This work is licensed under a Creative Commons Attribution 4.0 International License.

PyEMMA (EMMA = Emma's Markov Model Algorithms) is an open source Python/C package for analysis of extensive molecular dynamics (MD) simulations.

The notebooks in this tutorial guide through the necessary steps to analyze simulation data and provide exercises (and solutions). In detail the first four notebooks introduce to most common steps of a PyEMMA analysis pipeline:

1. extracting features and loading data
2. dimension reduction and discretization
3. Markov state model (MSM) estimation and validation
4. MSM coarse graining and analysis

The notebooks after that provide a more in-depth introduciton to special features of MSMs/PyEMMA:

5. hidden Markov state models (HMMs)
6. computing observables
7. VAMP-based feature selection
8. common pitfalls with bad data

Please note that this is a work in progress and we value any kind of feedback that helps us improving this tutorial.

We recommended to install the PyEMMA tutorials with conda. The following command will create a new environment that comes with all the dependencies of the tutorial.

If you do not have conda, please follow the instructions here:

https://conda.io/miniconda.html

conda create -n pyemma_tutorials -c conda-forge pyemma_tutorials

If you intend to install with pip, for which can not give any support, you feel free to run:

pip install git https://github.com/markovmodel/pyemma_tutorials

Now we have a fresh conda environment containing the notebooks and the software to run them. We can now just activate the environment and run the notebook server by invoking:

conda activate pyemma_tutorials
pyemma_tutorials

The last command will start the notebook server and your browser should pop up pointing to a list of notebooks. You can choose either to preview or to create your own copy of the notebook. The latter will create a copy of the chosen notebook in your home directory, so your changes will not be lost after shutting down the notebook server.

To uninstall you can remove the whole environment which will also uninstall the contained software again:

conda env remove -n pyemma_tutorials