lmdk_sel_cmp: Testing

code/expt/lmdk_sel_cmp.py

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+#!/usr/bin/env python3
+
+import sys
+sys.path.insert(1, '../lib')
+import argparse
+import lmdk_lib
+import lmdk_sel
+import exp_mech
+import numpy as np
+import os
+from matplotlib import pyplot as plt
+import time
+
+
+def main(args):
+  # Privacy goal
+  epsilon = 1.0
+  # Number of timestamps
+  seq = lmdk_lib.get_seq(1, args.time)
+  # Distribution type
+  dist_type = np.array(range(0, 4))
+  # Number of landmarks
+  lmdk_n = np.array(range(int(.2*args.time), args.time, int(args.time/5)))
+  # Initialize plot
+  lmdk_lib.plot_init()
+  # Width of bars
+  bar_width = 1/(len(dist_type) + 1)
+  # The x axis
+  x_i = np.arange(len(lmdk_n))
+  x_margin = bar_width*(len(dist_type)/2 + 1)
+  plt.xticks(x_i, ((lmdk_n/len(seq))*100).astype(int))
+  plt.xlabel('Landmarks (%)')  # Set x axis label.
+  plt.xlim(x_i.min() - x_margin, x_i.max() + x_margin)
+  # The y axis
+  plt.ylabel('Mean absolute error')  # Set y axis label.
+  # Bar offset
+  x_offset = -(bar_width/2)*(len(dist_type) - 1)
+  for d_i, d in enumerate(dist_type):
+    # Set label
+    label = lmdk_lib.dist_type_to_str(d)
+    if d_i == 1:
+      label = 'Skewed'
+    # Logging
+    title =  label + ' landmark distribution'
+    print('(%d/%d) %s... ' %(d_i + 1, len(dist_type), title), end='', flush=True)
+    mae = np.zeros(len(lmdk_n))
+    for n_i, n in enumerate(lmdk_n):
+      for r in range(args.reps):
+        lmdks = lmdk_lib.get_lmdks(seq, n, d)
+        hist, h = lmdk_lib.get_hist(seq, lmdks)
+        opts = lmdk_sel.get_opts_from_top_h(seq, lmdks)
+        delta = 1.0
+        res, _ = exp_mech.exponential_pareto(hist, opts, exp_mech.score, delta, epsilon)
+        mae[n_i] += lmdk_lib.get_norm(hist, res)/args.reps
+    print('[OK]', flush=True)
+    # Plot bar for current distribution
+    plt.bar(
+      x_i + x_offset,
+      mae,
+      bar_width,
+      label=label,
+      linewidth=lmdk_lib.line_width
+    )
+    # Change offset for next bar
+    x_offset += bar_width
+  path = str('../../rslt/lmdk_sel_cmp-pareto/' + 'lmdk_sel_cmp')
+  # Plot legend
+  lmdk_lib.plot_legend()
+  # Show plot
+  # plt.show()
+  # Save plot
+  lmdk_lib.save_plot(path + '.pdf')
+
+
+
+'''
+  Parse arguments.
+
+  Optional:
+    reps - The number of repetitions.
+    time - The time limit of the sequence.
+'''
+def parse_args():
+  # Create argument parser.
+  parser = argparse.ArgumentParser()
+
+  # Mandatory arguments.
+
+  # Optional arguments.
+  parser.add_argument('-r', '--reps', help='The number of repetitions.', type=int, default=1)
+  parser.add_argument('-t', '--time', help='The time limit of the sequence.', type=int, default=100)
+
+  # 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()