Mosviz provides two different ways to load data: Auto-recognition directory loading or manual 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")
If an instrument is not specified, Mosviz will default to NIRSpec parsing.
Specifying an instrument from the command line is not supported yet, and will default to NIRSpec parsing as if an instrument wasn't provided:
jdaviz mosviz /path/to/my/data
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 :meth:`~jdaviz.configs.mosviz.helper.Mosviz.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()