Research on modern computational quantum chemistry relies on a set of computational tools to carry out calculations. The complexity of the calculations usually requires intercommunication between the aforementioned tools, such communication is usually done through shell scripts that try to automate input/output actions like: launching the computations in a cluster, reading the resulting output and feeding the relevant numerical result to another program. Such scripts are difficult to maintain and extend, requiring a significant programming expertise to work with them. Being then desirable a set of automatic and extensible tools that allows to perform complex simulations in heterogeneous hardware platforms.
This library tackles the construction and efficient execution of computational chemistry workflows. This allows computational chemists to use the emerging massively parallel compute environments in an easy manner and focus on interpretation of scientific data rather than on tedious job submission procedures and manual data processing.
This library consists of a set of modules written in Python 3.5 to automate the following tasks:
First check that you have available in your system Python 3.5. Otherwise, you can download it from here. Because QMWorks depends on a set of libraries that are not pat of the python ecosystem, you need first to install these dependecies using a virtual-environment. Finally, you can proceed to the package installation
- Download miniconda for python 3.5: miniconda (also you can install the complete anaconda version).
- Install according to: installConda.
- Reopen terminal (or type
source ~/.bashrc
). - Create a new virtual environment using the following commands:
conda create -n qmworks python=3.5
- Activate the new virtual environment
source activate qmworks
To exit the virtual environment type source deactivate
.
Using the conda environment the following packages should be installed:
- install rdkit using the following command:
conda install -y -q --name qmworks -c https://conda.anaconda.org/rdkit rdkit
- install HDF5 using conda:
conda install -y -q --name qmworks -c anaconda hdf5
Type in your terminal,
source activate qmworks
Then
pip install https://github.com/SCM-NV/qmworks/tarball/master#egg=qmworks https://github.com/SCM-NV/plams/tarball/master#egg=plams --upgrade
Now you are ready to use qmworks.
Notes:
- Once the libraries and the virtual environment are installed, you only need to type
source activate qmworks
each time that you want to use the software.