DarkCurrentStep

class jwst.dark_current.DarkCurrentStep(name=None, parent=None, config_file=None, _validate_kwds=True, **kws)[source]

Bases: JwstStep

DarkCurrentStep: Performs dark current correction by subtracting dark current reference data from the input science data model.

Create a Step instance.

Parameters:

name (str, optional) – The name of the Step instance. Used in logging messages and in cache filenames. If not provided, one will be generated based on the class name.
parent (Step instance, optional) – The parent step of this step. Used to determine a fully-qualified name for this step, and to determine the mode in which to run this step.
config_file (str or pathlib.Path, optional) – The path to the config file that this step was initialized with. Use to determine relative path names of other config files.
**kws (dict) – Additional parameters to set. These will be set as member variables on the new Step instance.

Attributes Summary

`class_alias`
`reference_file_types`
`spec`

Methods Summary

`process`(input)	This is where real work happens.
`set_average_dark_current`(input_model, dark_model)	Take the three possible locations specifying the average dark current and assign them to the input model, in priority order: 1) Any value provided to the step parameter, either from the user or a parameter reference file 2) The 2-D array stored in dark_model.average_dark_current 3) The scalar value stored in dark_model.meta.exposure.average_dark_current

Attributes Documentation

class_alias = 'dark_current'

reference_file_types: ClassVar = ['dark']

spec

dark_output = output_file(default = None) # Dark model or averaged dark subtracted
average_dark_current = float(default=None) # The average dark current for this detector in units of e-/sec.

Methods Documentation

process(input)[source]: This is where real work happens. Every Step subclass has to override this method. The default behaviour is to raise a NotImplementedError exception.

set_average_dark_current(input_model, dark_model)[source]

Take the three possible locations specifying the average dark current and assign them to the input model, in priority order: 1) Any value provided to the step parameter, either from the user or a parameter reference file 2) The 2-D array stored in dark_model.average_dark_current 3) The scalar value stored in dark_model.meta.exposure.average_dark_current

Inputs

input_modelstdatamodels.jwst.datamodels.RampModel: The input datamodel containing the 4-D ramp array
dark_modelUnion[stdatamodels.jwst.datamodels.DarkModel, stdatamodels.jwst.datamodels.DarkMIRIModel]: The dark reference file datamodel