Create modules/simulator.py

modules/simulator.py

@@ -0,0 +1,65 @@
+# modules/simulator.py
+import pandas as pd
+import numpy as np
+import datetime
+from typing import List
+
+def simulate_data(n: int = 1000, faults: bool = True, batch_size: int = 10000) -> pd.DataFrame:
+    """Simulate pole data in batches for scalability."""
+    today = datetime.date.today()
+    all_data = []
+    
+    for batch in range(0, n, batch_size):
+        batch_n = min(batch_size, n - batch)
+        poles = [f"Pole_{batch + i + 1:07}" for i in range(batch_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("LowSolarOutput")
+                if wind < 0.7:
+                    anomaly.append("LowWindOutput")
+                if tilt > 10:
+                    anomaly.append("PoleTiltRisk")
+                if vib > 2.0:
+                    anomaly.append("VibrationAlert")
+                if cam == "Offline":
+                    anomaly.append("CameraOffline")
+                if sufficient == "No":
+                    anomaly.append("PowerInsufficient")
+            
+            alert = "Green"
+            if len(anomaly) == 1:
+                alert = "Yellow"
+            elif len(anomaly) > 1:
+                alert = "Red"
+            
+            data.append({
+                "PoleID": pole,
+                "Date": today,
+                "SolarGen(kWh)": solar,
+                "WindGen(kWh)": wind,
+                "PowerRequired(kWh)": required,
+                "PowerSufficient": sufficient,
+                "CameraStatus": cam,
+                "Tilt(°)": tilt,
+                "Vibration(g)": vib,
+                "Anomalies": ";".join(anomaly) if anomaly else "None",
+                "AlertLevel": alert,
+                "Timestamp": pd.Timestamp.now()
+            })
+        
+        all_data.append(pd.DataFrame(data))
+    
+    return pd.concat(all_data, ignore_index=True)