# Fluidsim documentation¶

Fluidsim is a framework for studying fluid dynamics with numerical simulations using Python. It is part of the wider project FluidDyn.

Fluidsim is an object-oriented library to develop solvers (mainly using pseudo-spectral methods) by writing mainly Python code. The result is really efficient compared to a pure Fortran or C++ code since the time-consuming tasks are performed by optimized compiled functions.

Fluidsim is a HPC code written mostly in Python. It uses the library fluidfft to use very efficient FFT libraries. Fluidfft is written in C++, Cython and python. Fluidfft and fluidsim take advantage of Pythran, a new static Python compiler which produces very efficient binaries by compiling Python via C++11.

An advantage of a CFD code written mostly in Python is that to run simulations and analyze the results, the users communicate (possibly interactively) together and with the machine with Python, which is nowadays among the best languages to do these tasks. Moreover, it is much simpler and faster than with pure Fortran or C++ codes to add any complicate analysis or to write a modified solver.

We have created fluidsim to be easy and nice to use and to develop, efficient and robust.

At this stage, not many solvers have been written, but fluidsim can already solve these equations:

- In a two-dimensional periodic space:
- Incompressible Navier-Stokes equations,
- Stratified Navier-Stokes equations under the Boussinesq approximation with constant Brunt-Väisälä frequency,
- One-layer shallow-water equations + modified versions of these equations,
- Föppl-von Kármán equations (elastic thin plate)

- In a three-dimensional periodic space:
- Incompressible Navier-Stokes equations.

## User Guide¶

## Modules Reference¶

`fluidsim.base` |
Base classes for writing solvers |

`fluidsim.operators` |
Numerical operators |

`fluidsim.solvers` |
Particular solvers |

`fluidsim.util` |
Utilities for FluidSim |

## More¶

- Fluidsim forge on Bitbucket
- Fluidsim in PyPI
- Unittest coverage
- Continuous integration with travis