Update app.py

app.py

@@ -11,56 +11,58 @@ import numpy as np
 
 from seir_model import *
 
-N = 10000 #Total Population
-initial_state = {
-    "S": N-10,
-    "E": 10,
-    "I":0,
-    "R":0
-}
-sys_params = {
-    "infection_rate":[1],
-    "recovery_rate":[1/14], 
-    "exposure_rate":[1/3]
-}
-
-partial_state_update_blocks = [
-    {
-        "policies":{
-            "expsoed_growth":p_exposed,
-            "infected_growth":p_infected,
-            "recovered_growth":p_recovered,
-            
-        },
-        "variables":{
-            "S":s_susceptible,
-            "E":s_exposed,
-            "I":s_infected,
-            "R":s_recovered,
-        }
-     
+def create_and_run_exp(population):
+    #Total Population : population
+    initial_state = {
+        "S": population-10,
+        "E": 10,
+        "I":0,
+        "R":0
     }
+    sys_params = {
+        "infection_rate":[1],
+        "recovery_rate":[1/14], 
+        "exposure_rate":[1/3]
+    }
+        
+    partial_state_update_blocks = [
+        {
+            "policies":{
+                "expsoed_growth":p_exposed,
+                "infected_growth":p_infected,
+                "recovered_growth":p_recovered,
+                
+            },
+            "variables":{
+                "S":s_susceptible,
+                "E":s_exposed,
+                "I":s_infected,
+                "R":s_recovered,
+            }
+         
+        }
+    
+    ]
+    
+    del configs[:]
+    
+    timesteps = 100
+    sim_config = config_sim({
+      "N":1,
+      "T":range(timesteps),
+      "M":sys_params  
+    })
+    
+    experiment = Experiment()
+    experiment.append_configs(
+        sim_configs=sim_config,
+        initial_state=initial_state,
+        partial_state_update_blocks=partial_state_update_blocks
+    )
 
-]
-
-del configs[:]
-
-timesteps = 100
-sim_config = config_sim({
-  "N":1,
-  "T":range(timesteps),
-  "M":sys_params  
-})
-
-experiment = Experiment()
-experiment.append_configs(
-    sim_configs=sim_config,
-    initial_state=initial_state,
-    partial_state_update_blocks=partial_state_update_blocks
-)
-
-exec_context = ExecutionContext()
-simulation = Executor(exec_context=exec_context, configs=experiment.configs)
+    exec_context = ExecutionContext()
+    simulation = Executor(exec_context=exec_context, configs=experiment.configs)
+    return simulation
 
 css = """
         .gradio-container {
@@ -131,7 +133,8 @@ css = """
         }
 """
   
-def plot_seir(name):
+def plot_seir(population):
+    simulation = create_and_run_exp(population)
     raw_result, tensor_fields, sessions = simulation.execute()
     result = pd.DataFrame(raw_result)
     pd.options.plotting.backend = "plotly"
@@ -148,9 +151,9 @@ with gr.Blocks(css = css) as demo:
     gr.Markdown("""
                 ## Epidemic Simulation
             """)
-    title_input = gr.Textbox(label = 'Enter title')
-    simulate_btn = gr.Button('Simulation')
+    population_input = gr.Slider(1000, 100000, value=10000)
+    simulate_btn = gr.Button('Run Simulation')
     graph = gr.Plot()
-    simulate_btn.click(plot_seir, inputs = title_input, outputs = graph)
+    simulate_btn.click(plot_seir, inputs = population_input, outputs = graph)
 
 demo.launch()