RampFitStep

class jwst.ramp_fitting.RampFitStep(name=None, parent=None, config_file=None, _validate_kwds=True, **kws)[source]

Bases: JwstStep

Fit line to determine the value of mean rate counts vs. time.

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

weighting

Methods Summary

process(step_input)

Fit ramps using the specified ramp fitting algorithm.

Attributes Documentation

class_alias = 'ramp_fit'
reference_file_types: ClassVar = ['readnoise', 'gain']
spec
algorithm = option('OLS', 'OLS_C', 'LIKELY', default='OLS_C') # 'OLS' and 'OLS_C' use the same underlying algorithm, but OLS_C is implemented in C
int_name = string(default='')
save_opt = boolean(default=False) # Save optional output
opt_name = string(default='')
suppress_one_group = boolean(default=True)  # Suppress saturated ramps with good 0th group
firstgroup = integer(default=None)   # Ignore groups before this one (zero indexed)
lastgroup = integer(default=None)   # Ignore groups after this one (zero indexed)
maximum_cores = string(default='1') # cores for multiprocessing. Can be an integer, 'half', 'quarter', or 'all'
weighting = 'optimal'

Methods Documentation

process(step_input)[source]

Fit ramps using the specified ramp fitting algorithm.

Parameters:

step_input (RampModel) – The input ramp model to fit the ramps.

Returns:

  • out_model (ImageModel) – The output 2-D image model with the fit ramps.

  • int_model (CubeModel) – The output 3-D image model with the fit ramps for each integration.