import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import os
from matplotlib.ticker import NullFormatter
#reading the data
os.chdir('E:/backup folder/paper')
test_data = pd.read_csv('keygenerationtime.csv')
print(test_data['Users'])
Users= test_data['Users']
Time=test_data['Time']
N = len(Users)
x2 = np.arange(N)
print(N)
plt.plot(x2, Time,linewidth=2,color='black')
plt.xticks(x2, Users)
plt.ylabel('Time(secs)',fontsize=14)
plt.xlabel('Number of Users',fontsize=14)
plt.subplots_adjust(bottom=0.2)
fig = plt.gcf()
fig.set_size_inches(5, 5)
fig.savefig('Fig3.png', dpi=200)
plt.show()
#----------------------------------------------
test_data = pd.read_csv('encryptiontime.csv')
print(test_data['File'])
File= test_data['File']
Time=test_data['Time']
N = len(File)
x2 = np.arange(N)
#print(N)
plt.bar(x2, Time,color='black',width=0.5)
plt.xticks(x2, File)
plt.ylabel('Time(secs)',fontsize=14)
plt.xlabel('File Size (KB)',fontsize=14)
plt.subplots_adjust(bottom=0.2)
fig = plt.gcf()
fig.set_size_inches(5, 5)
fig.savefig('Fig4.png', dpi=200)
plt.show()
#--------------------------------------------
test_data = pd.read_csv('decryptiontime.csv')
print(test_data['File'])
File= test_data['File']
Time=test_data['Time']
N = len(File)
x2 = np.arange(N)
#print(N)
plt.bar(x2, Time,color='black',width=0.5)
plt.xticks(x2, File)
plt.ylabel('Time(secs)',fontsize=14)
plt.xlabel('File Size (KB)',fontsize=14)
plt.subplots_adjust(bottom=0.2)
fig = plt.gcf()
fig.set_size_inches(5, 5)
fig.savefig('Fig5.png', dpi=200)
plt.show()
#------------------------------------------
test_data = pd.read_csv('turnaround.csv')
print(test_data)
File= test_data['File']
Ses_up=test_data['a']
up1=test_data['b']
up2=test_data['c']
Ses_down=test_data['d']
down1=test_data['e']
down2=test_data['f']
patterns = [ "/" , "\\" , "|" , "-" , "+" , "x", "o", "O", ".", "*" ]
width = 0.15
pos = list(range(len(Ses_up)))
fig, ax = plt.subplots(figsize=(5,5))
bar1=plt.bar(pos, Ses_up, width,
alpha=1,
color='black',
hatch="/", # this one defines the fill pattern
label=File[0])
plt.bar([p + width for p in pos], up1, width,
alpha=0.5,
color='w',
hatch="\\",
label=File[1])
plt.bar([p + width*2 for p in pos], up2, width,
alpha=0.5,
color='k',
hatch='-',
label=File[2])
plt.bar([p + width*3 for p in pos], Ses_down, width,
alpha=0.7,
color='black',hatch="//",
label=File[3])
plt.bar([p + width*4 for p in pos], down1, width,
alpha=0.5,
color='w',
hatch="...",
label=File[4])
plt.bar([p + width*5 for p in pos], down2, width,
alpha=0.5,
color='white',
hatch="///",
label=File[5])
ax.set_ylabel('Time (secs)',fontsize=14)
ax.set_xlabel('File Size (KB) ',fontsize=14)
#ax.set_title('Grouped bar plot')
ax.set_xticks([p + 1.5 * width for p in pos])
ax.set_xticklabels(File)
plt.legend(['SeSPHR T-up', '[14] T-up', '[27] T-up', 'SeSPHR T-down', '[14] T-down', '[27] T-down'], loc='upper left')
fig.savefig('Fig6.png', dpi=200)
plt.show()
import pandas as pd
import matplotlib.pyplot as plt
import os
from matplotlib.ticker import NullFormatter
#reading the data
os.chdir('E:/backup folder/paper')
test_data = pd.read_csv('keygenerationtime.csv')
print(test_data['Users'])
Users= test_data['Users']
Time=test_data['Time']
N = len(Users)
x2 = np.arange(N)
print(N)
plt.plot(x2, Time,linewidth=2,color='black')
plt.xticks(x2, Users)
plt.ylabel('Time(secs)',fontsize=14)
plt.xlabel('Number of Users',fontsize=14)
plt.subplots_adjust(bottom=0.2)
fig = plt.gcf()
fig.set_size_inches(5, 5)
fig.savefig('Fig3.png', dpi=200)
plt.show()
#----------------------------------------------
test_data = pd.read_csv('encryptiontime.csv')
print(test_data['File'])
File= test_data['File']
Time=test_data['Time']
N = len(File)
x2 = np.arange(N)
#print(N)
plt.bar(x2, Time,color='black',width=0.5)
plt.xticks(x2, File)
plt.ylabel('Time(secs)',fontsize=14)
plt.xlabel('File Size (KB)',fontsize=14)
plt.subplots_adjust(bottom=0.2)
fig = plt.gcf()
fig.set_size_inches(5, 5)
fig.savefig('Fig4.png', dpi=200)
plt.show()
#--------------------------------------------
test_data = pd.read_csv('decryptiontime.csv')
print(test_data['File'])
File= test_data['File']
Time=test_data['Time']
N = len(File)
x2 = np.arange(N)
#print(N)
plt.bar(x2, Time,color='black',width=0.5)
plt.xticks(x2, File)
plt.ylabel('Time(secs)',fontsize=14)
plt.xlabel('File Size (KB)',fontsize=14)
plt.subplots_adjust(bottom=0.2)
fig = plt.gcf()
fig.set_size_inches(5, 5)
fig.savefig('Fig5.png', dpi=200)
plt.show()
#------------------------------------------
test_data = pd.read_csv('turnaround.csv')
print(test_data)
File= test_data['File']
Ses_up=test_data['a']
up1=test_data['b']
up2=test_data['c']
Ses_down=test_data['d']
down1=test_data['e']
down2=test_data['f']
patterns = [ "/" , "\\" , "|" , "-" , "+" , "x", "o", "O", ".", "*" ]
width = 0.15
pos = list(range(len(Ses_up)))
fig, ax = plt.subplots(figsize=(5,5))
bar1=plt.bar(pos, Ses_up, width,
alpha=1,
color='black',
hatch="/", # this one defines the fill pattern
label=File[0])
plt.bar([p + width for p in pos], up1, width,
alpha=0.5,
color='w',
hatch="\\",
label=File[1])
plt.bar([p + width*2 for p in pos], up2, width,
alpha=0.5,
color='k',
hatch='-',
label=File[2])
plt.bar([p + width*3 for p in pos], Ses_down, width,
alpha=0.7,
color='black',hatch="//",
label=File[3])
plt.bar([p + width*4 for p in pos], down1, width,
alpha=0.5,
color='w',
hatch="...",
label=File[4])
plt.bar([p + width*5 for p in pos], down2, width,
alpha=0.5,
color='white',
hatch="///",
label=File[5])
ax.set_ylabel('Time (secs)',fontsize=14)
ax.set_xlabel('File Size (KB) ',fontsize=14)
#ax.set_title('Grouped bar plot')
ax.set_xticks([p + 1.5 * width for p in pos])
ax.set_xticklabels(File)
plt.legend(['SeSPHR T-up', '[14] T-up', '[27] T-up', 'SeSPHR T-down', '[14] T-down', '[27] T-down'], loc='upper left')
fig.savefig('Fig6.png', dpi=200)
plt.show()
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