Difference between revisions of "PythonsOnSHIPs"
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===Python distribution to use=== | ===Python distribution to use=== | ||
Based on our requirements of Windows+MacOS+Linux, the choice is Anaconda python. | Based on our requirements of Windows+MacOS+Linux, the choice is Anaconda python. | ||
| − | * | + | * [http://continuum.io/downloads.html http://continuum.io/downloads.html] |
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| + | ===Using Python=== | ||
| + | Some examples for which we can use Python for NITARP: | ||
| + | * Convert an APT photometry table file into a ds9 region file. | ||
| + | * Merge photometry tables. | ||
| + | * Analyze photometry tables. | ||
| + | * Create 2-dimensional plots of various types: scatter plots, line plots, histograms. These plots may have multiple data sets on them. | ||
| + | * Save plots to a JPG, PNG or similar graphic format file. | ||
| + | * Work directly with FITS images (advanced). | ||
Latest revision as of 20:49, 26 April 2014
The Python programming environment is a relatively easy to use tool that has gained considerable acceptance and use in astronomical data processing. We will use Python on an experimental basis to cover some basic work for SHIPs work.
Python distribution to use
Based on our requirements of Windows+MacOS+Linux, the choice is Anaconda python.
Using Python
Some examples for which we can use Python for NITARP:
- Convert an APT photometry table file into a ds9 region file.
- Merge photometry tables.
- Analyze photometry tables.
- Create 2-dimensional plots of various types: scatter plots, line plots, histograms. These plots may have multiple data sets on them.
- Save plots to a JPG, PNG or similar graphic format file.
- Work directly with FITS images (advanced).
