Importing Data into Mosviz

Mosviz provides two different ways to load data: Auto-recognition directory loading or manual loading:

Automatic Directory Loading

Mosviz provides instrument-specific directory parsers for select instruments. At this time, Mosviz supports automatic parsing for the following instruments:

JWST NIRSpec
JWST NIRISS

In a Jupyter context (notebook or Lab), you can specify the instrument with a directory as such:

from jdaviz import Mosviz
mosviz = Mosviz()
mosviz.load_data(directory="path/to/my/data", instrument="nirspec")
mosviz.show()

or for NIRISS:

mosviz.load_data(directory="path/to/my/data", instrument="niriss")

Similarly, an instrument keyword can be specified by the command line. For NIRSpec:

jdaviz mosviz /path/to/my/data --instrument=nirspec

and for NIRISS:

jdaviz mosviz /path/to/my/data --instrument=niriss

If an instrument is not specified in either case, Mosviz will default to NIRSpec parsing.

Manual Loading

If an automatic parser is not provided yet for your data, Mosviz provides manual loading by specifying which files are which, and the associations between them. This is done by generating three lists containing the filenames for the 1D spectra, 2D spectra, and images in your dataset. These three lists are taken as arguments by load_data(). The association between files is assumed to be the order of each list (e.g., the first object consists of the first filename specified in each list, the second target is the second in each list, and so forth).

Currently, manual loading is supported in the Jupyter context only.

An example is given below, where file_dir is a directory that contains all the files for the dataset to be loaded:

from jdaviz import Mosviz
mosviz = Mosviz()
spectra_1d = ['target1_1d.fits', 'target2_1d.fits']
spectra_2d = ['target1_2d.fits', 'target2_2d.fits']
images = ['target1_img.fits', 'target2_img.fits']
mosviz.load_data(spectra_1d, spectra_2d, images)
mosviz.show()