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								code/expt/bgt_cmp_hue.py
									
									
									
									
									
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										173
									
								
								code/expt/bgt_cmp_hue.py
									
									
									
									
									
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#!/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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import ast
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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 math
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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/HUE/Results.zip'
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  # User's consumption
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  seq = lmdk_lib.load_data(args, 'cons')
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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 = 'HUE'
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  # The landmarks percentages
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  lmdks_pct = [0, 20, 40, 60, 80, 100]
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  # Landmarks' thresholds
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  lmdks_th = [10.0, .3, .23, .15, .13, 0]
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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 = 3
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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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  # 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')  # Set y axis label.
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  # plt.yscale('log')
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  plt.ylim(0, 1.4)
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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_evt = np.zeros(len(lmdks_pct))
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  mae_usr = 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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    for _ in range(args.iter):
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      # Skip
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      rls_data_s, bgts_s = lmdk_bgt.skip_cont(seq, lmdks, epsilon)
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      # lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_s)
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      mae_s[i] += lmdk_bgt.mae_cont(rls_data_s)/args.iter
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      # Uniform
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      rls_data_u, bgts_u = lmdk_bgt.uniform_cont(seq, lmdks, epsilon)
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      # lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_u)
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      mae_u[i] += lmdk_bgt.mae_cont(rls_data_u)/args.iter
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      # Adaptive
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      rls_data_a, _, _ = lmdk_bgt.adaptive_cont(seq, lmdks, epsilon, .5, .5)
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      mae_a[i] += lmdk_bgt.mae_cont(rls_data_a)/args.iter
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      # Event
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      # Calculate once
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      if i == 0:
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        rls_data_evt, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 0), epsilon)
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      mae_evt[i] += lmdk_bgt.mae_cont(rls_data_evt)/args.iter
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      # User
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      # Calculate once
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      if i == 0:
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        rls_data_usr, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 100), epsilon)
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      mae_usr[i] += lmdk_bgt.mae_cont(rls_data_usr)/args.iter
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  plt.plot(
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    x_i,
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    mae_evt,
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    linewidth=lmdk_lib.line_width
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  )
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  plt.text(x_i[-1], mae_evt[-1], '        event')
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  plt.plot(
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    x_i,
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    mae_usr,
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    linewidth=lmdk_lib.line_width
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  )
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  plt.text(x_i[-1], mae_usr[-1], '        user')
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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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  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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  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/HUE/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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