https://github.com/arcticsnow/probextreme

Python Library for Extreme Event Characterisation

https://github.com/arcticsnow/probextreme

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (6.2%) to scientific vocabulary

Keywords

climate-science extreme-value-statistics extremes meteorology
Last synced: 6 months ago · JSON representation

Repository

Python Library for Extreme Event Characterisation

Basic Info
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
climate-science extreme-value-statistics extremes meteorology
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

Probextreme

Python Library for Extreme Event Characterisation.

See documentation: https://probextreme.readthedocs.io/en/latest/

This library is under construction

Installation

```bash git clone https://github.com/ArcticSnow/probextreme.git

install in development mode

pip install -e probextreme ```

Documentation

To display the documentation, install the package mkdocs, and run the command mkdocs serve from the probextreme root directory.

sh pip install mkdocs mkdocs serve

ToDo

Short term

  • [x] add Bayesian temporal dependencies
  • [ ] add example notebooks (see Bérarde cases). Provide sample datasets
  • [ ] add Bayesian Pareto
  • [ ] add Mann-Kendall test for trend significance
  • [ ] add trends fitting

Long term development

  • seasonal extremes
  • Bayesian plotting

Owner

  • Name: Simon Filhol
  • Login: ArcticSnow
  • Kind: user
  • Location: Norway
  • Company: University of Oslo

GitHub Events

Total
  • Member event: 1
  • Push event: 18
  • Create event: 2
Last Year
  • Member event: 1
  • Push event: 18
  • Create event: 2

Dependencies

setup.py pypi
  • xarray *