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, CURRENT, IRRADIANCE, VOLTAGE, POWER_DC, POWER_AC, T_AMBIENT, T_MODULE, T_HEATSINK, T_CPU, T_BOARD
+from consts import INVERTER_ID_MAPPING, TEMPERATURE_COLUMNS_TO_USE
 from plotting import (
     create_heatmap,
     create_iv_plot_with_power_curves,
@@ -11,33 +11,30 @@ from plotting import (
     create_iv_plot_with_temperature_curves,
 )
 
-def load_data_in_chunks(file_path, selected_columns, start_date=None, end_date=None, chunksize=10000):
-    # Load the entire header to get multi-level column names
-    header = pd.read_csv(file_path, nrows=0, header=[0, 1, 2], index_col=0)
-    
-    # Filter the required columns including datetime
-    columns = [col for col in header.columns if col[2] in selected_columns]
-    
-    chunks = []
-    for chunk in pd.read_csv(file_path, chunksize=chunksize, header=[0, 1, 2], index_col=0, parse_dates=True):
-        # Assign multi-level columns (excluding the index)
-        chunk.columns = header.columns
-        
-        # Filter the necessary columns
-        chunk = chunk[columns]
-        
-        # Apply date range filtering if necessary
-        if start_date and end_date:
-            chunk = chunk[(chunk.index >= start_date) & (chunk.index <= end_date)]
-        
-        chunks.append(chunk)
-    
-    return pd.concat(chunks)
+# Function to load chunked data based on date range
+def load_timeseries_data(start_date, end_date):
+    file_name = f"enel_timeseries_data_{start_date}_{end_date}.csv"
+    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):
+    file_name = f"enel_other_features_data_{start_date}_{end_date}.csv"
+    return pd.read_csv(file_name, index_col=0, header=0, parse_dates=True)
+
+kpi_data = pd.read_csv(
+    r"kpi_data.csv", index_col=0, header=0, parse_dates=True
+)
 
 # Initialize Panel extension
 pn.extension("plotly")
 
-# Widgets for selecting columns
+# Widgets for selecting date range and columns
+date_range_picker = pn.widgets.DateRangePicker(
+    name='Date Range', 
+    start=pd.Timestamp('2022-09-01'), 
+    end=pd.Timestamp('2023-08-31'),
+    value=(start, end + pd.DateOffset(months=1))
+)
+
 inverter_ids = pn.widgets.MultiSelect(
     name="Inverter IDs",
     value=[list(INVERTER_ID_MAPPING.keys())[0]],
@@ -62,31 +59,21 @@ heatmap_temperature = pn.widgets.Checkbox(
 # Create a loading spinner
 loading_spinner = pn.indicators.LoadingSpinner(width=50, height=50)
 
+# Panel interactive functions
 @pn.depends(
     inverter_ids.param.value,
     plot_power_curves.param.value,
     plot_temperature_curves.param.value,
+    date_range_picker.param.value
 )
-@pn.depends(
-    inverter_ids.param.value,
-    plot_power_curves.param.value,
-    plot_temperature_curves.param.value,
-)
-def update_iv_plot(inverter_ids, plot_power_curves, plot_temperature_curves):
+def update_iv_plot(inverter_ids, plot_power_curves, plot_temperature_curves, date_range):
+    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 not inverter_ids:
         return pn.pane.Markdown("No Inverters selected for Plotting.")
     else:
-        selected_columns = []
-        if plot_power_curves:
-            selected_columns += [CURRENT, IRRADIANCE, VOLTAGE, POWER_DC, POWER_AC]
-        if plot_temperature_curves:
-            selected_columns += [T_AMBIENT, T_MODULE, T_HEATSINK, T_CPU, T_BOARD]
-        if not plot_power_curves and not plot_temperature_curves:
-            selected_columns += [CURRENT, IRRADIANCE, VOLTAGE]
-
-        timeseries_data = load_data_in_chunks('multi_index_timeseries_data.csv', selected_columns)
-        other_features_data = load_data_in_chunks('other_features_data.csv', TEMPERATURE_COLUMNS_TO_USE)
-
         # Plot IV + Power + Temperature Curves
         if plot_power_curves and plot_temperature_curves:
             print("Plotting IV + Power + Temperature Curves")
@@ -108,6 +95,7 @@ def update_iv_plot(inverter_ids, plot_power_curves, plot_temperature_curves):
             print("Plot only IV Curves")
             return create_iv_plot(timeseries_data, inverter_ids)
 
+
 @pn.depends(heatmap_pr.param.value)
 def update_heatmap_pr(heatmap_pr):
     if heatmap_pr:
@@ -117,6 +105,7 @@ def update_heatmap_pr(heatmap_pr):
         return pn.Row(pr_heatmap)
     return pn.pane.Markdown("")
 
+
 @pn.depends(heatmap_sy.param.value)
 def update_heatmap_sy(heatmap_sy):
     if heatmap_sy:
@@ -126,6 +115,7 @@ def update_heatmap_sy(heatmap_sy):
         return pn.Row(sy_heatmap)
     return pn.pane.Markdown("")
 
+
 @pn.depends(heatmap_current.param.value)
 def update_heatmap_current(heatmap_current):
     if heatmap_current:
@@ -135,6 +125,7 @@ def update_heatmap_current(heatmap_current):
         return pn.Row(current_heatmap)
     return pn.pane.Markdown("")
 
+
 @pn.depends(heatmap_voltage.param.value)
 def update_heatmap_voltage(heatmap_voltage):
     if heatmap_voltage:
@@ -144,6 +135,7 @@ def update_heatmap_voltage(heatmap_voltage):
         return pn.Row(voltage_heatmap)
     return pn.pane.Markdown("")
 
+
 @pn.depends(heatmap_power.param.value)
 def update_heatmap_power(heatmap_power):
     if heatmap_power:
@@ -153,6 +145,7 @@ def update_heatmap_power(heatmap_power):
         return pn.Row(power_heatmap)
     return pn.pane.Markdown("")
 
+
 @pn.depends(heatmap_irradiance.param.value)
 def update_heatmap_irradiance(heatmap_irradiance):
     if heatmap_irradiance:
@@ -162,6 +155,7 @@ def update_heatmap_irradiance(heatmap_irradiance):
         return pn.Row(irradiance_heatmap)
     return pn.pane.Markdown("")
 
+
 @pn.depends(heatmap_temperature.param.value)
 def update_heatmap_temperature(heatmap_temperature):
     if heatmap_temperature:
@@ -171,6 +165,7 @@ def update_heatmap_temperature(heatmap_temperature):
         return pn.Row(temp_heatmap)
     return pn.pane.Markdown("")
 
+
 # Create dashboard layout
 dashboard = pn.Column(
     "# ENEL Dashboard",