What are Associations?¶
Associations are basically just lists of things, mostly exposures, that are somehow related. With respect to JWST and the Data Management System (DMS), associations have the following characteristics:
- Relationships between multiple exposures are captured in an association.
- An association is a means of identifying a set of exposures that belong together and may be dependent upon one another.
- The association concept permits exposures to be calibrated, archived, retrieved, and reprocessed as a set rather than as individual objects.
- For each association, DMS will generate the most combined and least combined data products.
Associations and JWST¶
The basic chunk in which science data arrives from the observatory is
exposure. An exposure contains the data from a single set
of integrations per detector per instrument. In general, it takes many
exposures to make up a single observation, and a whole program is made
up of a large number of observations.
On first arrival, an exposure is termed to be at
Level1b: The only
transformation that has occured is the extraction of the science data
from the observatory telemetry into a FITS file. At this point, the
science exposures enter the calibration pipeline.
The pipeline consists of two stages: Level2 processing and Level3
processing. Level2 processing is the calibration necessary to remove
instrumental effects from the data. The resulting files contain flux
and spatially calibrated data, called
Level2b data. The information
is still in individual exposures.
To be truly useful, the exposures need to be combined and, in the case
of multi-object spectrometry, separated, into data that is
source-oriented. This type of calibration is called
processing. Due to the nature of the individual instruments, observing
modes, and the interruptability of the observatory itself, how to
group the right exposures together is not straight-forward.
Enter the Association Generator. Given a set of exposures, called the Association Pool, and a set of rules found in an Association Registry, the generator groups the exposures into individual associations. These associations are then used as input to the Level3 calibration steps to perform the transformation from exposure-based data to source-based, high(er) signal-to-noise data.
In short, Level 2 andLevel 3 associations are created running the asn_generate task on an Association Pool using the default Level 2 and Level 3 Association Rules to produce level2-associations and level3-associations.
Users should not need to run the generator. Instead, it is expected that one edits an already existing association that accompanies the user’s JWST data. Or, if need be, an association can be created based on the existing Level2 or Level3 examples.
Once an association is in-hand, one can pass it as input to a pipeline routine. For example:
% strun calwebb_image3.cfg jw12345_xxxx_asn.json
Programmatically, to read in an Association, one uses the
from jwst.associations import load_asn with open('jw12345_xxxx_asn.json') as fp: asn = load_asn(fp)
What exactly is returned depends on what the association is. However,
for all Level2 and Level3 associations, a Python
dict is returned,
whose structure matches that of the
YAML file. Continuing
from the above example, the following shows how to access the first
exposure file name of a Level3 assocations:
exposure = asn['products']['members']['expname']
Since the JWST pipeline uses associations extensively, higher-level access is gained by opening an association as a JWST Data Model:
from jwst.datamodels import open as dm_open container_model = dm_open('jw12345_xxxx_asn.json')
Other useful utilities for creating and manipulating associations:
- many other TBD