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A time series data analysis toolbox: Markov State Model estimation and analysis.

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MCMM Project

Overview

A Markov State Model estimation and analysis toolbox for time series data inspired by msmtools and PyEMMA. Written in Python, mostly relying on numpy and scipy.

Contents

This package provides the following functionality:

  1. Basic data clustering (KMeans/KMeans++, Regspace, DBSCAN)
  2. Estimation of transition matrices from trajectory data
  3. Analysis functionality (eigenvalues/vectors, transition path theory, aperiodicity, irreducibility) for Markov State Models
  4. Visualization for clustering and analysis

Requirements:

numpy, msmtools>=1.0, matplotlib, scipy, pandas

Installation

Call python setup.py install from project directory. Alternatively, call

pip install git+https://github.com/Markov-Schmarkov/mcmm-project

to install from github.

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A time series data analysis toolbox: Markov State Model estimation and analysis.

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  • Python 68.7%
  • Jupyter Notebook 31.3%