3_epc/epc_comparison_slides.py

#!/usr/bin/env python
"""EPC comparison plot for slides - APS style.

2 subplots:
  1. AO (HPRO) vs ML (E3_AO)
  2. DFT vs ML (E3_AO)

Each subplot colors points by transition type:
  occ-occ, occ-cond (mixed), cond-cond

xlim/ylim start from 0 (plotting |g| magnitudes).
Output: pictures_ml/deep_h_epc.png
"""
import os
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
DISP_DIR   = os.path.join(SCRIPT_DIR, 'displacements')
OUT_PATH   = '/home/apolyukhin/git/aps_slides/random_slides/pictures_ml/deep_h_epc.png'

N_OCC  = 4
NK     = 216

# =============================================================================
# APS slides style
# =============================================================================
marp_text_color = "#575279"
color_vv   = "mediumseagreen"  # occ-occ   (pbe)
color_vc   = "#b4637a"         # occ-cond  (hse)
color_cc   = "#ea9d34"         # cond-cond (kcw)
alpha        = 0.4
legend_alpha = 0.5
fontsize     = 22

plt.rcParams.update({
    'font.size':        fontsize,
    'mathtext.fontset': 'cm',
    'text.color':       marp_text_color,
    'axes.labelcolor':  marp_text_color,
    'xtick.color':      marp_text_color,
    'ytick.color':      marp_text_color,
    'axes.edgecolor':   marp_text_color,
    'axes.labelpad':    10,
})


# =============================================================================
# Data loading
# =============================================================================

def parse_epc_dir(dir_path, nk=NK):
    g = {}
    for ik in range(1, nk + 1):
        fn = os.path.join(dir_path, f'comparison_{ik}_1.txt')
        if not os.path.isfile(fn):
            continue
        with open(fn) as f:
            for line in f:
                cols = line.split()
                if len(cols) < 8:
                    continue
                i, j, nu = int(cols[0]), int(cols[1]), int(cols[2])
                g[(ik, i, j, nu)] = float(cols[7])
    return g


out_dft_dir  = os.path.join(DISP_DIR, 'out_dft')
out_hpro_dir = os.path.join(DISP_DIR, 'out_hpro_ao')
out_e3_dir   = os.path.join(DISP_DIR, 'out_e3_ao')

print('Loading EPC data...')
g_dft  = parse_epc_dir(out_dft_dir)
g_hpro = parse_epc_dir(out_hpro_dir)
g_e3   = parse_epc_dir(out_e3_dir)
print(f'  DFT: {len(g_dft)}  HPRO: {len(g_hpro)}  E3: {len(g_e3)}')

# Use optical modes (nu >= 4) with non-negligible DFT value
optical_keys = [k for k in g_dft if k[3] >= 4 and abs(g_dft[k]) > 1e-4]

g_dft_arr  = np.array([g_dft[k]             for k in optical_keys]) * 1000  # meV
g_hpro_arr = np.array([g_hpro.get(k, 0.0)   for k in optical_keys]) * 1000
g_e3_arr   = np.array([g_e3.get(k, 0.0)     for k in optical_keys]) * 1000

# Transition type masks — standard (for AO vs ML panel)
is_vv = np.array([k[1] <= N_OCC and k[2] <= N_OCC for k in optical_keys])
is_cc = np.array([k[1] >  N_OCC and k[2] >  N_OCC for k in optical_keys])
is_vc = ~is_vv & ~is_cc

cats_ao_ml = [
    ('occ-occ',  is_vv, color_vv),
    ('occ-cond', is_vc, color_vc),
    ('cond-cond',is_cc, color_cc),
]

# Transition type masks — DFT vs ML: cond-cond restricted to 1st cond band only
N_OCC1 = N_OCC + 1
is_cc1 = np.array([k[1] == N_OCC1 and k[2] == N_OCC1 for k in optical_keys])

cats_dft_ml = [
    ('occ-occ',       is_vv,  color_vv),
    ('occ-cond',      is_vc,  color_vc),
    ('1st cond-cond', is_cc1, color_cc),
]


# =============================================================================
# Plot
# =============================================================================

def plot_panel(ax, g_x, g_y, label_x, label_y, cats):
    x_abs = np.abs(g_x)
    y_abs = np.abs(g_y)
    lim = max(x_abs.max(), y_abs.max()) * 1.05

    for cat_label, mask, color in cats:
        if not mask.any():
            continue
        mae = np.mean(np.abs(g_y[mask] - g_x[mask]))
        ax.scatter(x_abs[mask], y_abs[mask], s=4, alpha=alpha, color=color,
                   label=f'{cat_label} (MAE={mae:.1f} meV)', rasterized=True)

    ax.plot([0, lim], [0, lim], '--', color=marp_text_color, lw=1.0, alpha=0.6)
    ax.set_xlim(0, lim)
    ax.set_ylim(0, lim)
    ax.set_aspect('equal')
    ax.set_xlabel(f'|g| {label_x} (meV)')
    ax.set_ylabel(f'|g| {label_y} (meV)')
    ax.legend(loc='upper left', framealpha=legend_alpha, fontsize=0.65*fontsize)


fig, axes = plt.subplots(1, 2, figsize=(14, 6), facecolor='none')
for ax in axes:
    ax.set_facecolor('none')

plot_panel(axes[0], g_hpro_arr, g_e3_arr,  'AO',  'ML', cats_ao_ml)
plot_panel(axes[1], g_dft_arr,  g_e3_arr,  'DFT', 'ML', cats_dft_ml)

plt.tight_layout()
plt.savefig(OUT_PATH, dpi=300, transparent=True, bbox_inches='tight')
print(f'Saved: {OUT_PATH}')