Update modules/simulator.py

modules/simulator.py

@@ -1,65 +1,50 @@
-# 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."""
+def simulate_data(n=10, faults=True):
     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)
+    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)