Importing Data into Mosviz

Mosviz provides two different ways to load data: auto-recognition directory loading and 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 (levels 2 and 3)

  • JWST NIRISS

  • JWST NIRCam

The NIRSpec parser expects a directory with either level 2 files:

  • *_cal.fits : Single file containing level 2 2D spectra for all objects.

  • *_x1d.fits : Single file containing level 2 1D spectra for all objects.

or level 3 files:

  • *_s2d.fits : N files containing level 3 2D spectra, where N is the number of objects.

  • *_x1d.fits : N files containing level 3 1D spectra, where N is the number of objects.

In either the level 2 or 3 case, the NIRSpec data directory may contain a sub-directory named images, cutouts, or mosviz_cutouts. This sub-directory should contain FITS files containing images corresponding to each target, which may be sourced from a non-JWST telescope.

The NIRISS parser expects a directory with the following types of files:

  • *_i2d.fits : Level 3 2D images from the calwebb_image3 imaging pipeline

  • *_cat.ecsv : Level 3 source catalog from the calwebb_image3 imaging pipeline (For best performance, it’s recommended that your directory only contain one.)

  • *_cal.fits : Level 2 2D spectra in vertical (R) and horizontal (C) orientations from the calwebb_spec2 spectroscopic pipeline (C spectra are shown first in 2D viewer by default.)

  • *_x1d.fits : Level 2 1D spectra in vertical (R) and horizontal (C) orientations from the calwebb_spec2 spectroscopic pipeline (C spectra are shown first in 1D viewer by default.)

The NIRCam parser expects *_cal.fits and *_x1d files in the same format as the NIRISS parser.

In a Jupyter context (notebook or Lab), you must 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 a directory is input in either case without specifying an instrument, Mosviz will raise an error.

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()