the-last-thing/code/expt/hue-sel.py

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2021-10-06 01:44:50 +02:00
#!/usr/bin/env python3
import sys
sys.path.insert(1, '../lib')
import argparse
import ast
from datetime import datetime
from geopy.distance import distance
import lmdk_bgt
import lmdk_lib
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import lmdk_sel
import exp_mech
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import math
import numpy as np
from matplotlib import pyplot as plt
import time
def main(args):
# User's consumption
seq = lmdk_lib.load_data(args, 'cons')
# The name of the dataset
d = 'HUE'
# The landmarks percentages
lmdks_pct = [0, 20, 40, 60, 80, 100]
# Landmarks' thresholds
lmdks_th = [0, .54, .68, .88, 1.12, 10]
# The privacy budget
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epsilon = 1.0
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# Number of methods
n = 3
# 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')
# Initialize plot
lmdk_lib.plot_init()
# The x axis
plt.xticks(x_i, np.array(lmdks_pct, 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 (kWh)') # Set y axis label.
plt.yscale('log')
plt.ylim(.1, 100000)
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# Bar offset
x_offset = -(bar_width/2)*(n - 1)
mae_u = np.zeros(len(lmdks_pct))
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mae_u_sel= np.zeros(len(lmdks_pct))
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mae_s = np.zeros(len(lmdks_pct))
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mae_s_sel = np.zeros(len(lmdks_pct))
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mae_a = np.zeros(len(lmdks_pct))
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mae_a_sel = np.zeros(len(lmdks_pct))
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mae_evt = 0
mae_usr = 0
for i, pct in enumerate(lmdks_pct):
# Find landmarks
lmdks = seq[seq[:, 1] < lmdks_th[i]]
for _ in range(args.iter):
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lmdks_sel, eps_out = lmdk_sel.find_lmdks(seq, lmdks, epsilon)
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# Skip
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rls_data_s, _ = lmdk_bgt.skip_cons(seq, lmdks, eps_out)
mae_s[i] += (lmdk_bgt.mae_cons(seq, rls_data_s)/args.iter)*100
rls_data_s_sel, _ = lmdk_bgt.skip_cons(seq, lmdks_sel, eps_out)
mae_s_sel[i] += (lmdk_bgt.mae_cons(seq, rls_data_s_sel)/args.iter)*100
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# Uniform
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rls_data_u, _ = lmdk_bgt.uniform_cons(seq, lmdks, eps_out)
mae_u[i] += (lmdk_bgt.mae_cons(seq, rls_data_u)/args.iter)*100
rls_data_u_sel, _ = lmdk_bgt.uniform_cons(seq, lmdks_sel, eps_out)
mae_u_sel[i] += (lmdk_bgt.mae_cons(seq, rls_data_u_sel)/args.iter)*100
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# Adaptive
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rls_data_a, _, _ = lmdk_bgt.adaptive_cons(seq, lmdks, eps_out, .5, .5)
mae_a[i] += (lmdk_bgt.mae_cons(seq, rls_data_a)/args.iter)*100
rls_data_a_sel, _, _ = lmdk_bgt.adaptive_cons(seq, lmdks_sel, eps_out, .5, .5)
mae_a_sel[i] += (lmdk_bgt.mae_cons(seq, rls_data_a_sel)/args.iter)*100
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# Calculate once
if pct == lmdks_pct[0]:
# Event
rls_data_evt, _ = lmdk_bgt.uniform_cons(seq, lmdks, epsilon)
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mae_evt += lmdk_bgt.mae_cons(seq, rls_data_evt)/args.iter
elif pct == lmdks_pct[-1]:
# User
rls_data_usr, _ = lmdk_bgt.uniform_cons(seq, lmdks, epsilon)
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mae_usr += lmdk_bgt.mae_cons(seq, rls_data_usr)/args.iter
plt.axhline(
y = mae_evt,
color = '#212121',
linewidth=lmdk_lib.line_width
)
plt.text(x_i[-1] + x_i[-1]*.14, mae_evt - mae_evt*.14, 'event')
plt.axhline(
y = mae_usr,
color = '#616161',
linewidth=lmdk_lib.line_width
)
plt.text(x_i[-1] + x_i[-1]*.14, mae_usr - mae_usr*.14, 'user')
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# Plot bars
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plt.bar(
x_i + x_offset,
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mae_s_sel,
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bar_width,
label='Skip',
linewidth=lmdk_lib.line_width
)
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plt.bar(
x_i + x_offset,
mae_s,
bar_width,
color='none',
linestyle='dashed',
edgecolor='#bdbdbd',
linewidth=lmdk_lib.line_width
)
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x_offset += bar_width
plt.bar(
x_i + x_offset,
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mae_u_sel,
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bar_width,
label='Uniform',
linewidth=lmdk_lib.line_width
)
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plt.bar(
x_i + x_offset,
mae_u,
bar_width,
color='none',
linestyle='dashed',
edgecolor='#bdbdbd',
linewidth=lmdk_lib.line_width
)
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x_offset += bar_width
plt.bar(
x_i + x_offset,
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mae_a_sel,
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bar_width,
label='Adaptive',
linewidth=lmdk_lib.line_width
)
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plt.bar(
x_i + x_offset,
mae_a,
bar_width,
color='none',
linestyle='dashed',
edgecolor='#bdbdbd',
linewidth=lmdk_lib.line_width
)
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x_offset += bar_width
path = str('../../rslt/bgt_cmp/' + d)
# Plot legend
lmdk_lib.plot_legend()
# Show plot
# plt.show()
# Save plot
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lmdk_lib.save_plot(path + '-sel-cmp.pdf')
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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/HUE/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 elapsed: %s' % (time.strftime('%H:%M:%S', time.gmtime(end_time - start_time))))
print('##############################')
except KeyboardInterrupt:
print('Interrupted by user.')
exit()