def test_dataio_with_neo():
if os.path.exists('datatest_neo/data.h5'):
os.remove('datatest_neo/data.h5')
dataio = DataIO(dirname = 'datatest_neo')
import neo
import quantities as pq
filenames = ['Tem06c06.IOT', 'Tem06c07.IOT', 'Tem06c08.IOT', ]
for filename in filenames:
blocks = neo.RawBinarySignalIO(filename).read(sampling_rate = 10.*pq.kHz,
t_start = 0. *pq.S, unit = pq.V, nbchannel = 16, bytesoffset = 0,
dtype = 'int16', rangemin = -10, rangemax = 10)
channel_indexes = np.arange(14)
dataio.append_signals_from_neo(blocks, channel_indexes = channel_indexes, signal_type = 'unfiltered')
print(dataio.summary(level=1))
def test_dataio():
if os.path.exists('datatest/data.h5'):
os.remove('datatest/data.h5')
dataio = DataIO(dirname = 'datatest')
#~ print(data)
#data from locust
sigs_by_trials, sampling_rate, ch_names = download_locust(trial_names = ['trial_01', 'trial_02', 'trial_03'])
for seg_num in range(3):
sigs = sigs_by_trials[seg_num]
dataio.append_signals_from_numpy(sigs, seg_num = seg_num,t_start = 0.+5*seg_num, sampling_rate = sampling_rate,
signal_type = 'filtered', channels = ch_names)
#~ print(data)
#~ print(data.segments)
#~ print(data.store)
print(dataio.summary(level=0))
print(dataio.summary(level=1))
