#!/usr/bin/env python
"""
Compare QE band structure with HPRO real-space reconstruction for diamond.

Reads:
  - data/bands/kpath.json              (k-path from prepare.py)
  - data/bands/{uc,sc}/scf/bands.dat.gnu  (QE eigenvalues from bands.x)
  - data/bands/{uc,sc}/reconstruction/aohamiltonian/  (HPRO H(R))

Produces band comparison plots: band_compare_uc.png and band_compare_sc.png

Usage: python compare_bands.py [params.json]
"""
import json
import os
import sys

import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from scipy.linalg import eigh

SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))


def load_params(path=None):
    if path is None:
        path = os.path.join(SCRIPT_DIR, 'params.json')
    with open(path) as f:
        return json.load(f)


def load_kpath(data_dir):
    with open(os.path.join(data_dir, 'bands', 'kpath.json')) as f:
        return json.load(f)


def parse_bands_gnu(gnu_path):
    """Parse QE bands.dat.gnu: blocks separated by blank lines.

    Each block corresponds to one band; each line is 'k_dist  eigenvalue'.
    Returns eigs (nk, nbnd) in eV (same units as bands.x output).
    """
    bands, block = [], []
    with open(gnu_path) as f:
        for line in f:
            line = line.strip()
            if line:
                block.append(float(line.split()[1]))
            else:
                if block:
                    bands.append(block)
                    block = []
    if block:
        bands.append(block)
    if not bands:
        raise FileNotFoundError(f"No data found in {gnu_path}")
    return np.array(bands).T  # (nk, nbnd)


def compute_hpro_bands(aodir, kpts_all, x_arr, nbnd):
    """Compute band structure from HPRO H(R) via direct Fourier transform.

    Uses load_deeph_HS + scipy.eigh for each k-point.
    Hermitianizes H(k) (not H(R)) before diagonalizing.

    Returns:
      eigs   (nk, nbnd) eigenvalues in eV, aligned to kpts_all
    """
    from HPRO.deephio import load_deeph_HS
    from HPRO.constants import hartree2ev

    matH = load_deeph_HS(aodir, 'hamiltonians.h5', energy_unit=True)
    matS = load_deeph_HS(aodir, 'overlaps.h5', energy_unit=False)
    matS.hermitianize()  # S(R) is exact, hermitianize in real space

    nk = len(kpts_all)
    eigs_all = np.empty((nk, nbnd))

    print(f"  Diagonalizing at {nk} k-points...")
    for ik, kpt in enumerate(kpts_all):
        if ik % 50 == 0:
            print(f"  k-point {ik}/{nk}")
        Hk = matH.r2k(kpt).toarray()
        Sk = matS.r2k(kpt).toarray()
        Hk = 0.5 * (Hk + Hk.conj().T)  # hermitianize H(k) only
        eigs_k, _ = eigh(Hk, Sk)
        eigs_all[ik] = eigs_k[:nbnd] * hartree2ev

    return eigs_all


def plot_comparison(x, eigs_qe, eigs_hpro, x_hs, labels, title, outpath):
    """Plot QE vs HPRO band structures (both pre-aligned to their own VBM)."""
    fig, ax = plt.subplots(figsize=(6, 5))

    for ib in range(eigs_qe.shape[1]):
        ax.plot(x, eigs_qe[:, ib], 'b-', lw=1.2, alpha=0.8,
                label='QE' if ib == 0 else '')
    for ib in range(eigs_hpro.shape[1]):
        ax.plot(x, eigs_hpro[:, ib], 'r--', lw=1.0, alpha=0.8,
                label='HPRO' if ib == 0 else '')

    for xv in x_hs:
        ax.axvline(xv, color='k', lw=0.8, ls='--')
    ax.axhline(0, color='k', lw=0.5, ls=':')

    ax.set_xticks(x_hs)
    ax.set_xticklabels(labels, fontsize=11)
    ax.set_ylabel('Energy (eV)', fontsize=11)
    ax.set_xlim(x[0], x[-1])
    emax = max(np.max(eigs_qe), np.max(eigs_hpro))
    emin = min(np.min(eigs_qe), np.min(eigs_hpro))
    ax.set_ylim(emin - 1, emax + 1)
    ax.set_title(title, fontsize=11)
    ax.legend(fontsize=10)
    fig.tight_layout()
    fig.savefig(outpath, dpi=200)
    plt.close(fig)
    print(f"  Saved: {outpath}")


def main():
    params_path = sys.argv[1] if len(sys.argv) > 1 else \
        os.path.join(SCRIPT_DIR, 'params.json')
    params = load_params(params_path)

    data_dir = os.path.join(SCRIPT_DIR, 'data')
    kpath = load_kpath(data_dir)

    kpts_hs = np.array(kpath['kpts_hs'])
    npts = kpath['npts']
    labels = kpath['labels']
    x_ref = np.array(kpath['x'])
    x_hs = kpath['x_hs']

    for cell_label in ('uc', 'sc'):
        bands_dir = os.path.join(data_dir, 'bands', cell_label)
        scf_dir = os.path.join(bands_dir, 'scf')
        aodir = os.path.join(bands_dir, 'reconstruction', 'aohamiltonian')

        if not os.path.exists(os.path.join(aodir, 'hamiltonians.h5')):
            print(f"[{cell_label}] HPRO hamiltonians.h5 not found, "
                  "run reconstruct.py first")
            continue

        gnu = os.path.join(scf_dir, 'bands.dat.gnu')
        if not os.path.exists(gnu):
            print(f"[{cell_label}] bands.dat.gnu not found ({gnu}), "
                  "run run.py first")
            continue

        print(f"\n[{cell_label}] Loading QE bands from bands.dat.gnu...")
        eigs_qe = parse_bands_gnu(gnu)
        # VBM: highest occupied level
        n_occ = 4 if cell_label == 'uc' else 4 * 8  # 4 electrons per UC

        rec = params['reconstruction']
        nbnd_param = rec.get('nbnd_sc', rec['nbnd']) if cell_label == 'sc' else rec['nbnd']

        print(f"[{cell_label}] Computing HPRO bands...")
        kpts_all = np.array(kpath['kpts_all'])
        eigs_hpro = compute_hpro_bands(aodir, kpts_all, x_ref, nbnd_param)

        # Align each source independently to its own VBM
        nbnd_cmp = min(nbnd_param, eigs_qe.shape[1], eigs_hpro.shape[1])
        vbm_qe = np.max(eigs_qe[:, :n_occ])
        vbm_hpro = np.max(eigs_hpro[:, :n_occ])
        eigs_qe_al = eigs_qe[:, :nbnd_cmp] - vbm_qe
        eigs_hpro_al = eigs_hpro[:, :nbnd_cmp] - vbm_hpro

        mae = np.mean(np.abs(eigs_qe_al - eigs_hpro_al))
        print(f"[{cell_label}] MAE (first {nbnd_cmp} bands, VBM-aligned) = "
              f"{mae*1000:.1f} meV")

        outpath = os.path.join(SCRIPT_DIR, f'band_compare_{cell_label}.png')
        title = f'Diamond {cell_label.upper()}: QE vs HPRO reconstruction'
        plot_comparison(x_ref, eigs_qe_al, eigs_hpro_al,
                        x_hs, labels, title, outpath)

    print("\ncompare_bands.py done.")


if __name__ == '__main__':
    main()