RampFitStep

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

Fit ramp data to determine the mean count rate.

Create a Step instance.

Parameters:

namestr: 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.
parentStep: 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_filestr or pathlib.Path: The path to the config file that this step was initialized with. Use to determine relative path names of other config files.
_validate_kwdsbool: Validate given kws against specs/config.
**kwsdict: Additional parameters to set. These will be set as member variables on the new Step instance.

Attributes Summary

Methods Summary

process(step_input)

Fit ramps using the specified ramp fitting algorithm.

Attributes Documentation

spec = "\n algorithm = option('OLS_C', 'LIKELY', default='OLS_C')\n int_name = string(default='')\n save_opt = boolean(default=False) # Save optional output\n opt_name = string(default='')\n suppress_one_group = boolean(default=True) # Suppress saturated ramps with good 0th group\n firstgroup = integer(default=None) # Ignore groups before this one (zero indexed)\n lastgroup = integer(default=None) # Ignore groups after this one (zero indexed)\n maximum_cores = string(default='1') # cores for multiprocessing. Can be an integer, 'half', 'quarter', or 'all'\n "

Methods Documentation

process(step_input)[source]

Fit ramps using the specified ramp fitting algorithm.

Parameters:

step_inputstr or RampModel: The input file name or ramp model to fit the ramps.

Returns:

out_modelImageModel: The output 2-D image model with the fit ramps.
int_modelCubeModel: The output 3-D image model with the fit ramps for each integration.