optimizer.py
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	#!/usr/bin/env python3

	import matplotlib.pyplot as plt
	import numpy as np
	import scipy.optimize
	from mpl_toolkits.mplot3d import Axes3D


	def plot(func, iterations, title):
	'Plotting function for plane and iterations'

	x = np.linspace(-3, 3, 100)
	y = np.linspace(-3, 3, 100)
	x, y = np.meshgrid(x, y)

	X = np.stack([x.flatten(), y.flatten()], axis=1)
	z = func(X).reshape((100, 100))

	xy = np.array(iterations)
	zs = func(xy)

	fig = plt.figure()
	ax = Axes3D(fig)
	ax.plot_surface(x, y, z, linewidth=0, antialiased=True,
	cmap=plt.cm.viridis, alpha=0.2)
	ax.contour(x, y, z, 10, colors="k", linestyles="solid")
	ax.plot(xy[:, 0], xy[:, 1], zs, 'ro--')
	ax.grid(False)
	ax.set_title(title)

	plt.xlabel('$x$')
	plt.ylabel('$y$')
	plt.show()


	def solve(fun, x0, tol='1e-8', callback=None, **kwargs):
	'Minimize function with BFGS'

	res = scipy.optimize.minimize(
	fun, x0, method='BFGS',
	callback=callback,
	tol=tol)

	return res.x