Update part2_visualization.py

part2_visualization.py

@@ -4,7 +4,6 @@ import folium
 from folium import plugins
 import numpy as np
 import branca.colormap as cm
-from datetime import datetime, timedelta
 
 class VisualizationHandler:
     def __init__(self, optimal_conditions):
@@ -21,21 +20,20 @@ class VisualizationHandler:
         ]
 
     def create_interactive_plots(self, df):
-        """Create enhanced interactive Plotly visualizations with pattern emphasis"""
+        """Create enhanced interactive Plotly visualizations"""
         fig = make_subplots(
-            rows=5, cols=1,
+            rows=4, cols=1,
             subplot_titles=(
-                '<b>Temperature (°C)</b>',
-                '<b>Humidity (%)</b>',
-                '<b>Rainfall (mm/day)</b>',
-                '<b>Vegetation Index (NDVI)</b>',
-                '<b>Growing Suitability</b>'
+                '<b>Temperature Pattern (°C)</b>',
+                '<b>Humidity Pattern (%)</b>',
+                '<b>Rainfall Pattern (mm/day)</b>',
+                '<b>Vegetation & Suitability Patterns</b>'
             ),
             vertical_spacing=0.08,
-            row_heights=[0.23, 0.19, 0.19, 0.19, 0.20]
+            row_heights=[0.28, 0.24, 0.24, 0.24]
         )
 
-        # Add temperature visualization with range
+        # Add temperature visualization
         self.add_temperature_plot(fig, df)
         
         # Add humidity visualization
@@ -44,18 +42,15 @@ class VisualizationHandler:
         # Add rainfall visualization
         self.add_rainfall_plot(fig, df)
         
-        # Add NDVI visualization
-        self.add_ndvi_plot(fig, df)
-        
-        # Add suitability visualization
-        self.add_suitability_plot(fig, df)
-        
+        # Add combined NDVI and suitability visualization
+        self.add_combined_patterns_plot(fig, df)
+
         # Update layout
         fig.update_layout(
-            height=1200,
+            height=1000,
             showlegend=True,
             title={
-                'text': "Weather Patterns and Agricultural Conditions Analysis",
+                'text': "Agricultural Conditions Analysis with Pattern Recognition",
                 'y':0.95,
                 'x':0.5,
                 'xanchor': 'center',
@@ -75,23 +70,22 @@ class VisualizationHandler:
             margin=dict(l=60, r=30, t=100, b=60)
         )
 
-        # Add season shading for all plots
+        # Add season shading
         self.add_season_shading(fig, df)
         
-        # Update axes
         fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='rgba(0,0,0,0.1)')
         fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='rgba(0,0,0,0.1)')
         
         return fig
 
     def add_temperature_plot(self, fig, df):
-        """Add detailed temperature visualization"""
+        """Add temperature visualization with range and patterns"""
         # Temperature range area
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
                 y=df['temp_max'],
-                name='Max Temperature',
+                name='Temperature Range',
                 line=dict(color='rgba(255,0,0,0.0)'),
                 showlegend=False
             ),
@@ -102,16 +96,15 @@ class VisualizationHandler:
             go.Scatter(
                 x=df['date'],
                 y=df['temp_min'],
-                name='Temperature Range',
+                name='Daily Range',
                 fill='tonexty',
                 fillcolor='rgba(255,0,0,0.1)',
-                line=dict(color='rgba(255,0,0,0.0)'),
-                showlegend=True
+                line=dict(color='rgba(255,0,0,0.0)')
             ),
             row=1, col=1
         )
-        
-        # Main temperature line
+
+        # Add main temperature line
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
@@ -122,26 +115,31 @@ class VisualizationHandler:
             ),
             row=1, col=1
         )
-        
-        # Add optimal range
-        fig.add_hline(
-            y=self.optimal_conditions['temperature']['min'],
-            line_dash="dash",
-            line_color="green",
-            annotation_text="Min Optimal",
-            row=1, col=1
-        )
-        fig.add_hline(
-            y=self.optimal_conditions['temperature']['max'],
-            line_dash="dash",
-            line_color="green",
-            annotation_text="Max Optimal",
+
+        # Add 7-day average
+        fig.add_trace(
+            go.Scatter(
+                x=df['date'],
+                y=df['temp_7day_avg'],
+                name='7-Day Trend',
+                line=dict(color='darkred', width=1, dash='dot'),
+                mode='lines'
+            ),
             row=1, col=1
         )
 
+        # Add optimal range
+        fig.add_hline(y=self.optimal_conditions['temperature']['min'],
+                     line_dash="dash", line_color="green",
+                     annotation_text="Min Optimal",
+                     row=1, col=1)
+        fig.add_hline(y=self.optimal_conditions['temperature']['max'],
+                     line_dash="dash", line_color="green",
+                     annotation_text="Max Optimal",
+                     row=1, col=1)
+
     def add_humidity_plot(self, fig, df):
-        """Add humidity visualization with pattern emphasis"""
-        # Add main humidity line
+        """Add humidity visualization with patterns"""
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
@@ -153,77 +151,56 @@ class VisualizationHandler:
             row=2, col=1
         )
         
-        # Add rolling average
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
                 y=df['humidity_7day_avg'],
-                name='7-day Humidity Trend',
+                name='Humidity Trend',
                 line=dict(color='darkblue', width=1, dash='dot'),
                 mode='lines'
             ),
             row=2, col=1
         )
 
+        # Add optimal range
+        fig.add_hline(y=self.optimal_conditions['humidity']['min'],
+                     line_dash="dash", line_color="green",
+                     annotation_text="Min Optimal",
+                     row=2, col=1)
+        fig.add_hline(y=self.optimal_conditions['humidity']['max'],
+                     line_dash="dash", line_color="green",
+                     annotation_text="Max Optimal",
+                     row=2, col=1)
+
     def add_rainfall_plot(self, fig, df):
-        """Add enhanced rainfall visualization"""
-        # Add rainfall bars
+        """Add rainfall visualization with patterns"""
+        # Daily rainfall bars
         fig.add_trace(
             go.Bar(
                 x=df['date'],
                 y=df['rainfall'],
-                name='Rainfall',
-                marker_color='blue',
+                name='Daily Rainfall',
+                marker_color='lightblue',
                 opacity=0.6
             ),
             row=3, col=1
         )
-        
-        # Add cumulative rainfall line
-        cumulative_rainfall = df['rainfall'].cumsum()
+
+        # Rainfall trend
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
-                y=cumulative_rainfall,
-                name='Cumulative Rainfall',
-                line=dict(color='darkblue', width=1, dash='dot'),
-                yaxis='y2'
+                y=df['rainfall_7day_avg'],
+                name='Rainfall Trend',
+                line=dict(color='blue', width=2),
+                mode='lines'
             ),
             row=3, col=1
         )
 
-    def add_ndvi_plot(self, fig, df):
-        """Add NDVI visualization with confidence bands"""
-        # Calculate confidence bands
-        ndvi_std = df['estimated_ndvi'].std()
-        upper_band = df['estimated_ndvi'] + ndvi_std
-        lower_band = df['estimated_ndvi'] - ndvi_std
-        
-        # Add NDVI line with confidence band
-        fig.add_trace(
-            go.Scatter(
-                x=df['date'],
-                y=upper_band,
-                name='NDVI Upper Band',
-                line=dict(color='rgba(0,100,0,0)'),
-                showlegend=False
-            ),
-            row=4, col=1
-        )
-        
-        fig.add_trace(
-            go.Scatter(
-                x=df['date'],
-                y=lower_band,
-                name='NDVI Confidence',
-                fill='tonexty',
-                fillcolor='rgba(0,100,0,0.1)',
-                line=dict(color='rgba(0,100,0,0)'),
-                showlegend=True
-            ),
-            row=4, col=1
-        )
-        
+    def add_combined_patterns_plot(self, fig, df):
+        """Add combined NDVI and suitability visualization"""
+        # NDVI line
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
@@ -235,22 +212,20 @@ class VisualizationHandler:
             row=4, col=1
         )
 
-    def add_suitability_plot(self, fig, df):
-        """Add growing suitability visualization"""
+        # Suitability score
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
                 y=df['daily_suitability'],
                 name='Growing Suitability',
                 line=dict(color='purple', width=2),
-                fill='tozeroy',
-                fillcolor='rgba(128,0,128,0.1)'
+                mode='lines'
             ),
-            row=5, col=1
+            row=4, col=1
         )
 
     def add_season_shading(self, fig, df):
-        """Add season shading to all plots"""
+        """Add season indicators to all plots"""
         seasons = df['season'].unique()
         season_colors = {
             'Main': 'rgba(0,255,0,0.1)',    # Green
@@ -262,19 +237,20 @@ class VisualizationHandler:
         for season in seasons:
             season_data = df[df['season'] == season]
             if not season_data.empty:
-                fig.add_vrect(
-                    x0=season_data['date'].iloc[0],
-                    x1=season_data['date'].iloc[-1],
-                    fillcolor=season_colors[season],
-                    layer="below",
-                    line_width=0,
-                    annotation_text=season,
-                    annotation_position="top left",
-                    row="all"
-                )
+                for row in range(1, 5):
+                    fig.add_vrect(
+                        x0=season_data['date'].iloc[0],
+                        x1=season_data['date'].iloc[-1],
+                        fillcolor=season_colors[season],
+                        layer="below",
+                        line_width=0,
+                        annotation_text=season if row == 1 else None,
+                        annotation_position="top left",
+                        row=row, col=1
+                    )
 
     def create_enhanced_map(self, lat, lon, score, ndvi_value):
-        """Create an interactive map with enhanced visualizations"""
+        """Create an interactive map with both weather and vegetation analysis"""
         m = folium.Map(location=[lat, lon], zoom_start=13)
         
         # Add measurement tools
@@ -312,20 +288,18 @@ class VisualizationHandler:
             folium.Circle(
                 radius=radius,
                 location=[lat, lon],
-                popup=f'Growing Suitability: {score:.2f}',
+                popup=f'Suitability Score: {score:.2f}',
                 color=score_color,
                 fill=False,
                 weight=2
             ).add_to(m)
         
-        # Add heat map layer control
-        folium.LayerControl().add_to(m)
-        
         # Add mini map
         minimap = plugins.MiniMap()
         m.add_child(minimap)
         
-        # Add colormap to map
+        # Add layer control
+        folium.LayerControl().add_to(m)
         m.add_child(ndvi_colormap)
         
         return m._repr_html_()