| """Per-pair preview figures: top-down height maps of the aligned 2023 and 2025 crops plus a height-difference map. |
| Usage: python make_figures.py PairA PairB ... (default: Pair1..Pair20). Writes figures/<pair>.png and figures/contact_sheet.png""" |
| import os, sys, json |
| import numpy as np |
| import matplotlib; matplotlib.use('Agg') |
| import matplotlib.pyplot as plt |
| from align import load |
|
|
| ROOT = "E:/Subiaco Change Detection point cloud data/Pairs" |
| CELL = 0.5 |
| pairs = sys.argv[1:] or [f'Pair{i}' for i in range(1, 21)] |
| os.makedirs('figures', exist_ok=True) |
|
|
|
|
| def hmap(P, lo, hi): |
| nx = int(np.ceil((hi[0] - lo[0]) / CELL)); ny = int(np.ceil((hi[1] - lo[1]) / CELL)) |
| ix = np.clip(((P[:, 0] - lo[0]) / CELL).astype(int), 0, nx - 1); iy = np.clip(((P[:, 1] - lo[1]) / CELL).astype(int), 0, ny - 1) |
| g = np.full((ny, nx), -np.inf); np.maximum.at(g, (iy, ix), P[:, 2]); g[~np.isfinite(g)] = np.nan |
| return g |
|
|
|
|
| thumbs = [] |
| for pr in pairs: |
| d = f'{ROOT}/{pr}' |
| if not os.path.exists(f'{d}/2023.ply'): |
| print('skip', pr); continue |
| A = load(f'{d}/2023.ply'); B = load(f'{d}/2025.ply') |
| lo = np.minimum(A[:, :2].min(0), B[:, :2].min(0)); hi = np.maximum(A[:, :2].max(0), B[:, :2].max(0)) |
| ga, gb = hmap(A, lo, hi), hmap(B, lo, hi) |
| z0 = np.nanpercentile(np.r_[ga.ravel(), gb.ravel()], 1); z1 = np.nanpercentile(np.r_[ga.ravel(), gb.ravel()], 99) |
| diff = gb - ga |
| ext = (lo[0], hi[0], lo[1], hi[1]) |
| fig, axs = plt.subplots(1, 3, figsize=(15, 5.2)) |
| for ax, g, ttl in ((axs[0], ga, f'{pr}: 2023 (OS1-64) height'), (axs[1], gb, f'{pr}: 2025 (OS1-128) height')): |
| im = ax.imshow(g, origin='lower', extent=ext, cmap='Blues', vmin=z0, vmax=z1, interpolation='nearest') |
| ax.set_title(ttl, fontsize=10); ax.set_xlabel('x (m)'); ax.set_ylabel('y (m)') |
| plt.colorbar(im, ax=ax, fraction=0.046, pad=0.03, label='height above 2025 ground (m)') |
| im = axs[2].imshow(diff, origin='lower', extent=ext, cmap='RdBu_r', vmin=-5, vmax=5, interpolation='nearest') |
| axs[2].set_title(f'{pr}: 2025 minus 2023 max height (m)', fontsize=10); axs[2].set_xlabel('x (m)'); axs[2].set_ylabel('y (m)') |
| plt.colorbar(im, ax=axs[2], fraction=0.046, pad=0.03, label='height change (m); grey = missing in one epoch') |
| for ax in axs: |
| ax.set_facecolor('#e5e4df'); ax.tick_params(colors='#52514e') |
| for sp in ax.spines.values(): sp.set_color('#c3c2b7') |
| both = np.isfinite(ga) & np.isfinite(gb) |
| stats = {'cells_both': int(both.sum()), 'cells_2023_only': int((np.isfinite(ga) & ~np.isfinite(gb)).sum()), |
| 'cells_2025_only': int((~np.isfinite(ga) & np.isfinite(gb)).sum()), |
| 'dz_median_m': float(np.nanmedian(diff[both])), 'dz_p90_abs_m': float(np.nanpercentile(np.abs(diff[both]), 90)), |
| 'frac_cells_abs_dz_gt_1m': float((np.abs(diff[both]) > 1).mean()), |
| 'frac_cells_abs_dz_gt_2m': float((np.abs(diff[both]) > 2).mean())} |
| fig.suptitle(f"{pr} | {len(A):,} pts (2023) vs {len(B):,} pts (2025) | {stats['frac_cells_abs_dz_gt_1m']*100:.1f}% of shared 0.5 m cells changed height by >1 m", fontsize=11) |
| plt.tight_layout(); plt.savefig(f'figures/{pr}.png', dpi=110); plt.close(fig) |
| json.dump(stats, open(f'figures/{pr}_stats.json', 'w')) |
| thumbs.append((pr, gb, ext, z0, z1)) |
| print(pr, stats, flush=True) |
|
|
| if thumbs: |
| n = len(thumbs); cols = 5; rows = int(np.ceil(n / cols)) |
| fig, axs = plt.subplots(rows, cols, figsize=(3.2 * cols, 3.2 * rows)) |
| for ax in axs.ravel(): ax.axis('off') |
| for ax, (pr, g, ext, z0, z1) in zip(axs.ravel(), thumbs): |
| ax.imshow(g, origin='lower', extent=ext, cmap='Blues', vmin=z0, vmax=z1, interpolation='nearest'); ax.set_title(pr, fontsize=10) |
| fig.suptitle('2025 height maps of all change-detection pairs (Pair1-8 existing, Pair9-20 new)', fontsize=12) |
| plt.tight_layout(); plt.savefig('figures/contact_sheet.png', dpi=110); print('contact sheet written') |
|
|
