lines_by_metrics[metric] = dict()
datasets_present = keys_from_list_in_dict(metric_data, datasets)
if len(datasets_present) > 1:
for dataset in datasets_present:
lines_by_metrics[metric][label + '_' + dataset] = select_by_x(
extract_line_from_file(metric_data[dataset]), x_select)
else:
lines_by_metrics[metric][label] = select_by_x(
extract_line_from_file(metric_data[datasets_present[0]]),
x_select)
style = dict(
no_line=args.no_line,
error=args.error,
marker=args.marker,
)
plot_parameter_names = get_parameter_names(args.hp_names_file)
xscale = args.xscale
metric_scales = parse_metric_scales_str(args.metric_scales)
create_path(args.plot_name, file_name_is_in_path=True)
for metric, lines_for_metric in lines_by_metrics.items():
file_name = args.plot_name + '_' + metric
ylabel = plot_parameter_names[metric]
if metric in metric_scales:
yscale = metric_scales[metric]
else:
yscale = 'linear'
xlabel = args.xlabel
description = nested2string(lines_for_metric)
plot_outer_legend(
lines_for_metric,
style = dict(
no_line=args.no_line,
error=args.error,
marker=args.marker,
)
eval_dirs = parse_path_comb(args.eval_dir)
metric_scales = parse_metric_scales_str(args.metric_scales)
hp_plot_order = args.hp_order.split(',')
# abspath = os.path.abspath(__file__)
# dname = os.path.dirname(abspath)
# os.chdir(dname)
plot_parameter_names = get_parameter_names(
os.path.join(*(os.path.split(os.path.abspath(__file__))[:-1] +
(args.hp_names_file, ))))
xscale = args.xscale
for eval_dir in eval_dirs:
print(eval_dir)
plot_dir = os.path.join(*list(os.path.split(eval_dir)[:-1]) +
[args.plot_dir])
create_path(plot_dir)
if args.model == 'optimizer':
try:
plot_hp_search_optimizer(
eval_dir,
plot_dir,
hp_plot_order,
plot_parameter_names,