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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()
poles = [f"Pole_{i+1:03}" for i in range(n)]
data = []
for pole in poles:
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
cam = np.random.choice(['Online', 'Offline'], p=[0.85, 0.15]) if faults else "Online"
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"
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")
alert = "Green"
if len(anomaly) == 1:
alert = "Yellow"
elif len(anomaly) > 1:
alert = "Red"
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)
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