# initialize variables
data = None
tracer = None
cls_pred = None
cls_true = None
directory = None
#----------------------------------------
# Loading section
# load argv
if len(argv) != 3:
print("Error!\nUsage: test_tracer.py [directory] [keyword]")
exit()
directory = argv[1]
keyword = argv[2]
# load tracer
failure, data, tracer = load_lib.load_arrangement(keyword, directory)
if not failure:
print("load data and tracer success")
# load cls_pred
failure, cls_pred = load_lib.load_cls_pred(keyword, directory)
if not failure:
print("load cls_pred success")
# load cls_true
failure, cls_true = load_lib.load_cls_true(keyword, directory)
if not failure:
print("load cls_true success")
failure, coords = load_lib.load_coords(keyword, directory)
if not failure:
print("load coords success")
#----------------------------------------
# test if the loading is successful or not
print(
"Error!\nUsage: plot_sed.py [main_name] [ no-observation value ] [true label] [pred label]"
)
print("Example: plot_loss_freq.py MaxLoss15 '0.0' 1 2")
exit()
main_name = argv[1]
no_obs = float(argv[2])
true_label = int(argv[3])
pred_label = int(argv[4])
#----------------------------------------
data_list = glob("AI*test_on*")
for directory in data_list:
print("#################################")
print("start to loading data saved in {0}".format(directory))
# load tracer
failure, data, tracer = load_lib.load_arrangement(main_name, directory)
if not failure:
print("load data and tracer success")
# load cls_pred
failure, cls_pred = load_lib.load_cls_pred(main_name, directory)
if not failure:
print("load cls_pred success")
# load cls_true
failure, cls_true = load_lib.load_cls_true(main_name, directory)
if not failure:
print("load cls_true success")
# confusion matrix
print("### confusion matrix ###")
failure, cm = load_lib.confusion_matrix(cls_true, cls_pred)
if not failure:
print("confusion matrix success")