1.5.12.13. Minima and roots of a function

Demos finding minima and roots of a function.

Define the function

import numpy as np
x = np.arange(-10, 10, 0.1)
def f(x):
return x**2 + 10 * np.sin(x)

Find minima

import scipy as sp
# Global optimization
grid = (-10, 10, 0.1)
xmin_global = sp.optimize.brute(f, (grid,))
print(f"Global minima found {xmin_global}")
# Constrain optimization
xmin_local = sp.optimize.fminbound(f, 0, 10)
print(f"Local minimum found {xmin_local}")
Global minima found [-1.30641113]
Local minimum found 3.8374671194983834

Root finding

root = sp.optimize.root(f, 1)  # our initial guess is 1
print(f"First root found {root.x}")
root2 = sp.optimize.root(f, -2.5)
print(f"Second root found {root2.x}")
First root found [0.]
Second root found [-2.47948183]

Plot function, minima, and roots

import matplotlib.pyplot as plt
fig = plt.figure(figsize=(6, 4))
ax = fig.add_subplot(111)
# Plot the function
ax.plot(x, f(x), "b-", label="f(x)")
# Plot the minima
xmins = np.array([xmin_global[0], xmin_local])
ax.plot(xmins, f(xmins), "go", label="Minima")
# Plot the roots
roots = np.array([root.x, root2.x])
ax.plot(roots, f(roots), "kv", label="Roots")
# Decorate the figure
ax.legend(loc="best")
ax.set_xlabel("x")
ax.set_ylabel("f(x)")
ax.axhline(0, color="gray")
plt.show()
plot optimize example2

Total running time of the script: (0 minutes 0.060 seconds)

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