Source code for jdaviz.configs.cubeviz.plugins.moment_maps.moment_maps

import os
from pathlib import Path

from astropy import units as u
from astropy.nddata import CCDData

from traitlets import Unicode, Bool, observe
from specutils import Spectrum1D, manipulation, analysis

from jdaviz.core.custom_traitlets import IntHandleEmpty
from jdaviz.core.events import SnackbarMessage
from jdaviz.core.registries import tray_registry
from jdaviz.core.template_mixin import (PluginTemplateMixin,
                                        DatasetSelectMixin,
                                        SpectralSubsetSelectMixin,
                                        AddResultsMixin)
from jdaviz.core.user_api import PluginUserApi

__all__ = ['MomentMap']


spaxel = u.def_unit('spaxel', 1 * u.Unit(""))
u.add_enabled_units([spaxel])


[docs]@tray_registry('cubeviz-moment-maps', label="Moment Maps", viewer_requirements=['spectrum', 'image']) class MomentMap(PluginTemplateMixin, DatasetSelectMixin, SpectralSubsetSelectMixin, AddResultsMixin): """ See the :ref:`Moment Maps Plugin Documentation <moment-maps>` for more details. Only the following attributes and methods are available through the :ref:`public plugin API <plugin-apis>`: * :meth:`~jdaviz.core.template_mixin.PluginTemplateMixin.show` * :meth:`~jdaviz.core.template_mixin.PluginTemplateMixin.open_in_tray` * ``dataset`` (:class:`~jdaviz.core.template_mixin.DatasetSelect`): Dataset to use for computing line statistics. * ``spectral_subset`` (:class:`~jdaviz.core.template_mixin.SubsetSelect`): Subset to use for the line, or ``Entire Spectrum``. * ``n_moment`` * ``add_results`` (:class:`~jdaviz.core.template_mixin.AddResults`) * :meth:`calculate_moment` """ template_file = __file__, "moment_maps.vue" n_moment = IntHandleEmpty(0).tag(sync=True) filename = Unicode().tag(sync=True) moment_available = Bool(False).tag(sync=True) overwrite_warn = Bool(False).tag(sync=True) def __init__(self, *args, **kwargs): self._default_spectrum_viewer_reference_name = kwargs.get( "spectrum_viewer_reference_name", "spectrum-viewer" ) self._default_image_viewer_reference_name = kwargs.get( "image_viewer_reference_name", "image-viewer" ) super().__init__(*args, **kwargs) self.moment = None self.dataset.add_filter('is_image') self.add_results.viewer.filters = ['is_image_viewer'] @property def user_api(self): # NOTE: leaving save_as_fits out for now - we may want a more general API to do that # accross all plugins at some point return PluginUserApi(self, expose=('dataset', 'spectral_subset', 'n_moment', 'add_results', 'calculate_moment')) @observe("dataset_selected", "dataset_items", "n_moment") def _set_default_results_label(self, event={}): label_comps = [] if hasattr(self, 'dataset') and len(self.dataset.labels) > 1: label_comps += [self.dataset_selected] label_comps += [f"moment {self.n_moment}"] self.results_label_default = " ".join(label_comps)
[docs] def calculate_moment(self, add_data=True): """ Calculate the moment map Parameters ---------- add_data : bool Whether to add the resulting data object to the app according to ``add_results``. """ # Retrieve the data cube and slice out desired region, if specified cube = self.dataset.get_object(cls=Spectrum1D, statistic=None) spec_min, spec_max = self.spectral_subset.selected_min_max(cube) slab = manipulation.spectral_slab(cube, spec_min, spec_max) # Calculate the moment and convert to CCDData to add to the viewers try: n_moment = int(self.n_moment) if n_moment < 0: raise ValueError("Moment must be a positive integer") except ValueError: raise ValueError("Moment must be a positive integer") # Need transpose to align JWST mirror shape. Not sure why. # TODO: WCS can be grabbed from cube.wcs[:, :, 0] but CCDData will not take it. # But if we use NDData, glue-astronomy translator fails. self.moment = CCDData(analysis.moment(slab, order=n_moment).T) fname_label = self.dataset_selected.replace("[", "_").replace("]", "") self.filename = f"moment{n_moment}_{fname_label}.fits" if add_data: self.add_results.add_results_from_plugin(self.moment) msg = SnackbarMessage("{} added to data collection".format(self.results_label), sender=self, color="success") self.hub.broadcast(msg) self.moment_available = True return self.moment
[docs] def vue_calculate_moment(self, *args): self.calculate_moment(add_data=True)
[docs] def vue_save_as_fits(self, *args): self._write_moment_to_fits()
[docs] def vue_overwrite_fits(self, *args): """Attempt to force writing the moment map if the user confirms the desire to overwrite.""" self.overwrite_warn = False self._write_moment_to_fits(overwrite=True)
def _write_moment_to_fits(self, overwrite=False, *args): if self.moment is None or not self.filename: # pragma: no cover return path = Path(self.filename).resolve() if path.exists(): if overwrite: # Try to delete the file path.unlink() if path.exists(): # Warn the user if the file still exists raise FileExistsError(f"Unable to delete {path}. Check user permissions.") else: self.overwrite_warn = True return self.moment.write(str(path)) # Let the user know where we saved the file. self.hub.broadcast(SnackbarMessage( f"Moment map saved to {os.path.abspath(self.filename)}", sender=self, color="success"))