Metadata-Version: 2.1
Name: lcode
Version: 0.2.0
Summary: LCODE is a free software for simulationplasma wakefield acceleration based on QSA.
Home-page: https://lcode.info
Download-URL: https://github.com/lcodePy-team/lcodePy
Author: lcodePy-team
Author-email: team@lcode.info
License: BSD-3-Clause-extended
Keywords: plasma wakefield acceleration,quasistatic approximation,numerical simulation
Classifier: Programming Language :: Python
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Environment :: Console
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numba
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: mpi4py

# lcodePy

## Overview 

LCODE is a free software for numerical simulation of
particle beam-driven plasma wakefield acceleration.
LCODE is based on the quasistatic approximation, capable
of simulation in 2D and 3D geometry, and can use GPUs and CPUs.

For now, this is new and experimental software. This is
a complete overhaul of the old C version in Python.

You can also find a more mature 2D version of LCODE at
http://lcode.info/.

## Instalation 

We use [Anaconda](https://www.continuum.io/why-anaconda) and we recommend 
installing lcode in a separate environment. 
Any other python installation should work fine, but has not been tested. 


- Create a new environment and install the dependencies:
```
conda create -n lcode-env -c conda-forge numba numpy scipy matplotlib mpi4py
```
or 
```
conda env create -f conda-env.yml  
```
where `conda-env.yml` is avalible in sources.

- Acivate the new environment:
```
conda activate lcode-env
```

- **Optional**: in order to run simulations on GPU, add cupy and other necessary packages to the line of dependencies when creating a new eviroment. Check in advance if you have the drivers for your GPU installed. It is not necessary to install CUDA Toolkit in advance. For any other questions about cupy, please check https://docs.cupy.dev/en/stable/install.html
```
conda create -n lcode-env -c conda-forge numba numpy scipy matplotlib cupy
```

- Install lcode:
```
pip install lcode
```
or download sources from GitHub and run the forlowing command
in downloaded directory:
```
pip install .
```


----------

Fill free to contact `team@lcode.info` for assistance with it.

