Importing Data Into Specviz#

Note

This is the config-specific version of documentation and is deprecated. See the general documentation for the most up-to-date information.

By design, Specviz only supports data that can be parsed as Spectrum objects, as that allows the Python-level interface and parsing tools to be defined in specutils instead of being duplicated in Jdaviz. Spectrum objects are very flexible in their capabilities, however, and hence should address most astronomical spectrum use cases. If you are creating your own data products, please read the page Creating Jdaviz-readable Products.

Importing data through the Command Line#

You can load your data into the Specviz application through the command line. Specifying a data file is optional, and multiple data files may be provided:

jdaviz --layout=specviz /my/directory/spectrum1.fits /my/directory/spectrum2.fits

Importing data through the GUI#

You can load your data into the Specviz application by clicking the Import Data button at the top left of the application’s user interface. This opens a dialogue where the user can select a file that can be parsed as a Spectrum.

After clicking Import, the data file will be parsed and loaded into the application. A notification will appear to let users know if the data import was successful. Afterward, the new data set can be found in the Data tab of each viewer’s options menu as described in Selecting a Data Set.

Importing data via the API#

Alternatively, users who work in a coding environment like a Jupyter notebook can access the Specviz helper class API. Using this API, users can load data using the load() method, specifying the format explicitly:

specviz.load(data, format='1D Spectrum')

Available formats include:

'1D Spectrum' - For individual 1D Spectrum objects or files containing a single spectrum
'1D Spectrum List' - For SpectrumList objects or files containing multiple spectra
'1D Spectrum Concatenated' - For combining multiple spectra into a single spectrum

It is helpful to click the API Hints button in the top right to discover available options and parameters to customize the loading process.

For more information on loading data, see Importing Data.

FITS Files#

The example below loads a FITS file into Specviz:

from specutils import Spectrum
spec1d = Spectrum.read("/path/to/data/file")
specviz = Specviz()
specviz.load(spec1d, format="1D Spectrum", data_label="my_spec")
specviz.show()

You can also pass the path to a file that Spectrum understands directly to the load() method:

specviz.load("path/to/data/file", format="1D Spectrum")

Creating Your Own Array#

You can create your own array to load into Specviz:

import numpy as np
import astropy.units as u
from specutils import Spectrum
from jdaviz import Specviz

flux = np.random.randn(200) * u.Jy
wavelength = np.arange(5100, 5300) * u.AA
spec1d = Spectrum(spectral_axis=wavelength, flux=flux)
specviz = Specviz()
specviz.load(spec1d, format="1D Spectrum", data_label="my_spec")
specviz.show()

JWST datamodels#

If you have a stdatamodels.datamodels object, you can load it into Specviz as follows:

from specutils import Spectrum
from jdaviz import Specviz

# mydatamodel is a jwst.datamodels.MultiSpecModel object
a = mydatamodel.spec[0]
flux = a.spec_table['FLUX']
wave = a.spec_table['WAVELENGTH']

spec1d = Spectrum(flux=flux, spectral_axis=wave)
specviz = Specviz()
specviz.load(spec1d, format="1D Spectrum", data_label="MultiSpecModel")
specviz.show()

There is no plan to natively load such objects until datamodels is separated from the jwst pipeline package.

Importing a SpectrumList#

The load() also accepts a SpectrumList object, in which case it will both load the individual Spectrum objects in the list and additionally attempt to stitch together the spectra into a single data object so that they can be manipulated and analyzed in the application as a single entity:

from specutils import SpectrumList
spec_list = SpectrumList([spec1d_1, spec1d_2])
specviz.load(spec_list, format="1D Spectrum List")
specviz.show()

In the screenshot below, the combined spectrum is plotted in gray, and one of the single component spectra are also selected and plotted in red. Note that the “stitching” algorithm to combine the spectra is a simple concatenation of data, so in areas where the wavelength ranges of component spectra overlap you may see the line plot jumping between points of the two spectra, as at the beginning and end of the red region in the screenshot below:

This functionality is also available in limited instances by providing a directory path to the load() method. Note that the read method of SpectrumList is only set up to handle directory input in limited cases, for example JWST MIRI MRS data, and will throw an error in other cases. In cases that it does work, only files in the directory level specified will be read, with no recursion into deeper folders.

The load() method also takes an optional keyword argument concat_by_file. When set to True, the spectra loaded in the SpectrumList will be concatenated together into one combined spectrum per loaded file, which may be useful for MIRI observations, for example.