- 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>
180 lines
6.2 KiB
Python
180 lines
6.2 KiB
Python
import json
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from fastapi import APIRouter, HTTPException
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from app.config import BACKGROUND_SNAPSHOT_PATH, BACKGROUND_PATH, energy_axis, NUM_CHANNELS, ENERGY_OFFSET, ENERGY_SLOPE
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from app.theoretical_bg import generate_continuum_only
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from app.noise import extract_continuum
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import numpy as np
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router = APIRouter()
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def _load_snapshot():
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"""Load the live snapshot file, or raise 404."""
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if not BACKGROUND_SNAPSHOT_PATH.exists():
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raise HTTPException(status_code=404, detail="Background capture not available yet")
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try:
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with open(BACKGROUND_SNAPSHOT_PATH) as f:
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return json.load(f)
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except (json.JSONDecodeError, OSError):
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raise HTTPException(status_code=500, detail="Background snapshot file corrupt")
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def _load_reference():
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"""Load the 24h reference background, or return None."""
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if not BACKGROUND_PATH.exists():
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return None
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try:
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bg_data = np.load(str(BACKGROUND_PATH), allow_pickle=True).item()
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return {
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"counts": [round(float(c), 1) for c in bg_data["counts"][:NUM_CHANNELS]],
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"live_time_s": round(float(bg_data["duration"]), 1),
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}
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except Exception:
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return None
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@router.get("")
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async def get_background_info():
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"""Background metadata: elapsed time, CPS, top peaks."""
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snapshot = _load_snapshot()
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full_available = BACKGROUND_PATH.exists()
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return {
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"elapsed_hours": snapshot.get("elapsed_hours", 0),
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"live_time_s": snapshot.get("live_time_s", 0),
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"total_counts": snapshot.get("total_counts", 0),
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"cps": snapshot.get("cps", 0),
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"top_peaks": snapshot.get("top_peaks", []),
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"full_background_available": full_available,
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}
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@router.get("/spectrum")
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async def get_background_spectrum():
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"""Live background spectrum (from snapshot) with energy axis."""
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snapshot = _load_snapshot()
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live_time = snapshot.get("live_time_s", 0)
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return {
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"channels": list(range(NUM_CHANNELS)),
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"energy_kev": energy_axis(),
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"counts": snapshot.get("spectrum", [0] * 1024)[:NUM_CHANNELS],
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"live_time_s": live_time,
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"cps": snapshot.get("cps", 0),
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"top_peaks": snapshot.get("top_peaks", []),
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"reference_available": BACKGROUND_PATH.exists(),
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}
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@router.get("/reference")
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async def get_background_reference():
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"""24h reference background spectrum for overlay comparison."""
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ref = _load_reference()
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if ref is None:
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raise HTTPException(status_code=404, detail="No 24h reference background available")
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return {
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"channels": list(range(NUM_CHANNELS)),
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"energy_kev": energy_axis(),
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"counts": ref["counts"],
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"live_time_s": ref["live_time_s"],
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}
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@router.get("/continuum")
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async def get_continuum(cps: float = 6.0, live_time_s: float = 3600.0):
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"""CsI(Tl) detector response continuum only (no photopeaks, no noise)."""
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return generate_continuum_only(cps=cps, live_time_s=live_time_s)
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@router.get("/fit")
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async def fit_background():
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"""Fit the parametric CsI(Tl) detector response model to measured background data.
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Returns the fitted curve, parameters, and quality metrics.
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"""
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from app.bg_calibration import calibrate_background, build_calibrated_continuum
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# Load measured data
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measured_counts = None
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live_time = 0
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if BACKGROUND_PATH.exists():
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try:
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bg_data = np.load(str(BACKGROUND_PATH), allow_pickle=True).item()
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measured_counts = bg_data["counts"].astype(np.float64)[:NUM_CHANNELS]
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live_time = float(bg_data["duration"])
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except Exception:
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pass
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if measured_counts is None and BACKGROUND_SNAPSHOT_PATH.exists():
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try:
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with open(BACKGROUND_SNAPSHOT_PATH) as f:
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snapshot = json.load(f)
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measured_counts = np.array(snapshot.get("spectrum", [])[:NUM_CHANNELS], dtype=np.float64)
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live_time = float(snapshot.get("live_time_s", 0))
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except Exception:
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pass
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if measured_counts is None or live_time < 600:
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raise HTTPException(status_code=404, detail="No measured background available for fitting")
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channels = np.arange(NUM_CHANNELS, dtype=np.float64)
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e_axis = ENERGY_OFFSET + ENERGY_SLOPE * channels
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# Run calibration
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measured_cps = measured_counts / live_time
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result = calibrate_background(measured_cps, e_axis)
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if "error" in result:
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raise HTTPException(status_code=500, detail=f"Fitting failed: {result['error']}")
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# Build fitted curve at same scale as measured
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fitted_counts = build_calibrated_continuum(e_axis, measured_counts.sum(), result)
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return {
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"energy_kev": [round(float(E), 2) for E in e_axis],
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"measured_counts": [round(float(c), 1) for c in measured_counts],
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"fitted_counts": [round(float(c), 1) for c in fitted_counts],
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"method": result.get("method", "spline"),
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"r_squared": result["r_squared"],
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"residuals_rms": result["residuals_rms"],
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"live_time_s": round(live_time, 1),
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}
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@router.get("/noise")
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async def get_background_noise():
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"""Detector's intrinsic continuum curve (isotope peaks subtracted).
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Returns the smooth detector response shape without any isotope
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photopeak signatures. Works with any detector type.
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"""
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counts = None
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if BACKGROUND_PATH.exists():
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try:
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bg_data = np.load(str(BACKGROUND_PATH), allow_pickle=True).item()
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counts = bg_data["counts"].astype(np.float64)[:NUM_CHANNELS]
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except Exception:
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pass
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if counts is None and BACKGROUND_SNAPSHOT_PATH.exists():
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try:
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with open(BACKGROUND_SNAPSHOT_PATH) as f:
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snapshot = json.load(f)
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counts = np.array(snapshot.get("spectrum", [])[:NUM_CHANNELS], dtype=np.float64)
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except Exception:
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pass
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if counts is None:
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raise HTTPException(status_code=404, detail="No background data available")
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channels = np.arange(NUM_CHANNELS, dtype=np.float64)
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e_axis = ENERGY_OFFSET + ENERGY_SLOPE * channels
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continuum = extract_continuum(counts, energy_axis=e_axis)
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return {
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"energy_kev": [round(float(E), 2) for E in e_axis],
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"counts": [round(float(c), 1) for c in continuum],
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} |