add filter option for temp, and input button

app.py

@@ -19,6 +19,8 @@ original_df, df, X, Y, T = prepare_data(og_file, training_file)
 app_ui = ui.page_fluid(
     ui.input_radio_buttons("tab_choice", "Choose page:", ["Effect of trees on temperature", "Effect of temperature on trees"]),
     ui.output_ui("tab_slider"),
+    ui.input_radio_buttons("split_filter", "Apply filter?",
+               choices=["No filter", "Filter"], selected="No filter"),
     ui.output_ui("page_ui")
 )
 
@@ -49,13 +51,13 @@ def server(input, output, session):
     def page_ui():
         if input.tab_choice() == "Effect of trees on temperature":
             return ui.div(
-                ui.h2("Temperature Simulation Viewer", class_="text-center"),
+                ui.h2("Simulation Viewer - Increasing tree coverage", class_="text-center"),
                 ui.div(ui.output_plot("temp_after_treatment"), style="display: flex; justify-content: center;"),
                 ui.div(ui.output_plot("temp_change"), style="display: flex; justify-content: center;"),
             )
         else: #Effect of temperature on trees
             return ui.div(
-                ui.h2("Tree Simulation Viewer", class_="text-center"),
+                ui.h2("Simulation Viewer - Decreasing temperature", class_="text-center"),
                 ui.div(ui.output_plot("trees_after_decrease"), style="display: flex; justify-content: center;"),
                 ui.div(ui.output_plot("tree_coverage_change"), style="display: flex; justify-content: center;"),
             )
@@ -65,12 +67,17 @@ def server(input, output, session):
     def temp_after_treatment():
         gdf_trees = get_gdf_trees()
         value_trees = input.tree_pct()
+        apply_filter = input.split_filter()
+
+        if apply_filter == "Filter":
+            split = f'total_trees_treatment_{value_trees}%'
+        else:
+            split = False
+
         try:
             fig = show_two_plots(gdf_trees, f'simulated_temp_{value_trees}%', 'LST', 
-             15, 35, 'coolwarm',
-                   f"Temperature after treatment (+{value_trees}% Trees)",
-            "Original temperature",
-                  'Temperature (°C)')
+             15, 35, 'coolwarm',f"Temperature after treatment (+{value_trees}% Trees)",
+             "Original temperature",'Temperature (°C)',split=split)
             return fig
         except Exception as e:
             print("Plotting error:", e)
@@ -92,13 +99,20 @@ def server(input, output, session):
     def trees_after_decrease():
         gdf_temp = get_gdf_temp()
         value_temp = input.temp_goal()
+        apply_filter = input.split_filter()
+
+        if apply_filter == "Filter":
+            split = f'total_trees_needed_for_{value_temp}C'
+        else:
+            split = False
+
         min_cobertura_veg = 5
         max_cobertura = 100
         try:
             fig = show_two_plots(gdf_temp, f'total_trees_needed_for_{value_temp}C', '%CoberturaVeg', 
              min_cobertura_veg, max_cobertura, 'YlGn', 
              f"Tree coverage needed for {value_temp}°C decrease","Original tree canopy coverage",
-             "Tree canopy coverage (%)", split=True)
+             "Tree canopy coverage (%)", split=split)
             return fig
         except Exception as e:
             print("Plotting error:", e)

data_utils.py

@@ -46,7 +46,8 @@ def run_treatment_increase(X, T, original_df, df, value, name):
     treatment_df = prepare_treatment_df(original_df, df)
     T_sim = T.copy()  
     value_num = 1+ (value/100)
-    data = {"X": X.tolist(), "T0":T.tolist(), "T1":(T_sim*value_num).tolist()}
+    T_sim = T_sim*value_num
+    data = {"X": X.tolist(), "T0":T.tolist(), "T1":(T_sim).tolist()}
     response = requests.post(url, headers=headers, json=data)
     if response.ok:
         result = response.json()
@@ -55,6 +56,7 @@ def run_treatment_increase(X, T, original_df, df, value, name):
         print("Request failed:", response.status_code, response.text)
     
     treatment_df[name] = result["effect"]
+    treatment_df[f'total_trees_treatment_{value}%'] = T_sim
 
     return treatment_df
 

plot_utils.py

@@ -5,6 +5,7 @@ import matplotlib.gridspec as gridspec
 
 
 def show_two_plots(gdf, name1, name2, vmin, vmax, colorscheme, title1, title2, label, split=False):
+    print('split', split)
     if gdf.empty:
         raise ValueError("GeoDataFrame is empty")
 
@@ -23,36 +24,35 @@ def show_two_plots(gdf, name1, name2, vmin, vmax, colorscheme, title1, title2, l
 
     axes = [fig.add_subplot(gs[0]), fig.add_subplot(gs[1]), fig.add_subplot(gs[2]) ]
 
-    if split:
-        # Split data into three GeoDataFrames
-        below_100 = gdf[gdf[name1] <= 100]
-        above_capacity = gdf[gdf[name1] > (100-gdf['%Construccion'])]
-        above_100 = gdf[gdf[name1] > 100]
+    if split == False:
+        # First plot 
+        gdf.plot(column=name1, cmap=cmap, norm=norm, ax=axes[0], marker='s', markersize=10)
     
+    else:
+        # Split data into three GeoDataFrames
+        # below_100 = gdf[gdf[split] <= 100]
+        above_capacity = gdf[gdf[split] > (100-gdf['%Construccion'])]
+        above_100 = gdf[gdf[split] > 100]
+        above_colors = {"capacity":"chocolate", "100":"firebrick"}
         
         # Plot values ≤ 100 using colormap
-        below_100.plot(column=name1, cmap='YlGn', ax=axes[0], vmin=vmin, vmax=vmax, marker='s', markersize=10)
+        gdf.plot(column=name1, cmap=colorscheme, ax=axes[0], vmin=vmin, vmax=vmax, marker='s', markersize=10)
         
         # Plot values > capacity in orange
-        above_capacity.plot(color='orange', ax=axes[0], label='> capacity due to construction', marker='x', markersize=10)
+        above_capacity.plot(color=above_colors['capacity'], ax=axes[0], label='> capacity due to construction', marker='x', markersize=6)
         
         # Plot values > 100 in red
-        above_100.plot(color='firebrick', ax=axes[0], label='> 100% trees', marker='s', markersize=10)
+        above_100.plot(color=above_colors['100'], ax=axes[0], label='> 100% trees', marker='x', markersize=6)
         
         # Add legend manually for orange points
         orange_patch = plt.Line2D([0], [0], marker='o', color='w', label='> capacity due to construction', 
-                               markerfacecolor='orange', markersize=8)
+                               markerfacecolor=above_colors['capacity'], markersize=8)
     
         # Add legend manually for red points
         red_patch = plt.Line2D([0], [0], marker='o', color='w', label='> 100% trees', 
-                               markerfacecolor='firebrick', markersize=8)
+                               markerfacecolor=above_colors['100'], markersize=8)
         
         axes[0].legend(handles=[orange_patch, red_patch])
-
-
-    else:
-        # First plot 
-        gdf.plot(column=name1, cmap=cmap, norm=norm, ax=axes[0], marker='s', markersize=10)
     axes[0].set_title(title1)
     axes[0].set_axis_off()