Connect model to code

app.py

@@ -6,7 +6,7 @@ from shiny import reactive, render, ui, App
 from shinywidgets import render_widget
 
 from plot_utils import show_one_plot, show_two_plots
-from data_utils import prepare_data
+from data_utils import prepare_data, process_data_trees_to_temp
 
 import pandas as pd
 import geopandas as gpd
@@ -21,6 +21,8 @@ import requests
 
 url = "https://Projects-by-IF-model-temp-api.hf.space/model-effect"
 headers = {"Content-Type": "application/json"}
+
+####test####
 data = {
     "X": [[1462, -0.18, 234, 8]], "T0":[10], "T1":[15]
 }
@@ -32,8 +34,9 @@ if response.ok:
     print("Model response:", result["effect"])
 else:
     print("Request failed:", response.status_code, response.text)
+#######
 
-treatment_df = pd.read_csv("example.csv", index_col=0)
+# treatment_df = pd.read_csv("example.csv", index_col=0)
 og_file = "cleaned_dataframe.csv"
 training_file = "training_dataframe.csv"
 original_df, df, X, Y, T = prepare_data(og_file, training_file)
@@ -41,19 +44,27 @@ original_df, df, X, Y, T = prepare_data(og_file, training_file)
 print(X)
 
 
-ui.input_slider("trees", "Percentage increase in tree coverage", 0, 100, 20)
-
-
 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.output_ui("page_ui")
 )
 
 def server(input, output, session):
-# def show_effect_trees_on_temp():  
-    value = 40
-    name = f'treatment_effect_{value}%'
-    gdf = gpd.GeoDataFrame(treatment_df, geometry=gpd.points_from_xy(treatment_df.x, treatment_df.y))
+    @output
+    @render.ui
+    def tab_slider():
+        if input.tab_choice() == "Effect of trees on temperature":
+            return ui.input_slider("tree_pct", "Tree Increase (%)", min=0, max=100, value=40, step=5)
+        else:  # "Effect of temperature on trees"
+            return ui.input_slider("temp_goal", "Temperature Decrease (°C)", min=0, max=5, value=1, step=0.2)
+            
+ 
+    @reactive.Calc
+    def get_gdf_trees():
+        value_trees = input.tree_pct()
+        print(f"value inputed is {input.tree_pct()}")
+        return process_data_trees_to_temp(value_trees, original_df, df, X, Y, T)
     
     @output
     @render.ui
@@ -73,11 +84,12 @@ def server(input, output, session):
     @output
     @render.plot()
     def temp_after_treatment():
+        gdf_trees = get_gdf_trees()
+        value_trees = input.tree_pct()
         try:
-            fig = show_two_plots(gdf, f'simulated_temp_{value}%', 'LST', 
-             gdf['LST'].min() + treatment_df[name].min(), 
-             gdf['LST'].max(), 'coolwarm',
-                   f"Temperature after treatment (+{value}% Trees)",
+            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)')
             return fig
@@ -89,9 +101,12 @@ def server(input, output, session):
     @output
     @render.plot()
     def treatment_trees_effect():
-        fig = show_one_plot(gdf, name, gdf[name].min(), 
-                  gdf[name].max(), 'PuBu_r', 
-                  f"Decrease of temperature from treatment (+{value}% Trees)", 
+        gdf_trees = get_gdf_trees()
+        value_trees = input.tree_pct()
+        print(value_trees)
+        print(gdf_trees)
+        fig = show_one_plot(gdf_trees, f'treatment_effect_{value_trees}%', -2, 0, 'PuBu_r', 
+                  f"Decrease of temperature from treatment (+{value_trees}% Trees)", 
                   "Temperature decrease (°C)")
         return fig
     

data_utils.py

@@ -1,5 +1,11 @@
 import pandas as pd
 import numpy as np
+import geopandas as gpd
+
+import requests
+
+url = "https://Projects-by-IF-model-temp-api.hf.space/model-effect"
+headers = {"Content-Type": "application/json"}
 
 def make_XYT(df, treatment_col = '%CoberturaVeg', target_col = 'LST'):
     
@@ -25,3 +31,40 @@ def prepare_data(og_file, training_file):
     
     return original_df, df, X, Y, T
 
+
+def prepare_treatment_df(original_df, df):
+    treatment_df = original_df[['x','y','%CoberturaVeg']].copy()
+    treatment_df.loc[:, '%Construccion'] = original_df['%Construccion'].values
+    treatment_df.loc[:, 'LST'] = df['LST'].values
+    
+    treatment_df = treatment_df.reset_index()
+    return treatment_df
+    
+
+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()}
+    response = requests.post(url, headers=headers, json=data)
+    if response.ok:
+        result = response.json()
+        # print("Model response:", result["effect"])
+    else:
+        print("Request failed:", response.status_code, response.text)
+    
+    treatment_df[name] = result["effect"]
+
+    return treatment_df
+
+def process_data_trees_to_temp(value, original_df, df, X, Y, T):
+
+    name = f'treatment_effect_{value}%'
+    treatment_df = run_treatment_increase(X, T, original_df, df, value, name)
+
+    treatment_df[f'simulated_temp_{value}%'] = treatment_df['LST'] + treatment_df[name]
+
+    gdf = gpd.GeoDataFrame(treatment_df, geometry=gpd.points_from_xy(treatment_df.x, treatment_df.y))
+
+    return gdf

plot_utils.py

@@ -83,8 +83,9 @@ def show_one_plot(gdf, name, vmin, vmax, colorscheme, title, label):
 
     axes = [fig.add_subplot(gs[0]), fig.add_subplot(gs[1])]
     
+    print(gdf[name].min())
     # First plot (simulated)
-    gdf.plot(column=name, cmap=cmap, ax=axes[0], marker='s', markersize=10)
+    gdf.plot(column=name, cmap=cmap, norm=norm, ax=axes[0], marker='s', markersize=10)
     axes[0].set_title(title)
     axes[0].set_axis_off()