https://github.com/weber-s/py4pm

Python utilities to handle the EPA PMF 5.0 results, and more.
https://github.com/weber-s/py4pm

aerosols pmf

Last synced: 8 months ago
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Python utilities to handle the EPA PMF 5.0 results, and more.

• Host: GitHub
• URL: https://github.com/weber-s/py4pm
• Owner: weber-s
• Created: 2020-11-26T14:38:09.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-01-08T10:22:39.000Z (over 4 years ago)
• Last Synced: 2024-06-12T17:42:03.644Z (about 2 years ago)
• Topics: aerosols, pmf
• Language: Python
• Homepage:
• Size: 1.69 MB
• Stars: 5
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
[![Documentation Status](https://img.shields.io/badge/Documentation-API-green)](https://webersa.gricad-pages.univ-grenoble-alpes.fr/py4pm/)

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Utilities to handle PMF data

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Contents

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* [Usage](usage.md)

* [API](api_py4pm.md)

Description

-----------

`py4pm` is a set of utilities to handle the xlsx output of EPA PMF5 software in python.

This project started because I needed to run several PMF for my PhD  and also needed to run some computation on these results.

The raw output of the EPA PMF5 software is a bit messy and hard to understand at a first

glance, and copy/pasting xlsx file is not my taste... So I ended developping this tools

for handling the tasks of maping the xlsx output to nice python objects, on which I can easily run

some computation.

Since I needed to plot the results afterward, I also added some plot utilities in this

package. It then has built in support for ploting :

 * chemical profile (both absolute and normalized)

 * species repartition among factor

 * timeserie contribution (*for all species* and profiles)

 * uncertainties plots (Bootstrap and DISP)

 * seasonal contribution

Moreover, this package include some of the DeltaTool utilities developed by the JRC, notably for profile chemical similarities between several PMF results.