update dashbord: add fault table

dashboard.py

@@ -75,7 +75,8 @@ for i in range(1, 2):
 
 
 all_data = pd.read_csv("data/bootstrap_data.csv")
-
+df_faults = pd.DataFrame(columns = ["_______Time_______","__________Issue__________"])
+current_stat = [False,False,False,False]
 # energy_pipeline_north = EnergyPredictionPipeline(
 #     scaler_path="src/energy_prediction/models/scalerNorth.pkl",
 #     wing="north",
@@ -175,6 +176,8 @@ def update_status_boxes(df,fault):
             """,
                 unsafe_allow_html=True,
             )
+       
+
 
 
 # Zones
@@ -293,22 +296,26 @@ with row1_col2:
 
 # Faults
 with row1_col3:
-    st.markdown(
+    fault_placeholder = {"heading": st.empty(), "dataframe": st.empty()}
+    fault_placeholder["heading"].markdown(
         """
     <div style="background-color:#E2F0D9;padding:1px;border-radius:5px;margin-bottom:20px">
-    <h3 style="color:black;text-align:center;">Faults</h3>
+    <h3 style="color:black;text-align:center;">Fault Log</h3>
     </div>""",
         unsafe_allow_html=True,
     )
-
-    fault_data = {  # ---- REPLACE WITH ACTUAL DATA ----
-        "Start Time": ["28/12/17 10:00", "29/12/17 11:00"],
-        "End Time": ["28/12/17 12:00", "29/12/17 15:00"],
-        "Issue": ["RTU 3 – Damper stuck", "Zone 6 – Fan failure"],
-    }
-    df_faults = pd.DataFrame(fault_data)
-    st.dataframe(df_faults)
-
+    
+    fault_placeholder["dataframe"].dataframe(df_faults)
+    
+def fault_table_update(fault,df_faults,current_stat,df_time):
+    if fault[i]== 1 and current_stat[i] == False:
+        df_faults.loc[len(df_faults)] = [df_time,f'RTU_0{i+1}_fan/damper_fault - Start']
+        current_stat[i] = True
+        
+    if fault[i]== 0 and current_stat[i] == True:
+        df_faults.loc[len(df_faults)] = [df_time,f'RTU_0{i+1}_fan/damper_fault - End']
+        current_stat[i] = False
+    fault_placeholder["dataframe"].dataframe(df_faults)
 
 # Details
 with st.container():
@@ -368,6 +375,7 @@ def create_residual_plot(resid_pca_list, distance, rtu_id,lim=8):
         labels={"x": "Time", "y": "Residual"},
         width=500,
         height=500,
+        color_discrete_sequence=px.colors.qualitative.Set2,
     )
     fig.update_layout(
         xaxis_range=[-lim, lim],
@@ -392,6 +400,8 @@ resid_placeholder = st.empty()
 
 resid_vav_placeholder = st.empty()
 
+
+
 while True:
 
     if mqtt_client.data_list:
@@ -426,6 +436,7 @@ while True:
         rtu_4_distance = None
         fault_3 = None
         fault_4 = None
+        
 
         df_new1, df_trans1, df_new2, df_trans2 = rtu_data_pipeline.fit(
             pd.DataFrame(mqtt_client.data_list)
@@ -533,4 +544,5 @@ while True:
         #     ax.set_ylabel("Energy (kWh)")
         #     st.pyplot(fig)
         update_status_boxes(df,[fault_1,fault_2,fault_3,fault_4])
+        fault_table_update([fault_1,fault_2,fault_3,fault_4],df_faults,current_stat,df_time)
         mqtt_client.data_list.clear()