CHUNK_TYPE = 'Fixed Time' # 'Fixed beats number'
if CHUNK_TYPE == 'Fixed Time':
CHUNK_TIME_INTERVAL = 5.0 # minutes
MIN_NUMBER_OF_BEATS_IN_CHUNK = 10 # beats
elif CHUNK_TYPE == 'Fixed beats number':
NUMBER_OF_BEATS_IN_CHUNK = 1000
TEST_PARTITION = 'random' # method for train / test separation
TEST_PORTION = 0.3
###############################################################
# Initial configuration
np.random.seed(SEED)
logg.configure_logging() # For more details use logg.configure_logging(console_level=logging.DEBUG)
stat_info = { 'mortality': dl.read_dta('mortality_SAHR_ver101214', data_folder=conf.path_to_dta),
'selected_pp': dl.read_dta('selected_pp', data_folder=conf.path_to_dta),
'sleep': dl.get_sleep_time(conf.path_to_dta),
'selected': pd.read_csv(conf.path_to_dta+'selected.csv')
}
#print stat_info['selected'] #!!!
#zxc
#################################################################
# Specify patients GIDNS for study
if FIXED_GIDNS_LIST is not None:
logging.warning('Only %s patients are used in this study: %s'%(len(FIXED_GIDNS_LIST), FIXED_GIDNS_LIST))
asked_GIDNS = FIXED_GIDNS_LIST
trainX = h5f['trainX'][:]
trainY = h5f['trainY'][:]
testX = h5f['testX'][:]
testY = h5f['testY'][:]
h5f.close()
picke_filename = conf.path_to_sample+sample_name+'.pkl'
with open(picke_filename, 'rb') as f:
sample_info = pickle.load(f)
sample_info['path'] = hdf5_filename
return trainX, trainY, testX, testY, sample_info
if __name__ == '__main__':
logg.configure_logging(console_level=logging.DEBUG)
mortality = read_dta('mortality_SAHR_ver101214', data_folder=conf.path_to_dta)
selected_pp = read_dta('selected_pp', data_folder=conf.path_to_dta)
GIDNS = get_GIDNS(path_to_dta=conf.path_to_dta)
print GIDNS
print len(GIDNS), 'patients'
GIDN = GIDNS[0]
data_RR = load_RR_data(GIDN, path=conf.path_to_RR)
print '\ndata_RR:\n', data_RR, '\n'
data_RR = load_RR_data(GIDN=1234567890, path=conf.path_to_RR)
print 'data_RR:', data_RR
def load_hdf5_sample(sample_name):
hdf5_filename = conf.path_to_sample+sample_name+'.h5'
h5f = h5py.File(hdf5_filename,'r')
trainX = h5f['trainX'][:]
trainY = h5f['trainY'][:]
testX = h5f['testX'][:]
testY = h5f['testY'][:]
sample_info = {'path': hdf5_filename}
return trainX, trainY, testX, testY, sample_info
if __name__ == '__main__':
logg.configure_logging(console_level=logging.DEBUG)
mortality = read_dta('mortality_SAHR_ver101214', data_folder=conf.path_to_dta)
selected_pp = read_dta('selected_pp', data_folder=conf.path_to_dta)
GIDNS = get_GIDNS(path_to_dta=conf.path_to_dta)
print GIDNS
print len(GIDNS), 'patients'
GIDN = GIDNS[0]
data_RR = load_RR_data(GIDN, path=conf.path_to_RR)
print '\ndata_RR:\n', data_RR, '\n'
data_RR = load_RR_data(GIDN=1234567890, path=conf.path_to_RR)
print 'data_RR:', data_RR
CHUNK_TYPE = 'Fixed Time' # 'Fixed beats number'
if CHUNK_TYPE == 'Fixed Time':
CHUNK_TIME_INTERVAL = 5.0 # minutes
MIN_NUMBER_OF_BEATS_IN_CHUNK = 10 # beats
elif CHUNK_TYPE == 'Fixed beats number':
NUMBER_OF_BEATS_IN_CHUNK = 1000
TEST_PARTITION = 'random' # method for train / test separation
TEST_PORTION = 0.3
###############################################################
# Initial configuration
np.random.seed(SEED)
logg.configure_logging(
) # For more details use logg.configure_logging(console_level=logging.DEBUG)
stat_info = {
'mortality':
dl.read_dta('mortality_SAHR_ver101214', data_folder=conf.path_to_dta),
'selected_pp':
dl.read_dta('selected_pp', data_folder=conf.path_to_dta),
'sleep':
dl.read_dta('sleep', data_folder=conf.path_to_dta)
}
#################################################################
# Specify patients GIDNS for study
if FIXED_GIDNS_LIST is not None:
logging.warning('Only %s patients are used in this study: %s' %
