust) & (particle_type < idust + ndustlarge)
    ] = snap.particle_type['dust']
    try:
        idustbound = _get_dataset('idustbound', 'header')(snap)
        particle_type[
            (particle_type >= idustbound) & (particle_type < idustbound + ndustlarge)
        ] = snap.particle_type['boundary']
    except KeyError:
        if np.any(particle_type >= idust + ndustlarge):
            logger.error('Cannot determine dust boundary particles')
    return particle_type

The Snap object.
    """
    if data_source not in _data_sources:
        raise ValueError(
            f'Unknown data source. Available data sources:\n{_data_sources}'
        )

    if data_source == 'Phantom':
        try:
            return read_phantom(filename)
        except FileNotFoundError as e:
            logger.error(f'File not found: {filename}')
            raise e
        except OSError as e:
            # Catch errors raised by h5py due to file corruption
            logger.error(f'File likely corrupted: {filename}')
            raise e
    raise RuntimeError('Cannot load snap')