User Guide

In this page you may found different tutorials and exercises that will help you in the usage of BigDFT. The BigDFT code is a standard executable that can be run from the command line by passing an input file. However, the preferred way to drive BigDFT calculations is from its high level PyBigDFT interface. PyBigDFT will allow you to construct the system you wish to study, perform calculations with the BigDFT code, and extract scientific data from the results.

Jupyter notebooks are interactive lab notebooks that can run python code. Each of the tutorials presented here is built as a jupyter notebook. We encourage you to test out these notebooks on your own computer and to build on top of them by copying one from the bigdft-doc folder of the code.

Environment Variables

Before running the code, you will want to configure your system path to include the bigdft executable and libraries. This can be accomplished with:

source install/bin/bigdftvars.sh

Before running the code, you might want to manually set a few more variables manually. The variable BIGDFT_MPIRUN is the mpirun command you wish to use (i.e. mpirun -np 2). OMP_NUM_THREADS should also be set if you wish to enable multithreading. Notice that in the case of a execution triggered from a Jupyter notebook the above command should be issued before the opening of the notebook session.

BigDFT Training Lessons

One way to start is to go through the lessons we prepared for CCPBioSim. These lessons are available in colab notebook form:

  1. Go here with your google account: https://colab.research.google.com/

  2. File-> Open Notebook - > GitHub

  3. BigDFT-group/bigdft-school

  4. Start from the Notebook 0.Installation.ipynb

Tutorials

This is the older set of tutorials.

Building Systems Programmatically

Running The Code

Examining and postprocessing the output

Interoperability With Other Codes

Lessons and Workflows

Last we share some in depth lessons which put BigDFT into practice.