def test_extract_trajectory(self):
res = plot_util.extract_trajectory(experiment=branin_experiment,
maxvalue=1000)
expected_trajectory = ([1000.0] * 1) \
+ ([24.129964413622268] * 2) \
+ ([16.787197168652479] * 5) \
+ ([12.779763397329571] * 3) \
+ ([2.6962005134978178] * 6) \
+ ([0.72639128754424731] * 4)
self.assertListAlmostEqual(expected=expected_trajectory, actual=res)
res = plot_util.extract_trajectory(branin_experiment,
cut=22,
maxvalue=1000)
self.assertListAlmostEqual(expected_trajectory, res)
res = plot_util.extract_trajectory(branin_experiment,
cut=10,
maxvalue=1000)
self.assertListAlmostEqual(expected_trajectory[:10], res)
self.assertAlmostEqual(12.779763397329571, res[-1])
self.assertRaises(ValueError, plot_util.extract_trajectory,
branin_experiment, 0.5)
self.assertRaises(ValueError, plot_util.extract_trajectory,
branin_experiment, 0)
def main(pkl_list, name_list, autofill, optimum=0, save="", title="", log=False,
y_min=0, y_max=0, scale_std=1, cut=sys.maxint):
trial_list = list()
for i in range(len(pkl_list)):
trial_list.append(list())
for pkl in pkl_list[i]:
fh = open(pkl, "r")
trials = cPickle.load(fh)
fh.close()
trace = plot_util.extract_trajectory(trials, cut=cut)
trial_list[-1].append(np.array(trace))
for i in range(len(trial_list)):
max_len = max([len(ls) for ls in trial_list[i]])
for t in range(len(trial_list[i])):
if len(trial_list[i][t]) < max_len and autofill:
diff = max_len - len(trial_list[i][t])
# noinspection PyUnusedLocal
trial_list[i][t] = np.append(trial_list[i][t], [trial_list[i][t][-1] for x in range(diff)])
elif len(trial_list[i][t]) < max_len and not autofill:
raise ValueError("(%s != %s), Traces do not have the same length, please use -a" %
(str(max_len), str(len(trial_list[i][t]))))
plot_optimization_trace(trial_list, name_list, optimum, title=title, log=log,
save=save, y_min=y_min, y_max=y_max, scale_std=scale_std)
if save != "":
sys.stdout.write("Saved plot to " + save + "\n")
else:
sys.stdout.write("..Done\n")
def main(pkl_list,
name_list,
autofill,
optimum=0,
save="",
title="",
log=False,
y_min=0,
y_max=0,
scale_std=1,
cut=sys.maxint,
xmax=100,
every=10):
trial_list = list()
for i in range(len(pkl_list)):
trial_list.append(list())
for pkl in pkl_list[i]:
fh = open(pkl, "r")
trials = cPickle.load(fh)
fh.close()
trace = plot_util.extract_trajectory(trials, cut=cut)
trial_list[-1].append(np.array(trace))
for i in range(len(trial_list)):
max_len = max([len(ls) for ls in trial_list[i]])
for t in range(len(trial_list[i])):
if len(trial_list[i][t]) < max_len and autofill:
diff = max_len - len(trial_list[i][t])
# noinspection PyUnusedLocal
trial_list[i][t] = np.append(
trial_list[i][t],
[trial_list[i][t][-1] for x in range(diff)])
elif len(trial_list[i][t]) < max_len and not autofill:
raise ValueError(
"(%s != %s), Traces do not have the same length, please use -a"
% (str(max_len), str(len(trial_list[i][t]))))
plot_optimization_trace(trial_list,
name_list,
optimum,
title=title,
log=log,
save=save,
y_min=y_min,
y_max=y_max,
scale_std=scale_std,
xmax=xmax,
every=every)
if save != "":
sys.stdout.write("Saved plot to " + save + "\n")
else:
sys.stdout.write("..Done\n")
def test_extract_trajectory(self):
res = plot_util.extract_trajectory(experiment=branin_experiment,
maxvalue=1000)
expected_trajectory = ([1000.0] * 1) \
+ ([24.129964413622268] * 2) \
+ ([16.787197168652479] * 5) \
+ ([12.779763397329571] * 3) \
+ ([2.6962005134978178] * 6) \
+ ([0.72639128754424731] * 4)
self.assertListAlmostEqual(expected=expected_trajectory, actual=res)
res = plot_util.extract_trajectory(branin_experiment, cut=22, maxvalue=1000)
self.assertListAlmostEqual(expected_trajectory, res)
res = plot_util.extract_trajectory(branin_experiment, cut=10, maxvalue=1000)
self.assertListAlmostEqual(expected_trajectory[:10], res)
self.assertAlmostEqual(12.779763397329571, res[-1])
self.assertRaises(ValueError, plot_util.extract_trajectory,
branin_experiment, 0.5)
self.assertRaises(ValueError, plot_util.extract_trajectory,
branin_experiment, 0)
def main(pkl_list, name_list, autofill, optimum=0, save="", title="",
log=False, y_min=0, y_max=0, scale_std=1, cut=sys.maxint, xmax=10, every=10):
trial_list = list()
times_list = list()
for i in range(len(pkl_list)):
tmp_trial_list = list()
tmp_times_list = list()
for pkl in pkl_list[i]:
fh = open(pkl, "r")
trials = cPickle.load(fh)
fh.close()
trace = plot_util.extract_trajectory(trials)
times = plot_util.extract_runtime_timestamps(trials)
tmp_times_list.append(times)
tmp_trial_list.append(trace)
# We feed this function with two lists of lists and get one list of lists and one list
tmp_trial_list, tmp_times_list = fill_trajectories(tmp_trial_list, tmp_times_list)
trial_list.append(tmp_trial_list)
times_list.append(tmp_times_list)
for i in range(len(trial_list)):
max_len = max([len(ls) for ls in trial_list[i]])
for t in range(len(trial_list[i])):
if len(trial_list[i][t]) < max_len and autofill:
diff = max_len - len(trial_list[i][t])
# noinspection PyUnusedLocal
trial_list[i][t] = np.append(trial_list[i][t], [trial_list[i][t][-1] for x in range(diff)])
elif len(trial_list[i][t]) < max_len and not autofill:
raise ValueError("(%s != %s), Traces do not have the same length, please use -a" %
(str(max_len), str(len(trial_list[i][t]))))
plot_optimization_trace(trial_list, name_list, times_list, optimum, title=title, log=log,
save=save, y_min=y_min, y_max=y_max, scale_std=scale_std, xmax=xmax, every=every)
if save != "":
sys.stdout.write("Saved plot to " + save + "\n")
else:
sys.stdout.write("..Done\n")
def main(pkl_list,
name_list,
autofill,
optimum=0,
save="",
title="",
maxvalue=sys.maxint,
logy=False,
logx=False,
y_min=None,
y_max=None,
x_min=None,
x_max=None,
scale_std=1,
properties=None,
aggregation="mean",
print_length_trial_list=True,
ylabel="Minfunction value",
xlabel="Duration [sec]"):
trial_list = list()
times_list = list()
for i in range(len(pkl_list)):
tmp_trial_list = list()
tmp_times_list = list()
for pkl in pkl_list[i]:
fh = open(pkl, "r")
trials = cPickle.load(fh)
fh.close()
trace = plot_util.extract_trajectory(trials, maxvalue=maxvalue)
times = plot_util.extract_runtime_timestamps(trials=trials)
if np.isnan(times[-1]):
print "Last time is nan, removing trial"
times = times[:-1]
trace = trace[:-1]
tmp_times_list.append(times)
tmp_trial_list.append(trace)
# We feed this function with two lists of lists and get
# one list of lists and one list
tmp_trial_list, tmp_times_list = plot_util.\
fill_trajectories(tmp_trial_list, tmp_times_list)
trial_list.append(tmp_trial_list)
times_list.append(tmp_times_list)
for i in range(len(trial_list)):
max_len = max([len(ls) for ls in trial_list[i]])
for t in range(len(trial_list[i])):
if len(trial_list[i][t]) < max_len and autofill:
diff = max_len - len(trial_list[i][t])
# noinspection PyUnusedLocal
trial_list[i][t] = np.append(
trial_list[i][t],
[trial_list[i][t][-1] for x in range(diff)])
elif len(trial_list[i][t]) < max_len and not autofill:
raise ValueError("(%s != %s), Traces do not have the same "
"length, please use -a" %
(str(max_len), str(len(trial_list[i][t]))))
plot_trajectory.plot_trajectories(
trial_list=trial_list,
name_list=name_list,
x_ticks=times_list,
optimum=optimum,
logy=logy,
logx=logx,
aggregation=aggregation,
scale_std=scale_std,
y_max=y_max,
y_min=y_min,
x_max=x_max,
x_min=x_min,
properties=properties,
print_length_trial_list=print_length_trial_list,
title=title,
save=save,
ylabel=ylabel,
xlabel=xlabel)
return
def main(pkl_list, name_list, autofill, optimum=0, save="", title="",
maxvalue=sys.maxint, logy=False, logx=False,
y_min=None, y_max=None, x_min=None, x_max=None,
scale_std=1, properties=None,
aggregation="mean", print_length_trial_list=True,
ylabel="Minfunction value", xlabel="Duration [sec]"):
trial_list = list()
times_list = list()
for i in range(len(pkl_list)):
tmp_trial_list = list()
tmp_times_list = list()
for pkl in pkl_list[i]:
fh = open(pkl, "r")
trials = cPickle.load(fh)
fh.close()
trace = plot_util.extract_trajectory(trials, maxvalue=maxvalue)
times = plot_util.extract_runtime_timestamps(trials=trials)
if np.isnan(times[-1]):
print "Last time is nan, removing trial"
times = times[:-1]
trace = trace[:-1]
tmp_times_list.append(times)
tmp_trial_list.append(trace)
# We feed this function with two lists of lists and get
# one list of lists and one list
tmp_trial_list, tmp_times_list = plot_util.\
fill_trajectories(tmp_trial_list, tmp_times_list)
trial_list.append(tmp_trial_list)
times_list.append(tmp_times_list)
for i in range(len(trial_list)):
max_len = max([len(ls) for ls in trial_list[i]])
for t in range(len(trial_list[i])):
if len(trial_list[i][t]) < max_len and autofill:
diff = max_len - len(trial_list[i][t])
# noinspection PyUnusedLocal
trial_list[i][t] = np.append(trial_list[i][t],
[trial_list[i][t][-1]
for x in range(diff)])
elif len(trial_list[i][t]) < max_len and not autofill:
raise ValueError("(%s != %s), Traces do not have the same "
"length, please use -a" %
(str(max_len), str(len(trial_list[i][t]))))
plot_trajectory.plot_trajectories(trial_list=trial_list,
name_list=name_list,
x_ticks=times_list,
optimum=optimum,
logy=logy, logx=logx,
aggregation=aggregation,
scale_std=scale_std,
y_max=y_max, y_min=y_min,
x_max=x_max, x_min=x_min,
properties=properties,
print_length_trial_list=
print_length_trial_list,
title=title, save=save,
ylabel=ylabel, xlabel=xlabel)
return
def main(pkl_list,
name_list,
autofill,
optimum=0,
save="",
title="",
log=False,
y_min=0,
y_max=0,
scale_std=1,
cut=sys.maxint):
trial_list = list()
times_list = list()
for i in range(len(pkl_list)):
tmp_trial_list = list()
tmp_times_list = list()
for pkl in pkl_list[i]:
fh = open(pkl, "r")
trials = cPickle.load(fh)
fh.close()
trace = plot_util.extract_trajectory(trials)
times = plot_util.extract_runtime_timestamps(trials)
tmp_times_list.append(times)
tmp_trial_list.append(trace)
# We feed this function with two lists of lists and get one list of lists and one list
tmp_trial_list, tmp_times_list = fill_trajectories(
tmp_trial_list, tmp_times_list)
trial_list.append(tmp_trial_list)
times_list.append(tmp_times_list)
for i in range(len(trial_list)):
max_len = max([len(ls) for ls in trial_list[i]])
for t in range(len(trial_list[i])):
if len(trial_list[i][t]) < max_len and autofill:
diff = max_len - len(trial_list[i][t])
# noinspection PyUnusedLocal
trial_list[i][t] = np.append(
trial_list[i][t],
[trial_list[i][t][-1] for x in range(diff)])
elif len(trial_list[i][t]) < max_len and not autofill:
raise ValueError(
"(%s != %s), Traces do not have the same length, please use -a"
% (str(max_len), str(len(trial_list[i][t]))))
plot_optimization_trace(trial_list,
name_list,
times_list,
optimum,
title=title,
log=log,
save=save,
y_min=y_min,
y_max=y_max,
scale_std=scale_std)
if save != "":
sys.stdout.write("Saved plot to " + save + "\n")
else:
sys.stdout.write("..Done\n")
def main(pkl_list,
name_list,
autofill,
optimum=0,
save="",
title="",
log=False,
maxvalue=sys.maxint,
y_min=None,
y_max=None,
scale_std=1,
aggregation="mean",
cut=sys.maxint,
xlabel="#Function evaluations",
ylabel="Loss",
properties=None,
print_lenght_trial_list=False,
plot_test_performance=False):
trial_list = list()
test_list = list()
x_ticks = list()
for i in range(len(pkl_list)):
trial_list.append(list())
test_list.append(list())
for pkl in pkl_list[i]:
if pkl in plot_util.cache:
trials = plot_util.cache[pkl]
else:
fh = open(pkl, "r")
trials = cPickle.load(fh)
fh.close()
plot_util.cache[pkl] = trials
if plot_test_performance:
trace, test = plot_util.extract_trajectory(trials,
cut=cut,
maxvalue=maxvalue,
test=True)
# TODO: We can only plot one test result
if len(test) > 1:
raise NotImplementedError(
"Cannot yet plot more than one testresult")
else:
test = test[0]
print test_list
if len(test_list) == 0 or len(test_list[-1]) == 0:
test_list[-1].extend([[
test[0],
], [
test[1],
]])
else:
test_list[-1][0].append(test[0])
test_list[-1][1].append(test[1])
else:
trace = plot_util.extract_trajectory(trials,
cut=cut,
maxvalue=maxvalue,
test=False)
trial_list[-1].append(np.array(trace))
if not plot_test_performance:
test_list = None
for i in range(len(trial_list)):
max_len = max([len(ls) for ls in trial_list[i]])
for t in range(len(trial_list[i])):
if len(trial_list[i][t]) < max_len and autofill:
diff = max_len - len(trial_list[i][t])
# noinspection PyUnusedLocal
trial_list[i][t] = np.append(
trial_list[i][t],
[trial_list[i][t][-1] for x in range(diff)])
elif len(trial_list[i][t]) < max_len and not autofill:
raise ValueError("(%s != %s), Traces do not have the same "
"length, please use -a" %
(str(max_len), str(len(trial_list[i][t]))))
x_ticks.append(range(np.max([len(ls) for ls in trial_list[i]])))
plot_trajectory.plot_trajectories(
trial_list=trial_list,
name_list=name_list,
x_ticks=x_ticks,
optimum=optimum,
y_min=y_min,
y_max=y_max,
title=title,
ylabel=ylabel,
xlabel=xlabel,
logy=log,
save=save,
aggregation=aggregation,
properties=properties,
scale_std=scale_std,
test_trials=test_list,
print_length_trial_list=print_lenght_trial_list)
return