75d271c696
- Remplace le continuum exponentiel par un modèle réaliste CsI(Tl) dans l'entraînement (bosse asymétrique ~110 keV + queue Compton) - Ajoute l'injection de background mesuré (70% mesuré / 30% synthétique) via --measured_background et MEASURED_BACKGROUND_PATH - Ajoute l'endpoint /api/background/continuum et le toggle "Continuum CsI" sur le dashboard background - Exclut le canal 1023 (overflow bin) de l'affichage web (NUM_CHANNELS=1023) - Corrige le lissage Gaussien du background (normalisation locale aux bords) - Met à jour README.md, CLAUDE.md, TUTORIEL.md, TOTO.md, vega_ml/README.md Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
95 lines
3.2 KiB
Python
95 lines
3.2 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
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from app.theoretical_bg import generate_theoretical_bg, generate_continuum_only
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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("/theoretical")
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async def get_theoretical_bg(cps: float = 6.0, live_time_s: float = 3600.0):
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"""Theoretical natural background spectrum (K-40, U-238 chain, Th-232 chain)."""
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return generate_theoretical_bg(cps=cps, live_time_s=live_time_s)
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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) continuum shape only (hump + Compton tail, no photopeaks, no noise).
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Matches the model used in training (generate_realistic_continuum).
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"""
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return generate_continuum_only(cps=cps, live_time_s=live_time_s) |