dft2ml_formatter_full

Usage Guide

This page shows how to use dft2ml_formatter to extract useful features from quantum chemistry output files (VASP, Gaussian, ORCA, CP2K) and convert them into ML-ready formats (e.g., JSON, CSV).

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Installation

You can install the package using:

pip install dft2ml_formatter

Or clone the repo and install locally:

git clone https://github.com/naveen-dandu/dft2ml_formatter_full
cd dft2ml_formatter_full
pip install -e .

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Basic Example (VASP)

Assume you have an OUTCAR and DOSCAR in examples/vasp/. You can extract features like bandgap, number of atoms, total energy, and Fermi level using:

from dft2ml_formatter.vasp_parser import extract_vasp_features

features = extract_vasp_features(
    outcar_path="examples/vasp/OUTCAR",
    doscar_path="examples/vasp/DOSCAR"
)

print(features)

This will output a dictionary:

{
    "num_atoms": 108,
    "total_energy": -315.72,
    "fermi_energy": -4.45,
    "bandgap": 1.73
}

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Output Formats

You can save to JSON/CSV using:

import json
import pandas as pd

with open("vasp_features.json", "w") as f:
    json.dump(features, f)

pd.DataFrame([features]).to_csv("vasp_features.csv", index=False)

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End-to-End Demo

See notebooks/DFT2ML_Demo.ipynb for a full walkthrough.

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