Implementation of Modern Quantum Chemical Analysis in cclib

The usual approach taken in computational chemistry is to first run a simulation, which can often be long, on a target molecule and then to analyze the results to obtain an insight about the molecule. Usually, electron density assigned in the atoms that constitute the molecule is a key element in this process. This partitioning of the electrons itself do not suggest any observable properties of a molecule. However, many observable features of a molecule are derived directly from the electron densities, hence motivating chemists to relentlessly improve this noumena step by step. Currently, cclib can calculate some common atomic charge potential methods, including C-squared Population Analysis, Mulliken Population Analysis, and Lowdin Population Analysis. Because Mulliken Population Analysis and Lowdin Population Analysis are similar in its theory (Lowdin uses a different basis set to reduce the basis set dependence observed in Mulliken Analysis), it would be advantageous to have other modern calculation methods implemented in cclib. Some examples of the methods that can be implemented include DDEC6, Hirshfeld method, Bader analysis, ISA (through a bridge to Horton) and so on.