See documentation for tutorials and documentation.
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 Python3 to automate the following tasks:
Tutorial and Examples
- Download miniconda for python3: miniconda (also you can install the complete anaconda version).
- Install according to: installConda.
- Create a new virtual environment using the following commands:
conda create -n qmflows
- Activate the new virtual environment
source activate qmflows
To exit the virtual environment type
Type in your terminal:
conda activate qmflows
Using the conda environment the following packages should be installed:
Finally install the package:
- Install QMFlows using pip:
pip install git+https://github.com/SCM-NV/qmflows@master#egg=qmflows
Now you are ready to use qmflows.
- Once the libraries and the virtual environment are installed, you only need to type
conda activate qmflowseach time that you want to use the software.