From 7d4865d5d14cc58955f9e5e0a9ae7c9601c1870d Mon Sep 17 00:00:00 2001 From: Manos Katsomallos Date: Wed, 29 Sep 2021 00:13:26 +0200 Subject: [PATCH] code: Experimenting with copenhagen data --- code/expt/bgt_cmp_copenhagen.py | 187 ++++++++++++++++++++++++++++++++ 1 file changed, 187 insertions(+) create mode 100644 code/expt/bgt_cmp_copenhagen.py diff --git a/code/expt/bgt_cmp_copenhagen.py b/code/expt/bgt_cmp_copenhagen.py new file mode 100644 index 0000000..cd7b256 --- /dev/null +++ b/code/expt/bgt_cmp_copenhagen.py @@ -0,0 +1,187 @@ +#!/usr/bin/env python3 + +import sys +sys.path.insert(1, '../lib') +import argparse +from datetime import datetime +from geopy.distance import distance +import lmdk_bgt +import lmdk_lib +import numpy as np +from matplotlib import pyplot as plt +import time + + +def main(args): + res_file = '/home/manos/Cloud/Data/Copenhagen/Results.zip' + # 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_expt') + # The name of the dataset + d = 'Copenhagen' + # The user's id + uid = '623' + # The landmarks percentages + lmdks_pct = [0, 20, 40, 60, 80, 100] + # The privacy budget + epsilon = 1.0 + + # Number of methods + n = 6 + # Width of bars + bar_width = 1/(n + 1) + # The x axis + x_i = np.arange(len(lmdks_pct)) + x_margin = bar_width*(n/2 + 1) + + print('\n##############################', d, '\n') + # Get user's contacts sequence + seq = cont_data[cont_data[:, 1] == float(uid)] + + # Initialize plot + lmdk_lib.plot_init() + # The x axis + plt.xticks(x_i, np.array(lmdks_pct, int)) + plt.xlabel('Landmarks percentage') # Set x axis label. + plt.xlim(x_i.min() - x_margin, x_i.max() + x_margin) + # The y axis + plt.ylabel('Mean absolute error (m)') # Set y axis label. + plt.yscale('log') + plt.ylim(1, 100000000) + # Bar offset + x_offset = -(bar_width/2)*(n - 1) + + mae_u = np.zeros(len(lmdks_pct)) + mae_s = np.zeros(len(lmdks_pct)) + mae_a = np.zeros(len(lmdks_pct)) + mae_r = np.zeros(len(lmdks_pct)) + mae_d = np.zeros(len(lmdks_pct)) + mae_i = 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) + + print(pct, np.shape(lmdks)[0]/np.shape(seq)[0]) + + # for _ in range(args.iter): + # # Skip + # rls_data_s, _ = lmdk_bgt.skip(seq, lmdks, epsilon) + # mae_s[i] += lmdk_bgt.mae(seq, rls_data_s)/args.iter + + # # Uniform + # rls_data_u, _ = lmdk_bgt.uniform_r(seq, lmdks, epsilon) + # mae_u[i] += lmdk_bgt.mae(seq, rls_data_u)/args.iter + + # # Adaptive + # rls_data_a, _, _ = lmdk_bgt.adaptive(seq, lmdks, epsilon, .5, .5) + # mae_a[i] += lmdk_bgt.mae(seq, rls_data_a)/args.iter + + # # Sample + # rls_data_r, _, _ = lmdk_bgt.sample(seq, lmdks, epsilon) + # mae_r[i] += lmdk_bgt.mae(seq, rls_data_r)/args.iter + + # # Discount + # rls_data_d, _, _ = lmdk_bgt.discount(seq, lmdks, epsilon) + # mae_d[i] += lmdk_bgt.mae(seq, rls_data_d)/args.iter + + # # Incremental + # rls_data_i, _, _ = lmdk_bgt.incremental(seq, lmdks, epsilon, .5) + # mae_i[i] += lmdk_bgt.mae(seq, rls_data_i)/args.iter + + # plt.bar( + # x_i + x_offset, + # mae_s, + # bar_width, + # label='Skip', + # linewidth=lmdk_lib.line_width + # ) + # x_offset += bar_width + # # Plot bars + # plt.bar( + # x_i + x_offset, + # mae_u, + # bar_width, + # label='Uniform', + # linewidth=lmdk_lib.line_width + # ) + # x_offset += bar_width + # plt.bar( + # x_i + x_offset, + # mae_a, + # bar_width, + # label='Adaptive', + # linewidth=lmdk_lib.line_width + # ) + # x_offset += bar_width + # plt.bar( + # x_i + x_offset, + # mae_r, + # bar_width, + # label='Sample', + # linewidth=lmdk_lib.line_width + # ) + # x_offset += bar_width + # plt.bar( + # x_i + x_offset, + # mae_d, + # bar_width, + # label='Discount', + # linewidth=lmdk_lib.line_width + # ) + # x_offset += bar_width + # plt.bar( + # x_i + x_offset, + # mae_i, + # bar_width, + # label='Incremental', + # linewidth=lmdk_lib.line_width + # ) + # x_offset += bar_width + + # path = str('rslt/bgt_cmp/' + d) + # # Plot legend + # lmdk_lib.plot_legend() + # # Show plot + # # plt.show() + # # Save plot + # lmdk_lib.save_plot(path + '.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 : %.4fs' % (end_time - start_time)) + print('##############################') + except KeyboardInterrupt: + print('Interrupted by user.') + exit()