Astronomical Data Analysis Software & Systems XV

October 2-5, 2005
San Lorenzo de El Escorial, Spain

Hosted by ESA, European Space Agency

ESAC, European Space Astronomy Centre

Tutorials

1) R: A powerful public software environment for statistical analysis of astronomical data

David R. Hunter, Eric D. Feigelson, G. Jogesh Babu

Speaker: David R. Hunter

Sunday, October 2, 2005, 14:00-16:00

Abstract

For many years, all comprehensive statistical software packages were proprietary and costly. This inhibited the astronomical community, which is largely committed to public domain software, from inheriting substantial expert software in statistics. The R system, an implementation of the S language on which S-plus is based, has recently emerged as the leading publicly available statistical software environment. The core of R has particular strengths in graphics, multivariate analysis and classification, statistical distributions and tests, smoothing, bootstrapping, linear and nonlinear regression, survival analysis, nonparametrics, neural nets, spatial processes, and time series analysis. Dozens of supplemental specialized packages (CRAN) can be instantly installed. R features an interactive command-line interface with links to many languages and protocols (e.g. Fortran, C, Python, XML, HTML, SOAP), varied host operating systems, and extensive documentation. This tutorial will introduce R and outline its capabilities to astronomers and data analysts.

About the main Author:

David Hunter received his PhD in statistics from the University of Michigan in 1999. A computational statistician, he has written numerous applications and developed several packages for the R computing environment. He is currently assistant professor of statistics at Pennsylvania State University.

2) Using Python for Interactive Data Analysis

Perry Greenfield

Sunday, October 2, 2005, 16:30-18:30

Abstract

Although Python is gaining recognition as a tool that can be used to script astronomical applications, there is less awareness that it is also a powerful environment for interactive data analysis. This tutorial will center on using Python as an interactive data analysis environment for reducing and analyzing astronomical data. The focus is on the use of existing tools to read FITS data, display images, plot data, and manipulate and analyze data using array facilities and numerical libraries. The Python programming language will be introduced as needed to perform the interactive functions but no attempt will be made to teach all aspects of Python. A written tutorial (covering this as well as much more additional material) and manuals will be provided to all participants. Topics will include:

• Reading and writing image and table data from and to FITS files
• Displaying images using DS9 and similar image display tools
• Manipulating arrays
• Plotting data
• Python strings, lists and dictionaries
• Survey of more advanced capabilities

About the main Author:

Perry Greenfield is the Science Analysis Tools Project Lead at the Space Telescope Science Institute. He was the original developer for numarray (an array manipulation package for Python) and a co-developer of PyRAF (which allows Python to be used as a scripting language for IRAF). He has managed the implementation of calibration pipelines for HST, STSDAS analysis tools and infrastructure, and exposure time calculators for over 10 years.

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