BigDFT-suite manifesto

The code is not a monolithic piece of software but a collection of independent packages that may be installed independently. The Installer script has been designed for the purpose.

Tips for developers

Choose the correct package in which to insert the developments

The first question to ask yourself is the generality of the functionality you are going to implement. The spirit is to work at the lowest possible level for a given task. The idea is to make available the functionality also to other potential users of the BigDFT-suite subpackages. This will also help in a better structure of the API of each package.

For instance, suppose you would like to implement a continuum solvent cavity determination for a particular DFT run of a molecular system. The correct level of development in this case would be the psolver package, as this is presently dealing with continuum solvents and cavities.

For a general overview one might say that:

  • futile deals with low-level functionalities like stdlib (but for FORTRAN). New MPI wrappers, strategies for memory copy and allocations should be implemented there.
  • at_lab library (will) deal with all the operations which are associated to position
  • <to_B_continued>

Read the coding rules

For some inspiration on coding style and strategies, read this.

Document the API of the high-level routines


write something here

Create a test for the functionality

Each of the packages has its own continuous integration procedure, refer to it for a suitable implementation.

  • futile, psolver: F_REGTEST_INSTRUCTION (to be documented)
  • bigdft see here.

Make a notebook which demonstrates the functionality in PyBigDFT

For each new high level functionality, you should create a jupyter notebook which demonstrates the new capability. The idea is to ensure continuity and to help acquaint users with the new feature. Some examples of notebooks can be found on github.

Insert the notebook as a tutorial in the PyBigDFT documentation

Once an appropriate notebook has been written, this should be added to the tutorial directory (BIGDFT_ROOT/PyBigDFT/source/tutorials), so that the documentation will be automatically generated and available as a tutorial at pybigdft_tutorials.