CLI Input and Script Generators#
Setting up a PAOFLOW calculation involves quite a bit of boilerplate — QE input files, driver scripts, plotting routines. These two command-line tools handle that for you, letting you focus on the science rather than the setup. Both rely primarily on Python’s standard library and produce static, well-commented scripts that are easy to read and modify.
paoflow-gen-qe#
Converts an AFLOW database entry into a ready-to-run Quantum ESPRESSO scf input file, with sensible defaults for smearing, magnetism, spin-orbit coupling, and the band count needed for PAOFLOW’s extended-basis projections.
Accepted input formats:
AFLOWDATA URLs
Material-page URLs
Bare AUID tokens (e.g.,
aflow:0a66d228d896a855)
What it figures out for you:
Lattice type (
ibravandcelldmparameters)Kinetic energy cutoffs from reference data
Whether the material is a metal or insulator (via band-gap analysis)
Spin polarization when needed
Spin-orbit coupling setup
Band count optimized for extended PAO basis calculations
Recommended intersite-V cutoffs for follow-up U+V runs
Main options: pseudopotential directory (required), spin-orbit coupling flag, output path, smearing width, and symmetry tolerance.
paoflow-gen#
Generates a PAOFLOW property-calculation driver (main.py) from a completed QE run, along with an optional plotting script (plot.py) that visualizes the properties you selected.
Two supported workflows:
Workflow A — ACBN0/eACBN0: Self-consistent Hubbard U calculations, with or without intersite V terms. See ACBN0 Module for details on the underlying implementation.
Workflow B — Property runs: Pick from band structure, DOS, transport, Fermi surface, spin texture, spin Hall conductivity, anomalous Hall effects, topology, optical properties, and more. The generated plot.py includes only the visualization routines for the properties you chose.
A Complete Workflow#
Here’s what a typical end-to-end session looks like:
# Generate a QE input file from an AFLOW entry
paoflow-gen-qe --pseudo /path/to/pseudos aflow:0a66d228d896a855
# Run the QE SCF calculation
pw.x < scf.in > scf.out
# Generate the PAOFLOW driver script interactively
paoflow-gen
# Run the property calculation
python main.py
# Visualize the results
python plot.py