train_character_list[i]._perimeter_path = ms.walk_around_ccw(train_character._data_bw)
train_character._xseries = ms.convert_path_to_xseries(train_character._perimeter_path)
train_character._yseries = ms.convert_path_to_yseries(train_character._perimeter_path)
for i in range(test_character_list.shape[0]):
test_character = test_character_list[i]
test_character._perimeter_path = ms.walk_around_ccw(test_character._data_bw)
test_character._xseries = ms.convert_path_to_xseries(test_character._perimeter_path)
test_character._yseries = ms.convert_path_to_yseries(test_character._perimeter_path)
chf.dtw_classify_character(test_character, train_character_list)
if(test_character._classification == test_character._predicted_classification):
correct_list[int(test_character._classification)] = correct_list[int(test_character_list[i]._classification)] + 1
total_list[int(test_character._classification)] = total_list[int(test_character._classification)] + 1
for i in range(0, 10):
print('i = ' + str(i) + ': ' + str(correct_list[i]) + '/' + str(total_list[i]))
