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 first notebook 📓 in this tutorial guides through the basic analysis workflow using real MD data of a pentapeptide:
We keep the details minimal throughout the showcase but point to the more specialized notebooks which allow you to go in-depth on selected topics.
In detail, the remaining eight notebooks revisit all aspects shown in the showcase, provide additional details and variants, and contain exercises (and solutions) to self-check your learning progress:
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
After installing miniconda, you can install the tutorial either via
conda create -n pyemma_tutorials -c conda-forge pyemma_tutorials
... or you can also install the tutorial in an existing environment by
conda install -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
If you wish to install the tutorial manually, you will need the following packages (including all their dependencies):
pyemma
mdshare
nglview
nbexamples
jupyter_contrib_nbextensions
This can be done, for example, with conda:
conda install -c conda-forge pyemma mdshare nglview nbexamples jupyter_contrib_nbextensions
After installing jupyter_contrib_nbextensions
, you need to activate the toc2
and exercise2
extensions:
jupyter nbextension enable toc2/main
jupyter nbextension enable exercise2/main
Now all remains is to clone the repository to get the tutorial notebooks:
git clone https://github.com/markovmodel/pyemma_tutorials.git
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 # skip this, if you have installed in your root environment or used pip to install.
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.
If you have a manual installation, move to the repository's notebook directory...
cd path_to_pyemma_tutorials/notebooks
... and start the notebook server there:
jupyter notebook
To uninstall you can remove the whole environment which will also uninstall the contained software again:
conda env remove -n pyemma_tutorials
or if you have installed the package directly
conda remove pyemma_tutorials