Python 3.6 or newer.
A C++ compiler that supports C++11.
The easiest way to install KLIFF is using a package manager, do either
$ conda intall -c conda-forge kliff
$ pip install kliff
Alternatively, you can install from source:
$ git clone https://github.com/openkim/kliff $ pip install ./kliff
kim-api can be installed via conda:
$ conda install -c conda-forge kim-api
Other installation methods are provided at kim-api; refer to the instructions there for more information.
After installation, you can do
$ kim-api-collections-management list.
If you see a list of directories where the KIM model drivers and models are
placed, then you are good to go. Otherwise, you may forget to set up the
PATH and bash completions, which can be achieved by (assuming you are
$ source path/to/the/kim/library/bin/kim-api-activate. See
the kim-api documentation for more information.
$ conda-install -c conda-forge kimpy
$ pip install kimpy
For machine learning potentials, KLIFF takes advantage of PyTorch to build neural network models and conduct the training. So if you want to train neural network potentials, PyTorch needs to be installed. Please follow the instructions given on the official PyTorch website to install it.