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pyextremes

Extreme Value Analysis (EVA) in Python

https://github.com/georgebv/pyextremes

Science Score: 44.0%

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

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (17.1%) to scientific vocabulary

Keywords

block-maxima eva extreme-events extreme-value-analysis extreme-value-statistics extremes peaks-over-threshold python statistics
Last synced: 6 months ago · JSON representation ·

Repository

Extreme Value Analysis (EVA) in Python

Basic Info
Statistics
  • Stars: 260
  • Watchers: 7
  • Forks: 49
  • Open Issues: 2
  • Releases: 18
Topics
block-maxima eva extreme-events extreme-value-analysis extreme-value-statistics extremes peaks-over-threshold python statistics
Created almost 6 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

pyextremes

Extreme Value Analysis (EVA) in Python

Test Coverage PyPI Package Anaconda Package

About

Documentation: https://georgebv.github.io/pyextremes/

License: MIT

Support: ask a question or create an issue, any input is appreciated and would help develop the project

pyextremes is a Python library aimed at performing univariate Extreme Value Analysis (EVA). It provides tools necessary to perform a wide range of tasks required to perform EVA, such as:

  • extraction of extreme events from time series using methods such as Block Maxima (BM) or Peaks Over Threshold (POT)
  • fitting continuous distributions, such as GEVD, GPD, or user-specified continous distributions to the extracted extreme events
  • visualization of model inputs, results, and goodness-of-fit statistics
  • estimation of extreme events of given probability or return period (e.g. 100-year event) and of corresponding confidence intervals
  • tools assisting with model selection and tuning, such as selection of block size in BM and threshold in POT

Check out this repository with Jupyter notebooks used to produce figures for this readme and for the official documentation.

Installation

Get latest version from PyPI:

shell pip install pyextremes

Install with optional dependencies:

shell pip install pyextremes[full]

Get latest experimental build from GitHub:

shell pip install "git+https://github.com/georgebv/pyextremes.git#egg=pyextremes"

Get pyextremes for the Anaconda Python distribution:

shell conda install -c conda-forge pyextremes

Illustrations

Model diagnostic

Diagnostic plot

Extreme value extraction

Diagnostic plot

Trace plot

Diagnostic plot

Corner plot

Diagnostic plot

Acknowledgements

I wanted to give kudos to Jean Toilliez who has inspired me to develop this open-source project and who taught me a lot about the extreme value theory. Also big thanks to Max Larson who has introduced me to software development and statistics.

Owner

  • Name: George Bocharov
  • Login: georgebv
  • Kind: user
  • Location: San Francisco Bay Area
  • Company: kicksaw @Kicksaw-Consulting

Senior software engineer

Citation (CITATION.cff) 

cff-version: 1.2.0
title: pyextremes
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Georgii
    family-names: Bocharov
    email: bocharovgeorgii@gmail.com
repository-code: 'https://github.com/georgebv/pyextremes'
url: 'https://georgebv.github.io/pyextremes'
abstract: >-
  pyextremes is a Python library aimed at performing
  univariate Extreme Value Analysis.
keywords:
  - Extreme Value Analysis
  - EVA
  - Python
  - Statistics
license: MIT
commit: b003286e436db73e7f12c9f7c3298c05773bdf88
version: 2.3.3
date-released: '2023-10-14'

GitHub Events

Total
  • Issues event: 5
  • Watch event: 20
  • Delete event: 2
  • Issue comment event: 6
  • Push event: 9
  • Pull request review comment event: 4
  • Pull request review event: 5
  • Pull request event: 4
  • Fork event: 4
  • Create event: 1
Last Year
  • Issues event: 5
  • Watch event: 20
  • Delete event: 2
  • Issue comment event: 6
  • Push event: 9
  • Pull request review comment event: 4
  • Pull request review event: 5
  • Pull request event: 4
  • Fork event: 4
  • Create event: 1

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 167
  • Total Committers: 5
  • Avg Commits per committer: 33.4
  • Development Distribution Score (DDS): 0.036
Past Year
  • Commits: 2
  • Committers: 2
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.5
Top Committers
Name Email Commits
georgebv g****7@g****m 161
Mathew Shen d****r@g****m 3
eastjames 4****s 1
connortann 7****n 1
Henrik Andersson j****n@d****m 1
Committer Domains (Top 20 + Academic)
dhigroup.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 28
  • Total pull requests: 24
  • Average time to close issues: 2 months
  • Average time to close pull requests: 6 days
  • Total issue authors: 22
  • Total pull request authors: 7
  • Average comments per issue: 2.75
  • Average comments per pull request: 1.25
  • Merged pull requests: 20
  • Bot issues: 0
  • Bot pull requests: 2
Past Year
  • Issues: 5
  • Pull requests: 2
  • Average time to close issues: about 8 hours
  • Average time to close pull requests: about 3 hours
  • Issue authors: 5
  • Pull request authors: 2
  • Average comments per issue: 1.0
  • Average comments per pull request: 1.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • wiz21b (3)
  • Goddysen (2)
  • DamienIrving (2)
  • dhirendrajnu (1)
  • bbalaji-ucsd (1)
  • Lqs66 (1)
  • TanguyRiou (1)
  • nucflash (1)
  • kuhnfe (1)
  • tch521 (1)
  • jtoilliez (1)
  • jultou-raa (1)
  • eastjames (1)
  • ghost (1)
  • Yun-Tianming (1)
Pull Request Authors
  • georgebv (16)
  • jschueller (4)
  • shenxiangzhuang (3)
  • connortann (2)
  • dependabot[bot] (2)
  • rsignell (1)
  • eastjames (1)
  • ecomodeller (1)
Top Labels
Issue Labels
enhancement (12) bug (6) question (3)
Pull Request Labels
dependencies (3) bug (2) enhancement (1)

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 4,844 last-month
  • Total dependent packages: 1
    (may contain duplicates)
  • Total dependent repositories: 2
    (may contain duplicates)
  • Total versions: 31
  • Total maintainers: 1
pypi.org: pyextremes

Extreme Value Analysis (EVA) in Python

  • Versions: 22
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 4,844 Last month
Rankings
Dependent packages count: 3.2%
Stargazers count: 5.1%
Downloads: 6.4%
Forks count: 6.6%
Average: 8.7%
Dependent repos count: 22.1%
Maintainers (1)
georgebv
Last synced: 6 months ago
conda-forge.org: pyextremes

pyextremes is a Python library aimed at performing univariate Extreme Value Analysis (EVA).

  • Versions: 9
  • Dependent Packages: 0
  • Dependent Repositories: 1
Rankings
Dependent repos count: 24.1%
Stargazers count: 29.2%
Forks count: 30.6%
Average: 33.9%
Dependent packages count: 51.5%
Last synced: 6 months ago

Dependencies

.github/workflows/lint.yml actions
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.github/workflows/build_docs.yml actions
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.github/workflows/publish.yml actions
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  • actions/checkout v3 composite
  • actions/setup-python v4 composite
.github/workflows/test.yml actions
  • actions/cache v3 composite
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  • actions/setup-python v4 composite
  • codecov/codecov-action v3 composite
poetry.lock pypi
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  • emcee 3.1.3
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  • packaging 23.0
  • pandas 1.5.2
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  • python-dateutil 2.8.2
  • pytz 2022.7.1
  • scipy 1.9.3
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pyproject.toml pypi
  • emcee ^3.0.3
  • matplotlib ^3.3.0
  • numpy ^1.19.0
  • pandas ^1.0.0
  • python ^3.8
  • scipy ^1.5.0
  • tqdm ^4.0.0