Skip to main content

Framework for studying fluid dynamics.

Project description

alt:

Heptapod CI

FluidDyn project is an ecosystem of packages for research and teaching in fluid dynamics. The Python package fluiddyn contains:

  • basic utilities to manage: File I/O for some esoteric formats, publication quality figures, job submission on clusters, MPI

  • powerful classes to handle: parameters, arrays, series of files

  • simplified interfaces to calculate: FFT, spherical harmonics

and much more. It is used as a library in the other specialized packages of the FluidDyn project (in particular in fluidfft, fluidsim, fluidlab and fluidimage).

Documentation: https://fluiddyn.readthedocs.io

Getting started

To try fluiddyn without installation: Binder notebook

Installation

The simplest way to install fluiddyn is by using pip:

pip install fluiddyn

You can also get the source code from https://foss.heptapod.net/fluiddyn/fluiddyn or from the Python Package Index. The development mode is often useful if you intend to modify fluiddyn. From the root directory:

pip install -e .[dev]

Requirements

Minimum

Python (>=3.6), numpy matplotlib h5py psutil

Full functionality

h5py h5netcdf pillow imageio mpi4py scipy pyfftw (requires FFTW library), SHTns

Optional

OpenCV with Python bindings, scikit-image

Note: Detailed instructions to install the above dependencies using Anaconda / Miniconda or in a specific operating system such as Ubuntu, macOS etc. can be found here.

Tests

With an editable installation, you can run the tests with:

pytest

Metapaper and citation

If you use any of the FluidDyn packages to produce scientific articles, please cite our metapaper presenting the FluidDyn project and the fluiddyn package:

@article{fluiddyn,
doi = {10.5334/jors.237},
year = {2019},
publisher = {Ubiquity Press,  Ltd.},
volume = {7},
author = {Pierre Augier and Ashwin Vishnu Mohanan and Cyrille Bonamy},
title = {{FluidDyn}: A Python Open-Source Framework for Research and Teaching in Fluid Dynamics
    by Simulations,  Experiments and Data Processing},
journal = {Journal of Open Research Software}
}

History

The FluidDyn project started in 2015 as the evolution of two packages previously developed by Pierre Augier (CNRS researcher at LEGI, Grenoble): solveq2d (a numerical code to solve fluid equations in a periodic two-dimensional space with a pseudo-spectral method, developed at KTH, Stockholm) and fluidlab (a toolkit to do experiments, developed in the G. K. Batchelor Fluid Dynamics Laboratory at DAMTP, University of Cambridge).

Keywords and ambitions: fluid dynamics research with Python (>= 3.6), modular, object-oriented, collaborative, tested and documented, free and open-source software.

License

FluidDyn is distributed under the CeCILL-B License, a BSD compatible french license.

Project details


Release history Release notifications | RSS feed

This version

0.5.2

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fluiddyn-0.5.2.tar.gz (259.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fluiddyn-0.5.2-py3-none-any.whl (149.4 kB view details)

Uploaded Python 3

File details

Details for the file fluiddyn-0.5.2.tar.gz.

File metadata

  • Download URL: fluiddyn-0.5.2.tar.gz
  • Upload date:
  • Size: 259.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.7

File hashes

Hashes for fluiddyn-0.5.2.tar.gz
Algorithm Hash digest
SHA256 0eb3319694e7b9ef53d038773bd2c1981a637e0d0e2d00be5a848390939254e6
MD5 e07226ef849edcaf10e9d7169fc1bed6
BLAKE2b-256 68cdf7f392be7e977b0caca3f67253ed8a1f26e34e133cc95f967e2a48b29434

See more details on using hashes here.

File details

Details for the file fluiddyn-0.5.2-py3-none-any.whl.

File metadata

  • Download URL: fluiddyn-0.5.2-py3-none-any.whl
  • Upload date:
  • Size: 149.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.7

File hashes

Hashes for fluiddyn-0.5.2-py3-none-any.whl
Algorithm Hash digest
SHA256 1a7ad00f7c72f87f9dff9244a291ac0a31714a8ba6ce4d69d25364a8465369bd
MD5 59ee7b45a9ea99ab9b8d2d3fc35d6739
BLAKE2b-256 0977c9d32ae789e4e25b3e72e8feb517bc9f5d81cedb5a4d20a5e876c6fc927c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page