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>
76 lines
2.7 KiB
Python
76 lines
2.7 KiB
Python
import json
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from fastapi import APIRouter, HTTPException
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from app.config import STATE_PATH, BACKGROUND_PATH, energy_axis, NUM_CHANNELS
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import numpy as np
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router = APIRouter()
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@router.get("/current")
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async def get_current_spectrum():
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"""Current accumulated spectrum with energy axis."""
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if not STATE_PATH.exists():
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raise HTTPException(status_code=503, detail="Monitor not started yet")
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try:
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with open(STATE_PATH) as f:
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state = json.load(f)
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except (json.JSONDecodeError, OSError):
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raise HTTPException(status_code=503, detail="Monitor state file corrupt")
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return {
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"timestamp": state.get("timestamp", ""),
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"connected": state.get("connected", False),
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"cumulated_live_time_s": state.get("cumulated_live_time_s", 0),
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"cumulated_live_time_h": state.get("cumulated_live_time_h", 0),
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"cps": state.get("cps", 0),
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"total_counts": state.get("total_counts", 0),
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"background_subtracted": state.get("background_subtracted", False),
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"isotopes_detected": state.get("isotopes_detected", []),
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"channels": list(range(NUM_CHANNELS)),
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"energy_kev": energy_axis(),
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"counts": state.get("counts", [0] * 1024)[:NUM_CHANNELS],
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}
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@router.get("/difference")
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async def get_difference_spectrum():
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"""Background-subtracted spectrum (net signal)."""
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if not STATE_PATH.exists():
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raise HTTPException(status_code=503, detail="Monitor not started yet")
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try:
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with open(STATE_PATH) as f:
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state = json.load(f)
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except (json.JSONDecodeError, OSError):
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raise HTTPException(status_code=503, detail="Monitor state file corrupt")
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counts = np.array(state.get("counts", [0] * 1024), dtype=np.float64)[:NUM_CHANNELS]
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live_time = state.get("cumulated_live_time_s", 0)
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if live_time <= 0:
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raise HTTPException(status_code=503, detail="No live time data yet")
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rate = counts / live_time
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if BACKGROUND_PATH.exists():
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bg_data = np.load(str(BACKGROUND_PATH), allow_pickle=True).item()
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bg_counts = bg_data["counts"].astype(np.float64)[:NUM_CHANNELS]
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bg_live_time = float(bg_data["duration"])
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bg_rate = bg_counts / bg_live_time
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net_rate = np.clip(rate - bg_rate, 0, None)
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net_counts = net_rate * live_time
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bg_available = True
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else:
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net_counts = counts
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bg_available = False
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return {
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"timestamp": state.get("timestamp", ""),
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"cumulated_live_time_s": live_time,
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"background_subtracted": bg_available,
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"channels": list(range(NUM_CHANNELS)),
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"energy_kev": energy_axis(),
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"counts": [round(float(c), 1) for c in net_counts],
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"raw_counts": state.get("counts", [])[:NUM_CHANNELS],
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} |