def plot_chart(experiment_root_folder,
show_drift_times,
show_sync_times,
loss_function,
plotBaseLines=True):
envs = read_results_column(experiment_root_folder + RESULT_FILENAME,
ENV_ID_COLUMN)
labels = read_results_column(experiment_root_folder + RESULT_FILENAME,
ENV_LABEL_COLUMN)
index = -1
max_y = 0
max_x = 0
colors = ColorUtil().generateDistinctColors(len(envs))
for env in envs:
if not plotBaseLines and "nosync" in env:
print "skipped: ", env
continue
index += 1
metric = read_cumulative_error(
experiment_root_folder + 'logs/prediction_%s.log' % (envs[index]),
loss_function)
xpoints, ypoints = metric
max_env_x = max(xpoints)
max_env_y = max(ypoints)
if max_env_x > max_x: max_x = max_env_x
if max_env_y > max_y: max_y = max_env_y
#color = generate_color(index,len(envs))
color = colors[index]
plt.plot(xpoints, ypoints, label=labels[index], color=color)
if show_sync_times:
plot_sync_times(experiment_root_folder, env, color,
(xpoints, ypoints))
plt.xlim(0, max_x)
plt.ylim(0, max_y * 1.05)
if show_drift_times: plot_drift_times(experiment_root_folder)
def plot_chart(results_root_folder, show_drift_times, show_sync_times):
envs=read_results_column(results_root_folder+RESULT_FILENAME,ENV_ID_COLUMN)
labels=read_results_column(results_root_folder+RESULT_FILENAME,ENV_LABEL_COLUMN)
index=-1
colors = ColorUtil().generateDistinctColors(len(envs))
for env in envs:
index+=1
file_name=results_root_folder+'logs/communication_%s.log' % (env)
if os.path.isfile(file_name):
metric = read_cumulative_communication(file_name,
read_number_of_rounds(results_root_folder+SUMMARY_FILENAME))
xpoints, ypoints = metric
color = generate_color(index,len(envs))
color = colors[index]
# if 'static-SGD' in labels[index]:
# color = 'g'
# if 'static-Kernel' in labels[index]:
# color = 'c'
# if 'dynamic-SGD' in labels[index]:
# color = 'r'
# if 'dynamic-Kernel' in labels[index]:
# color = 'm'
plt.plot(xpoints, ypoints, label = labels[index], color = color, linewidth=2.0)
# if not "communication" in chart:
if show_sync_times:
plot_sync_times(results_root_folder, env, sync_times_marker, sync_times_size, color, xpoints, ypoints)
if show_drift_times:
plot_drift_times(results_root_folder)
def plot_chart(experiment_root_folder, show_drift_times, show_sync_times,
loss_function):
envs = read_results_column(experiment_root_folder + RESULT_FILENAME,
ENV_ID_COLUMN)
labels = read_results_column(experiment_root_folder + RESULT_FILENAME,
ENV_LABEL_COLUMN)
index = -1
max_y = 0
max_x = 0
for env in envs:
index += 1
metric = read_average_error(
experiment_root_folder + 'logs/prediction_%s.log' % (env),
loss_function)
write_metric(experiment_root_folder, metric)
xpoints, ypoints = metric
max_env_x = max(xpoints)
max_env_y = max(ypoints)
if max_env_x > max_x: max_x = max_env_x
if max_env_y > max_y: max_y = max_env_y
color = generate_color(index, len(envs))
plt.plot(xpoints, ypoints, label=labels[index], color=color)
if show_sync_times:
plot_sync_times(experiment_root_folder, env, color,
(xpoints, ypoints))
plt.xlim(0, max_x)
plt.ylim(0, max_y * 1.05)
if show_drift_times: plot_drift_times(experiment_root_folder)
def read_metrics(envs, result_filename, predictive_performance_column):
result = []
errors = read_results_column(result_filename,
predictive_performance_column)
communication = read_results_column(result_filename,
ENV_COMM_MESSAGE_COLUMN)
for i in xrange(len(envs)):
result.append((float(communication[i]), float(errors[i])))
print envs
print result
print errors
return result
def plot_baselines_annotation(envs, types, labels, result_file,
predictive_performance_column):
_, xmax, _, _ = plt.axis()
x_annotation_position = 0.9 * xmax
for i in xrange(len(envs)):
env_type = types[i]
if env_type == 'baseline':
y = read_results_column(result_file,
predictive_performance_column)[i]
annotation = read_results_column(result_file, ENV_LABEL_COLUMN)[i]
plt.annotate(annotation,
xy=(x_annotation_position, y),
xytext=(0, 15),
textcoords='offset points',
ha='right',
va='top')
def plot_baselines(types, result_file, predictive_performance_column):
baseline_markers = ['--', '-.', '-', ':', '--', '-.', '-', ':']
baseline_color = 'k'
marker_index = 0
for i in xrange(len(types)):
env_type = types[i]
if env_type == 'baseline':
marker = baseline_markers[marker_index]
marker_index += 1
y = read_results_column(result_file,
predictive_performance_column)[i]
name = read_results_column(result_file, 1)[i]
plt.axhline(y,
color=baseline_color,
linestyle=marker,
label=r'' + name)
def generate(result_root_folder,
predictive_performance_column=ENV_ERROR_COLUMN,
plotBaseLines=True,
loss_function=None):
print "Plotting Performance"
result_filename = result_root_folder + RESULT_FILENAME
envs = read_results_column(result_filename, ENV_ID_COLUMN)
labels = read_results_column(result_filename, ENV_LABEL_COLUMN)
types = read_results_column(result_filename, ENV_TYPE_COLUMN)
_ = read_results_column(result_filename, ENV_PARAM_COLUMN)
values = read_metrics(envs, result_filename, predictive_performance_column)
#if loss_function != None:
# for index in xrange(len(envs)):
# cumError = read_cumulative_error(result_root_folder+'logs/prediction_%s.log' % (envs[index]),loss_function)
# values[index] = (values[index][0],cumError)
# matplotlib.rcParams.update({'font.size': 16})
# matplotlib.rc('xtick', labelsize=12)
# matplotlib.rc('ytick', labelsize=12)
matplotlib.rcParams.update({'axes.labelsize': 14})
plot_points(values, labels, types, markers_size)
if plotBaseLines:
plot_baselines(types, result_filename, predictive_performance_column)
# set_plot_axes(x_axis, y_axis)
#plot_baselines_annotation(envs, types, labels,result_filename,predictive_performance_column)
plt.title(title)
x_label = "Cumulative Communication"
y_label = "Cumulative Error"
plt.xlabel(x_label)
plt.ylabel(y_label)
plt.ylim(-3000, 88000)
#plt.legend(loc='upper left')
fig = plt.gcf()
fig.set_size_inches(*CHART_DIMENSIONS)
# plt.savefig(result_root_folder+'charts/performance.%s' % (FILE_FORMAT),
# format=FILE_FORMAT, dpi = CHART_DPI, bbox_inches='tight')
save_chart(result_root_folder + 'charts/performance.%s' % (FILE_FORMAT))
plt.clf()
