Metadata-Version: 2.1
Name: lbmpy
Version: 0.3.3
Summary: Code Generation for Lattice Boltzmann Methods
Home-page: https://i10git.cs.fau.de/pycodegen/lbmpy/
Author: Martin Bauer
Author-email: martin.bauer@fau.de
License: AGPLv3
Description: lbmpy
        =====
        
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/mabau/lbmpy/master?filepath=doc%2Fnotebooks)
        [![Docs](https://img.shields.io/badge/read-the_docs-brightgreen.svg)](http://pycodegen.pages.i10git.cs.fau.de/lbmpy)
        [![pipeline status](https://i10git.cs.fau.de/pycodegen/lbmpy/badges/master/pipeline.svg)](https://i10git.cs.fau.de/pycodegen/lbmpy/commits/master)
        [![coverage report](https://i10git.cs.fau.de/pycodegen/lbmpy/badges/master/coverage.svg)](http://pycodegen.pages.i10git.cs.fau.de/lbmpy/coverage_report)
        
        
        Run fast fluid simulations based on the lattice Boltzmann method in Python on CPUs and GPUs.
        lbmpy creates highly optimized LB compute kernels in C or CUDA, for a wide variety of different collision operators, including MRT,
        entropic, and cumulant schemes.
        
        All collision operators can be easily adapted, for example, to integrate turbulence models, custom force terms, or multi-phase models. 
        It even comes with an integrated Chapman Enskog analysis based on sympy!
        
        Common test scenarios can be set up quickly:
        ```python
        from lbmpy.scenarios import create_channel
        
        ch = create_channel(domain_size=(300,100, 100), force=1e-7, method="trt",
                            equilibrium_order=2, compressible=True,
                            relaxation_rates=[1.97, 1.6], optimization={'target': 'gpu'})
        ```
        
        To find out more, check out the interactive [tutorial notebooks online with binder](https://mybinder.org/v2/gh/mabau/lbmpy/master?filepath=doc%2Fnotebooks).
        
        
        Installation
        ------------
        
        For local installation use pip:
        
        ```bash
        pip install lbmpy[interactive]
        ```
        
        
        Without `[interactive]` you get a minimal version with very little dependencies.
        
        All options:
        - `gpu`: use this if a NVIDIA GPU is available and CUDA is installed
        - `opencl`: use this to enable the target `opencl` (execution using OpenCL)
        - `alltrafos`: pulls in additional dependencies for loop simplification e.g. libisl
        - `interactive`: installs dependencies to work in Jupyter including image I/O, plotting etc.
        
        Options can be combined e.g.
        ```bash
        pip install lbmpy[interactive,gpu,doc]
        ```
        
        
        Documentation
        -------------
        
        Read the docs [here](http://pycodegen.pages.i10git.cs.fau.de/lbmpy) and
        check out the Jupyter notebooks in `doc/notebooks`. 
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Framework :: Jupyter
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: gpu
Provides-Extra: opencl
Provides-Extra: alltrafos
Provides-Extra: interactive
Provides-Extra: doc
Provides-Extra: phasefield
