OutlierDetectionStackStep

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

Bases: JwstStep

Class definition for stacked outlier detection.

Flag outlier bad pixels and cosmic rays in the DQ array of each input image of a stack of exposures, which in the case of TSO data are from the same data cube.

Input images can listed in an input association file or already opened with a ModelContainer.

DQ arrays are modified in place.

By default, resampling has been disabled. The ‘resample_data’ attribute can be reset to ‘True’ to turn on resampling if desired for the data.

Parameters:

input (asn file or ModelContainer) – Single filename association table, or a datamodels.ModelContainer.

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

spec

Methods Summary

process(input)

Step interface for performing outlier_detection processing.

Attributes Documentation

class_alias = 'outlier_detection_stack'
spec
weight_type = option('ivm','exptime',default='ivm')
pixfrac = float(default=1.0)
kernel = string(default='square') # drizzle kernel
fillval = string(default='INDEF')
nlow = integer(default=0)
nhigh = integer(default=0)
maskpt = float(default=0.7)
snr = string(default='4.0 3.0')
scale = string(default='0.5 0.4')
backg = float(default=0.0)
save_intermediate_results = boolean(default=False)
resample_data = boolean(default=False)
good_bits = string(default="~DO_NOT_USE")  # DQ flags to allow

Methods Documentation

process(input)[source]

Step interface for performing outlier_detection processing.