Dash web: crosshair, zoom/pan X, scale log/lin, continuum extraction, background resume

- Tooltip entier (intersect:false) + ligne verticale crosshair sur tous les graphes
- Zoom molette/pinch sur l'axe X, pan souris, limites clamped 30-3000 keV
- Toggle échelle log/linéaire onglet Background
- Extraction continuum détecteur (isotope peaks subtracted + Gaussian smoothing)
- Reprise snapshot précédent au démarrage capture_background.py
- Suppression refs "Théorique" et "Bruit capteur" de l'interface
- Plugin chartjs-plugin-zoom + hammerjs via CDN
- Fix Chart constructor spread operator

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

web/app/routers/background.py

@@ -1,7 +1,8 @@
 import json
 from fastapi import APIRouter, HTTPException
-from app.config import BACKGROUND_SNAPSHOT_PATH, BACKGROUND_PATH, energy_axis, NUM_CHANNELS
-from app.theoretical_bg import generate_theoretical_bg, generate_continuum_only
+from app.config import BACKGROUND_SNAPSHOT_PATH, BACKGROUND_PATH, energy_axis, NUM_CHANNELS, ENERGY_OFFSET, ENERGY_SLOPE
+from app.theoretical_bg import generate_continuum_only
+from app.noise import extract_continuum
 import numpy as np
 
 router = APIRouter()
@@ -80,16 +81,100 @@ async def get_background_reference():
     }
 
 
-@router.get("/theoretical")
-async def get_theoretical_bg(cps: float = 6.0, live_time_s: float = 3600.0):
-    """Theoretical natural background spectrum (K-40, U-238 chain, Th-232 chain)."""
-    return generate_theoretical_bg(cps=cps, live_time_s=live_time_s)
-
-
 @router.get("/continuum")
 async def get_continuum(cps: float = 6.0, live_time_s: float = 3600.0):
-    """CsI(Tl) continuum shape only (hump + Compton tail, no photopeaks, no noise).
+    """CsI(Tl) detector response continuum only (no photopeaks, no noise)."""
+    return generate_continuum_only(cps=cps, live_time_s=live_time_s)
 
-    Matches the model used in training (generate_realistic_continuum).
+
+@router.get("/fit")
+async def fit_background():
+    """Fit the parametric CsI(Tl) detector response model to measured background data.
+
+    Returns the fitted curve, parameters, and quality metrics.
     """
-    return generate_continuum_only(cps=cps, live_time_s=live_time_s)
+    from app.bg_calibration import calibrate_background, build_calibrated_continuum
+
+    # Load measured data
+    measured_counts = None
+    live_time = 0
+
+    if BACKGROUND_PATH.exists():
+        try:
+            bg_data = np.load(str(BACKGROUND_PATH), allow_pickle=True).item()
+            measured_counts = bg_data["counts"].astype(np.float64)[:NUM_CHANNELS]
+            live_time = float(bg_data["duration"])
+        except Exception:
+            pass
+
+    if measured_counts is None and BACKGROUND_SNAPSHOT_PATH.exists():
+        try:
+            with open(BACKGROUND_SNAPSHOT_PATH) as f:
+                snapshot = json.load(f)
+            measured_counts = np.array(snapshot.get("spectrum", [])[:NUM_CHANNELS], dtype=np.float64)
+            live_time = float(snapshot.get("live_time_s", 0))
+        except Exception:
+            pass
+
+    if measured_counts is None or live_time < 600:
+        raise HTTPException(status_code=404, detail="No measured background available for fitting")
+
+    channels = np.arange(NUM_CHANNELS, dtype=np.float64)
+    e_axis = ENERGY_OFFSET + ENERGY_SLOPE * channels
+
+    # Run calibration
+    measured_cps = measured_counts / live_time
+    result = calibrate_background(measured_cps, e_axis)
+
+    if "error" in result:
+        raise HTTPException(status_code=500, detail=f"Fitting failed: {result['error']}")
+
+    # Build fitted curve at same scale as measured
+    fitted_counts = build_calibrated_continuum(e_axis, measured_counts.sum(), result)
+
+    return {
+        "energy_kev": [round(float(E), 2) for E in e_axis],
+        "measured_counts": [round(float(c), 1) for c in measured_counts],
+        "fitted_counts": [round(float(c), 1) for c in fitted_counts],
+        "method": result.get("method", "spline"),
+        "r_squared": result["r_squared"],
+        "residuals_rms": result["residuals_rms"],
+        "live_time_s": round(live_time, 1),
+    }
+
+
+@router.get("/noise")
+async def get_background_noise():
+    """Detector's intrinsic continuum curve (isotope peaks subtracted).
+
+    Returns the smooth detector response shape without any isotope
+    photopeak signatures. Works with any detector type.
+    """
+    counts = None
+
+    if BACKGROUND_PATH.exists():
+        try:
+            bg_data = np.load(str(BACKGROUND_PATH), allow_pickle=True).item()
+            counts = bg_data["counts"].astype(np.float64)[:NUM_CHANNELS]
+        except Exception:
+            pass
+
+    if counts is None and BACKGROUND_SNAPSHOT_PATH.exists():
+        try:
+            with open(BACKGROUND_SNAPSHOT_PATH) as f:
+                snapshot = json.load(f)
+            counts = np.array(snapshot.get("spectrum", [])[:NUM_CHANNELS], dtype=np.float64)
+        except Exception:
+            pass
+
+    if counts is None:
+        raise HTTPException(status_code=404, detail="No background data available")
+
+    channels = np.arange(NUM_CHANNELS, dtype=np.float64)
+    e_axis = ENERGY_OFFSET + ENERGY_SLOPE * channels
+    continuum = extract_continuum(counts, energy_axis=e_axis)
+
+    return {
+        "energy_kev": [round(float(E), 2) for E in e_axis],
+        "counts": [round(float(c), 1) for c in continuum],
+    }