from scipy.interpolate import interp1d
import numpy as np

old_time = np.linspace(0, 10, num=11, endpoint=True)
old_vals = np.sin(old_time)
f = interp1d(old_time, old_vals)
f2 = interp1d(old_time, old_vals, kind='cubic')

new_time = np.linspace(0, 10, num=1000, endpoint=True)

new_vals = f(new_time)


print(np.array([new_time, new_vals]).shape)
print(new_vals)
import matplotlib.pyplot as plt
plt.plot(old_time, old_vals, 'o', new_time, new_vals, '-', new_time, f2(new_time), '--')
plt.legend(['data', 'linear', 'cubic'], loc='best')
plt.show()