chore: Update energy usage statistics display in dashboard.py

dashboard.py

@@ -13,6 +13,10 @@ from src.rtu.RTUPipeline import RTUPipeline
 from src.rtu.RTUAnomalizer1 import RTUAnomalizer1
 from src.rtu.RTUAnomalizer2 import RTUAnomalizer2
 import plotly.express as px
+import sys
+import subprocess
+
+# subprocess.run([f"{sys.executable}", "mqttpublisher.py"])
 
 rtu_data_pipeline = RTUPipeline(
     scaler1_path="src/rtu/models/scaler_rtu_1_2.pkl",
@@ -21,6 +25,8 @@ rtu_data_pipeline = RTUPipeline(
 
 rtu_anomalizers = []
 
+average_energy = 0
+max_energy = 0
 
 rtu_anomalizers.append(
     RTUAnomalizer1(
@@ -368,9 +374,11 @@ with st.container():
 
             # Energy Comsumption Statistics
             with row2_row2_col2:
-                st.subheader("Energy Usage Statistics")
-                st.text(
-                    f"Average: 475 kWh\nHighest: 600 kWh"
+                energy_stats_placeholder = {"box": st.empty(), "sub": st.empty()}
+
+                energy_stats_placeholder["box"].title("Energy Usage Statistics")
+                energy_stats_placeholder["sub"].text(
+                    f"Average: {max_energy} kWh\nHighest: {average_energy} kWh"
                 )  # ---- REPLACE WITH ACTUAL DATA ----
 
 
@@ -416,6 +424,7 @@ resid_placeholder = st.empty()
 
 resid_vav_placeholder = st.empty()
 
+k = 0
 
 while True:
 
@@ -452,6 +461,21 @@ while True:
         fault_3 = None
         fault_4 = None
 
+        energy = (
+            pd.DataFrame(mqtt_client.data_list)["hvac_N"].item()
+            + pd.DataFrame(mqtt_client.data_list)["hvac_N"].item()
+        )
+        k += 1
+
+        average_energy = average_energy + (energy - average_energy) / k
+
+        if energy > max_energy:
+            max_energy = energy
+
+        energy_stats_placeholder["sub"].text(
+            f"Average: {max_energy} kWh\nHighest: {average_energy} kWh"
+        )  # ---- REPLACE WITH ACTUAL DATA ----
+
         df_new1, df_trans1, df_new2, df_trans2 = rtu_data_pipeline.fit(
             pd.DataFrame(mqtt_client.data_list)
         )

mqttpublisher.py

@@ -5,10 +5,9 @@ import pandas as pd
 import json
 
 clientId = "smartbuilding"
-broker_address = "test.mosquito.org"
+broker_address = "test.mosquitto.org"
 broker_port = 1883
 
-
 client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION1, clientId)
 client.connect(broker_address, broker_port)
 topic = "sensor_data"