Skip to content

HTTPS clone URL

Subversion checkout URL

You can clone with HTTPS or Subversion.

Download ZIP
Cambridge University Spaceflight landing predictor - a web-based tool for predicting the flight paths of meteorological sounding balloons.
C JavaScript PHP Python Objective-C C++ Other
branch: rename-ears

This branch is 24 commits behind master

Fetching latest commit…

Cannot retrieve the latest commit at this time

Failed to load latest commit information.
cron
gfs
pred_src
predict
.gitignore
AUTHORS
CREDITS
LICENSE
README.md
predict.py

README.md

CUSF Standalone Predictor - Version 2

Cambridge University Spaceflight landing predictor - a web-based tool for predicting the flight path and landing location of latex meteorological sounding balloons.

Install

The source for the predictor itself is in pred_src/ and instructions for building it can be found there.

The following items need to be executable (chmod +x ./predict.py) by the user under which the predictor runs:

  • predict.py
  • pred_src/pred (once compiled)
  • cron/clear-pydap-cache-cronjob.sh
  • cron/purge-predictions-cronjob.sh

The predict/preds/ and gfs/ directories need to have rwx access by the PHP interpreter and the predict.py python script. You will need to install the following python packages: pydap, numpy, json, simple-json. We use at to automatically background the predictor, so you will need that installed.

Other than that, just clone this repo to a non web-accessible folder and create symlinks to the predict/ directory in the repo.

There are useful configuration options in predict/includes/config.inc.php.

Information

The two shell scripts in the cron/ directory should both be run daily. clear-pydap-cache-cronjob.sh clears the cache used by pydap so that old data does not build up. purge-predictions-cronjob.sh deletes scenarios and predictions not accessed or modified within the last 7 days. Re-running a prediction for a scenario will therefore reset its time to live to 7 more days.

The directory names are UUIDs comprised of an SHA1 hash of the launch parameters, and re-running predictions will overwrite data in the existing directory, rather than create a new one.

We use GFS data provided by the NOAA, accessed via NDAP and their NOMADS distribution system. The 1.0x1.0 degree data (26 vertical pressure levels) is used for standard predictions, and the 0.5x0.5 degree data (47 vertical pressure levels) is used for the high definition (HD) predictions.

License

This work is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or any later version. This work is distributed in the hope that it will be useful, but without any warranty; without even the implied warranty of merchantability or fitness for a particular purpose.

Credits & Acknowledgments

Credit as detailed in individual files, but notably:

  • Rich Wareham - The new predictor and the hourly predictor system
  • Fergus Noble, Ed Moore and many others

Adam Greig - http://www.randomskk.net - random@randomskk.net
Jon Sowman - http://www.hexoc.com - jon@hexoc.com

Copyright Cambridge University Spaceflight 2009-2011 - All Rights Reserved

Something went wrong with that request. Please try again.