Update part2_visualization.py

part2_visualization.py

@@ -4,6 +4,7 @@ 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):
@@ -20,33 +21,33 @@ class VisualizationHandler:
         ]
 
     def create_interactive_plots(self, df):
-        """Create enhanced interactive Plotly visualizations"""
+        """Create enhanced interactive Plotly visualizations with pattern emphasis"""
         fig = make_subplots(
-            rows=5, cols=1,  # Added rows for NDVI and Daily Suitability
+            rows=5, cols=1,
             subplot_titles=(
                 '<b>Temperature (°C)</b>',
                 '<b>Humidity (%)</b>',
                 '<b>Rainfall (mm/day)</b>',
                 '<b>Vegetation Index (NDVI)</b>',
-                '<b>Daily Growing Suitability</b>'
+                '<b>Growing Suitability</b>'
             ),
-            vertical_spacing=0.07,
-            row_heights=[0.2, 0.2, 0.2, 0.2, 0.2]
+            vertical_spacing=0.08,
+            row_heights=[0.23, 0.19, 0.19, 0.19, 0.20]
         )
-        
-        # Temperature plot
+
+        # Add temperature visualization with range
         self.add_temperature_plot(fig, df)
         
-        # Humidity plot
+        # Add humidity visualization
         self.add_humidity_plot(fig, df)
         
-        # Rainfall plot
+        # Add rainfall visualization
         self.add_rainfall_plot(fig, df)
         
-        # NDVI plot
+        # Add NDVI visualization
         self.add_ndvi_plot(fig, df)
         
-        # Daily Suitability plot
+        # Add suitability visualization
         self.add_suitability_plot(fig, df)
         
         # Update layout
@@ -54,7 +55,7 @@ class VisualizationHandler:
             height=1200,
             showlegend=True,
             title={
-                'text': "Enhanced Tobacco Growing Conditions Analysis",
+                'text': "Weather Patterns and Agricultural Conditions Analysis",
                 'y':0.95,
                 'x':0.5,
                 'xanchor': 'center',
@@ -74,23 +75,25 @@ class VisualizationHandler:
             margin=dict(l=60, r=30, t=100, b=60)
         )
 
+        # Add season shading for all plots
+        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 temperature visualization"""
-        # Add detailed temperature data
+        """Add detailed temperature visualization"""
+        # Temperature range area
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
                 y=df['temp_max'],
                 name='Max Temperature',
-                line=dict(color='red', width=1),
-                mode='lines',
-                fillcolor='rgba(255,0,0,0.1)',
-                fill='tonexty'
+                line=dict(color='rgba(255,0,0,0.0)'),
+                showlegend=False
             ),
             row=1, col=1
         )
@@ -99,27 +102,46 @@ class VisualizationHandler:
             go.Scatter(
                 x=df['date'],
                 y=df['temp_min'],
-                name='Min Temperature',
-                line=dict(color='blue', width=1),
-                mode='lines',
-                fillcolor='rgba(0,0,255,0.1)',
-                fill='tonexty'
+                name='Temperature Range',
+                fill='tonexty',
+                fillcolor='rgba(255,0,0,0.1)',
+                line=dict(color='rgba(255,0,0,0.0)'),
+                showlegend=True
+            ),
+            row=1, col=1
+        )
+        
+        # Main temperature line
+        fig.add_trace(
+            go.Scatter(
+                x=df['date'],
+                y=df['temperature'],
+                name='Temperature',
+                line=dict(color='red', width=2),
+                mode='lines'
             ),
             row=1, col=1
         )
         
         # Add optimal range
-        for limit in ['min', 'max']:
-            fig.add_hline(
-                y=self.optimal_conditions['temperature'][limit],
-                line_dash="dash",
-                line_color="green",
-                annotation_text=f"Optimal {limit}",
-                row=1, col=1
-            )
+        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"""
+        """Add humidity visualization with pattern emphasis"""
+        # Add main humidity line
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
@@ -131,42 +153,77 @@ 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 Average',
-                line=dict(color='purple', width=1, dash='dot'),
+                name='7-day Humidity Trend',
+                line=dict(color='darkblue', width=1, dash='dot'),
                 mode='lines'
             ),
             row=2, col=1
         )
 
     def add_rainfall_plot(self, fig, df):
-        """Add rainfall visualization"""
+        """Add enhanced rainfall visualization"""
+        # Add rainfall bars
         fig.add_trace(
             go.Bar(
                 x=df['date'],
                 y=df['rainfall'],
                 name='Rainfall',
-                marker_color='blue'
+                marker_color='blue',
+                opacity=0.6
             ),
             row=3, col=1
         )
         
+        # Add cumulative rainfall line
+        cumulative_rainfall = df['rainfall'].cumsum()
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
-                y=df['rainfall_7day_avg'],
-                name='7-day Rainfall Average',
-                line=dict(color='purple', width=1, dash='dot'),
-                mode='lines'
+                y=cumulative_rainfall,
+                name='Cumulative Rainfall',
+                line=dict(color='darkblue', width=1, dash='dot'),
+                yaxis='y2'
             ),
             row=3, col=1
         )
 
     def add_ndvi_plot(self, fig, df):
-        """Add NDVI visualization"""
+        """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
+        )
+        
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
@@ -177,33 +234,47 @@ class VisualizationHandler:
             ),
             row=4, col=1
         )
-        
-        # Add optimal NDVI range
-        for limit in ['min', 'max']:
-            fig.add_hline(
-                y=self.optimal_conditions['ndvi'][limit],
-                line_dash="dash",
-                line_color="green",
-                annotation_text=f"Optimal {limit}",
-                row=4, col=1
-            )
 
     def add_suitability_plot(self, fig, df):
-        """Add daily suitability visualization"""
+        """Add growing suitability visualization"""
         fig.add_trace(
             go.Scatter(
                 x=df['date'],
                 y=df['daily_suitability'],
                 name='Growing Suitability',
-                line=dict(color='darkblue', width=2),
-                mode='lines',
-                fill='tozeroy'
+                line=dict(color='purple', width=2),
+                fill='tozeroy',
+                fillcolor='rgba(128,0,128,0.1)'
             ),
             row=5, col=1
         )
 
+    def add_season_shading(self, fig, df):
+        """Add season shading to all plots"""
+        seasons = df['season'].unique()
+        season_colors = {
+            'Main': 'rgba(0,255,0,0.1)',    # Green
+            'Early': 'rgba(255,255,0,0.1)',  # Yellow
+            'Late': 'rgba(255,165,0,0.1)',   # Orange
+            'Dry': 'rgba(255,0,0,0.1)'       # Red
+        }
+        
+        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"
+                )
+
     def create_enhanced_map(self, lat, lon, score, ndvi_value):
-        """Create an interactive map with both weather and vegetation analysis"""
+        """Create an interactive map with enhanced visualizations"""
         m = folium.Map(location=[lat, lon], zoom_start=13)
         
         # Add measurement tools
@@ -222,7 +293,7 @@ class VisualizationHandler:
             colors=self.ndvi_colors,
             vmin=-1,
             vmax=1,
-            caption='NDVI Values'
+            caption='Vegetation Index (NDVI)'
         )
         
         # Add NDVI circle
@@ -235,46 +306,38 @@ class VisualizationHandler:
             fillOpacity=0.4
         ).add_to(m)
         
-        # Add growing suitability circles
+        # Add suitability circles
         score_color = self.get_score_color(score)
         for radius in [500, 1000, 1500]:
             folium.Circle(
                 radius=radius,
                 location=[lat, lon],
-                popup=f'Suitability Score: {score:.2f}',
+                popup=f'Growing Suitability: {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 layer control and colormap
-        folium.LayerControl().add_to(m)
+        # Add colormap to map
         m.add_child(ndvi_colormap)
         
         return m._repr_html_()
 
-    def get_score_color(self, score):
-        """Get color based on score"""
-        if score >= 0.8:
-            return 'green'
-        elif score >= 0.6:
-            return 'yellow'
-        elif score >= 0.4:
-            return 'orange'
-        return 'red'
-
-    def create_gauge_chart(self, score, title="Growing Conditions Score"):
+    def create_gauge_chart(self, score):
         """Create an enhanced gauge chart for the overall score"""
         fig = go.Figure(go.Indicator(
             mode="gauge+number+delta",
             value=score,
             domain={'x': [0, 1], 'y': [0, 1]},
             title={
-                'text': title,
+                'text': "Growing Conditions Score",
                 'font': {'size': 24}
             },
             delta={
@@ -309,4 +372,14 @@ class VisualizationHandler:
             font={'color': "darkblue", 'family': "Arial"}
         )
         
-        return fig
+        return fig
+
+    def get_score_color(self, score):
+        """Get color based on score"""
+        if score >= 0.8:
+            return 'green'
+        elif score >= 0.6:
+            return 'yellow'
+        elif score >= 0.4:
+            return 'orange'
+        return 'red'