ModelLibrary

class jwst.datamodels.library.ModelLibrary(init, asn_exptypes=None, asn_n_members=None, on_disk=False, temp_directory=None, **datamodels_open_kwargs)[source]

Bases: AbstractModelLibrary

JWST implementation of the ModelLibrary.

ModelLibrary is a container designed to allow efficient processing of datamodel instances created from an association. See the stpipe library documentation for more information.

Create a new ModelLibrary based on the provided “init”.

Parameters:

initstr or Path or list (of DataModels): If a string or Path this should point to a valid association file. If a list of models consider continuing to use the list instead of making a library (the list will be more efficient and easier to use).
asn_exptypeslist of str, optional: List of “exptypes” to load from the “init” value. Any association member with a “exptype” that matches (case insensitive) a value in this list will be available through the library.
asn_n_membersint, optional: Number of association members to include in the library. This filtering will occur after “asn_exptypes” is applied. By default all members will be included.
on_diskbool, optional, default=False: When enabled, keep the models in the library “on disk”, writing out temporary files when the models are “shelved”. This option is only compatible with models loaded from an association (not a list of models).
temp_directorystr or Path, optional: The temporary directory in which to store models when “on_disk” is enabled. By default a tempfile.TemporaryDirectory will be created in the working directory.
**datamodels_open_kwargsdict: Keyword arguments that will provided to _datamodels_open when models are opened.

Attributes Summary

`asn_dir`	Return the directory from which the association was loaded.
`crds_observatory`	Return the observatory name for CRDS queries.
`exptypes`	List exposure types for all members in the library.
`on_disk`	Return the library's on_disk attribute.

Methods Summary

`get_crds_parameters`()	Override base method so lazy-loading of metadata can be used to get CRDS parameters.
`indices_for_exptype`(exptype)	Determine the indices of models corresponding to `exptype`.
`read_metadata`(idx[, flatten])	Read metadata for a model at the given index.

Attributes Documentation

asn_dir

Return the directory from which the association was loaded.

Returns:

str: The directory from which the association was loaded.

crds_observatory

Return the observatory name for CRDS queries.

Returns:

str: The observatory name for CRDS queries.

exptypes

List exposure types for all members in the library.

Returns:

list: List of exposure types for all members in the library.

on_disk

Return the library’s on_disk attribute.

If True, the library is using temporary files to store the models when not in use. If False, the library is storing the models in memory.

Returns:

bool: Whether the library is on disk.

Methods Documentation

get_crds_parameters()[source]

Override base method so lazy-loading of metadata can be used to get CRDS parameters.

Get the “crds_parameters” from either:

the first “science” member (based on exptype)
the first model (if no “science” member is found)

If no “science” members are found in the library a UserWarning will be issued.

Returns:

crds_parametersdict: The result of get_crds_parameters called on the selected model.

indices_for_exptype(exptype)[source]

Determine the indices of models corresponding to exptype.

Parameters:

exptypestr: Exposure type as defined in an association, e.g. “science”. case-insensitive

Returns:

indlist: Indices of models in ModelLibrary with member exposure types matching exptype.

Notes

Library does NOT need to be open (i.e., this can be called outside the with context)

read_metadata(idx, flatten=True)[source]

Read metadata for a model at the given index.

Parameters:

idxint: Index of the model in the library.

Returns:

dict: The metadata dictionary for the model.