# merge all dataframes df_joined = df_actigraph_acc.join(df_true_non_wear_time, how='outer').join(df_actiwave_acc, how='outer').join(df_hecht_3_non_wear_time, how='outer') \ .join(df_troiano_non_wear_time, how='outer').join(df_choi_non_wear_time, how='outer').join(df_hees_non_wear_time, how='outer').join(df_epoch_60_vmu, how='outer').join(df_actiwave_hr, how='outer') # call plot function plot_non_wear_algorithms(data = df_joined, subject = subject, plot_folder = plot_folder) if __name__ == "__main__": # start timer and memory counter tic, process, logging = set_start() # 1) batch process Hecht 2009 non-wear method batch_process_non_wear_algorithm(algorithm = process_hecht_2009_triaxial) # # 2) batch process Troiano 2007 non-wear method # batch_process_non_wear_algorithm(algorithm = process_troiano_2007) # # 3) batch process Choi 2011 non-wear method # batch_process_non_wear_algorithm(algorithm = process_choi_2011) # # 4) batch process Hees 2013 non-wear method # batch_process_non_wear_algorithm(algorithm = process_hees_2013) # 5) batch process the plotting of the non-wear algorithms including true non-wear time # batch_process_plot_non_wear_algorithms() # print time and memory set_end(tic, process)
def process_gt3x_file(f,
i=1,
total=1,
hdf5_save_location=HDF5_SAVE,
delete_zip_folder=True):
"""
Process .gt3x file
- unzip into log.bin and info.txt
- extract information from info.txt
- extract information from log.bin
- save data to hdf5 file
Parameters
----------
f : string
file location of the .gt3x file
i : int (optional)
index of file to be processed, is used to display a counter of the process. Default = 1. For example, processing 12/20
total : int (optional)
total number of files to be processed, is used to display a counter of the process. Default = 1. For example, processing 12/20
hdf5_save_location : os.path
folder location where to save the extracted acceleration data to.
"""
logging.debug('Processing GTX3 binary file: {} {}/{}'.format(
f, i + 1, total))
# unzip the raw .gt3x file: this will provide a log.bin and info.txt file
# the save_location is a new folder with the same name as the .gt3x file
log_bin, info_txt = unzip_gt3x_file(f, save_location=f.split('.')[0])
# check if unzipping went ok
if log_bin is not None:
# print verbose
logging.debug('log.bin location: {}'.format(log_bin))
logging.debug('info.txt location: {}'.format(info_txt))
# get info data from info file
info_data = extract_info(info_txt)
# check if subject name could be read from the binary file
if info_data['Subject_Name'] is not "":
# check if subject ID already processed
if info_data['Subject_Name'] not in get_all_subjects_hdf5(
hdf5_file=HDF5_SAVE):
# retrieve log_data; i.e. accellerometer data and log_time; timestamps of acceleration data
log_data, log_time = extract_log(
log_bin,
acceleration_scale=float(info_data['Acceleration_Scale']),
sample_rate=int(info_data['Sample_Rate']))
# check if log data is not None (with None something went wrong during reading of the binary file)
if log_data is not None:
# save log_data to HDF5 file
save_data_to_group_hdf5(group=info_data['Subject_Name'],
data=log_data,
data_name='log',
meta_data=info_data,
overwrite=True,
hdf5_file=hdf5_save_location)
# save log_time data to HDF file
save_data_to_group_hdf5(group=info_data['Subject_Name'],
data=log_time,
data_name='time',
meta_data=info_data,
overwrite=True,
hdf5_file=hdf5_save_location)
else:
logging.error(
'Unable to convert .gt3x file: {} (subject {})'.format(
f, info_data['Subject_Name']))
else:
logging.info(
'Subject name already defined as group in HDF5 file: {}, skipping..'
.format(info_data['Subject_Name']))
else:
logging.error(
"Unable to read subject from info.txt file, skipping file: {}".
format(f))
else:
logging.error("Error unzipping file: {}".format(f))
# delete the created zip folder
if delete_zip_folder:
delete_directory(f.split('.')[0])
# print time and memory
set_end(tic, process)
