Parallel Transient Simulation in Water Networks
Project description
Parallel Transient Simulation in Water Networks
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Getting Started
To get a local copy up and running follow these simple steps. PTSNET can be downloaded via pip
Prerequisites
We highly encourage using a conda environment for the installation
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Install conda
# Linux https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.html
# Windows https://conda.io/projects/conda/en/latest/user-guide/install/windows.html
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Basic dependencies
# Open the shell and type conda init conda create -n ptsnet python=3.6 # create conda environment conda activate ptsnet conda install numpy matplotlib pandas scipy conda install -c conda-forge tqdm conda install -c conda-forge wntr
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Dependencies for parallelization
conda install openmpi conda install openmpi-mpicc conda install -c conda-forge mpi4py # Install parallel HDF5 wget https://support.hdfgroup.org/ftp/HDF5/current/src/hdf5-1.10.5.tar tar xvf hdf5-1.10.5.tar cd hdf5-1.10.5 ./configure --enable-shared --enable-parallel CC=mpicc MPICCc=mpiccmake make install # Install h5py CC="mpicc" HDF5_MPI="ON" HDF5_DIR=/path/to/parallel-hdf5 pip install --no-binary=h5py h5py
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Install ptsnet
pip install ptsnet
Installation
- Clone the repo
git clone https://github.com/gandresr/PTSNET.git
- Install NPM packages
npm install
Usage
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For more examples, please refer to the Documentation
License
Distributed under the Unlicense License. See LICENSE
for more information.
Contact
Gerardo Riano - griano@utexas.edu
Project Link: https://github.com/gandresr/PTSNET
Acknowledgements
This publication was developed under Cooperative Agreement No. 83595001 awarded by the U.S. Environmental Protection Agency to The University of Texas at Austin. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors, and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper. URL: http://www.tacc.utexas.edu
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