26 lines
1.0 KiB
Python
26 lines
1.0 KiB
Python
import os
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import sys
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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import pandas as pd
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import torch
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from inverse.config_inverse import MEASUREMENTS_PATH
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def load_measurements(device: torch.device):
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"""Carica measurements.csv e restituisce tensori (x_s, t_s, T_meas) sul device."""
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if not os.path.exists(MEASUREMENTS_PATH):
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raise FileNotFoundError(
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f"File misure non trovato: {MEASUREMENTS_PATH}\n"
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"Esegui prima 'python inverse/sample_sensors.py' per generare i dati."
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)
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df = pd.read_csv(MEASUREMENTS_PATH)
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x_s = torch.tensor(df["x"].values, dtype=torch.float32, device=device)
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t_s = torch.tensor(df["t"].values, dtype=torch.float32, device=device)
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T_meas = torch.tensor(df["T"].values, dtype=torch.float32, device=device)
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print(f"Misure caricate: {len(df)} punti da {MEASUREMENTS_PATH}")
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print(f" Sensori x: {sorted(df['x'].unique().tolist())}")
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print(f" T range: [{df['T'].min():.2f}, {df['T'].max():.2f}] °C")
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return x_s, t_s, T_meas
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