Delete App.py

App.py

@@ -1,114 +0,0 @@
-import pandas as pd
-import streamlit as st
-import numpy as np
-from scipy.integrate import odeint
-import matplotlib.pyplot as plt
-
-#dowload file
-!wget https://raw.githubusercontent.com/owid/monkeypox/main/owid-monkeypox-data.csv
-
-#read files
-data = pd.read_csv('owid-monkeypox-data.csv')
-data = data[['location','date','new_cases','total_cases','new_deaths','total_deaths']]
-
-#preprocessiong data
-all_location = {}
-for i in data['location'].unique():
-  all_location[i] = data[data['location'] == i].reset_index(drop=True)
-
-# SIR model differential equations.
-def deriv(x, t, beta, gamma):
-    s, i, r = x
-    dsdt = -beta * s * i
-    didt = beta * s * i - gamma * i
-    drdt =  gamma * i
-    return [dsdt, didt, drdt]
-
-#plot model
-def plotdata(t, s, i, e=None):
-    # plot the data
-    fig = plt.figure(figsize=(12,6))
-    ax = [fig.add_subplot(221, axisbelow=True), 
-          fig.add_subplot(223),
-          fig.add_subplot(122)]
-
-    ax[0].plot(t, s, lw=3, label='Fraction Susceptible')
-    ax[0].plot(t, i, lw=3, label='Fraction Infective')
-    ax[0].plot(t, r, lw=3, label='Recovered')
-    ax[0].set_title('Susceptible and Recovered Populations')
-    ax[0].set_xlabel('Time /days')
-    ax[0].set_ylabel('Fraction')
-
-    ax[1].plot(t, i, lw=3, label='Infective')
-    ax[1].set_title('Infectious Population')
-    if e is not None: ax[1].plot(t, e, lw=3, label='Exposed')
-    ax[1].set_ylim(0, 1.0)
-    ax[1].set_xlabel('Time /days')
-    ax[1].set_ylabel('Fraction')
-
-    ax[2].plot(s, i, lw=3, label='s, i trajectory')
-    ax[2].plot([1/R0, 1/R0], [0, 1], '--', lw=3, label='di/dt = 0')
-    ax[2].plot(s[0], i[0], '.', ms=20, label='Initial Condition')
-    ax[2].plot(s[-1], i[-1], '.', ms=20, label='Final Condition')
-    ax[2].set_title('State Trajectory')
-    ax[2].set_aspect('equal')
-    ax[2].set_ylim(0, 1.05)
-    ax[2].set_xlim(0, 1.05)
-    ax[2].set_xlabel('Susceptible')
-    ax[2].set_ylabel('Infectious')
-
-    for a in ax: 
-        a.grid(True)
-        a.legend()
-
-    plt.tight_layout()
-
-#final model
-def SIR(country,t_infective):
-  # parameter values
-  R0 = (all_location[country]['new_cases'].sum()/len(all_location[country]['date'].unique()))/t_infective
-  t_infective = t_infective
-
-  # initial number of infected and recovered individuals
-  i_initial = 1/20000
-  r_initial = 0.00
-  s_initial = 1 - i_initial - r_initial
-
-  gamma = 1/t_infective
-  beta = R0*gamma
-
-  t = np.linspace(0, 100, 1000)
-  x_initial = s_initial, i_initial, r_initial
-  soln = odeint(deriv, x_initial, t, args=(beta, gamma))
-  s, i, r = soln.T
-  e = None
-
-  plotdata(t, s, i)
-
-  return R0,t_infective,gamma,beta
-
-def main():
-    st.title("SIR Model for Monkeypox")
-
-    with st.form("questionaire"):
-        country = st.selectbox("Country")# user's input
-        recovery = st.slider("How long Monkeypox recover?", 21, 31, 21)# user's input
-
-        # clicked==True only when the button is clicked
-        clicked = st.form_submit_button("Show Graph")
-        if clicked:
-
-            #show total cases graph
-            all_location[country]['total_cases'].plot()
-
-            # Show SIR
-            SIR_param = SIR(country,recovery)
-
-            st.success("SIR model parameters for "+str(country)+" is")
-            st.success("R0 = "+str(SIR_param[0]))
-            st.success("Beta = "+str(SIR_param[3]))
-            st.success("Gamma = "+str(SIR_param[2]))
-
-# Run main()
-if __name__ == "__main__":
-    main()