def plot_final_scores():
''' Plot the scores '''
font = {'size': 12}
mpl.rc('font', **font)
fig, ax = plt.subplots(nrows=1, ncols=1,
figsize=(7, 4)) # create figure & 1 axis
outfiles = [
RESULT_DIR + 'seq2seq_teacher_imagenet_%s_iter_5000.json',
RESULT_DIR + 'seq2seq_sample_imagenet_%s_iter_20000.json',
RESULT_DIR + '%s_stop_agent.json', RESULT_DIR + '%s_random_agent.json'
]
for split in ['val_seen']:
ev = Evaluation([split])
for i, outfile in enumerate(outfiles):
score_summary, scores = ev.score(outfile % split)
if i == 0:
method = 'Teacher-forcing'
ax.hist(scores['nav_errors'],
bins=range(0, 30, 3),
label=method,
normed=True,
histtype='step',
linewidth=2.5,
color='C1')
elif i == 1:
method = 'Student-forcing'
ax.hist(scores['nav_errors'],
bins=range(0, 30, 3),
label=method,
alpha=0.7,
normed=True,
color='C0')
elif i == 2:
method = 'Start locations'
ax.hist(scores['nav_errors'],
bins=range(0, 30, 3),
label=method,
normed=True,
histtype='step',
linewidth=2.5,
color='C3')
elif i == 3:
method = 'Random agent'
ax.hist(scores['nav_errors'],
bins=range(0, 30, 3),
label=method,
normed=True,
histtype='step',
linewidth=2.5,
color='C2')
ax.set_title('Val Seen Navigation Error')
ax.set_xlabel('Error (m)')
ax.set_ylabel('Frequency')
ax.set_ylim([0, 0.14])
ax.set_xlim([0, 30])
plt.axvline(x=3, color='black', linestyle='--')
legend = ax.legend(loc='upper right')
plt.tight_layout()
plt.savefig('%s/val_seen_error.png' % (PLOT_DIR))
plt.close(fig)
def plot_final_scores():
''' Plot the scores '''
font = {
'size' : 12
}
mpl.rc('font', **font)
fig, ax = plt.subplots( nrows=1, ncols=1, figsize=(7,4) ) # create figure & 1 axis
outfiles = [
RESULT_DIR + 'seq2seq_sample_imagenet_%s_iter_20000.json',
RESULT_DIR + 'seq2seq_teacher_imagenet_%s_iter_5000.json',
RESULT_DIR + '%s_stop_agent.json',
RESULT_DIR + '%s_random_agent.json'
]
for split in ['val_seen']:
ev = Evaluation([split])
for i,outfile in enumerate(outfiles):
score_summary,scores = ev.score(outfile % split)
if i == 1:
method = 'Teacher-forcing'
ax.hist(scores['nav_errors'], bins=range(0,30,3), label=method, normed=True, histtype = 'step', linewidth=2.5, color='C1')
elif i == 0:
method = 'Student-forcing'
ax.hist(scores['nav_errors'], bins=range(0,30,3), label=method, alpha=0.7, normed=True, color='C0')
elif i == 2:
method = 'Start locations'
ax.hist(scores['nav_errors'], bins=range(0,30,3), label=method, normed=True, histtype = 'step', linewidth=2.5, color='C3')
elif i == 3:
method = 'Random agent'
ax.hist(scores['nav_errors'], bins=range(0,30,3), label=method, normed=True, histtype = 'step', linewidth=2.5, color='C2')
ax.set_title('Val Seen Navigation Error')
ax.set_xlabel('Error (m)')
ax.set_ylabel('Frequency')
ax.set_ylim([0,0.14])
ax.set_xlim([0,30])
plt.axvline(x=3, color='black', linestyle='--')
legend = ax.legend(loc='upper right')
plt.tight_layout()
plt.savefig('%s/val_seen_error.png' % (PLOT_DIR))
plt.close(fig)
def plot_final_scores():
""" Plot the scores """
font = {"size": 12}
mpl.rc("font", **font)
fig, ax = plt.subplots(nrows=1, ncols=1,
figsize=(7, 4)) # create figure & 1 axis
outfiles = [
RESULT_DIR + "seq2seq_sample_imagenet_%s_iter_20000.json",
RESULT_DIR + "seq2seq_teacher_imagenet_%s_iter_5000.json",
RESULT_DIR + "%s_stop_agent.json",
RESULT_DIR + "%s_random_agent.json",
]
for split in ["val_seen"]:
ev = Evaluation([split])
for i, outfile in enumerate(outfiles):
score_summary, scores = ev.score(outfile % split)
if i == 1:
method = "Teacher-forcing"
ax.hist(
scores["nav_errors"],
bins=list(range(0, 30, 3)),
label=method,
normed=True,
histtype="step",
linewidth=2.5,
color="C1",
)
elif i == 0:
method = "Student-forcing"
ax.hist(
scores["nav_errors"],
bins=list(range(0, 30, 3)),
label=method,
alpha=0.7,
normed=True,
color="C0",
)
elif i == 2:
method = "Start locations"
ax.hist(
scores["nav_errors"],
bins=list(range(0, 30, 3)),
label=method,
normed=True,
histtype="step",
linewidth=2.5,
color="C3",
)
elif i == 3:
method = "Random agent"
ax.hist(
scores["nav_errors"],
bins=list(range(0, 30, 3)),
label=method,
normed=True,
histtype="step",
linewidth=2.5,
color="C2",
)
ax.set_title("Val Seen Navigation Error")
ax.set_xlabel("Error (m)")
ax.set_ylabel("Frequency")
ax.set_ylim([0, 0.14])
ax.set_xlim([0, 30])
plt.axvline(x=3, color="black", linestyle="--")
legend = ax.legend(loc="upper right")
plt.tight_layout()
plt.savefig("%s/val_seen_error.png" % (PLOT_DIR))
plt.close(fig)