188 lines
4.6 KiB
Python
188 lines
4.6 KiB
Python
#!/usr/bin/env python3
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import sys
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sys.path.insert(1, '../lib')
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import argparse
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from datetime import datetime
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from geopy.distance import distance
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import lmdk_bgt
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import lmdk_lib
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import numpy as np
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from matplotlib import pyplot as plt
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import time
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def main(args):
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res_file = '/home/manos/Cloud/Data/Copenhagen/Results.zip'
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# Contacts for all users
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cont_data = lmdk_lib.load_data(args, 'cont')
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# Contacts for landmark's percentages for all users
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lmdk_data = lmdk_lib.load_data(args, 'usrs_expt')
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# The name of the dataset
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d = 'Copenhagen'
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# The user's id
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uid = '623'
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# The landmarks percentages
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lmdks_pct = [0, 20, 40, 60, 80, 100]
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# The privacy budget
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epsilon = 1.0
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# Number of methods
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n = 6
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# Width of bars
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bar_width = 1/(n + 1)
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# The x axis
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x_i = np.arange(len(lmdks_pct))
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x_margin = bar_width*(n/2 + 1)
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print('\n##############################', d, '\n')
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# Get user's contacts sequence
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seq = cont_data[cont_data[:, 1] == float(uid)]
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# Initialize plot
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lmdk_lib.plot_init()
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# The x axis
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plt.xticks(x_i, np.array(lmdks_pct, int))
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plt.xlabel('Landmarks percentage') # Set x axis label.
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plt.xlim(x_i.min() - x_margin, x_i.max() + x_margin)
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# The y axis
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plt.ylabel('Mean absolute error (m)') # Set y axis label.
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plt.yscale('log')
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plt.ylim(1, 100000000)
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# Bar offset
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x_offset = -(bar_width/2)*(n - 1)
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mae_u = np.zeros(len(lmdks_pct))
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mae_s = np.zeros(len(lmdks_pct))
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mae_a = np.zeros(len(lmdks_pct))
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mae_r = np.zeros(len(lmdks_pct))
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mae_d = np.zeros(len(lmdks_pct))
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mae_i = np.zeros(len(lmdks_pct))
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for i, pct in enumerate(lmdks_pct):
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# Find landmarks
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lmdks = lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, pct)
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print(pct, np.shape(lmdks)[0]/np.shape(seq)[0])
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# for _ in range(args.iter):
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# # Skip
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# rls_data_s, _ = lmdk_bgt.skip(seq, lmdks, epsilon)
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# mae_s[i] += lmdk_bgt.mae(seq, rls_data_s)/args.iter
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# # Uniform
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# rls_data_u, _ = lmdk_bgt.uniform_r(seq, lmdks, epsilon)
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# mae_u[i] += lmdk_bgt.mae(seq, rls_data_u)/args.iter
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# # Adaptive
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# rls_data_a, _, _ = lmdk_bgt.adaptive(seq, lmdks, epsilon, .5, .5)
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# mae_a[i] += lmdk_bgt.mae(seq, rls_data_a)/args.iter
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# # Sample
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# rls_data_r, _, _ = lmdk_bgt.sample(seq, lmdks, epsilon)
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# mae_r[i] += lmdk_bgt.mae(seq, rls_data_r)/args.iter
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# # Discount
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# rls_data_d, _, _ = lmdk_bgt.discount(seq, lmdks, epsilon)
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# mae_d[i] += lmdk_bgt.mae(seq, rls_data_d)/args.iter
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# # Incremental
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# rls_data_i, _, _ = lmdk_bgt.incremental(seq, lmdks, epsilon, .5)
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# mae_i[i] += lmdk_bgt.mae(seq, rls_data_i)/args.iter
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# plt.bar(
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# x_i + x_offset,
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# mae_s,
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# bar_width,
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# label='Skip',
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# linewidth=lmdk_lib.line_width
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# )
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# x_offset += bar_width
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# # Plot bars
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# plt.bar(
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# x_i + x_offset,
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# mae_u,
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# bar_width,
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# label='Uniform',
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# linewidth=lmdk_lib.line_width
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# )
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# x_offset += bar_width
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# plt.bar(
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# x_i + x_offset,
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# mae_a,
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# bar_width,
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# label='Adaptive',
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# linewidth=lmdk_lib.line_width
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# )
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# x_offset += bar_width
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# plt.bar(
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# x_i + x_offset,
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# mae_r,
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# bar_width,
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# label='Sample',
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# linewidth=lmdk_lib.line_width
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# )
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# x_offset += bar_width
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# plt.bar(
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# x_i + x_offset,
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# mae_d,
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# bar_width,
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# label='Discount',
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# linewidth=lmdk_lib.line_width
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# )
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# x_offset += bar_width
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# plt.bar(
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# x_i + x_offset,
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# mae_i,
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# bar_width,
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# label='Incremental',
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# linewidth=lmdk_lib.line_width
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# )
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# x_offset += bar_width
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# path = str('rslt/bgt_cmp/' + d)
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# # Plot legend
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# lmdk_lib.plot_legend()
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# # Show plot
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# # plt.show()
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# # Save plot
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# lmdk_lib.save_plot(path + '.pdf')
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print('[OK]', flush=True)
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def parse_args():
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'''
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Parse arguments.
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Optional:
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res - The results archive file.
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iter - The total iterations.
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'''
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# Create argument parser.
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parser = argparse.ArgumentParser()
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# Mandatory arguments.
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# Optional arguments.
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parser.add_argument('-r', '--res', help='The results archive file.', type=str, default='/home/manos/Cloud/Data/Copenhagen/Results.zip')
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parser.add_argument('-i', '--iter', help='The total iterations.', type=int, default=1)
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# Parse arguments.
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args = parser.parse_args()
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return args
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if __name__ == '__main__':
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try:
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start_time = time.time()
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main(parse_args())
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end_time = time.time()
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print('##############################')
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print('Time : %.4fs' % (end_time - start_time))
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print('##############################')
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except KeyboardInterrupt:
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print('Interrupted by user.')
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exit()
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