def draw_graph(dates, counts):
###########################################################
# Drawing takes place here.
pylab.figure(1)
ax = pylab.subplot(111)
pylab.plot_date(dates,
counts,
color='r',
linestyle='-',
marker='o',
markersize=3)
ax.xaxis.set_major_formatter(pylab.DateFormatter('%Y'))
ax.xaxis.set_major_locator(pylab.YearLocator())
ax.xaxis.set_minor_locator(pylab.MonthLocator())
ax.set_xlim((dates[0] - 92, dates[len(dates) - 1] + 92))
ax.yaxis.set_major_formatter(pylab.FormatStrFormatter('%d'))
pylab.ylabel('Total # of Public DAV Servers')
lastdate = datetime.datetime.fromordinal(dates[len(dates) -
1]).strftime("%B %Y")
pylab.xlabel("Data as of " + lastdate)
pylab.title('Security Space Survey of\nPublic Subversion DAV Servers')
# End drawing
###########################################################
png = open(OUTPUT_FILE, 'w')
pylab.savefig(png)
png.close()
os.rename(OUTPUT_FILE, OUTPUT_FILE + ".tmp.png")
try:
im = Image.open(OUTPUT_FILE + ".tmp.png", 'r')
(width, height) = im.size
print("Original size: %d x %d pixels" % (width, height))
scale = float(OUTPUT_IMAGE_WIDTH) / float(width)
width = OUTPUT_IMAGE_WIDTH
height = int(float(height) * scale)
print("Final size: %d x %d pixels" % (width, height))
im = im.resize((width, height), Image.ANTIALIAS)
im.save(OUTPUT_FILE, im.format)
os.unlink(OUTPUT_FILE + ".tmp.png")
except Exception as e:
sys.stderr.write("Error attempting to resize the graphic: %s\n" %
(str(e)))
os.rename(OUTPUT_FILE + ".tmp.png", OUTPUT_FILE)
raise
pylab.close()
def plot_all_line(self):
data = []
label = []
for each_line in Line_list:
data.append([
Line_list[each_line].CA_Current_G,
Line_list[each_line].CA_Opti_G, Line_list[each_line].CA_Audit_G
])
label.append(Line_list[each_line].name)
pylab.xlabel("Lignes")
pylab.ylabel("Chiffre d'Affaires")
pylab.title("Chiffre d'affaires par ligne")
dim = len(data[0])
w = 0.75
dimw = w / dim
color = ['r', 'g', 'y']
titre = ['CA actuelle', 'CA optimal', 'CA audit']
x = pylab.arange(len(data))
for i in range(len(data[0])):
y = [d[i] for d in data]
pylab.bar(x + i * dimw,
y,
dimw,
bottom=0.001,
color=color[i % 3],
label=titre[i % 3])
pylab.legend()
pylab.gca().set_xticks(x + w / 2)
pylab.gca().set_xticklabels(label, rotation=90)
pylab.subplots_adjust(bottom=0.1, top=0.96, right=0.98, left=0.05)
major_formatter = pylab.FormatStrFormatter('%2.0f')
pylab.gca().yaxis.set_major_formatter(major_formatter)
pylab.get_current_fig_manager().window.showMaximized()
pylab.show()
import numpy as np
import torch
from matplotlib import pylab
from torch.autograd import Variable
data = Variable(
torch.FloatTensor([[0.1, 0.2, 0.4, 0.3, 0.1], [0.05, 0.09, 0.8, 0.1, 0.02],
[0.01, 0.9, 0.04, 0.08, 0.07]]))
print(data)
x = np.arange(5)
x = np.tile(x, (3, 1))
#print(x)
group_labels = ['type 1', 'type 2', 'type 3', 'type 4', 'type 5']
ymajorLocator = pylab.MultipleLocator(0.1) #将y的刻度设置为0.1的倍数
ymajorFormatter = pylab.FormatStrFormatter('%1.1f') #设置y轴标签文本的格式
yminorLocator = pylab.MultipleLocator(0.01) #将此y轴次刻度标签设置为0.1的倍数
ax = plt.subplot(111)
ax.yaxis.set_major_locator(ymajorLocator)
ax.yaxis.set_major_formatter(ymajorFormatter)
ax.yaxis.set_minor_locator(yminorLocator)
for i in range(x.shape[0]):
ax.plot(x[i], data.data.numpy()[i], label='sample ' + str(i))
ax.set_xticks(x[0])
ax.set_xticklabels(group_labels, rotation=0)
ax.legend()
ax.grid()
plt.show()
ax = plt.subplot(111)