evaluation: Re-executed some experiments

This commit is contained in:
Manos Katsomallos 2021-10-11 01:12:35 +02:00
parent f84cfb205d
commit f48dca02aa
18 changed files with 39 additions and 35 deletions

View File

@ -68,29 +68,30 @@ def main(args):
for _ in range(args.iter): for _ in range(args.iter):
lmdks, eps_out = lmdk_sel.find_lmdks(seq, lmdks, epsilon) lmdks_sel, eps_out = lmdk_sel.find_lmdks(seq, lmdks, epsilon)
# Skip # Skip
rls_data_s, bgts_s = lmdk_bgt.skip_cont(seq, lmdks, eps_out) rls_data_s, bgts_s = lmdk_bgt.skip_cont(seq, lmdks_sel, eps_out)
# lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_s) # lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_s)
mae_s[i] += (lmdk_bgt.mae_cont(rls_data_s)/args.iter)*100 mae_s[i] += (lmdk_bgt.mae_cont(rls_data_s)/args.iter)*100
# Uniform # Uniform
rls_data_u, bgts_u = lmdk_bgt.uniform_cont(seq, lmdks, eps_out) rls_data_u, bgts_u = lmdk_bgt.uniform_cont(seq, lmdks_sel, eps_out)
# lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_u) # lmdk_bgt.validate_bgts(seq, lmdks, epsilon, bgts_u)
mae_u[i] += (lmdk_bgt.mae_cont(rls_data_u)/args.iter)*100 mae_u[i] += (lmdk_bgt.mae_cont(rls_data_u)/args.iter)*100
# Adaptive # Adaptive
rls_data_a, _, _ = lmdk_bgt.adaptive_cont(seq, lmdks, eps_out, .5, .5) rls_data_a, _, _ = lmdk_bgt.adaptive_cont(seq, lmdks_sel, eps_out, .5, .5)
mae_a[i] += (lmdk_bgt.mae_cont(rls_data_a)/args.iter)*100 mae_a[i] += (lmdk_bgt.mae_cont(rls_data_a)/args.iter)*100
# Calculate once # Calculate once
if i == 0: if pct == lmdks_pct[0]:
# Event # Event
rls_data_evt, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 0), epsilon) rls_data_evt, _ = lmdk_bgt.uniform_cont(seq, lmdks, epsilon)
mae_evt += (lmdk_bgt.mae_cont(rls_data_evt)/args.iter)*100 mae_evt += (lmdk_bgt.mae_cont(rls_data_evt)/args.iter)*100
elif pct == lmdks_pct[-1]:
# User # User
rls_data_usr, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 100), epsilon) rls_data_usr, _ = lmdk_bgt.uniform_cont(seq, lmdks, epsilon)
mae_usr += (lmdk_bgt.mae_cont(rls_data_usr)/args.iter)*100 mae_usr += (lmdk_bgt.mae_cont(rls_data_usr)/args.iter)*100
plt.axhline( plt.axhline(

View File

@ -80,12 +80,13 @@ def main(args):
mae_a[i] += (lmdk_bgt.mae_cont(rls_data_a)/args.iter)*100 mae_a[i] += (lmdk_bgt.mae_cont(rls_data_a)/args.iter)*100
# Calculate once # Calculate once
if i == 0: if pct == lmdks_pct[0]:
# Event # Event
rls_data_evt, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 0), epsilon) rls_data_evt, _ = lmdk_bgt.uniform_cont(seq, lmdks, epsilon)
mae_evt += (lmdk_bgt.mae_cont(rls_data_evt)/args.iter)*100 mae_evt += (lmdk_bgt.mae_cont(rls_data_evt)/args.iter)*100
elif pct == lmdks_pct[-1]:
# User # User
rls_data_usr, _ = lmdk_bgt.uniform_cont(seq, lmdk_lib.find_lmdks_cont(lmdk_data, seq, uid, 100), epsilon) rls_data_usr, _ = lmdk_bgt.uniform_cont(seq, lmdks, epsilon)
mae_usr += (lmdk_bgt.mae_cont(rls_data_usr)/args.iter)*100 mae_usr += (lmdk_bgt.mae_cont(rls_data_usr)/args.iter)*100
plt.axhline( plt.axhline(

View File

@ -48,7 +48,7 @@ def main(args):
# The y axis # The y axis
plt.ylabel('Mean absolute error (kWh)') # Set y axis label. plt.ylabel('Mean absolute error (kWh)') # Set y axis label.
plt.yscale('log') plt.yscale('log')
plt.ylim(.1, 10000) plt.ylim(.1, 100000)
# Bar offset # Bar offset
x_offset = -(bar_width/2)*(n - 1) x_offset = -(bar_width/2)*(n - 1)
@ -80,13 +80,13 @@ def main(args):
mae_a[i] += lmdk_bgt.mae_cons(seq, rls_data_a)/args.iter mae_a[i] += lmdk_bgt.mae_cons(seq, rls_data_a)/args.iter
# Calculate once # Calculate once
if pct == lmdks_pct[0]:
# Event # Event
if i == 0: rls_data_evt, _ = lmdk_bgt.uniform_cons(seq, lmdks, epsilon)
rls_data_evt, _ = lmdk_bgt.uniform_cons(seq, seq[seq[:, 1] < lmdks_th[0]], epsilon)
mae_evt += lmdk_bgt.mae_cons(seq, rls_data_evt)/args.iter mae_evt += lmdk_bgt.mae_cons(seq, rls_data_evt)/args.iter
elif pct == lmdks_pct[-1]:
# User # User
if i == 0: rls_data_usr, _ = lmdk_bgt.uniform_cons(seq, lmdks, epsilon)
rls_data_usr, _ = lmdk_bgt.uniform_cons(seq, seq[seq[:, 1] < lmdks_th[len(lmdks_th)-1]], epsilon)
mae_usr += lmdk_bgt.mae_cons(seq, rls_data_usr)/args.iter mae_usr += lmdk_bgt.mae_cons(seq, rls_data_usr)/args.iter
plt.axhline( plt.axhline(

View File

@ -46,7 +46,7 @@ def main(args):
# The y axis # The y axis
plt.ylabel('Mean absolute error (kWh)') # Set y axis label. plt.ylabel('Mean absolute error (kWh)') # Set y axis label.
plt.yscale('log') plt.yscale('log')
plt.ylim(.1, 10000) plt.ylim(.1, 100000)
# Bar offset # Bar offset
x_offset = -(bar_width/2)*(n - 1) x_offset = -(bar_width/2)*(n - 1)
@ -75,13 +75,13 @@ def main(args):
mae_a[i] += lmdk_bgt.mae_cons(seq, rls_data_a)/args.iter mae_a[i] += lmdk_bgt.mae_cons(seq, rls_data_a)/args.iter
# Calculate once # Calculate once
if pct == lmdks_pct[0]:
# Event # Event
if i == 0: rls_data_evt, _ = lmdk_bgt.uniform_cons(seq, lmdks, epsilon)
rls_data_evt, _ = lmdk_bgt.uniform_cons(seq, seq[seq[:, 1] < lmdks_th[0]], epsilon)
mae_evt += lmdk_bgt.mae_cons(seq, rls_data_evt)/args.iter mae_evt += lmdk_bgt.mae_cons(seq, rls_data_evt)/args.iter
elif pct == lmdks_pct[-1]:
# User # User
if i == 0: rls_data_usr, _ = lmdk_bgt.uniform_cons(seq, lmdks, epsilon)
rls_data_usr, _ = lmdk_bgt.uniform_cons(seq, seq[seq[:, 1] < lmdks_th[len(lmdks_th)-1]], epsilon)
mae_usr += lmdk_bgt.mae_cons(seq, rls_data_usr)/args.iter mae_usr += lmdk_bgt.mae_cons(seq, rls_data_usr)/args.iter
plt.axhline( plt.axhline(

View File

@ -70,7 +70,7 @@ def main(args):
# The y axis # The y axis
plt.ylabel('Mean absolute error (m)') # Set y axis label. plt.ylabel('Mean absolute error (m)') # Set y axis label.
plt.yscale('log') plt.yscale('log')
# plt.ylim(1, 100000000) plt.ylim(1, 1000000)
# Bar offset # Bar offset
x_offset = -(bar_width/2)*(n - 1) x_offset = -(bar_width/2)*(n - 1)
@ -101,12 +101,13 @@ def main(args):
rls_data_a, _, _ = lmdk_bgt.adaptive(seq, lmdks, eps_out, .5, .5) rls_data_a, _, _ = lmdk_bgt.adaptive(seq, lmdks, eps_out, .5, .5)
mae_a[i] += lmdk_bgt.mae(seq, rls_data_a)/args.iter mae_a[i] += lmdk_bgt.mae(seq, rls_data_a)/args.iter
# Calculate once
if lmdk == min(data_info[d]['lmdks']):
# Event # Event
if lmdk == 0:
rls_data_evt, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon']) rls_data_evt, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon'])
mae_evt += lmdk_bgt.mae(seq, rls_data_evt)/args.iter mae_evt += lmdk_bgt.mae(seq, rls_data_evt)/args.iter
elif lmdk == max(data_info[d]['lmdks']):
# User # User
if lmdk == 100:
rls_data_usr, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon']) rls_data_usr, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon'])
mae_usr += lmdk_bgt.mae(seq, rls_data_usr)/args.iter mae_usr += lmdk_bgt.mae(seq, rls_data_usr)/args.iter

View File

@ -68,7 +68,7 @@ def main(args):
# The y axis # The y axis
plt.ylabel('Mean absolute error (m)') # Set y axis label. plt.ylabel('Mean absolute error (m)') # Set y axis label.
plt.yscale('log') plt.yscale('log')
# plt.ylim(1, 100000000) plt.ylim(1, 1000000)
# Bar offset # Bar offset
x_offset = -(bar_width/2)*(n - 1) x_offset = -(bar_width/2)*(n - 1)
@ -103,12 +103,13 @@ def main(args):
# mae_d[i] += lmdk_bgt.mae(seq, rls_data_a)/args.iter # mae_d[i] += lmdk_bgt.mae(seq, rls_data_a)/args.iter
# s_d += s_d_c/args.iter # s_d += s_d_c/args.iter
# Calculate once
if lmdk == min(data_info[d]['lmdks']):
# Event # Event
if lmdk == 0:
rls_data_evt, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon']) rls_data_evt, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon'])
mae_evt += lmdk_bgt.mae(seq, rls_data_evt)/args.iter mae_evt += lmdk_bgt.mae(seq, rls_data_evt)/args.iter
elif lmdk == max(data_info[d]['lmdks']):
# User # User
if lmdk == 100:
rls_data_usr, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon']) rls_data_usr, _ = lmdk_bgt.uniform_r(seq, lmdks, bgt['epsilon'])
mae_usr += lmdk_bgt.mae(seq, rls_data_usr)/args.iter mae_usr += lmdk_bgt.mae(seq, rls_data_usr)/args.iter

View File

@ -558,10 +558,10 @@ def skip_cont(seq, lmdks, epsilon):
# Add noise # Add noise
o = lmdk_lib.randomized_response(is_landmark, bgts[i]) o = lmdk_lib.randomized_response(is_landmark, bgts[i])
if is_landmark: if is_landmark:
bgts[i] = 0
if i > 0: if i > 0:
# Approximate with previous # Approximate with previous
o = rls_data[i - 1][1] o = rls_data[i - 1][1]
bgts[i] = 0
rls_data[i] = [is_landmark, o] rls_data[i] = [is_landmark, o]
return rls_data, bgts return rls_data, bgts

Binary file not shown.

Binary file not shown.

Binary file not shown.

Binary file not shown.

Binary file not shown.

Binary file not shown.

Binary file not shown.

Binary file not shown.

Binary file not shown.