source

Welcome

PSimPy (Predictive and probabilistic simulation with Python) implements a Gaussian process emulation-based framework that enables systematically and efficiently performing uncertainty-related analyses of physics-based models, which are often computationlly expensive. Examples are variance-based global sensitvity analysis, uncertainty quantification, and parameter calibration.

Installation

:py:mod:`PSimPy` is a pure Python package. All Python-related dependencies are automatically taken care of. It should be noted that some modules rely on or use non-Python package and software. More specifically, the emulator module :py:mod:`robustgasp.py` relies on the R package RobustGaSP; the simulator module :py:mod:`ravaflow24.py` relies on the open source software r.avaflow 2.4.

If the simulator module :py:mod:`ravaflow24.py` is desired, you may follow the official r.avaflow User manual to install it. The installation of the R package RobustGaSP is covered in following steps.

We recommond you to install :py:mod:`PSimPy` in a virtual environment such as a conda environment. You may want to first install Anaconda or Miniconda if you haven't. The steps afterwards are as follows.

1. Create a conda environment with Python 3.9:

   conda create --name your_env_name python=3.9

2. Install R if you don't have it on your machine (if you have R, you can skip this step; alternatively, you can still follow this step to install R in the conda environment):

   conda activate your_env_name
   conda install -c conda-forge r-base=3.6

3. Install the R package RobustGaSP in the R terminal:

   R
   install.packages("RobustGaSP",repos="https://cran.r-project.org",version="0.6.4")

   Try if it is successfully installed by:

   library("RobustGaSP")

4. Configure the environment variable R_HOME so that rpy2 knows where to find R packages. You can find your R_HOME by typing the following command in the R terminal:

   R.home()
   q()

   It is a path like ".../lib/R". Set the environment variable R_HOME in your conda environment by:

   conda env config vars set R_HOME=your_R_HOME

   Afterwards reactivate your conda environment to make the change take effect by:

   conda deactivate
   conda activate your_env_name

5. Install :py:mod:`PSimPy` using pip in your conda environment by:

   conda install -c conda-forge pip
   pip install psimpy

Now you should have :py:mod:`PSimPy` and its dependencies successfully installed in your conda environment. You can use it in the Python terminal or in your Python IDE.

If you would like to use it with Jupyter Notebook (iPython Notebook), there is one extra step needed to set your conda environment on your Notebook:

6. Install ipykernel and install a kernel that points to your conda environment by:

   conda install -c conda-forge ipykernel
   python -m ipykernel install --user --name=your_env_name

Now you can start your Notebook, change the kernel to your conda environment, and use :py:mod:`PSimPy`.