Exporting Data from Cubeviz

After data have been manipulated or analyzed, it is possible to export those data currently back into your Jupyter notebook.

Spatial Regions

See also

Export Spatial Regions: Documentation on how to export spatial regions.

Since Specviz can be accessed from Cubeviz, the following line of code can be used to extract the spectrum of a spatial subset named “Subset 1”:

subset1_spec1d = cubeviz.specviz.get_spectra("Subset 1")

An example without accessing Specviz:

subset1_spec1d = cubeviz.app.get_data_from_viewer("flux-viewer", data_label="Subset 1")

To get all subsets from a viewer:

subset1_spec1d = cubeviz.app.get_subsets_from_viewer("spectrum-viewer")

To access the spatial region itself:

dc = cubeviz.app.data_collection
subset1 = dc.subset_groups[0]

# Circular ROI
x, y = subset1.subset_state.roi.get_center()
radius = subset1.subset_state.roi.radius

# Rectangular ROI
rectangular_roi = subset1.subset_state.roi
rectangular_roi.xmin, rectangular_roi.xmax, rectangular_roi.ymin, rectangular_roi.ymax

The syntax to output a subset as an astropy region looks like:

dc.subset_groups[0].subsets[0].data.get_selection_definition(subset_id="Subset 1", format='astropy-regions')  # noqa

Where the first 0 corresponds to what number subset it is and the second 0 corresponds to which data the subset is being applied to (flux, variance, data quality, etc.). If you have multiple subsets present in the application, you need to fill out the subset_id parameter.

1D Spectra and Spectral Regions

2D images and 3D Data Cubes

2D images and 3D data cubes can be extracted from their respective viewers. The viewer options in the Cubeviz configuration are flux-viewer, uncert-viewer, and mask-viewer. For example, to list the data available in a particular viewer::

mydata = cubeviz.app.get_data_from_viewer("flux-viewer")

To extract the data you want (replace “data_name” with the name of your data):

mydata = cubeviz.app.get_data_from_viewer("uncert-viewer", "data_name")

The data is returned as a glue-jupyter object. To convert to a numpy array:

mydata_flux = mydata["flux"]

To retrieve the data cube as a specutils.Spectrum1D object, you can do the following:

from specutils import Spectrum1D
mydata.get_object(cls=Spectrum1D, statistic=None)

Alternatively, you can wrap this all into a single command:

mydata = cubeviz.app.get_data_from_viewer("uncert-viewer", "data_name")

Data can also be accessed directly from data_collection using the following code:

cubeviz.app.data_collection[0]

Which is returned as a Data object. The DataCollection object can be indexed to return all available data (i.e., not just using 0 like in the previous example).

Model Fits

For a list of model labels:

models = cubeviz.get_models()
models

Once you know the model labels, to get a specific model:

mymodel = cubeviz.get_models(model_label="ModelLabel", x=10)

To extract all of the model parameters:

myparams = cubeviz.get_model_parameters(model_label="ModelLabel", x=x, y=y)
myparams

where the model_label parameter identifies which model should be returned and the x and y parameters identify specifically which spaxel fits are to be returned, for models applied to every spaxel using the Apply to Cube button. Leaving x or y as None will mean that the models fit to every spaxel across that axis will be returned.