import warnings
from glue.core import Data
from glue.core.link_helpers import LinkSame
from specutils import Spectrum1D
from specutils.manipulation import spectral_slab
from traitlets import List, Unicode, observe
from jdaviz.core.events import SnackbarMessage
from jdaviz.core.registries import tray_registry
from jdaviz.core.template_mixin import (PluginTemplateMixin,
DatasetSelectMixin,
SpectralSubsetSelectMixin,
AddResultsMixin)
__all__ = ['Collapse']
[docs]@tray_registry('g-collapse', label="Collapse")
class Collapse(PluginTemplateMixin, DatasetSelectMixin, SpectralSubsetSelectMixin, AddResultsMixin):
template_file = __file__, "collapse.vue"
funcs = List(['Mean', 'Median', 'Min', 'Max', 'Sum']).tag(sync=True)
selected_func = Unicode('Sum').tag(sync=True)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._label_counter = 0
self.dataset.add_filter('is_image')
self.add_results.viewer.filters = ['is_image_viewer']
@observe("dataset_selected", "dataset_items")
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 += ["collapsed"]
self.results_label_default = " ".join(label_comps)
[docs] def vue_collapse(self, *args, **kwargs):
# Collapsing over the spectral axis. Cut out the desired spectral
# region. Defaults to the entire spectrum.
cube = self.dataset.get_object(cls=Spectrum1D, statistic=None)
spec_min, spec_max = self.spectral_subset.selected_min_max(cube)
with warnings.catch_warnings():
warnings.filterwarnings('ignore', message='No observer defined on WCS')
spec = spectral_slab(cube, spec_min, spec_max)
# Spatial-spatial image only.
collapsed_spec = spec.collapse(self.selected_func.lower(), axis=-1).T # Quantity
data = Data()
data['flux'] = collapsed_spec.value
data.get_component('flux').units = str(collapsed_spec.unit)
self.add_results.add_results_from_plugin(data)
self._link_collapse_data()
snackbar_message = SnackbarMessage(
f"Data set '{self.dataset_selected}' collapsed successfully.",
color="success",
sender=self)
self.hub.broadcast(snackbar_message)
def _link_collapse_data(self):
"""
Link the new dataset pixel-wise to the original dataset. In general
direct pixel to pixel links are the most efficient and should be
used in cases like this where we know there is a 1-to-1 mapping of
pixel coordinates.
"""
new_len = len(self.app.data_collection)
pc_new = self.app.data_collection[-1].pixel_component_ids
# Link to the first dataset with compatible coordinates
for i in range(new_len - 1):
pc_old = self.app.data_collection[i].pixel_component_ids
# If data_collection[i] is also from the collapse plugin
if self.app.data_collection[i].meta.get("Plugin", None) == self.__class__.__name__:
links = [LinkSame(pc_old[0], pc_new[0]),
LinkSame(pc_old[1], pc_new[1])]
else:
links = [LinkSame(pc_old[0], pc_new[1]),
LinkSame(pc_old[1], pc_new[0])]
self.app.data_collection.add_link(links)
break