{ "info": { "author": "Samu\u00ebl Weber", "author_email": "samuel.weber@univ-grenoble-alpes.fr", "bugtrack_url": null, "classifiers": [ "Development Status :: 1 - Planning", "License :: OSI Approved", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3.5", "Topic :: Scientific/Engineering :: Atmospheric Science" ], "description": "[![Documentation Status](https://readthedocs.org/projects/pypscf/badge/?version=latest)](http://pypscf.readthedocs.io/en/latest/?badge=latest) On [readthedocs](https://pypscf.readthedocs.org).\n\n# pyPSCF\n\nThe Potential Source Contribution Function is a tool to investigate the\ngeographical sources origin of chemical species in the atmosphere.\n\nSee the UserGuide for detailed information.\n\n# Compute large number of backtrajectories\n\nUnder the hood [hysplit](https://ready.arl.noaa.gov/HYSPLIT.php) is used to\ncompute backtrajectories. This GUI allows you to compute easily large number of\nbacktrajectories given a starting date and an end date.\n\n![backtraj](static/img/BackTrajGUI.png)\n\n# Install\n\nSimply clone this repo if you are used to git:\n\n git clone https://gricad-gitlab.univ-grenoble-alpes.fr/webersa/pyPSCF.git\n\nor download the zipped archive.\n\nYou will need python and some other dependancies. See the\n[docs](https://pyPSCF.readthedocs.org).\n\n# Compute PSCF \n\n## Select parameters \n\nThe second tab of the GUI are the PSCF parameters.\n\n![PSCF](static/img/PSCF.png)\n\n## Output\n\nA figure will show up with the PSCF in colorscale. 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