A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
pygpc can be used to analyze a variety of different of problems. It is used for example in the frameworks of:
Nondestructive testing:
Noninvasive brain stimulation:
Transcranial magnetic stimulation:
Transcranial direct current stimulation:
Cancer treatment
If you use pygpc in your studies, please contact Konstantin Weise to extend the list above.
Installation using pip:
Pygpc can be installed via the pip
command with Python >= 3.6. Simply run the following command in your terminal:
pip install pygpc
If you want to use the plot functionalities of pygpc, please also install matplotlib and seaborn:
pip install matplotlib seaborn
Installation using the GitHub repository: Alternatively, it is possible to clone this repository and run the setup manually. This requires a compiler that supports OpenMP which is used by the C-extensions and NumPy for some headers. You can install NumPy by running the following command:
pip install numpy
Alternatively you can install the build dependencies with the following command:
pip install -r requirements.txt
Afterwards, pygpc can be installed by running the following line from the directory in which the repository was cloned:
python setup.py install
Installation of the CUDA backend:
Pygpc also provides a CUDA-backend to speed up some computations. To use the backend you need to build it manually. This requires the CUDA-toolkit and CMake.
CMake can be installd via the pip
command. Simply run the following command in your terminal:
pip install cmake
For the installation of the CUDA-toolkit, please refer to this website. If CMake and the CUDA-toolkit are installed on your machine you can build the extension with:
python build_pygpc_extensions_cuda.py
Troubleshooting for OSX:
On a Mac you need GCC to install pygpc. If you are using the brew
package manager you can simply run:
brew install gcc libomp
Then install pygpc with:
CC=gcc-9 CXX=g++-9 python setup.py install
Troubleshooting for Windows:
On windows you might need a compiler to install pygpc. To install the Visual C++ Build Tools
, please refer to this website.
For a full API of pygpc, see https://pygpc.readthedocs.io/en/latest/. For examplary simulations and model configurations, please have a look at the jupyter notebooks provided in the /tutorial folder and the templates in the /example folder.
If you use this framework, please cite:
If you have questions, problems or suggestions regarding pygpc, please contact Konstantin Weise.