Metadata-Version: 2.1
Name: pylsewave
Version: 1.0.1
Summary: A python package for pulse wave dynamics and/or any hyperbolic system of PDEs
Home-page: https://giorag.bitbucket.io/pylsewave/pyw_doc.html
Author: Georgios E. Ragkousis
Author-email: giorgosragos@gmail.com
License: GNU GPL v3.0
Description: # pylsewave
        
        ![pylsewavelogo](./doc/sphinx-rootdir/figures/pylsewave_logo64x64.png)
        
        # Repository structure
        
        ```bash
        .
        +-- doc # documentation directory
        +-- JupyterNbs # jupyter notebooks
        +-- data # input data for case studies
        +-- pylsewave # the package directory (contains all modules)
        +-- test # unit test files
        +. README.md
        +. LICENCE
        +. setup.py
        +. pyproject.toml
        +. Adan_77_example.py # case study for a whole arterial network (linear-elastic arterial walls)
        +. vtk_example.py (example with vtk)
        ```
        
        ### A Python package to solve pulse wave dynamics in arterial networks
        
        The following diagram depicts the rationale along with the structure of the package
        
        ![pylsewave toolkit](./JupyterNbs/images/pylsewave.png)
        
        A c/python library to solve 1D pulse wave propagation in blood vessels or any hyperbolic PDE system in the form of
        
        ![Hyperbolic system](https://latex.codecogs.com/gif.latex?%5Cfrac%7B%5Cpartial%20%5Cbf%7BU%7D%7D%7B%5Cpartial%20t%7D%20&plus;%20%5Cfrac%7B%5Cpartial%20%5Cbf%7BF%7D%7D%7B%5Cpartial%20x%7D%20%3D%20%5Cbf%7BS%7D)
        
        ### Purpose
        This library is designed to solve efficiently pulse wave dynamics in human arteries. It is written in python, cython and there are some bits of C++.
        
        ### Install pylsewave
        
        To install pylsewave toolkit, use pip:
        
        ```
        pip install pylsewave
        ```
        
        ### Run the example
        
        There are two examples in this directory:
        
        * Adan_77_example.py
        
        To run the case go to the top level directory of the repository and type:
        
        ```bash
        python Adan_77_example.py -ivesseldatafile data\Arterial_Network_ADAN56.txt -ibcinflowfile data\inflow_Aorta.txt -oresfile arterial_network_77_vessels -language py
        ```
        
        `NOTE: You can execute the file with python classes translated via cython by changing the -language py to -language cy.`
        
        * vtk_example.py
        
        This is an example for storing the results in vtk multiblock file. The user should install pyvtk first (it can be found on [PYPI](https://pypi.org/project/vtk/)).
        
        ```bash
        python vtk_example.py -resfile <resfile> -ovisfile <visfile>
        ```
        
        ### Examples in Jupyter notebooks
        
        There are several case studies in jupyter notebooks under `JupyterNbs` directory. To run the cases, the user should install jupyter either with conda or pip (see the latest install instructions`` in [Jupyter documentaion](https://jupyter.readthedocs.io/en/latest/install.html)):
        
        * conda
        
        ```bash
        conda install jupyter
        ```
        
        * pip
        
        ```bash
        pip install jupyter
        ```
        
        ### Build the docs
        
        To build the documentation, under the `docs` directory type (you will need sphinx):
        
        ```bash
        make html
        ```
        
        ### Cite pylsewave
        
        Prefered citation style for pylsewave:
        
        Georgios E. Ragkousis (2019). PylseWave: A python package to solve pulse wave dynamics in arterial networks. Zenodo. [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3426789.svg)](https://doi.org/10.5281/zenodo.3426789)
Keywords: pdes fdm pulsewave blood-vessels
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Environment :: Win32 (MS Windows)
Requires: numpy
Requires: scipy
Requires: matplotlib
Description-Content-Type: text/markdown
