MultiExposureModel¶
-
class
jwst.datamodels.
MultiExposureModel
(init=None, **kwargs)[source]¶ Bases:
jwst.datamodels.JwstDataModel
A data model for multi-slit images derived from numerous exposures. The intent is that all slits in this model are of the same source, with each slit representing a separate exposure of that source.
This model has a special member
exposures
that can be used to deal with an entire slit at a time. It behaves like a list:>>> from .image import ImageModel >>> multiexposure_model = MultiExposureModel() >>> multiexposure_model.exposures.append(ImageModel()) >>> multiexposure_model.exposures[0] <ImageModel>
Also, there is an extra attribute,
meta
. This will contain the meta attribute from the exposure from which each slit has been taken.See the module
exp_to_source
for the initial creation of these models. This is part of the Level 3 processing of multi-objection observations.- Parameters
exposures.items.data (numpy float32 array) –
exposures.items.dq (numpy uint32 array) –
exposures.items.err (numpy float32 array) –
exposures.items.area (numpy float32 array) –
init (str, tuple,
HDUList
, ndarray, dict, None) –None : Create a default data model with no shape.
tuple : Shape of the data array. Initialize with empty data array with shape specified by the.
file path: Initialize from the given file (FITS or ASDF)
readable file object: Initialize from the given file object
HDUList
: Initialize from the givenHDUList
.A numpy array: Used to initialize the data array
dict: The object model tree for the data model
schema (dict, str (optional)) – Tree of objects representing a JSON schema, or string naming a schema. The schema to use to understand the elements on the model. If not provided, the schema associated with this class will be used.
memmap (bool) – Turn memmap of FITS file on or off. (default: False). Ignored for ASDF files.
pass_invalid_values (bool or None) – If
True
, values that do not validate the schema will be added to the metadata. IfFalse
, they will be set toNone
. IfNone
, value will be taken from the environmental PASS_INVALID_VALUES. Otherwise the default value isFalse
.strict_validation (bool or None) – If
True
, schema validation errors will generate an exception. IfFalse
, they will generate a warning. IfNone
, value will be taken from the environmental STRICT_VALIDATION. Otherwise, the default value isFalse
.validate_on_assignment (bool or None) – Defaults to ‘None’. If
None
, value will be taken from the environmental VALIDATE_ON_ASSIGNMENT, defaulting to ‘True’ if no environment variable is set. If ‘True’, attribute assignments are validated at the time of assignment. Validation errors generate warnings and values will be set toNone
. If ‘False’, schema validation occurs only once at the time of write. Validation errors generate warnings.ignore_missing_extensions (bool) – When
False
, raise warnings when a file is read that contains metadata about extensions that are not available. Defaults toTrue
.kwargs (dict) –
Additional keyword arguments passed to lower level functions. These arguments are generally file format-specific. Arguments of note are:
available built-in formats are (The) –
==== ===== ============= (=========) – Format Read Write Auto-identify
==== ===== ============= –
Yes Yes Yes (datamodel) –
==== ===== ============= –
Attributes Summary
Attributes Documentation
-
core_schema_url
= 'http://stsci.edu/schemas/jwst_datamodel/core.schema'¶
-
schema_url
= 'http://stsci.edu/schemas/jwst_datamodel/multiexposure.schema'¶