The algorithms for CALWEBB_TSO3, which is Stage 3 of the JWST science calibration pipeline for all Time Series Observations (TSO) data, are described. These algorithms process the data from calibrated slope images to extracted photometry and spectroscopy for each integration. 

On this page

The CALWEBB_TSO3 module is Stage 3 of the JWST science calibration pipeline for all TSO data. The inputs to this stage are the calibrated slope images (CALWEBB_IMAGE2 and CALWEBB_SPEC2 output) and the outputs are extracted photometry and spectroscopy as appropriate. The steps are listed in Figure 1 with the flow from the top to the bottom.

Unless otherwise stated, the algorithms described are the baseline version.

Figure 1. CALWEBB_TSO3

Graphical representation of all the steps in the CALWEBB_TSO3 module. Checkmarks indicate which steps are applicable to which modes, for NIR and MIR observations.

Steps for all TSO data

Outlier detection

See also: Outlier Detection (more detailed software module documentation)

A 2nd pass at outlier detection is done using the image stack. The majority of the outliers will be due to cosmic rays undetected during the 1st pass at outlier detection done in CALWEBB_DETECTOR1. An iterative sigma clipping algorithm is used in pixel coordinates on the image stack. The presence of an outlier results in a pixel flag being set.

Exposure level products

The exposure level products are re-created at this stage to provide the highest quality products that include the results of the ensemble processing (a 2nd pass outlier detection). These products are for the archive and include the unrectified 2D images and rectified 2D images.

Imaging-specific steps

Extract photometry

See also: TSO Photometry (more detailed software module documentation)

Aperture photometry with a predefined aperture is performed for each integration providing the time series photometry. 

Spectroscopy-specific steps

Spectral extraction

See also: Extract 2D (more detailed software module documentation)

The extraction is done using a boxcar for each integration providing time series spectroscopy.

White-light photometry

See also: White Light Curve Generation (more detailed software module documentation)

The 1D extracted spectra are collapsed to create time series white-light photometry for the spectral observations.

Latest updates

  • Addressed v1.1 comments.


Originally published