def _plot_sec_eval(sec_eval):
figure = CFigure(height=5, width=5)
figure.sp.plot_sec_eval(sec_eval.sec_eval_data,
label='SVM', marker='o',
show_average=True, mean=True)
figure.sp.title(sec_eval.attack.__class__.__name__)
figure.subplots_adjust()
figure.show()
def _plot_sec_eval(self):
# figure creation
figure = CFigure(height=5, width=5)
sec_eval_data = [
sec_eval.sec_eval_data for sec_eval in self.sec_eval]
# plot security evaluation
figure.sp.plot_sec_eval(sec_eval_data, label='SVM', marker='o',
show_average=True, mean=True)
figure.subplots_adjust()
figure.show()
from secml.array import CArray
from secml.figure import CFigure
n = 5
fig = CFigure()
x = CArray.arange(100)
y = 3. * CArray.sin(x * 2. * 3.14 / 100.)
for i in range(n):
temp = 510 + i
sp = fig.subplot(n, 1, i)
fig.sp.plot(x, y)
# for add space from the figure's border you must increased default value parameters
fig.subplots_adjust(bottom=0.4, top=0.85, hspace=0.001)
fig.sp.xticklabels(())
fig.sp.yticklabels(())
fig.show()
from secml.array import CArray
from secml.figure import CFigure
fig = CFigure(fontsize=14)
# example data
mu = 100 # mean of distribution
sigma = 15 # standard deviation of distribution
x = mu + sigma * CArray.randn((10000, ))
num_bins = 50
# the histogram of the data
n, bins, patches = fig.sp.hist(x,
num_bins,
density=1,
facecolor='green',
alpha=0.5)
# add a 'best fit' line
y = bins.normpdf(mu, sigma)
fig.sp.plot(bins, y, 'r--')
fig.sp.xlabel('Smarts')
fig.sp.ylabel('Probability')
fig.title(r'Histogram of IQ: $\mu=100$, $\sigma=15$')
# Tweak spacing to prevent clipping of ylabel
fig.subplots_adjust(left=0.15)
fig.sp.grid()
fig.show()