Source code for jdaviz.configs.default.plugins.collapse.collapse

from astropy import units as u
from glue.core.message import (DataCollectionAddMessage,
                               DataCollectionDeleteMessage)
from glue.core import Data
from glue.core.link_helpers import LinkSame
from spectral_cube import SpectralCube
from specutils import SpectralRegion
from traitlets import List, Unicode, Int, Any, observe
from regions import RectanglePixelRegion

from jdaviz.core.events import SnackbarMessage
from jdaviz.core.registries import tray_registry
from jdaviz.core.template_mixin import TemplateMixin
from jdaviz.utils import load_template

__all__ = ['Collapse']


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


# Mapping of pixel axes before and after collapse, as a function of selected axis
AXES_MAPPING = [((1, 2), (0, 1)), ((0, 2), (0, 1)), ((0, 1), (0, 1))]


[docs]@tray_registry('g-collapse', label="Collapse") class Collapse(TemplateMixin): template = load_template("collapse.vue", __file__).tag(sync=True) data_items = List([]).tag(sync=True) selected_data_item = Unicode().tag(sync=True) axes = List([]).tag(sync=True) selected_axis = Int(0).tag(sync=True) funcs = List(['Mean', 'Median', 'Min', 'Max', 'Sum']).tag(sync=True) selected_func = Unicode('Mean').tag(sync=True) spectral_min = Any().tag(sync=True) spectral_max = Any().tag(sync=True) spectral_unit = Unicode().tag(sync=True) spectral_subset_items = List(["None"]).tag(sync=True) selected_subset = Unicode("None").tag(sync=True) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.hub.subscribe(self, DataCollectionAddMessage, handler=self._on_data_updated) self.hub.subscribe(self, DataCollectionDeleteMessage, handler=self._on_data_updated) self._selected_data = None self._label_counter = 0 def _on_data_updated(self, msg): self.data_items = [x.label for x in self.data_collection] # Default to selecting the first loaded cube if self._selected_data is None: for i in range(len(self.data_items)): try: self.selected_data_item = self.data_items[i] except (ValueError, TypeError): continue @observe('selected_data_item') def _on_data_item_selected(self, event): self._selected_data = next((x for x in self.data_collection if x.label == event['new'])) # Also set the spectral min and max to default to the full range cube = self._selected_data.get_object(cls=SpectralCube) self.spectral_min = cube.spectral_axis[0].value self.spectral_max = cube.spectral_axis[-1].value self.spectral_unit = str(cube.spectral_axis.unit) self.axes = list(range(len(self._selected_data.shape))) @observe("selected_subset") def _on_subset_selected(self, event): # If "None" selected, reset based on bounds of selected data self._selected_subset = self.selected_subset if self._selected_subset == "None": cube = self._selected_data.get_object(cls=SpectralCube) self.spectral_min = cube.spectral_axis[0].value self.spectral_max = cube.spectral_axis[-1].value else: spec_sub = self._spectral_subsets[self._selected_subset] unit = u.Unit(self.spectral_unit) spec_reg = SpectralRegion.from_center(spec_sub.center.x * unit, spec_sub.width * unit) self.spectral_min = spec_reg.lower.value self.spectral_max = spec_reg.upper.value
[docs] def vue_list_subsets(self, event): """Populate the spectral subset selection dropdown""" temp_subsets = self.app.get_subsets_from_viewer("spectrum-viewer") temp_list = ["None"] temp_dict = {} # Attempt to filter out spatial subsets for key, region in temp_subsets.items(): if type(region) == RectanglePixelRegion: temp_dict[key] = region temp_list.append(key) self._spectral_subsets = temp_dict self.spectral_subset_items = temp_list
[docs] def vue_collapse(self, *args, **kwargs): try: spec = self._selected_data.get_object(cls=SpectralCube) except AttributeError: snackbar_message = SnackbarMessage( f"Unable to perform collapse over selected data.", color="error", sender=self) self.hub.broadcast(snackbar_message) return # If collapsing over the spectral axis, cut out the desired spectral # region. Defaults to the entire spectrum. if self.selected_axis == 0: spec_min = float(self.spectral_min) * u.Unit(self.spectral_unit) spec_max = float(self.spectral_max) * u.Unit(self.spectral_unit) spec = spec.spectral_slab(spec_min, spec_max) collapsed_spec = getattr(spec, self.selected_func.lower())( axis=self.selected_axis) data = Data(coords=collapsed_spec.wcs) data['flux'] = collapsed_spec.filled_data[...] data.get_component('flux').units = str(collapsed_spec.unit) data.meta.update(collapsed_spec.meta) self._label_counter += 1 label = f"Collapsed {self._label_counter} {self._selected_data.label}" self.data_collection[label] = data # 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. Here which axes are linked to which depends on # the selected axis. (i1, i2), (i1c, i2c) = AXES_MAPPING[self.selected_axis] self.data_collection.add_link(LinkSame(self._selected_data.pixel_component_ids[i1], self.data_collection[label].pixel_component_ids[i1c])) self.data_collection.add_link(LinkSame(self._selected_data.pixel_component_ids[i2], self.data_collection[label].pixel_component_ids[i2c])) snackbar_message = SnackbarMessage( f"Data set '{self._selected_data.label}' collapsed successfully.", color="success", sender=self) self.hub.broadcast(snackbar_message)