auto-iter 20260513-2231: GX019817 RoPE skip, 4 PLY done ready for stage06

scripts/dvl_focal_sweep.py

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+#!/usr/bin/env python3
+"""Test multiple focal lengths on DVL and compare trajectory drift."""
+import subprocess, csv, sys, math
+from pathlib import Path
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+
+FRAMES = '/home/cosma/cosma-pipeline/data/20260505-Lepradet/frames/AUV210/GX039839'
+START = '2026-05-05T08:33:41'
+LABEL = 'GX039839'
+SCRIPT = '/home/cosma/cosma-qc/scripts/dvl_optical_full.py'
+
+# focal in px equivalent to W/2 / tan(fov/2). W=518
+# fov 100°→f=217, 110°→f=185, 122°→f=143, 130°→f=121, 140°→f=94, 150°→f=70
+# But focal in px doesn't directly map to FOV unless we use that conversion. We pass --fov-deg.
+fovs = [90, 100, 110, 122, 135, 150]
+
+results = []
+for fov in fovs:
+    out_csv = f'/tmp/sweep_fov{fov}.csv'
+    print(f'[sweep] fov={fov}', flush=True)
+    r = subprocess.run(['python3', SCRIPT, '--frames-dir', FRAMES, '--altitude', '1.5',
+                        '--fov-deg', str(fov), '--fps', '1.0', '--start-iso', START,
+                        '--label', LABEL, '--out', out_csv], capture_output=True, text=True, timeout=600)
+    if r.returncode != 0:
+        print(f'  FAIL: {r.stderr[-300:]}', flush=True)
+        continue
+    # parse last position + drift metrics
+    rows = list(csv.DictReader(open(out_csv)))
+    e = [float(r['east_m']) for r in rows]
+    n = [float(r['north_m']) for r in rows]
+    h = [float(r['heading_deg']) for r in rows]
+    end_x, end_y = e[-1], n[-1]
+    end_dist = math.sqrt(end_x**2 + end_y**2)
+    path_len = sum(math.sqrt((e[i]-e[i-1])**2 + (n[i]-n[i-1])**2) for i in range(1, len(e)))
+    bbox = (max(e)-min(e), max(n)-min(n))
+    results.append({'fov': fov, 'csv': out_csv, 'end_x': end_x, 'end_y': end_y, 
+                    'end_dist': end_dist, 'path_len': path_len, 'bbox': bbox, 'rows': rows,
+                    'e_arr': e, 'n_arr': n, 'h_arr': h})
+    print(f'  end=({end_x:.1f},{end_y:.1f}) dist={end_dist:.1f}m path={path_len:.1f}m bbox={bbox}', flush=True)
+
+# Plot all trajectories
+fig, axes = plt.subplots(2, 3, figsize=(18, 12))
+axes = axes.flatten()
+for ax, res in zip(axes, results):
+    ax.plot(res['e_arr'], res['n_arr'], '-b', linewidth=0.8)
+    ax.plot(res['e_arr'][0], res['n_arr'][0], 'go', markersize=8)
+    ax.plot(res['e_arr'][-1], res['n_arr'][-1], 'r^', markersize=8)
+    ax.set_xlabel('East (m)'); ax.set_ylabel('North (m)')
+    ax.set_title(f'FOV={res["fov"]}° bbox=({res["bbox"][0]:.0f}×{res["bbox"][1]:.0f})m\nend_dist={res["end_dist"]:.1f}m path={res["path_len"]:.0f}m')
+    ax.set_aspect('equal'); ax.grid(True, alpha=0.3)
+plt.suptitle(f'DVL focal sweep — {LABEL} (assume closed-loop survey → smaller end_dist=better)')
+plt.tight_layout()
+plt.savefig('/tmp/sweep_focal.png', dpi=110, bbox_inches='tight')
+print('[plot] /tmp/sweep_focal.png', flush=True)
+
+# Summary
+print('\n=== Summary ===')
+for r in sorted(results, key=lambda x: x['end_dist']):
+    print(f"FOV={r['fov']}°: end_dist={r['end_dist']:.1f}m  path={r['path_len']:.0f}m  bbox={r['bbox'][0]:.0f}×{r['bbox'][1]:.0f}m")