import json
from fastapi import APIRouter, HTTPException
from app.config import (STATE_PATH, BACKGROUND_PATH, energy_axis, NUM_CHANNELS,
                        clip_to_range, correct_csi_nonlinear)
import numpy as np

router = APIRouter()


@router.get("/current")
async def get_current_spectrum():
    """Current accumulated spectrum with energy axis (CsI-corrected)."""
    if not STATE_PATH.exists():
        raise HTTPException(status_code=503, detail="Monitor not started yet")

    try:
        with open(STATE_PATH) as f:
            state = json.load(f)
    except (json.JSONDecodeError, OSError):
        raise HTTPException(status_code=503, detail="Monitor state file corrupt")

    raw_counts = state.get("counts", [0] * 1024)[:NUM_CHANNELS]
    # Apply CsI correction so peaks appear at theoretical energy positions
    corrected_counts = correct_csi_nonlinear(np.array(raw_counts, dtype=np.float64))
    return {
        "timestamp": state.get("timestamp", ""),
        "connected": state.get("connected", False),
        "cumulated_live_time_s": state.get("cumulated_live_time_s", 0),
        "cumulated_live_time_h": state.get("cumulated_live_time_h", 0),
        "cps": state.get("cps", 0),
        "total_counts": state.get("total_counts", 0),
        "background_subtracted": state.get("background_subtracted", False),
        "isotopes_detected": state.get("isotopes_detected", []),
        "channels": clip_to_range(list(range(NUM_CHANNELS))),
        "energy_kev": energy_axis(),
        "counts": clip_to_range([round(float(c), 1) for c in corrected_counts]),
    }


@router.get("/difference")
async def get_difference_spectrum():
    """Background-subtracted spectrum (net signal, CsI-corrected)."""
    if not STATE_PATH.exists():
        raise HTTPException(status_code=503, detail="Monitor not started yet")

    try:
        with open(STATE_PATH) as f:
            state = json.load(f)
    except (json.JSONDecodeError, OSError):
        raise HTTPException(status_code=503, detail="Monitor state file corrupt")

    counts = np.array(state.get("counts", [0] * 1024), dtype=np.float64)[:NUM_CHANNELS]
    live_time = state.get("cumulated_live_time_s", 0)

    if live_time <= 0:
        raise HTTPException(status_code=503, detail="No live time data yet")

    rate = counts / live_time

    if BACKGROUND_PATH.exists():
        bg_data = np.load(str(BACKGROUND_PATH), allow_pickle=True).item()
        bg_counts = bg_data["counts"].astype(np.float64)[:NUM_CHANNELS]
        bg_live_time = float(bg_data["duration"])
        bg_rate = bg_counts / bg_live_time
        net_rate = np.clip(rate - bg_rate, 0, None)
        # Apply CsI correction to net spectrum
        corrected_net = correct_csi_nonlinear(net_rate)
        net_counts = corrected_net * live_time
        bg_available = True
    else:
        net_counts = counts
        bg_available = False

    net_counts_list = [round(float(c), 1) for c in net_counts]
    return {
        "timestamp": state.get("timestamp", ""),
        "cumulated_live_time_s": live_time,
        "background_subtracted": bg_available,
        "channels": clip_to_range(list(range(NUM_CHANNELS))),
        "energy_kev": energy_axis(),
        "counts": clip_to_range(net_counts_list),
        "raw_counts": clip_to_range(state.get("counts", [])[:NUM_CHANNELS]),
    }