pysteps

Python framework for short-term ensemble prediction systems.

Science Score: 77.0%

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

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DOI references
Found 6 DOI reference(s) in README
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Academic publication links
Links to: zenodo.org
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1 of 35 committers (2.9%) from academic institutions
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Scientific vocabulary similarity
Low similarity (11.0%) to scientific vocabulary

Keywords

advection ensemble-prediction forecast-verification hydrology nowcasting optical-flow precipitation rainfall rainfall-prediction stochastic-processes weather weather-radar

Keywords from Contributors

atmospheric-modelling meteorology

Last synced: 6 months ago · JSON representation ·

Repository

Python framework for short-term ensemble prediction systems.

Basic Info

Host: GitHub
Owner: pySTEPS
License: bsd-3-clause
Language: Python
Default Branch: master
Homepage: https://pysteps.github.io/
Size: 3.54 MB

Statistics

Stars: 514
Watchers: 17
Forks: 180
Open Issues: 57
Releases: 36

Topics

advection ensemble-prediction forecast-verification hydrology nowcasting optical-flow precipitation rainfall rainfall-prediction stochastic-processes weather weather-radar

Created over 7 years ago · Last pushed 7 months ago

Metadata Files

Readme Contributing License Citation

README.rst

pysteps - Python framework for short-term ensemble prediction systems
=====================================================================

.. start-badges

.. list-table::
    :stub-columns: 1
    :widths: 10 90

    * - docs
      - |stable| |colab| |gallery|
    * - status
      - |test| |docs| |codecov| |codacy| |black|
    * - package
      - |github| |conda| |pypi| |zenodo|
    * - community
      - |contributors| |downloads| |license|


.. |docs| image:: https://readthedocs.org/projects/pysteps/badge/?version=latest
    :alt: Documentation Status
    :target: https://pysteps.readthedocs.io/

.. |test| image:: https://github.com/pySTEPS/pysteps/workflows/Test%20pysteps/badge.svg
    :alt: Test pysteps
    :target: https://github.com/pySTEPS/pysteps/actions?query=workflow%3A"Test+Pysteps"

.. |black| image:: https://github.com/pySTEPS/pysteps/workflows/Check%20Black/badge.svg
    :alt: Check Black
    :target: https://github.com/pySTEPS/pysteps/actions?query=workflow%3A"Check+Black"

.. |codecov| image:: https://codecov.io/gh/pySTEPS/pysteps/branch/master/graph/badge.svg
    :alt: Coverage
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.. |github| image:: https://img.shields.io/github/release/pySTEPS/pysteps.svg
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    :alt: Latest github release

.. |conda| image:: https://anaconda.org/conda-forge/pysteps/badges/version.svg
    :target: https://anaconda.org/conda-forge/pysteps
    :alt: Anaconda Cloud

.. |pypi| image:: https://badge.fury.io/py/pysteps.svg
    :target: https://pypi.org/project/pysteps/
    :alt: Latest PyPI version

.. |license| image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg
    :alt: License
    :target: https://opensource.org/licenses/BSD-3-Clause

.. |contributors| image:: https://img.shields.io/github/contributors/pySTEPS/pysteps
    :alt: GitHub contributors
    :target: https://github.com/pySTEPS/pysteps/graphs/contributors

.. |downloads| image:: https://img.shields.io/conda/dn/conda-forge/pysteps
    :alt: Conda downloads
    :target: https://anaconda.org/conda-forge/pysteps

.. |colab| image:: https://colab.research.google.com/assets/colab-badge.svg
    :alt: My first nowcast
    :target: https://colab.research.google.com/github/pySTEPS/pysteps/blob/master/examples/my_first_nowcast.ipynb

.. |gallery| image:: https://img.shields.io/badge/example-gallery-blue.svg
    :alt: pysteps example gallery
    :target: https://pysteps.readthedocs.io/en/stable/auto_examples/index.html
    
.. |stable| image:: https://img.shields.io/badge/docs-stable-blue.svg
    :alt: pysteps documentation
    :target: https://pysteps.readthedocs.io/en/stable/
    
.. |codacy| image:: https://api.codacy.com/project/badge/Grade/6cff9e046c5341a4afebc0347362f8de
   :alt: Codacy Badge
   :target: https://app.codacy.com/gh/pySTEPS/pysteps?utm_source=github.com&utm_medium=referral&utm_content=pySTEPS/pysteps&utm_campaign=Badge_Grade

.. |zenodo| image:: https://zenodo.org/badge/140263418.svg
   :alt: DOI
   :target: https://zenodo.org/badge/latestdoi/140263418

.. end-badges

What is pysteps?
================

Pysteps is an open-source and community-driven Python library for probabilistic precipitation nowcasting, i.e. short-term ensemble prediction systems.

The aim of pysteps is to serve two different needs. The first is to provide a modular and well-documented framework for researchers interested in developing new methods for nowcasting and stochastic space-time simulation of precipitation. The second aim is to offer a highly configurable and easily accessible platform for practitioners ranging from weather forecasters to hydrologists.

The pysteps library supports standard input/output file formats and implements several optical flow methods as well as advanced stochastic generators to produce ensemble nowcasts. In addition, it includes tools for visualizing and post-processing the nowcasts and methods for deterministic, probabilistic, and neighbourhood forecast verification.


Quick start
-----------

Use pysteps to compute and plot a radar extrapolation nowcast in Google Colab with `this interactive notebook `_.

Installation
============

The recommended way to install pysteps is with `conda `_ from the conda-forge channel::

    $ conda install -c conda-forge pysteps

More details can be found in the `installation guide `_.

Usage
=====

Have a look at the `gallery of examples `__ to get a good overview of what pysteps can do.

For a more detailed description of all the available methods, check the  `API reference `_ page.

Example data
============

A set of example radar data is available in a separate repository: `pysteps-data `_.
More information on how to download and install them is available `here `_.

Contributions
=============

*We welcome contributions!*

For feedback, suggestions for developments, and bug reports please use the dedicated `issues page `_.

For more information, please read our `contributors guidelines `_.


Reference publications
======================

The overall library is described in

Pulkkinen, S., D. Nerini, A. Perez Hortal, C. Velasco-Forero, U. Germann,
A. Seed, and L. Foresti, 2019:  Pysteps:  an open-source Python library for
probabilistic precipitation nowcasting (v1.0). *Geosci. Model Dev.*, **12 (10)**,
4185–4219, doi:`10.5194/gmd-12-4185-2019 `_.

While the more recent blending module is described in

Imhoff, R.O., L. De Cruz, W. Dewettinck, C.C. Brauer, R. Uijlenhoet, K-J. van Heeringen, 
C. Velasco-Forero, D. Nerini, M. Van Ginderachter, and A.H. Weerts, 2023:
Scale-dependent blending of ensemble rainfall nowcasts and NWP in the open-source
pysteps library. *Q J R Meteorol Soc.*, 1-30,
doi: `10.1002/qj.4461 `_.


Contributors
============

.. image:: https://contrib.rocks/image?repo=pySTEPS/pysteps
   :target: https://github.com/pySTEPS/pysteps/graphs/contributors

Owner

Name: pySTEPS
Login: pySTEPS
Kind: organization

Website: https://pysteps.github.io/
Repositories: 5
Profile: https://github.com/pySTEPS

The nowcasting initiative

Citation (CITATION.bib)

@Article{gmd-12-4185-2019,
  AUTHOR = {Pulkkinen, S. and Nerini, D. and P\'erez Hortal, A. A. and Velasco-Forero, C. and Seed, A. and Germann, U. and Foresti, L.},
  TITLE = {Pysteps: an open-source Python library  for probabilistic precipitation nowcasting (v1.0)},
  JOURNAL = {Geoscientific Model Development},
  VOLUME = {12},
  YEAR = {2019},
  NUMBER = {10},
  PAGES = {4185--4219},
  URL = {https://gmd.copernicus.org/articles/12/4185/2019/},
  DOI = {10.5194/gmd-12-4185-2019}
}
@article{qj.4461,
  AUTHOR = {Imhoff, Ruben O. and De Cruz, Lesley and Dewettinck, Wout and Brauer, Claudia C. and Uijlenhoet, Remko and van Heeringen, Klaas-Jan and Velasco-Forero, Carlos and Nerini, Daniele and Van Ginderachter, Michiel and Weerts, Albrecht H.},
  TITLE = {Scale-dependent blending of ensemble rainfall nowcasts and NWP in the open-source pysteps library},
  JOURNAL = {Quarterly Journal of the Royal Meteorological Society},
  VOLUME = {n/a},
  NUMBER = {n/a},
  YEAR = {2023},
  PAGES ={1--30},
  DOI = {https://doi.org/10.1002/qj.4461},
  URL = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.4461},
}

GitHub Events

Total

Create event: 26
Release event: 6
Issues event: 36
Watch event: 51
Delete event: 14
Issue comment event: 194
Push event: 142
Pull request event: 43
Pull request review event: 145
Pull request review comment event: 143
Fork event: 11

Last Year

Create event: 26
Release event: 6
Issues event: 36
Watch event: 51
Delete event: 14
Issue comment event: 194
Push event: 142
Pull request event: 43
Pull request review event: 145
Pull request review comment event: 143
Fork event: 11

Committers

Last synced: 7 months ago

All Time

Total Commits: 1,438
Total Committers: 35
Avg Commits per committer: 41.086
Development Distribution Score (DDS): 0.563

Past Year

Commits: 45
Committers: 12
Avg Commits per committer: 3.75
Development Distribution Score (DDS): 0.578

Top Committers

Name	Email	Commits
ned	d**i@m**h	629
Seppo Pulkkinen	p**s@g**m	514
Andres Perez Hortal	a**a@g**m	100
Carlos Velasco	c**o@b**u	53
Ruben Imhoff	3****f	34
lforesti	l**i@m**h	32
Seppo Pulkkinen	s**n@f**i	27
mats-knmi	1****i	7
Simon De Kock	s**k@v**e	4
EsmailGhaemi	4****i	3
Monika Feldmann	m**n@e**h	3
mpvginde	8****e	3
Jenna Ritvanen	j**n@f**i	3
Petteri Karsisto	p**o@f**i	2
Daan Buekenhout	7****t	2
Lesley De Cruz	l**z@m**e	2
chiara-arpae	7****e	2
tjniemi	t**i@a**i	1
Jussi Tiira	j**a@h**i	1
vklaus	7****h	1
Aleksei Rutkovskii	7****i	1
Codacy Badger	b**r@c**m	1
Coder_Hong	f**9@g**m	1
FelixE91	f**n@m**e	1
Joep1999	1****9	1
Katelyn FitzGerald	7****d	1
NathalieRombeek	1****k	1
Petteri Karsisto	3****s	1
Simon Beylat	7****t	1
Viktor VN	v**r@g**m	1
and 5 more...

Committer Domains (Top 20 + Academic)

fmi.fi: 3 meteo.be: 2 meteoswiss.ch: 2 codacy.com: 1 helsinki.fi: 1 aalto.fi: 1 epfl.ch: 1 vub.be: 1 bom.gov.au: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 205
Total pull requests: 350
Average time to close issues: 2 months
Average time to close pull requests: about 1 month
Total issue authors: 67
Total pull request authors: 41
Average comments per issue: 2.88
Average comments per pull request: 3.32
Merged pull requests: 297
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 27
Pull requests: 55
Average time to close issues: 7 days
Average time to close pull requests: 10 days
Issue authors: 14
Pull request authors: 8
Average comments per issue: 0.48
Average comments per pull request: 5.42
Merged pull requests: 46
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

dnerini (37)
ladc (21)
pulkkins (20)
RubenImhoff (11)
Fangyh09 (9)
aperezhortal (9)
mats-knmi (9)
sidekock (6)
5fcgdaeb (4)
mpvginde (4)
meteoswiss-mdr (3)
HY-10 (3)
pkars (3)
miaoneng (2)
winash12 (2)

Pull Request Authors

dnerini (100)
RubenImhoff (45)
aperezhortal (39)
mats-knmi (29)
cvelascof (24)
pulkkins (20)
sidekock (12)
ladc (6)
EsmailGhaemi (6)
gjm174 (6)
ritvje (5)
aitaten (5)
loforest (4)
mpvginde (4)
feldmann-m (4)

Top Labels

Issue Labels

enhancement (35) bug (28) discussion (14) low priority (8) medium priority (8) support (7) documentation (5) good first issue (5) high priority (4) question (4) help wanted (4) wontfix (1) release (1)

Pull Request Labels

enhancement (38) documentation (11) bug (7) help wanted (3) low priority (1) medium priority (1) discussion (1) good first issue (1)

Packages

Total packages: 4
Total downloads:
- pypi 3,143 last-month

Total dependent packages: 1
(may contain duplicates)
Total dependent repositories: 5
(may contain duplicates)
Total versions: 112
Total maintainers: 3

pypi.org: pysteps

Python framework for short-term ensemble prediction systems

Homepage: https://pysteps.github.io/
Documentation: https://pysteps.readthedocs.io
License: LICENSE
Latest release: 1.18.1
published 7 months ago

Versions: 33
Dependent Packages: 1
Dependent Repositories: 4
Downloads: 3,143 Last month

Rankings

Dependent packages count: 3.2%

Stargazers count: 3.3%

Forks count: 4.1%

Average: 5.1%

Downloads: 7.4%

Dependent repos count: 7.6%

Maintainers (3)

aperezhortal dnerini pulkkins

Last synced: 6 months ago

proxy.golang.org: github.com/pysteps/pysteps

Documentation: https://pkg.go.dev/github.com/pysteps/pysteps#section-documentation
License: bsd-3-clause
Latest release: v1.18.1
published 7 months ago

Versions: 31
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.4%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 6 months ago

proxy.golang.org: github.com/pySTEPS/pysteps

Documentation: https://pkg.go.dev/github.com/pySTEPS/pysteps#section-documentation
License: bsd-3-clause
Latest release: v1.18.1
published 7 months ago

Versions: 31
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.4%

Average: 5.6%

Dependent repos count: 5.8%

Last synced: 6 months ago

conda-forge.org: pysteps

pySTEPS is a community-driven initiative for developing and maintaining an easy to use, modular, free and open-source Python framework for short-term ensemble prediction systems.

Homepage: https://pysteps.github.io/
License: BSD-3-Clause
Latest release: 1.7.1
published over 3 years ago

Versions: 17
Dependent Packages: 0
Dependent Repositories: 1

Rankings

Forks count: 15.9%

Stargazers count: 21.4%

Dependent repos count: 24.1%

Average: 28.3%

Dependent packages count: 51.5%

Last synced: 6 months ago

Dependencies

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actions/checkout v3 composite
actions/setup-python v4 composite

.github/workflows/python-publish.yml actions

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.github/workflows/test_pysteps.yml actions

actions/checkout v3 composite
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mamba-org/provision-with-micromamba main composite

doc/requirements.txt pypi

pandas *
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sphinx-book-theme *
sphinx_gallery *
sphinxcontrib.bibtex *

requirements.txt pypi

jsmin *
jsonschema *
matplotlib *
netCDF4 *
numpy *
opencv-python *
pillow *
pyproj *
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requirements_dev.txt pypi

cartopy >=0.18 development
dask * development
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numpy * development
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pyfftw * development
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pytest * development
python >=3.7 development
rasterio * development
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scipy * development

pyproject.toml pypi

setup.py pypi

environment.yml conda

jsmin
jsonschema
matplotlib
netcdf4
numpy
opencv
pillow
pyproj
python >=3.9
scipy