Dynamic legend n yaxis log

dash_power_room_n_customer.py

@@ -1,5 +1,5 @@
 import dash
-from dash import dcc, html, Input, Output
+from dash import dcc, html, Input, Output, callback_context
 import plotly.express as px
 import pandas as pd
 import sqlite3
@@ -73,20 +73,41 @@ app.layout = html.Div([
     ])
 ])
 
-# Callback to update the building total graph
+# Combined callback to update the building total graph and handle zoom events
 @app.callback(
     Output('building-graph', 'figure'),
-    [Input('time-range', 'value')]
+    [Input('time-range', 'value'),
+     Input('building-graph', 'relayoutData')],
+    [dash.dependencies.State('building-graph', 'figure')]
 )
-def update_building_graph(time_range):
+def update_building_graph(time_range, relayoutData, figure):
+    ctx = callback_context
+
+    if not ctx.triggered:
+        return dash.no_update
+
     df = fetch_data(time_range)
     df = calculate_building_kwh(df)
+
+    # Initialize fig
     fig = px.line(df, x=df.index, y=['total_current', 'total_power', 'kWh'],
                   labels={'value': 'Value', 'variable': 'Metric'},
                   title='Building Total Metrics')
-    fig.update_layout(legend_title_text='Metrics')
+    fig.update_layout(legend_title_text='Metrics', yaxis_type="log")  # Use logarithmic scale
 
-    # Update legend to show recent values
+    if 'time-range' in ctx.triggered[0]['prop_id']:
+        pass  # fig is already initialized
+
+    elif relayoutData and 'xaxis.range[0]' in relayoutData and 'xaxis.range[1]' in relayoutData:
+        start = pd.to_datetime(relayoutData['xaxis.range[0]'])
+        end = pd.to_datetime(relayoutData['xaxis.range[1]'])
+        df = df.loc[start:end]
+        fig = px.line(df, x=df.index, y=['total_current', 'total_power', 'kWh'],
+                      labels={'value': 'Value', 'variable': 'Metric'},
+                      title='Building Total Metrics')
+        fig.update_layout(legend_title_text='Metrics', yaxis_type="log")  # Use logarithmic scale
+
+    # Update legend to show total values
     for trace in fig.data:
         if trace.name == 'kWh':
             trace.name = f"{trace.name}: {df['kWh'].sum():.2f}"
@@ -147,9 +168,9 @@ def update_breakdown_graph(tab, drill_down, time_range):
     fig = px.line(df, x=df.index, y=['current', 'power', 'kWh'],
                   labels={'value': 'Value', 'variable': 'Metric'},
                   title=f'{tab.replace("-", " ").title()} Metrics')
-    fig.update_layout(legend_title_text='Metrics')
+    fig.update_layout(legend_title_text='Metrics', yaxis_type="log")  # Use logarithmic scale
 
-    # Update legend to show recent values
+    # Update legend to show total values
     for trace in fig.data:
         if trace.name == 'kWh':
             trace.name = f"{trace.name}: {df['kWh'].sum():.2f}"