# Parameters configuration
config = configparser.ConfigParser()
config.read('config_file/' + config_file)
path_data = config[config_type]["path_data"]
path_model = config[config_type]["path_model"]
name_model = config[config_type]["name_model"]
tracks = config[config_type]["tracks"].split(' ')
list_features_final = config[config_type]["list_features"].split(' ')
flag_save = int(config[config_type]["flag_save"])
ratio_split = list(
map(int, config[config_type]["ratio_split_sets"].split(' ')))
nbr_cross_val = int(config[config_type]["nbr_cross_validation"])
print('Loading data...')
data_win, real_labels, list_states, list_features = tools.load_data_from_dump(
path_data)
num_track = 0
name_track = tracks[num_track]
num_track = taxonomy.index(name_track)
# Loop on all the tracks from the taxonomy
# for num_track, name_track in enumerate(tracks):
# print(name_track)
F1_score = []
for n_iter in range(nbr_cross_val):
data_train, labels_train, data_test, labels_test, id_train, id_test = tools.split_data_base(
data_win, real_labels[num_track], ratio_split)
nbr_component = 15
print('Loading data...')
data_win2 = []
real_labels = [[], [], [], []]
list_states = [[], [], [], []]
tracks = [
'general_posture', 'detailed_posture', 'details', 'current_action'
]
path_annotation = '/home/amalaise/Documents/These/experiments/ANDY_DATASET/AndyData-lab-onePerson/annotations/labels_csv2/'
data_win2, real_labels, list_states, list_features = tools.load_data_from_dump(
'score/')
if (local_features):
list_reduce_features = tools.list_features_local(list_features)
for data in data_win2:
df_data = pd.DataFrame(data, columns=list_features)
data = df_data[list_reduce_features].values
# for participant, nbr in zip(list_participant, range(len(list_participant))):
# path_data = path_data_root + participant
# print('Loading: ' + participant)
# list_files = os.listdir(path_data)[0:3]
# list_files.sort()
# for file in list_files:
# name_seq = os.path.splitext(file)[0]