#######################################
# pyGPGO examples
# gif_gen: generates a gif (the one in paper.md) showing how the BO framework
# works on the Franke function, step by step.
#######################################
import numpy as np
from pyGPGO.covfunc import matern32
from pyGPGO.acquisition import Acquisition
from pyGPGO.surrogates.GaussianProcess import GaussianProcess
from pyGPGO.GPGO import GPGO
import matplotlib.pyplot as plt
from matplotlib import cm
def f(x, y):
# Franke's function (https://www.mathworks.com/help/curvefit/franke.html)
one = 0.75 * np.exp(-(9 * x - 2)**2/4 - (9 * y - 2)**2/4)
two = 0.75 * np.exp(-(9 * x + 1)**2/49 - (9 * y + 1)/10)
three = 0.5 * np.exp(-(9 * x - 7)**2/4 - (9*y - 3)**2/4)
four = 0.25 * np.exp(-(9 * x - 4)**2 - (9*y - 7)**2)
return one + two + three - four
def plotFranke():
x = np.linspace(0, 1, num=1000)
y = np.linspace(0, 1, num=1000)
X, Y = np.meshgrid(x, y)
Z = f(X, Y)
ax = fig.add_subplot(1, 2, 1, projection='3d')
ax.set_title('Original function')
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
linewidth=0)
fig.colorbar(surf, shrink=0.5, aspect=5)
def plotPred(gpgo, num=100):
X = np.linspace(0, 1, num=num)
Y = np.linspace(0, 1, num=num)
U = np.zeros((num**2, 2))
i = 0
for x in X:
for y in Y:
U[i, :] = [x, y]
i += 1
z = gpgo.GP.predict(U)[0]
Z = z.reshape((num, num))
X, Y = np.meshgrid(X, Y)
ax = fig.add_subplot(1, 2, 2, projection='3d')
ax.set_title('Gaussian Process surrogate')
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
linewidth=0)
fig.colorbar(surf, shrink=0.5, aspect=5)
best = gpgo.best
ax.scatter([best[0]], [best[1]], s=40, marker='x', c='r', label='Sampled point')
plt.legend(loc='lower right')
#plt.show()
return Z
if __name__ == '__main__':
n_iter = 10
cov = matern32()
gp = GaussianProcess(cov)
acq = Acquisition(mode='ExpectedImprovement')
param = {'x': ('cont', [0, 1]),
'y': ('cont', [0, 1])}
np.random.seed(85)
gpgo = GPGO(gp, acq, f, param)
gpgo.run(max_iter=1)
for i in range(n_iter):
fig = plt.figure(figsize=plt.figaspect(0.5))
fig.suptitle("Franke's function (Iteration {})".format(i+1))
gpgo.run(max_iter=1, resume=True)
plotFranke()
plotPred(gpgo)
plt.show()
#plt.savefig('/home/jose/gif/{}.png'.format(i), dpi=300)
plt.close()
