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Loading Data into Specviz

By design, Specviz only supports data that can be parsed as :class:`~specutils.Spectrum1D` objects, as that allows the Python-level interface and parsing tools to be defined in specutils instead of being duplicated in Jdaviz. :class:`~specutils.Spectrum1D` objects are very flexible in their capabilities, however, and hence should address most astronomical spectrum use cases.

.. seealso::

    `Reading from a File <https://specutils.readthedocs.io/en/stable/spectrum1d.html#reading-from-a-file>`_
        Specutils documentation on loading data as :class:`~specutils.Spectrum1D` objects.

There are two primary ways in which a user can load their data into the Specviz application: through the UI, or via the Python API (for most user cases this means inside a notebook). These are separately detailed below.

Importing data through the GUI

The first way that users can load their data into the Specviz application is by using the :guilabel:`Import Data` button in the application's user interface.

img/specviz_viewer.png

This process is fairly straightforward, users need only click on the :guilabel:`Import Data` button:

img/import_data_1.png

and choose a file that can be parsed as a :class:`~specutils.Spectrum1D` in the text field:

img/import_data_2.png

After clicking :guilabel:`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 :guilabel:`Data` tab of each viewer's menu.

img/import_data_3.png

Here, users can select the loaded data set to be visualized in the viewer.

img/data_selected_1.png

Loading data via the API

Alternatively, if users are working in a coding environment like a Jupyter notebook, they have access to the :class:`~jdaviz.configs.specviz.helper.Specviz` helper class API. Using this API, users can load data into the application through code. Below is an example of importing the :class:`~jdaviz.configs.specviz.helper.Specviz` helper class, creating a :class:`~specutils.Spectrum1D` object from a data file via the specutils.Spectrum1D.read method:

>>> from specutils import Spectrum1D
>>> spec1d = Spectrum1D.read("/path/to/data/file") #doctest: +SKIP
>>> specviz = Specviz()  # doctest: +SKIP
>>> specviz.load_spectrum(spec1d)  # doctest: +SKIP

This method works well for data files that specutils understands. However, if you are using your own data file or in-memory data, you can instead create a :class:`~specutils.Spectrum1D` object directly. In this example that is done using randomly generated data, and then that :class:`~specutils.Spectrum1D` object is loaded into the Specviz application:

>>> from jdaviz import Specviz
>>> import numpy as np
>>> import astropy.units as u
>>> from specutils import Spectrum1D
>>> flux = np.random.randn(200)*u.Jy
>>> wavelength = np.arange(5100, 5300)*u.AA
>>> spec1d = Spectrum1D(spectral_axis=wavelength, flux=flux)
>>> specviz = Specviz()
>>> specviz.load_spectrum(spec1d)  # doctest: +IGNORE_OUTPUT

For more information about using the Specutils package, please see the Specutils documentation.