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| import pandas as pd | |
| import numpy as np | |
| import datetime | |
| def simulate_data(n=10, faults=True): | |
| today = datetime.date.today() | |
| # Generating simulated pole IDs | |
| poles = [f"Pole_{i+1:03}" for i in range(n)] | |
| # Data structure to store the simulated data | |
| data = [] | |
| for pole in poles: | |
| # Randomized values for solar and wind power generation | |
| solar = round(np.random.uniform(3.0, 7.5), 2) | |
| wind = round(np.random.uniform(0.5, 2.0), 2) | |
| required = round(np.random.uniform(1.0, 1.5), 2) | |
| total = solar + wind | |
| # Simulate camera status (randomly online or offline) | |
| cam = np.random.choice(['Online', 'Offline'], p=[0.85, 0.15]) if faults else "Online" | |
| # Randomized tilt and vibration values | |
| tilt = round(np.random.uniform(0, 12), 1) | |
| vib = round(np.random.uniform(0.1, 2.5), 2) | |
| sufficient = "Yes" if total >= required else "No" | |
| # Create anomalies if faults are enabled | |
| anomaly = [] | |
| if faults: | |
| if solar < 4.0: | |
| anomaly.append("Low Solar Output") | |
| if wind < 0.7: | |
| anomaly.append("Low Wind Output") | |
| if tilt > 10: | |
| anomaly.append("Pole Tilt Risk") | |
| if vib > 2.0: | |
| anomaly.append("Vibration Alert") | |
| if cam == "Offline": | |
| anomaly.append("Camera Offline") | |
| if sufficient == "No": | |
| anomaly.append("Power Insufficient") | |
| # Determine alert level based on anomalies | |
| alert = "Green" | |
| if len(anomaly) == 1: | |
| alert = "Yellow" | |
| elif len(anomaly) > 1: | |
| alert = "Red" | |
| # Append the data for the current pole | |
| data.append({ | |
| "Pole ID": pole, | |
| "Date": today, | |
| "Solar Gen (kWh)": solar, | |
| "Wind Gen (kWh)": wind, | |
| "Power Required (kWh)": required, | |
| "Power Sufficient": sufficient, | |
| "Camera Status": cam, | |
| "Tilt (°)": tilt, | |
| "Vibration (g)": vib, | |
| "Anomalies": "; ".join(anomaly) if anomaly else "None", | |
| "Alert Level": alert | |
| }) | |
| return pd.DataFrame(data) | |