Metadata-Version: 2.1
Name: pytpt
Version: 0.0.1
Summary: Implementation of Transition Path Theory for stationary, periodically varying, and finite-time Markov chains.
Home-page: https://github.com/LuzieH/pytpt
Author: Luzie Helfmann and Enric Ribera Borrell
Author-email: luzie.helfmann@fu-berlin.de
License: UNKNOWN
Description: ﻿# PyTPT
        
        Implementation of Transition Path Theory for:
        - stationary Markov chains (pytpt/stationary.py),
        - for periodically varying Markov chains (pytpt/periodic.py),
        - for time-inhomogenous Markov chains over finite time intervals (pytpt/finite.py).
        
        Based on: 
        Helfmann, L., Ribera Borrell, E., Schütte, C., & Koltai, P. (2020). Extending Transition Path Theory: Periodically-Driven and Finite-Time Dynamics. [arXiv preprint arXiv:2002.07474.](https://arxiv.org/pdf/2002.07474.pdf)  
        
        ## PyTPT Package Installation
        1. Clone the project in a local repository: 
        `
        git clone https://github.com/LuzieH/pytpt.git
        `
        2. Add the package to your local python library:
        ` 
        pip install -e.
        ` 
         
        ## Quick Start (run examples)
        1. Clone the project in a local repository
        `
        git clone https://github.com/LuzieH/pytpt.git
        `
        \
        and install pytpt: 
        `
        pip install -e.
        `
        2. Install project requirements:
        ` 
        pip install -r requirements
        ` 
        3. Run small network example
        ```
        python examples/small_network_construction.py
        python examples/small_network_example.py
        python examples/small_network_plotting.py
        ``` 
        4. Run triplewell example
        ```
        python examples/triplewell_construction.py
        python examples/triplewell_example.py
        python examples/triplewell_plotting.py
        ``` 
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
