153 lines
3.8 KiB
Python
153 lines
3.8 KiB
Python
#!/usr/bin/env python3
|
|
|
|
import sys
|
|
sys.path.insert(1, '../lib')
|
|
import argparse
|
|
import ast
|
|
from datetime import datetime
|
|
from geopy.distance import distance
|
|
import lmdk_bgt
|
|
import lmdk_lib
|
|
import lmdk_sel
|
|
import exp_mech
|
|
import math
|
|
import numpy as np
|
|
from matplotlib import pyplot as plt
|
|
import time
|
|
|
|
|
|
def main(args):
|
|
# Contacts for all users
|
|
cont_data = lmdk_lib.load_data(args, 'cont')
|
|
# Contacts for landmark's percentages for all users
|
|
lmdk_data = lmdk_lib.load_data(args, 'usrs_data')
|
|
# The name of the dataset
|
|
d = 'Copenhagen'
|
|
# The user's id
|
|
uid = '449'
|
|
# The landmarks percentages
|
|
lmdks_pct = [0, 20, 40, 60, 80, 100]
|
|
# The privacy budget
|
|
epsilon = 1.0
|
|
eps_pct = [.201, .51, .725, .95]
|
|
|
|
markers = [
|
|
'^',
|
|
'v',
|
|
'D',
|
|
's'
|
|
]
|
|
|
|
print('\n##############################', d, '\n')
|
|
# Get user's contacts sequence
|
|
seq = cont_data[cont_data[:, 1] == float(uid)][:1000]
|
|
|
|
# Initialize plot
|
|
lmdk_lib.plot_init()
|
|
# The x axis
|
|
x_i = np.arange(len(lmdks_pct))
|
|
plt.xticks(x_i, np.array(lmdks_pct, int))
|
|
plt.xlabel('Landmarks (%)') # Set x axis label.
|
|
plt.xlim(x_i.min(), x_i.max())
|
|
# The y axis
|
|
plt.ylabel('Mean absolute error (%)') # Set y axis label.
|
|
plt.ylim(0, 100)
|
|
|
|
mae_evt = 0
|
|
mae_usr = 0
|
|
|
|
for i_e, e in enumerate(eps_pct):
|
|
mae = np.zeros(len(lmdks_pct))
|
|
|
|
for i, pct in enumerate(lmdks_pct):
|
|
# Find landmarks
|
|
lmdks = lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, pct)
|
|
|
|
for _ in range(args.iter):
|
|
|
|
lmdks_sel = lmdk_sel.find_lmdks_eps(seq, lmdks, epsilon*e/100)
|
|
|
|
# Uniform
|
|
rls_data, _ = lmdk_bgt.uniform_cont(seq, lmdks_sel, epsilon*(1 - e/100))
|
|
mae[i] += (lmdk_bgt.mae_cont(rls_data)/args.iter)*100
|
|
|
|
# Calculate once
|
|
if e == eps_pct[0] and pct == lmdks_pct[0]:
|
|
# Event
|
|
rls_data_evt, _ = lmdk_bgt.uniform_cont(seq, lmdks, epsilon)
|
|
mae_evt += (lmdk_bgt.mae_cont(rls_data_evt)/args.iter)*100
|
|
elif e == eps_pct[-1] and pct == lmdks_pct[-1]:
|
|
# User
|
|
rls_data_usr, _ = lmdk_bgt.uniform_cont(seq, lmdks, epsilon)
|
|
mae_usr += (lmdk_bgt.mae_cont(rls_data_usr)/args.iter)*100
|
|
|
|
# Plot line
|
|
plt.plot(
|
|
x_i,
|
|
mae,
|
|
label='{0:.2f}'.format(e) + 'ε',
|
|
marker=markers[i_e],
|
|
markersize=lmdk_lib.marker_size,
|
|
markeredgewidth=0,
|
|
linewidth=lmdk_lib.line_width
|
|
)
|
|
|
|
plt.axhline(
|
|
y = mae_evt,
|
|
color = '#212121',
|
|
linewidth=lmdk_lib.line_width
|
|
)
|
|
plt.text(x_i[-1] + x_i[-1]*.01, mae_evt - mae_evt*.05, 'event')
|
|
|
|
plt.axhline(
|
|
y = mae_usr,
|
|
color = '#616161',
|
|
linewidth=lmdk_lib.line_width
|
|
)
|
|
plt.text(x_i[-1] + x_i[-1]*.01, mae_usr - mae_usr*.05, 'user')
|
|
|
|
path = str('../../rslt/lmdk_sel_eps/' + d)
|
|
# Plot legend
|
|
lmdk_lib.plot_legend()
|
|
# # Show plot
|
|
# plt.show()
|
|
# Save plot
|
|
lmdk_lib.save_plot(path + '-sel-eps.pdf')
|
|
print('[OK]', flush=True)
|
|
|
|
|
|
def parse_args():
|
|
'''
|
|
Parse arguments.
|
|
|
|
Optional:
|
|
res - The results archive file.
|
|
iter - The total iterations.
|
|
'''
|
|
# Create argument parser.
|
|
parser = argparse.ArgumentParser()
|
|
|
|
# Mandatory arguments.
|
|
|
|
# Optional arguments.
|
|
parser.add_argument('-r', '--res', help='The results archive file.', type=str, default='/home/manos/Cloud/Data/Copenhagen/Results.zip')
|
|
parser.add_argument('-i', '--iter', help='The total iterations.', type=int, default=1)
|
|
|
|
# Parse arguments.
|
|
args = parser.parse_args()
|
|
|
|
return args
|
|
|
|
|
|
if __name__ == '__main__':
|
|
try:
|
|
start_time = time.time()
|
|
main(parse_args())
|
|
end_time = time.time()
|
|
print('##############################')
|
|
print('Time elapsed: %s' % (time.strftime('%H:%M:%S', time.gmtime(end_time - start_time))))
|
|
print('##############################')
|
|
except KeyboardInterrupt:
|
|
print('Interrupted by user.')
|
|
exit()
|