import os
import sys
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

import pandas as pd
import torch

from inverse.config_inverse import MEASUREMENTS_PATH


def load_measurements(device: torch.device):
    """Carica measurements.csv e restituisce tensori (x_s, t_s, T_meas) sul device."""
    if not os.path.exists(MEASUREMENTS_PATH):
        raise FileNotFoundError(
            f"File misure non trovato: {MEASUREMENTS_PATH}\n"
            "Esegui prima 'python inverse/sample_sensors.py' per generare i dati."
        )
    df = pd.read_csv(MEASUREMENTS_PATH)
    x_s   = torch.tensor(df["x"].values, dtype=torch.float32, device=device)
    t_s   = torch.tensor(df["t"].values, dtype=torch.float32, device=device)
    T_meas = torch.tensor(df["T"].values, dtype=torch.float32, device=device)
    print(f"Misure caricate: {len(df)} punti da {MEASUREMENTS_PATH}")
    print(f"  Sensori x: {sorted(df['x'].unique().tolist())}")
    print(f"  T range: [{df['T'].min():.2f}, {df['T'].max():.2f}] °C")
    return x_s, t_s, T_meas