res = minimize(func, x0=1.0) print(res.x) import numpy as np from scipy.interpolate import interp1d
import matplotlib.pyplot as plt plt.plot(x_new, y_new) plt.show() numerical recipes python pdf
f = interp1d(x, y, kind='cubic') x_new = np.linspace(0, 10, 101) y_new = f(x_new) res = minimize(func, x0=1