Update app.py

app.py

@@ -7,7 +7,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 
 # load the model from disk
-loaded_model = pickle.load(open("XGB_softprob (1).pkl", 'rb'))
+loaded_model = pickle.load(open("XGB_softprob_new_v5.pkl", 'rb'))
 
 # Setup SHAP
 explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
@@ -15,9 +15,9 @@ explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
 # Create the main function for server
 # Create the main function for server
 
-def main_func(CLIMATE_SCENARIO, EAL_SCORE,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT):
+def main_func(CLIMATE_SCENARIO,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT):
     
-    new_row = pd.DataFrame.from_dict({'CLIMATE_SCENARIO': CLIMATE_SCENARIO, 'EAL_SCORE':EAL_SCORE,'SOVI_SCORE':SOVI_SCORE,
+    new_row = pd.DataFrame.from_dict({'CLIMATE_SCENARIO': CLIMATE_SCENARIO,'SOVI_SCORE':SOVI_SCORE,
               'SOCIAL':SOCIAL,'ECONOMY':ECONOMY,'HOUSING_INFRASTRUCTURE':HOUSING_INFRASTRUCTURE,
               'COMMUNITY_CAPITAL':COMMUNITY_CAPITAL,'INSTITUTIONAL':INSTITUTIONAL,'ENVIRONMENT':ENVIRONMENT}, orient = 'index').transpose()
     
@@ -58,7 +58,7 @@ with gr.Blocks(title=title) as demo:
     with gr.Row():        
         with gr.Column():                 
             CLIMATE_SCENARIO = gr.Slider(label="Climate Scenario", minimum=0, maximum=2, value=0, step=1)        
-            EAL_SCORE = gr.Slider(label="EAL Score", minimum=0, maximum=100, value=20, step=5)
+            ##EAL_SCORE = gr.Slider(label="EAL Score", minimum=0, maximum=100, value=20, step=5)
             SOVI_SCORE = gr.Slider(label="SOVI Score", minimum=0, maximum=100, value=20, step=5)
             SOCIAL = gr.Slider(label="Social", minimum=0, maximum=1, value=.5, step=.1)
             ECONOMY = gr.Slider(label="Economy", minimum=0, maximum=1, value=.5, step=.1)
@@ -74,19 +74,19 @@ with gr.Blocks(title=title) as demo:
         
             submit_btn.click(
                 main_func,
-                [CLIMATE_SCENARIO,EAL_SCORE,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT],
+                [CLIMATE_SCENARIO,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT],
                 [label,local_plot], api_name="Climate Risk Model"
             )
     
     gr.Markdown("### Click on any of the examples below to see how it works:")
     gr.Examples([[0, 46.23, 63.85, .564, .4703, .3068, .2161, .3623, .6264]], 
-                [CLIMATE_SCENARIO,EAL_SCORE,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT], 
+                [CLIMATE_SCENARIO,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT], 
                 [label,local_plot], main_func, cache_examples=True, label="Miami-Dade County, Florida")
     gr.Examples([[0, 21.05, 15.37, .7231, .5359, .2884, .3828, .4070, .5015]], 
-                [CLIMATE_SCENARIO,EAL_SCORE,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT], 
+                [CLIMATE_SCENARIO,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT], 
                 [label,local_plot], main_func, cache_examples=True, label="Washington County, Minnesota")
     gr.Examples([[0, 6.929, 4.178, .8181, .5221, .3878, .2463, .389,.3921]], 
-                [CLIMATE_SCENARIO,EAL_SCORE,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT], 
+                [CLIMATE_SCENARIO,SOVI_SCORE,SOCIAL,ECONOMY,HOUSING_INFRASTRUCTURE,COMMUNITY_CAPITAL,INSTITUTIONAL,ENVIRONMENT], 
                 [label,local_plot], main_func, cache_examples=True, label="Falls Church, Virginia")
 
 demo.launch()