OutlierDetectionStep

class jwst.outlier_detection.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 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.
  • **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 = integer(default=4)\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.