OutlierDetectionStep

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

Bases: jwst.stpipe.Step

Flag outlier bad pixels and cosmic rays in DQ array of each input image.

Input images can be listed in an input association file or already opened with a ModelContainer. DQ arrays are modified in place.

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 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

spec

Methods Summary

check_input()

Use this method to determine whether input is valid or not.

process(input)

Perform outlier detection processing on input data.

Attributes Documentation

spec = '\n weight_type = option(\'exptime\',\'error\',None,default=\'exptime\')\n pixfrac = float(default=1.0)\n kernel = string(default=\'square\') # drizzle kernel\n fillval = string(default=\'INDEF\')\n nlow = integer(default=0)\n nhigh = integer(default=0)\n maskpt = float(default=0.7)\n grow = integer(default=1)\n snr = string(default=\'4.0 3.0\')\n scale = string(default=\'0.5 0.4\')\n backg = float(default=0.0)\n save_intermediate_results = boolean(default=False)\n resample_data = boolean(default=True)\n good_bits = string(default="~DO_NOT_USE") # DQ flags to allow\n scale_detection = boolean(default=False)\n search_output_file = boolean(default=False)\n '

Methods Documentation

check_input()[source]

Use this method to determine whether input is valid or not.

process(input)[source]

Perform outlier detection processing on input data.