Outlier Detection for Slit-like Spectroscopic Data

This module serves as the interface for applying outlier_detection to slit-like spectroscopic observations. The code implements the basic outlier detection algorithm used with HST data, as adapted to JWST spectroscopic observations.

Specifically, this routine performs the following operations (modified from the Default Outlier Detection Algorithm ):

1. Extract parameter settings from input model and merge them with any user-provided values

   • the same set of parameters available to: ref:Default Outlier Detection Algorithm also applies to this code

2. Convert input data, as needed, to make sure it is in a format that can be processed

   • A ModelContainer serves as the basic format for all processing performed by this step, as each entry will be treated as an element of a stack of images to be processed to identify bad pixels, cosmic-rays and other artifacts

   • If the input data is a CubeModel, convert it into a ModelContainer. This allows each plane of the cube to be treated as a separate 2D image for resampling (if done) and for combining into a median image.

3. Resample all input images into a ModelContainer using ResampleSpecData

   • Resampled images are written out to disk if the save_intermediate_results parameter is set to True

   • If resampling is turned off, the original unrectified inputs are used to create the median image for cosmic-ray detection

4. Create a median image from (possibly) resampled ModelContainer

   • The median image is written out to disk if the save_intermediate_results parameter is set to True

5. Blot median image to match each original input image

   • Resampled/blotted images are written out to disk if the save_intermediate_results parameter is set to True

   • If resampling is turned off, the median image is used for comparison with the original input models for detecting outliers

6. Perform statistical comparison between blotted image and original image to identify outliers

7. Update input data model DQ arrays with mask of detected outliers

jwst.outlier_detection.outlier_detection_spec Module

Class definition for performing outlier detection on spectra.

Classes

OutlierDetectionSpec(input_models[, reffiles])

Class definition for performing outlier detection on spectra.

Class Inheritance Diagram