import os
import numpy as np
from pathlib import Path

STATE_PATH = Path(os.environ.get("STATE_PATH", "/data/monitor_state.json"))
CPS_LOG_PATH = Path(os.environ.get("CPS_LOG_PATH", "/data/cps_log.jsonl"))
BACKGROUND_PATH = Path(os.environ.get("BACKGROUND_PATH", "/data/background_24h.npy"))
BACKGROUND_SNAPSHOT_PATH = Path(os.environ.get("BACKGROUND_SNAPSHOT_PATH", "/data/background_snapshot.json"))
LOG_DIR = Path(os.environ.get("LOG_DIR", "/logs"))
ISOTOPE_INDEX_PATH = Path(os.environ.get("ISOTOPE_INDEX_PATH", "/models/vega_isotope_index.txt"))

ENERGY_OFFSET = float(os.environ.get("ENERGY_CALIBRATION_OFFSET", "0.33"))
ENERGY_SLOPE = float(os.environ.get("ENERGY_CALIBRATION_SLOPE", "2.97"))
NUM_CHANNELS = 1023  # Last channel (1023) is overflow bin, excluded from display
ENERGY_MIN = 30.0  # keV - detector lower limit
ENERGY_MAX = 3000.0  # keV - detector upper limit (3 MeV)

# CsI(Tl) non-linear response correction parameters
# Matches the detector's non-proportional scintillation response
CSI_NONLINEAR_ALPHA = float(os.environ.get("CSI_NONLINEAR_ALPHA", "0.37"))
CSI_NONLINEAR_BETA = float(os.environ.get("CSI_NONLINEAR_BETA", "100.0"))


def correct_csi_nonlinear(spectrum, num_channels=1023):
    """Apply inverse CsI(Tl) non-linear response correction.

    Remaps spectrum channels so peaks appear at their theoretical energy
    positions, correcting for the detector's non-proportional scintillation
    response that shifts low-energy peaks upward.
    """
    alpha = CSI_NONLINEAR_ALPHA
    beta = CSI_NONLINEAR_BETA
    output_channels = np.arange(num_channels, dtype=np.float64)
    e_true = ENERGY_OFFSET + ENERGY_SLOPE * output_channels
    e_apparent = e_true * (1 + alpha * np.exp(-e_true / beta))
    source_channels = (e_apparent - ENERGY_OFFSET) / ENERGY_SLOPE
    source_channels = np.clip(source_channels, 0, num_channels - 1.001)
    lower = np.floor(source_channels).astype(int)
    upper = np.minimum(lower + 1, num_channels - 1)
    frac = source_channels - lower
    return spectrum[lower] * (1 - frac) + spectrum[upper] * frac


def energy_axis():
    """Generate energy axis in keV from channel numbers, clipped to detector range."""
    axis = [round(ENERGY_OFFSET + ENERGY_SLOPE * i, 2) for i in range(NUM_CHANNELS)]
    return [e for e in axis if ENERGY_MIN <= e <= ENERGY_MAX]


def energy_mask():
    """Return boolean mask of channels within detector energy range."""
    return [ENERGY_MIN <= ENERGY_OFFSET + ENERGY_SLOPE * i <= ENERGY_MAX for i in range(NUM_CHANNELS)]


def clip_to_range(arr):
    """Clip array to detector energy range using energy mask."""
    mask = energy_mask()
    return [arr[i] for i in range(len(arr)) if mask[i]]