The Kallisto software enables the efficient calculation of atomic features that can be used within a quantitative structure-activity relationship (QSAR) approach. Furthermore, several modelling helpers are implemented.
Project description
Table of Contents
- Full Author List
- Introduction
- Installation
- Reference
Full Author List
Eike Caldeweyher and Philipp Pracht
Introduction
We developed the kallisto
program for the efficient and robust calculation of atomic features using molecular geometries either in a xmol
or a Turbomole
format.
Furthermore, several modelling tools are implemented, e.g., to calculate root-mean squared deviations via quaternions (including rotation matrices), sorting of molecular geometries and many more. All features of kallisto
are described in detail within our documentation (GitBook repository).
Installation from PyPI
To install kallisto
via pip
use our published PyPI package
pip install kallisto
Installation from Source
kallisto
runs on python3
Python development setup. Install the pyenv
python version manager:
curl https://pyenv.run | bash
and add this to the ~/.bashrc
and source it:
export PATH="~/.pyenv/bin:$PATH"
eval "$(pyenv init -)"
eval "$(pyenv virtualenv-init -)"
Install the latest python versions:
pyenv install 3.8.2
pyenv install 3.7.7
pyenv local 3.8.2 3.7.7
Now we are ready to set up kallisto
.
Clone the repository:
git clone git@github.com:AstraZeneca/kallisto.git
Install a python dependency manager. We choose to go with poetry
:
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
source ~/.poetry/env
or alternatively via pip
:
pip install --user poetry
Now, if you haven't already done so, change into the cloned kallisto
directory and
download the dependencies via poetry
:
cd kallisto
poetry install
Finally install the test automation environment nox
via pip
:
pip install --user --upgrade nox
Run nox
to test the setup.
Reference
tba
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