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mosvizVisualization and quick interactive analysis
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This article provides an overview of JWST post-pipeline data analysis tools and contains pointers to software installation and training materials.

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Introduction 

JWST Post-pipeline data-analysis tools are distributed as part of AstroConda to assist observers in viewing and analyzing their JWST data. The tools are generally written in Python and work together with Astropy. Development is ongoing. All software is open source and community contributions are welcome in the form of suggestions, bug reports, or actual code.  Further details on how to contribute can be found at the Data Analysis Tools Development Forum.

The suite of post-pipeline data-analysis tools is intended to help astronomers with the often iterative and interactive workflow involved in converting these pipeline data products into meaningful scientific results. This involves tasks such as:

  • inspecting data and data-quality information;
  • masking or flagging data and using those annotations to guide later steps in the analysis;
  • using the results of interactive analysis to guide a custom run of the pipeline (e.g. tweaking spectral extraction parameters or background estimates);
  • combining data sets in various ways, with careful attention to astrometry, PSF matching, and other issues;
  • source detection and photometry using different choices or algorithms than those used in the pipeline;
  • measuring lines and continuum in spectral data; and
  • fitting models to data or otherwise testing hypotheses.

A typical workflow involves highly interactive exploratory analysis on small portions of the data, followed by development of custom scripts to automate the analysis on larger data sets.

 


Software installation

The recommended way to install stable versions of the JWST data-analysis tools is to use AstroConda

There are development versions of many of the tools in STScI's Github repositories. You are welcome to test these and to contribute directly by creating or commenting on Github issues or modifying code and issuing linked in the Repository column in the table below, which links to the open-source development locations on Github. We welcome contributions to the development via bug reports (most effectively filed as github issues, but the JWST help desk is fine as well), or contributions of code through github pull requests. Use of the development versions of the code straight from github comes with the following caveats: At any given time the code may not actually run or return correct results, and the documentation may be inconsistent with the code.  If you are not interested in contributing to the development, please use the versions in AstroConda.

 


Software packages

The table below provides links to further information about the tools. User-training workshops are being offered to help familiarize new users.

Name

Package

Purpose

/Comments
photutils

astropy

Astronomy-related tools for python.

glue

Linked dataset visualization.

ginga

2-D image visualization with python plug-in capability.

Repository

Maturity

Astropy

A community python library for astronomy (documentation & tutorials)

Astropy

 Image Added

glue

A Python library to explore relationships within and among related datasets.

glue

 Image Added

ginga

A toolkit designed for building viewers for scientific image data in Python.

ginga

 Image Added

Photutils

Tools for detecting and performing photometry of astronomical sources.

imexam
Interactive image analysis (Python equivalent of IRAF imexam).
specvizOne-dimensional spectra visualization and analysis (Python equivalent of IRAF splot)
Photutils

Image Added

psfutils

Convenience tools for working with point-spread functions (PSFs)

psfutils

Image Added 

astroimtools

Cconvenience tools for working with astronomical images.

astroimtools

Image Added 

imexam

Tool for simple image examination, and plotting, with similar functionality to IRAF's imexamine.

imexam

Image Added

specviz

An interactive astronomical 1D spectra analysis tool with similar functionality to IRAF's splot.

specviz

Image Added

mosviz

A quick-look analysis and visualization tool for multi-object spectroscopy.

mosviz

 Image Added

cubeviz

Visualization and quick interactive

Interactive analysis tool for 3-

D spectroscopypysynphotSynthetic photometrygwcsTools for constructing and manipulating world-coordinate systems (WCS).
Supports a data model which includes the entire transformation pipeline from input coordinates (detector by default) to world coordinates.

d spectroscopy (coming soon)

cubeviz

 Image Added

asdf

Advanced Scientific Data Format

(ASDF)

is a next generation interchange format for scientific data (

which can be packaged in FITS files, but which has much richer capabilities for handling metadata).astroimtoolsConvenience tools for working with astronomical images

 

docs)

asdf

Image Added

gwcs

Generalized World Coordinate System tools for dealing with image and spectral geometries (docs)

gwcs

Image Added

synphot

Synthetic photometry toolkit for building model spectra and estimating count-rates. (docs)

synphot

Image Added

Levels of maturity run from prototypes with little or no documentation, symbolized by buds, Image Added progressing through various levels:  Image Added Image Added to Image AddedThe exact meanings of these icons are a bit hard to quantify, but the flowers will tend to be still lacking in documentation and important features. The cherries are generally quite robust and well documented. The cherry pies are ready to be baked into your day-to-day workflow. Be aware that all of the packages above are in very active stages of development, including Astropy and glue. For the ones at the cherry-pie level, there is significant attention given to backwards compatibility as the APIs to the different modules evolve.

 


Training resources

There are many resources available for learning Python and for using Python for astronomical data analysis. This section provides pointers to astronomy-focused materials and to the more JWST-specific training materials.

General python astronomical data analysis training

Materials Documents
ResourceWritten materialsVideosComments
Practical Python for AstronomersWeb Documents 2011, 2012, 2013 Smithsonian Astrophysical Observatory
Using Python for Astronomical Data AnalysisNotebooks January 2017 American Astronomical Society Special Session
Astropy

Tutorials

  
Scientific Python Course at STScINotebooksVideosNotebooks are from 2015 version of course; videos from 2012-13
Astronomical Data Analysis with PythonDocuments, notebooksVideos2014 Lecture series
Practical Python for AstronomersWeb documents 2011, 2012, 2013 Smithsonian Astrophysical Observatory

JWST

-

focused training materials

Training materials for JWST data analysis will eventually include worked examples of common workflows, using outputs from the JWST pipeline. Currently the materials are more general than that, and often example data sets from other observatories. The table below provides links to these materials.

ResourceWritten MaterialsmaterialsVideosComments
JWST User Training in Data AnalysisNotebooksWebcast2016 Workshop at STScI

Below is a more topic-oriented map of the materials from the 2016 Workshop.

Introductory material

Introductory lectures
PythonNotebooksWebcast
NumpyNotebooksWebcast
PlottingNotebooksWebcast
UnitsNotebooksWebcast
Tables, I/O and FITSNotebooksWebcast

Coordinates

NotebooksWebcast
ModelingNotebooksWebcast

More specialized material

JWST User Traininguser training
JWST pipeline overview Webcast starts at 50:00
Astropy & JWST tools overview Webcast
Image examination (imexam)NotebooksWebcast
Image display toolkit (ginga)Ginga embedded in a Jupiter Notebook

Webcast starts at 26:00
Glue-Ginga Interoperability Webcast 1:03:00 

Photometry (photutils)

Intro Notebooks
PSF-photometry Notebook 

Webcast starts at 55:30
PSF-fitting Webcast 46:00
Data exploration (glue) 

Webcast
Customizing Glue webcastWebcast 27:30 

Interactive spectral analysis (SpecViz, MosViz, CubeViz) Webcast starts at 1:01:30
NIRCam Data Reduction Webcast
Advanced Astropy TablesNotebookWebcast
Generalized World Coordinate System (gwcs)NotebookWebcast

 

 


 

 

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Related links

JWST User Documentation Home
AstroConda software Installation
JWST Data Analysis Tools webpage
Astropy – A community Python library for astronomy
Glue  – Multidimensional data exploration
Ginga – Image viewer and toolkit

 

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References

Reference papers and reportsJWST technical documents

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MultiExcerptNameGeneric data templateJWST Post-Pipeline Data Analysis
PageWithExcerptMR:Generic data icon - dlpDL Post-Pipeline Data Analysis

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Last updated

Published May 15, 2017


 

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