def plot_svm_decision_function(svm: SVM.NuSVR, x_test: np.array,
y_test: np.array, fig_name: str) -> None:
interval = [-5.5, 6]
xx, yy = np.meshgrid(np.linspace(interval[0], interval[1], 500),
np.linspace(interval[0], interval[1], 500))
# plot the decision function for each datapoint on the grid
Z = svm.decision_function(np.c_[xx.ravel(), yy.ravel()])
Z = Z.reshape(xx.shape)
pyplot.figure(fig_name)
pyplot.title(fig_name)
pyplot.imshow(Z,
interpolation='nearest',
extent=(xx.min(), xx.max(), yy.min(), yy.max()),
aspect='auto',
origin='lower',
cmap=pyplot.cm.PuOr_r)
pyplot.contour(xx, yy, Z, levels=[0], linewidths=2, linestyles='dashed')
pyplot.scatter(x_test[:, 0],
x_test[:, 1],
s=30,
c=y_test,
cmap=pyplot.cm.Paired,
edgecolors='k')
pyplot.xticks(())
pyplot.yticks(())
pyplot.axis([interval[0], interval[1], interval[0], interval[1]])
pyplot.savefig("graficos/" + fig_name, format="png")
pyplot.show()
