Exporting Data From Specviz

1D Spectra

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

specviz.get_spectra()

which yields a either a single specutils.Spectrum1D object or a dictionary of specutils.Spectrum1D (if there are multiple displayed spectra) that you can manipulate however you wish. You can then load the modified spectrum back into the notebook via the API described in Importing data via the API.

Alternatively, if you want more control over Specviz, you can access it the via the get_data method of the Specviz helper class. This method always returns a single spectrum; if there are multiple spectra loaded you must supply a label to the data_label argument. For example:

specviz.get_data(data_label='Spectrum 1')

To extract a spectrum with a spectral subset applied:

specviz.get_data(spectral_subset='Subset 1')

In this case, the returned specutils.Spectrum1D object will have a mask attribute, where True corresponds to the region outside the selected subset (i.e., the region that has been masked out). You could load back in a copy of the spectrum containing only your subset by running:

spec = specviz.get_data(spectral_subset='Subset 1')
subset_spec = Spectrum1D(flux=spec.flux[~spec.mask],
                         spectral_axis=spec.spectral_axis[~spec.mask])
specviz.load_data(subset_spec)

See also

Export From Plugins

Calculations (i.e., not spectroscopic data) from the plugins can also be exported back into the Jupyter notebook in some cases.

Spectral Regions

If you have spectral region subsets, you can extract the parameters of these subsets as a specutils spectral region. For a list of available spectral regions to extract, you can type:

regions = specviz.get_spectral_regions()
regions

To extract the spectral region you want:

myregion = regions["Subset 2"]

See also

Export From Plugins

Spectral region subsets can also be exported to disk as an ECSV file.

Model Fits

For a list of model labels:

models = specviz.get_models()
models

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

mymodel = specviz.get_models(model_label="ModelLabel")

To extract all of the model parameters:

myparams = specviz.get_model_parameters(model_label="ModelLabel")
myparams

where the model_label parameter identifies which model should be returned.

Alternatively, the table of logged parameter values in the model fitting plugin can be exported to an astropy table by calling export_table() (see Accessing Plugin APIs):

model_fitting = specviz.plugins['Model Fitting']
model_fitting.export_table()

Markers Table

All mouseover information in the markers plugin can be exported to an astropy table by calling export_table() (see Accessing Plugin APIs).