code: WIP
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								code/expt/expt_lmdk_sel.py
									
									
									
									
									
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										105
									
								
								code/expt/expt_lmdk_sel.py
									
									
									
									
									
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					#!/usr/bin/env python3
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					import argparse
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					import lmdk_lib
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					import lmdk_sel
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					import exp_mech
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					import numpy as np
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					import os
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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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					  # Privacy goal
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					  epsilon = [.01, .1, 1.0, 10.0, 100.0]
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					  # Number of timestamps
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					  seq = lmdk_lib.get_seq(1, args.time)
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					  # Distribution type
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					  dist_type = np.array(range(-1, 4))
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					  # Number of landmarks
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					  lmdk_n = np.array(range(int(.2*args.time), args.time, int(args.time/5)))
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					  # Width of bars
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					  bar_width = 1/(len(epsilon) + 1)
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					  # The x axis
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					  x_i = np.arange(len(lmdk_n))
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					  x_margin = bar_width*(len(epsilon)/2 + 1)
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					  for d_i, d in enumerate(dist_type):
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					    # Logging
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					    title =  lmdk_lib.dist_type_to_str(d) + ' landmark distribution'
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					    print('(%d/%d) %s... ' %(d_i + 1, len(dist_type), title), end='', flush=True)
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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, ((lmdk_n/len(seq))*100).astype(int))
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					    plt.xlabel('Landmarks (%)')  # 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.ylim(0, len(seq)/3)
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					    # Bar offset
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					    x_offset = -(bar_width/2)*(len(epsilon) - 1)
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					    for e_i, e in enumerate(epsilon):
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					      mae = np.zeros(len(lmdk_n))
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					      for n_i, n in enumerate(lmdk_n):
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					        for r in range(args.reps):
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					          lmdks = lmdk_lib.get_lmdks(seq, n, d)
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					          hist, h = lmdk_lib.get_hist(seq, lmdks)
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					          opts = lmdk_sel.get_opts_from_top_h(seq, lmdks)
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					          delta = 1.0
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					          res, _ = exp_mech.exponential(hist, opts, exp_mech.score, delta, e)
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					          mae[n_i] += lmdk_lib.get_norm(hist, res)/args.reps
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					      # Plot bar for current epsilon
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					      plt.bar(
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					        x_i + x_offset,
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					        mae,
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					        bar_width,
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					        label=u'\u03B5 = ' + str("{:.0e}".format(e)),
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					        linewidth=lmdk_lib.line_width
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					      )
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					      # Change offset for next bar
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					      x_offset += bar_width
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					    path = str('/home/manos/Git/the-thing/code/expt_lmdk_sel/' + title)
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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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					'''
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					  Parse arguments.
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					  Optional:
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					    reps - The number of repetitions.
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					    time - The time limit of the sequence.
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					'''
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					def parse_args():
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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', '--reps', help='The number of repetitions.', type=int, default=1)
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					  parser.add_argument('-t', '--time', help='The time limit of the sequence.', type=int, default=100)
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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 elapsed: %s' % (time.strftime('%H:%M:%S', time.gmtime(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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