import os
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)
__all__ = ['MomentMap']
spaxel = u.def_unit('spaxel', 1 * u.Unit(""))
u.add_enabled_units([spaxel])
[docs]@tray_registry('cubeviz-moment-maps', label="Moment Maps")
class MomentMap(PluginTemplateMixin, DatasetSelectMixin, SpectralSubsetSelectMixin,
AddResultsMixin):
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)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.moment = None
self.dataset.add_filter('is_image')
self.add_results.viewer.filters = ['is_image_viewer']
@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 vue_calculate_moment(self, *args):
# 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.
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"
self.add_results.add_results_from_plugin(self.moment)
self.moment_available = True
msg = SnackbarMessage("{} added to data collection".format(self.results_label),
sender=self, color="success")
self.hub.broadcast(msg)
[docs] def vue_save_as_fits(self, *args):
if self.moment is None or not self.filename: # pragma: no cover
return
self.moment.write(self.filename)
# 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"))