Metadata-Version: 2.1
Name: CarnaPy
Version: 0.1.0
Summary: General-purpose real-time 3D visualization
Home-page: https://github.com/kostrykin/CarnaPy
Author: Leonid Kostrykin
Author-email: leonid.kostrykin@bioquant.uni-heidelberg.de
License: BSD
Description: CarnaPy
        ========
        
        The aim of this package is to provide real-time 3D visualization in Python for specifically, but not limited to, biomedical data. The library is based on [Carna](https://github.com/kostrykin/Carna).
        
        See [examples/kalinin2018.ipynb](examples/kalinin2018.ipynb) for an example.
        
        [![Anaconda-Server Badge](https://anaconda.org/kostrykin/carnapy/badges/version.svg)](https://anaconda.org/kostrykin/carnapy)
        [![Anaconda-Server Badge](https://anaconda.org/kostrykin/carnapy/badges/platforms.svg)](https://anaconda.org/kostrykin/carnapy)
        [![Anaconda-Server Badge](https://anaconda.org/kostrykin/carnapy/badges/installer/conda.svg)](https://conda.anaconda.org/kostrykin)
        
        ---
        ## Contents
        
        * [Limitations](#1-limitations)
        * [Dependencies](#2-dependencies)
        * [Installation](#3-installation)
        * [Build instructions](#4-build-instructions)
         
        ---
        ## 1. Limitations
        
        * Only 8bit and 16bit volume data are supported at the moment.
        * DRR renderings are not exposed to Python yet.
        * Build process is currently limited to Linux-based systems.
        
        ---
        ## 2. Dependencies
        
        Using the library requires the following dependencies:
        * [numpy](https://numpy.org/) ≥ 1.16
        * EGL driver support
        * OpenGL 3.3
        * Python ≥ 3.7
        
        The following dependencies must be satisfied for the build process:
        * [Carna](https://github.com/kostrykin/Carna) ≥ 3.1
        * [Eigen](http://eigen.tuxfamily.org/) ≥ 3.0.5
        * [libboost-iostreams](https://www.boost.org/doc/libs/1_76_0/libs/iostreams/doc/index.html)
        * [pybind11](https://github.com/pybind/pybind11)
        * EGL development files
        
        In addition, the following dependencies are required to run the test suite:
        * [matplotlib](https://matplotlib.org/)
        * [scipy](https://www.scipy.org/)
        
        ---
        ## 3. Installation
        
        The easiest way to install and use the library is to use one of the binary [Conda](https://docs.anaconda.com/anaconda/install/) packages:
        
        ```bash
        conda install -c kostrykin carnapy
        ```
        
        Conda packages are available for Python 3.7–3.9.
        
        ---
        ## 4. Build instructions
        
        Assuming you are using a recent version of Ubuntu:
        
        ```bash
        sudo apt-get -qq install libegl1-mesa-dev libboost-iostreams-dev
        ```
        
        Create and activate a Conda environment to work in, then:
        
        ```bash
        conda install -c conda-forge pybind11
        ```
        
        Grab a recent version of [Eigen](http://eigen.tuxfamily.org), unpack it, and tell CMake where it is located:
        
        ```bash
        wget https://gitlab.com/libeigen/eigen/-/archive/3.2.10/eigen-3.2.10.tar.gz
        tar -vzxf eigen-3.2.10.tar.gz -C /tmp/
        export CMAKE_PREFIX_PATH="/tmp/eigen-3.2.10:$CMAKE_PREFIX_PATH"
        ```
        
        If you have not already, download, build, and install Carna:
        
        ```bash
        git clone git@github.com:kostrykin/Carna.git build_carna
        cd build_carna
        sh linux_build.sh
        ```
        
        Now it is time to build, package, and install CarnaPy:
        ```
        cd ..
        python setup.py build
        python setup.py install
        ```
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: GPU
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: C++
Classifier: Programming Language :: Python
Classifier: Topic :: Education
Classifier: Topic :: Multimedia :: Graphics :: 3D Rendering
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: User Interfaces
Description-Content-Type: text/markdown
