population = float(46750238)
country_df = pd.DataFrame()
country_df['ConfirmedCases'] = train.loc[train['Country_Region']=='Spain'].ConfirmedCases.diff().fillna(0)
country_df = country_df[10:]
country_df['day_count'] = list(range(1,len(country_df)+1))
ydata = [i for i in country_df.ConfirmedCases]
xdata = country_df.day_count
ydata = np.array(ydata, dtype=float)
xdata = np.array(xdata, dtype=float)
N = population
inf0 = ydata[0]
sus0 = N - inf0
rec0 = 0.0
def sir_model(y, x, beta, gamma):
sus = -beta * y[0] * y[1] / N
rec = gamma * y[1]
inf = -(sus + rec)
return sus, inf, rec
def fit_odeint(x, beta, gamma):
return integrate.odeint(sir_model, (sus0, inf0, rec0), x, args=(beta, gamma))[:,1]
popt, pcov = optimize.curve_fit(fit_odeint, xdata, ydata)
fitted = fit_odeint(xdata, *popt)
plt.plot(xdata, ydata, 'o')
plt.plot(xdata, fitted)
plt.title("Fit of SIR model for Spain infected cases")
plt.ylabel("Population infected")
plt.xlabel("Days")
plt.show()
print("Optimal parameters: beta =", popt[0], " and gamma = ", popt[1])
Error:
RuntimeError Traceback (most recent call last)
<ipython-input-60-01ea0e369b77> in <module>
24 return integrate.odeint(sir_model, (sus0, inf0, rec0), x, args=(beta, gamma))[:,1]
25
---> 26 popt, pcov = optimize.curve_fit(fit_odeint, xdata, ydata)
27 fitted = fit_odeint(xdata, *popt)
28
C:\ProgramData\Anaconda3\lib\site-packages\scipy\optimize\minpack.py in curve_fit(f, xdata, ydata, p0, sigma, absolute_sigma, check_finite, bounds, method, jac, **kwargs)
746 cost = np.sum(infodict['fvec'] ** 2)
747 if ier not in [1, 2, 3, 4]:
--> 748 raise RuntimeError("Optimal parameters not found: " + errmsg)
749 else:
750 # Rename maxfev (leastsq) to max_nfev (least_squares), if specified.
RuntimeError: Optimal parameters not found: Number of calls to function has reached maxfev = 600.