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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)]
# Coordinates for sites
sites = {
"Hyderabad": (17.3850, 78.4867),
"Gadwal": (16.2356, 77.7956),
"Kurnool": (15.8281, 78.0373),
"Ballari": (15.1394, 76.9214)
}
site_names = list(sites.keys())
data = []
for pole in poles:
site = np.random.choice(site_names)
lat, lon = sites[site]
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")
if len(anomaly) == 0:
alert = "Green"
alert_weight = 1
elif len(anomaly) == 1:
alert = "Yellow"
alert_weight = 2
else:
alert = "Red"
alert_weight = 3
data.append({
"Pole ID": pole,
"Date": today,
"Site": site,
"Latitude": lat,
"Longitude": lon,
"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,
"Alert Weight": alert_weight
})
return pd.DataFrame(data)
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