akaitools: A Python package for parsing and analyzing AkaiKKR electronic structure calculations

Abstract

The Korringa-Kohn-Rostoker (KKR) Green's function method is a first-principles electronic structure approach well suited to substitutionally disordered alloys through the Coherent Potential Approximation (CPA). AkaiKKR is a widely used implementation, known for efficient treatment of metallic systems and their magnetic properties. Its output, however, is unstructured plain text with no programmatic interface, leaving data extraction entirely to the user and making systematic or high-throughput studies impractical. akaitools is a Python package that parses AkaiKKR output files into structured, type-annotated Python objects. The package covers three output types: self-consistent field (SCF) results, which capture convergence history and per-atom electronic and magnetic properties; spin-resolved, orbital projected density of states for each CPA component; and Bloch spectral functions on a user-defined k-point path. Results come back as immutable dataclasses backed by NumPy arrays. Energy quantities are available in both Rydbergs and electronvolts, and results can be exported to Pandas DataFrames. A built-in plotting module produces Matplotlib figures for DOS curves and SCF convergence. A command-line interface provides file summaries and JSON export without any Python scripting. The package also includes a programmatic input file generator, so full calculation pipelines from input preparation to output analysis can be run in Python.