Update app.py

app.py

@@ -2,7 +2,7 @@ import panel as pn
 import pandas as pd
 import os
 
-from consts import INVERTER_ID_MAPPING, TEMPERATURE_COLUMNS_TO_USE
+from consts import INVERTER_ID_MAPPING, TEMPERATURE_COLUMNS_TO_USE, CURRENT, IRRADIANCE, VOLTAGE, POWER_DC, POWER_AC, T_AMBIENT, T_MODULE, T_HEATSINK, T_CPU, T_BOARD
 from plotting import (
     create_heatmap,
     create_iv_plot_with_power_curves,
@@ -11,33 +11,32 @@ from plotting import (
     create_iv_plot_with_temperature_curves,
 )
 
-# Function to load chunked data based on date range
-def load_timeseries_data(start_date, end_date):
-    start_date_str = pd.to_datetime(start_date).strftime('%Y-%m-%d')
-    end_date_str = (pd.to_datetime(start_date) + pd.offsets.MonthEnd()).strftime('%Y-%m-%d')
-    file_name = f"enel_timeseries_data_{start_date_str}_{end_date_str}.csv"
+# Function to load chunked data based on month selection
+def load_timeseries_data_for_month(month):
+    start_date = pd.to_datetime(month).strftime('%Y-%m-01')
+    end_date = (pd.to_datetime(month) + pd.offsets.MonthEnd()).strftime('%Y-%m-%d')
+    file_name = f"enel_timeseries_data_{start_date}_{end_date}.csv"
     if not os.path.exists(file_name):
         return None
     return pd.read_csv(file_name, index_col=0, header=[0, 1, 2], parse_dates=True)
 
-def load_other_features_data(start_date, end_date):
-    start_date_str = pd.to_datetime(start_date).strftime('%Y-%m-%d')
-    end_date_str = (pd.to_datetime(start_date) + pd.offsets.MonthEnd()).strftime('%Y-%m-%d')
-    file_name = f"enel_other_features_data_{start_date_str}_{end_date_str}.csv"
+def load_other_features_data_for_month(month):
+    start_date = pd.to_datetime(month).strftime('%Y-%m-01')
+    end_date = (pd.to_datetime(month) + pd.offsets.MonthEnd()).strftime('%Y-%m-%d')
+    file_name = f"enel_other_features_data_{start_date}_{end_date}.csv"
     if not os.path.exists(file_name):
         return None
     return pd.read_csv(file_name, index_col=0, header=0, parse_dates=True)
 
-# Define the start and end dates
-start_date = pd.Timestamp('2022-09-01').date()
-end_date = pd.Timestamp('2023-08-31').date()
+# Define the available months
+months = pd.date_range(start='2022-09-01', end='2023-08-31', freq='MS').strftime('%Y-%m').tolist()
 
 kpi_data = pd.read_csv(
-    r"kpi_data.csv", index_col=0, header=0, parse_dates=True
+    "kpi_data.csv", index_col=0, header=0, parse_dates=True
 )
 
 daily_timeseries_data = pd.read_csv(
-    r"daily_aggregated_timeseries_data.csv",
+    "daily_aggregated_timeseries_data.csv",
     index_col=0,
     header=0,
     parse_dates=True,
@@ -46,12 +45,10 @@ daily_timeseries_data = pd.read_csv(
 # Initialize Panel extension
 pn.extension("plotly")
 
-# Widgets for selecting date range and columns
-date_range_picker = pn.widgets.DateRangePicker(
-    name='Date Range', 
-    start=start_date, 
-    end=end_date,
-    value=(start_date, (start_date + pd.DateOffset(months=1)).date())
+# Widgets for selecting month and columns
+month_selector = pn.widgets.Select(
+    name='Choose a Month',
+    options=months,
 )
 
 inverter_ids = pn.widgets.MultiSelect(
@@ -78,23 +75,28 @@ heatmap_temperature = pn.widgets.Checkbox(
 # Create a loading spinner
 loading_spinner = pn.indicators.LoadingSpinner(width=50, height=50)
 
+# Global variables to store loaded data
+loaded_timeseries_data = None
+loaded_other_features_data = None
+
 # Panel interactive functions
 @pn.depends(
     inverter_ids.param.value,
     plot_power_curves.param.value,
     plot_temperature_curves.param.value,
-    date_range_picker.param.value
+    month_selector.param.value
 )
-def update_iv_plot(inverter_ids, plot_power_curves, plot_temperature_curves, date_range):
-    if date_range[0] is None or date_range[1] is None:
-        return pn.pane.Markdown("Please select a date range to load data.")
+def update_iv_plot(inverter_ids, plot_power_curves, plot_temperature_curves, selected_month):
+    global loaded_timeseries_data, loaded_other_features_data
+    if not selected_month:
+        return pn.pane.Markdown("Please select a month to load data.")
     
-    start_date, end_date = date_range
-    timeseries_data = load_timeseries_data(start_date, end_date)
-    other_features_data = load_other_features_data(start_date, end_date)
-
-    if timeseries_data is None or other_features_data is None:
-        return pn.pane.Markdown("No data available for the selected date range.")
+    if loaded_timeseries_data is None or loaded_other_features_data is None:
+        loaded_timeseries_data = load_timeseries_data_for_month(selected_month)
+        loaded_other_features_data = load_other_features_data_for_month(selected_month)
+    
+    if loaded_timeseries_data is None or loaded_other_features_data is None:
+        return pn.pane.Markdown("No data available for the selected month.")
     
     if not inverter_ids:
         return pn.pane.Markdown("No Inverters selected for Plotting.")
@@ -102,19 +104,19 @@ def update_iv_plot(inverter_ids, plot_power_curves, plot_temperature_curves, dat
         # Plot IV + Power + Temperature Curves
         if plot_power_curves and plot_temperature_curves:
             return create_iv_plot_with_power_and_temperature_curves(
-                timeseries_data, other_features_data, inverter_ids
+                loaded_timeseries_data, loaded_other_features_data, inverter_ids
             )
         # Plot IV + Temperature Curves
         elif (not plot_power_curves) and plot_temperature_curves:
             return create_iv_plot_with_temperature_curves(
-                timeseries_data, other_features_data, inverter_ids
+                loaded_timeseries_data, loaded_other_features_data, inverter_ids
             )
         # Plot IV + Power Curves
         elif plot_power_curves and (not plot_temperature_curves):
-            return create_iv_plot_with_power_curves(timeseries_data, inverter_ids)
+            return create_iv_plot_with_power_curves(loaded_timeseries_data, inverter_ids)
         # Plot only IV Curves
         else:
-            return create_iv_plot(timeseries_data, inverter_ids)
+            return create_iv_plot(loaded_timeseries_data, inverter_ids)
 
 
 @pn.depends(heatmap_pr.param.value)
@@ -190,7 +192,7 @@ def update_heatmap_temperature(heatmap_temperature):
 # Create dashboard layout
 dashboard = pn.Column(
     "# ENEL Dashboard",
-    date_range_picker,
+    month_selector,
     # IV Plots
     pn.Row(
         pn.Column(inverter_ids, plot_power_curves, plot_temperature_curves),