jwst package also contains the interface for JWST Datamodels.
are the recommended way of reading and writing JWST data files (.fits) and
reference files (.fits and .asdf). JWST data are encoded in FITS files, and reference
files consist of a mix of FITS and ASDF - datamodels were designed to
abstract away these intricacies and provide a simple interface to the data. They
represent the data in FITS extensions and meta data in FITS headers in a Python object
with a tree-like structure. The following section gives a brief overview of
Datamodels as they pertain to the pipeline - see Data Models
detailed documentation on Datamodels.
Datamodels and the JWST pipeline
When running the pipeline in python, the inputs and
outputs of running a pipeline or a step are JWST
The input to a pipeline/step can be a
Datamodel, created from an input
file on disk. E.g:
# running a single pipeline step, input is datamodel object
from jwst.linearity import LinearityStep
import stdatamodels.jwst.datamodels as dm
input_model = dm.open('jw00001001001_01101_00001_mirimage_uncal.fits')
result = LinearityStep.call(input_model)
If a string path to a file on disk is passed in, a
DataModel object will be
created internally when the pipeline/step is run.
By default, when running in Python, the corrected data will be returned in-memory
DataModel instead of being written as an output file.
See controlling output file behavior` for instrucions on
how to write the returned
DataModel to an output file.