A Guide to STIS Analysis and Supporting Software

The STIS Data Handbook contains the primary guide to STIS data characteristics and analysis. Requests for STIS data from the HST Archive always return data reprocessed with the current version of CALSTIS and the best available reference files. In many cases, it is optimal to let the archive pipeline reprocess data for you. If standard pipeline processing is inadequate, however, CALSTIS may be downloaded and run locally. Other topics related to STIS data analysis are listed below, including available software packages.

The STIS team manages a public Git repository containing a set of Jupyter Notebooks to aid the STIS user community with observation planning and data analysis, available here: https://github.com/spacetelescope/STIS-Notebooks.  This includes a series of introductory Notebooks, meant to provide walk-through examples of concepts in our Data Handbook.  The current list of operational Notebooks is provided below under 'Example and Introductory Notebooks'.

Orbital Ephemeris Files

HST Orbital Ephemeris files are used for correcting observation time events of STIS TIME-TAG data. A tabulated list of all the HST ephemeris files and instruction on how to download is available. 

Tools for Planning STIS Observations
Software Tool Purpose
STIS Exposure Time Calculators (ETCs) An online tool that predicts the count rates and S/N in various observing modes given specified source characteristics. STIS has both an Imaging and Spectroscopic ETC.
Target Acquisition Simulator (TAS) A downloadable tool that applies the actual STIS target acquisition algorithm to a user supplied image.
Astronomer's Proposal Tool (APT) The general proposal planning tool for all HST instruments. The Bright Object Tool (BOT) in APT is available for STIS CCD and STIS MAMA observations.

STIS Coronagraphic Visualization Tool:

Zipped Jupyter Notebook (v2)

HTML Rendered Version

STIS-Notebooks GitHub Repository

Jupyter Notebook that assists users in planning and preparing STIS coronagraphic observations.

 

Software Tools for Analyzing STIS Data
Software Tools Purpose
stistools

The stistools Python package provides Python-based data processing tools for working with Space Telescope Imaging Spectrograph (STIS) data. It contains the full STIS calibration pipeline as well as its individual components should the user wish to do their calibrations manually.

stisblazefix

The stisblazefix Python package is designed to empirically correct STIS echelle data for misalignment in the blaze function.

stis_cti

The stis_cti Python package implements the Anderson & Bedin (PASP 2010, 122: 1035-1064) pixel-based Charge Transfer Inefficiency (CTI)-correction on HST/STIS CCD data. It performs bias corrections on the data, performs CTI correction on the intermediate products, and finishes running the remaining CalSTIS processing steps. The complete package documentation can be found here.

TinyTim

A tool that generates STIS point spread function (PSF) images.

 

Example and Introductory Notebooks
Process Purpose

Viewing STIS Data (view_data)

HTML Rendered Version

STIS-Notebooks GitHub Repository

An introductory Jupyter Notebook that walks through different types of STIS data and shows how to access important information in the fits files.  It covers how to read in and plot the data, handle the data quality flags, visualize a STIS image, work with TIME-TAG data, and how to access and plot echelle data.

Calstis 2D CCD Calibration Steps (calstis)

HTML Rendered Version

STIS-Notebooks GitHub Repository

An introductory Jupyter Notebook that provides background for the different calibration steps for the CCD from the raw fits file to the flat fielded (flt) file.  This also shows why there is often negative counts (or flux) values in STIS data.  The six calibration steps shown are initializing the data quality array, large scale bias and overscale subtraction, small scale bias subtraction, cosmic ray correction, dark signal subtraction, and flat field correction.

1D Spectra Extraction (extraction)

HTML Rendered Version

STIS-Notebooks GitHub Repository

An introductory Jupyter Notebook that shows how to visualize the 1-D extraction. This is useful for cases where a user may want to do a custom extraction or background subtraction.  It shows how to find the important keywords and plot the extraction and background regions used for the extraction to generate x1d data.  The notebook contains an example with a first order spectrum and with echelle data.

Custom CCD Darks (custom_ccd_dark)

HTML Rendered Version

STIS-Notebooks GitHub Repository

An introductory Jupyter Notebook showing how to create a custom CCD dark reference file by making the baseline dark and then the week dark using the refstis package.

Evaluating STIS Target Acquisitions (target_acquisition)

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STIS-Notebooks GitHub Repository

An introductory Jupyter Notebook that shows how to visualize and obtain information about a target acquisition. It provides examples for a successful acquisition and several typical failure cases.

Correcting for Missing Wavecals with Cross-Correlation (cross-correlation)

HTML Rendered Version

STIS-Notebooks GitHub Repository

A complementary Jupyter Notebook to the Acquisition Notebook, that shows how to find and correct the zero point spectral shift using cross-correlation.

Defringing a G750M Observation: View or Download

Defringing a G750L Observation: View or Download

STIS CCD observations with the G750M and G750L modes often experience optical fringes in wavelengths greater than 7500 Angstroms. In order to perform the best science possible, these fringes must be divided out. The downloadable notebooks to the left are example workflows for using the defringe routines in stistools to remove unwanted fringing effects in both G750M and G750L data. To learn more about the routines used, check the stistools defringe documentation  as well as section 3.5.5 of the STIS Data Handbook .

stisblazefix Notebooks

The stisblazefix Python package is designed to empirically correct STIS echelle data for misalignment in the blaze function.

STIS DrizzlePac Tutorial:

Zipped Jupyter Notebook (v1)

HTML Rendered Version

STIS-Notebooks GitHub Repository

Jupyter Notebook for aligning and combining STIS images with DrizzlePac.

 

 

Last Updated: 03/05/2024

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