fix(oid): code cleanup — fix NameError, remove ROI cropping, consolidate

- Fix NameError (cfg_sid -> cfg["scene_id"]) in collect_controlled.py
- Remove ROI cropping in phase1_correction_pod.py (use full 1280x512)
- Add pinball_baseline_illusion to configs.py and data_dir_for_scene()
- Deprecate compute_delta_fields.py (superseded by phase1_correction_pod)
- Fix absolute path in save_robustness.py
- Clean redundant import in phase3_force_oid.py
- Suppress module-level print in phase6_comparison.py

Co-authored-by: Cursor <cursoragent@cursor.com>

src/OID_analysis/analysis/phase1_correction_pod.py

@@ -107,13 +107,6 @@ def load_scene_fields(scene_key: str) -> Optional[Dict]:
     return result
 
 
-def mask_field(ux: np.ndarray, uy: np.ndarray,
-               x_start: int = 400, x_end: int = 1000,
-               y_start: int = 100, y_end: int = 400) -> Tuple[np.ndarray, np.ndarray]:
-    """Crop field to ROI region."""
-    return ux[:, y_start:y_end, x_start:x_end], uy[:, y_start:y_end, x_start:x_end]
-
-
 def fields_to_snapshot_matrix(ux: np.ndarray, uy: np.ndarray) -> np.ndarray:
     """Convert (N, ny, nx) field time series to (N, DOF) snapshot matrix."""
     N = ux.shape[0]
@@ -142,27 +135,22 @@ def run_phase1(scene_key: str):
     ux_blk, uy_blk = fields["q_blk_dir"]
     ux_ctl, uy_ctl = fields["q_ctl_dir"]
 
-    # Mask to ROI
-    ux_in_m, uy_in_m = mask_field(ux_in, uy_in)
-    ux_blk_m, uy_blk_m = mask_field(ux_blk, uy_blk)
-    ux_ctl_m, uy_ctl_m = mask_field(ux_ctl, uy_ctl)
-
-    # Delta fields
-    ux_delta_blk = ux_blk_m - ux_in_m
-    uy_delta_blk = uy_blk_m - uy_in_m
-    ux_delta_ctl = ux_ctl_m - ux_blk_m
-    uy_delta_ctl = uy_ctl_m - uy_blk_m
+    # Build delta fields (full 1280x512, no ROI cropping per project rules)
+    delta_ux_blk = ux_blk - ux_in
+    delta_uy_blk = uy_blk - uy_in
+    delta_ux_ctl = ux_ctl - ux_blk
+    delta_uy_ctl = uy_ctl - uy_blk
 
     # Save delta fields
     np.savez_compressed(os.path.join(out_dir, "delta_q_blk.npz"),
-                        ux=ux_delta_blk, uy=uy_delta_blk)
+                        ux=delta_ux_blk, uy=delta_uy_blk)
     np.savez_compressed(os.path.join(out_dir, "delta_q_ctl.npz"),
-                        ux=ux_delta_ctl, uy=uy_delta_ctl)
+                        ux=delta_ux_ctl, uy=delta_uy_ctl)
     print(f"  Delta fields saved")
 
     # Snapshot matrices
-    Q_delta = fields_to_snapshot_matrix(ux_delta_ctl, uy_delta_ctl)
-    Q_raw = fields_to_snapshot_matrix(ux_ctl_m, uy_ctl_m)
+    Q_delta = fields_to_snapshot_matrix(delta_ux_ctl, delta_uy_ctl)
+    Q_raw = fields_to_snapshot_matrix(ux_ctl, uy_ctl)
 
     print(f"  Snapshot matrix: {Q_delta.shape} (N={Q_delta.shape[0]}, DOF={Q_delta.shape[1]})")
 

src/OID_analysis/analysis/phase3_force_oid.py

@@ -21,7 +21,7 @@ if _REPO not in sys.path:
 
 from OID_analysis.configs import DATA_DIR  # noqa: E402
 from OID_analysis.utils.analysis import (  # noqa: E402
-    compute_force_oid, compute_force_oid as compute_oid,
+    compute_force_oid,
     standardize, reconstruct_oid_modes,
 )
 

src/OID_analysis/analysis/phase6_comparison.py

@@ -35,7 +35,7 @@ try:
     HAS_SKLEARN = True
 except ImportError:
     HAS_SKLEARN = False
-    print("WARNING: sklearn not available. Install: pip install scikit-learn")
+    # sklearn unavailable — comparison will be skipped
 
 
 SCENES = ["steady_cloak", "karman_re100",

src/OID_analysis/analysis/save_robustness.py

@@ -1,9 +1,16 @@
-"""Save robustness results and write comprehensive report."""
+"""Save robustness results.
+
+WARNING: This file contains hardcoded numerical results from a previous run.
+It is a one-shot results-saver. If the pipeline is re-run with different data
+or parameters, this file MUST be manually updated or replaced by
+robustness_analysis.py which generates robustness_results.json dynamically.
+"""
 import json, os, sys
-_REPO = "/home/frank14f/DynamisLab"
-sys.path.insert(0, os.path.join(_REPO, "src"))
+_REPO = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
+sys.path.insert(0, _REPO)
 from OID_analysis.configs import DATA_DIR
 
+# Hardcoded results from ~2026-06-22 run. Update if pipeline re-runs.
 results = {
     "rank_sensitivity": {
         "steady_cloak": {"r6": -0.4865, "r8": -0.7764, "r10": -0.7631, "r12": -0.7261, "r16": -0.6756},
@@ -37,4 +44,4 @@ out_dir = os.path.join(DATA_DIR, "derived", "robustness")
 os.makedirs(out_dir, exist_ok=True)
 with open(os.path.join(out_dir, "robustness_results.json"), "w") as f:
     json.dump(results, f, indent=2)
-print("Saved.")
+print("Saved robustness_results.json (hardcoded — update manually if re-running pipeline).")

src/OID_analysis/configs.py

@@ -74,6 +74,26 @@ SCENES["pinball_baseline"] = {
     "u0": U0,
 }
 
+# -- Pure Pinball (illusion positions) ---------------------------------------
+SCENES["pinball_baseline_illusion"] = {
+    "scene_id": "pinball_baseline_illusion",
+    "re_code": 100,
+    "nu": 0.004,
+    "has_disturbance": False,
+    "sample_interval": 800,
+    "action_scale": 8.0,
+    "action_bias": (0.0, -2.0, 2.0),
+    "source": "open_loop",
+    "n_objects_env": 6,
+    "obs_slice": (0, 12),
+    "sensor_x": 30.0,
+    "pinball_front_x": 19.0,
+    "pinball_rear_x": 20.3,
+    "target_type": "periodic",
+    "s_dim": 12,
+    "u0": U0,
+}
+
 # -- Disturbance Only (Karman inflow) ----------------------------------------
 SCENES["disturbance_only"] = {
     "scene_id": "disturbance_only",
@@ -244,6 +264,8 @@ def data_dir_for_scene(scene_name: str) -> str:
         return os.path.join(DATA_DIR, "steady_cloak", "empty_channel")
     elif sid == "pinball_baseline":
         return os.path.join(DATA_DIR, "steady_cloak", "pinball_baseline")
+    elif sid == "pinball_baseline_illusion":
+        return os.path.join(DATA_DIR, "steady_cloak", "pinball_baseline_illusion")
     elif sid == "steady_cloak":
         return os.path.join(DATA_DIR, "steady_cloak", "steady_cloak")
     # Karman group: separate dirs for q_in, q_blk, q_ctl

src/OID_analysis/scripts/collect_controlled.py

@@ -171,7 +171,7 @@ def collect_single(scene_name: str, device_id: int, n_steps: int) -> dict:
     # ---- Target signals (needed for s_dim=14 illusion) ----
     target_states = None
     target_harmonics = None
-    if cfg_sid == "illusion":
+    if cfg["scene_id"] == "illusion":
         target_path = os.path.join(out_dir, "target.npz")
         harm_path = os.path.join(out_dir, "target_harmonics.json")
         if os.path.isfile(target_path) and os.path.isfile(harm_path):
@@ -248,9 +248,9 @@ def collect_single(scene_name: str, device_id: int, n_steps: int) -> dict:
     # Compute similarity
     conv_len = cfg.get("conv_len", CONV_LEN_DEFAULT)
     if target_states is not None:
-        if cfg_sid == "karman":
+        if "karman" in cfg["scene_id"]:
             sim = compute_similarity(target_states, sens_arr, conv_len)
-        elif cfg_sid == "illusion":
+        elif cfg["scene_id"] == "illusion":
             # For illusion, target_states[:, 2:8] has the sensor references
             target_sensors = target_states[:, 2:8] if target_states.shape[1] >= 8 else target_states
             sim = compute_similarity(target_sensors, sens_arr, conv_len)

src/OID_analysis/scripts/compute_delta_fields.py

@@ -1,8 +1,12 @@
 # OID_analysis/scripts/compute_delta_fields.py
 """
-Compute Delta_q_blk and Delta_q_ctl from collected fields.
-Compute zone statistics.
-Gate check: does Delta_q_ctl have clear structure?
+DEPRECATED — Phase 0 draft. Always SKIPPED at runtime due to filename collision.
+This file is superseded by analysis/phase1_correction_pod.py which handles the full
+correction-field computation, POD, and saves delta_q_blk/delta_q_ctl.
+Kept for reference only. Do NOT use for pipeline runs.
+"""
+# This file is intentionally non-functional. See phase1_correction_pod.py for
+# the canonical correction-field computation.
 
 Usage:
     python3 src/OID_analysis/scripts/compute_delta_fields.py