Installation

DiffNets is currently under development, and cannot yet be installed with PyPI. Therefore, the install instructions are long-winded, but hopefully sufficiently explicit.

These instructions assume you have the python package manager `conda` installed.

Go to directory you would like diffnets (and enspara) to live in:

cd /desired/path/for/packages

Create a conda environment that will be used for diffnets:

conda create --name diffnets python=3.6

Enter this conda environment and install enspara:

conda activate diffnets
git clone https://github.com/bowman-lab/enspara
conda install -c conda-forge mdtraj=1.8.0
conda install numpy==1.14
conda install cython
conda install mpi4py -c conda-forge
cd enspara
pip install -e .

Check that enspara was installed successfully:

cd /any/random/directory
python
import enspara

Great! Now you have enspara installed, which is a dependency of diffnets but is also great on it’s own for clustering and building MSMs.

Return to /desired/path/for/packages and download diffnets:

cd /desired/path/for/packages
git clone https://github.com/bowman-lab/diffnets

Install pytorch

If you are installing on a mac or CPU only machine use this command. Note: Training is much slower on CPUs:

conda install pytorch torchvision -c pytorch

If you are installing on a cuda enabled GPU you will need cuda installed. Recommended to use cuda 10.1:

conda install pytorch torchvision cudatoolkit=10.1 -c pytorch

Install Click:

conda install click

Install diffnets:

cd diffnets
pip install -e .

Check that diffnets was installed successfully:

cd /any/random/directory
python
import diffnets

You now have diffnets installed. When using diffnets, remember to be in the proper conda environment! For example, run this before using diffnets:

conda activate diffnets