Slit-like Spectroscopic Data
This module serves as the interface for applying outlier_detection
to slit-like
spectroscopic observations. The algorithm is very similar to the
imaging algorithm, and much of the same code is used.
Please refer to those docs for more information.
A Stage 3 association,
which is loaded into a ModelContainer
object,
serves as the input and output to this step, and the ModelContainer
is converted into a ModelLibrary
object to allow sharing code
with the imaging mode.
This routine performs identical operations to the imaging mode, with the following exceptions:
Error thresholding is handled differently: the error arrays are resampled and median-combined along with the data arrays, and the median error image is used to identify outliers instead of the input error images for each exposure. This median error image is included alongside the median datamodel (in the
err
extension) ifsave_intermediate_results
isTrue
.Resampling is handled by a different class,
ResampleSpec
instead ofResampleImage
.The resampled images are written out to disk with suffix “outlier_s2d” instead of “outlier_i2d” if the
save_intermediate_results
parameter is set toTrue
.The
in_memory
parameter has no effect, and all operations are performed in memory.
jwst.outlier_detection.spec Module
Perform outlier detection on spectra.
Functions
|
Flag outliers in slit-like spectroscopic data. |