homework_2018_1_06_1038414799.ipynb

Kernel: Python 3

%pylab inline
import pandas as pd
from scipy import optimize

Populating the interactive namespace from numpy and matplotlib

df= pd.DataFrame({'X':[0.3,0.5,1.3,3.2,4.5,5.2,6.0,7.5], 'Y':[0.11406,-0.1775,-1.87334,2.30704,24.8025,150.45,160.564,0.847]})

#Interpolacion de puntos
S=np.polyfit(df.X,df.Y,deg=7)
P=np.poly1d(S)      

#Grafica de puntos
x=np.linspace(df.X[0],df.X[7])
plt.plot(df.X,df.Y, "or", label="Puntos")
plt.plot(x,P(x), "-b", label="Polinomio de interpolación")
plt.legend()

<matplotlib.legend.Legend at 0x7f11eb0f6a20>

loc=optimize.fmin_powell(P,4, full_output=True)#Minimo local
glo=optimize.fmin_powell(P,7, full_output=True)#Minimo global

Optimization terminated successfully.
         Current function value: -27.114802
         Iterations: 2
         Function evaluations: 32
Optimization terminated successfully.
         Current function value: -229.774318
         Iterations: 2
         Function evaluations: 28

print(" Minimo global=({},{}), Minimo local=({},{}) ".format(glo[0],glo[1],loc[0],loc[1]))

 Minimo global=(7.119927707838121,-229.77431802644736), Minimo local=(3.8202928576617037,-27.114802418687447)