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Black formatting #4

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31 changes: 15 additions & 16 deletions neo/rawio/neuralynxrawio/ncssections.py
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Original file line number Diff line number Diff line change
Expand Up @@ -190,17 +190,19 @@ def _buildNcsSections(ncsMemMap, sampFreq, gapTolerance=0):
and ncsMemMap["sample_rate"][0] == ncsMemMap["sample_rate"][-1]
and ncsMemMap["timestamp"][-1] == predLastBlockStartTime
):
lastBlkEndTime = NcsSectionsFactory.calc_sample_time(sampFreq, ncsMemMap["timestamp"][-1], ncsMemMap["nb_valid"][-1])
lastBlkEndTime = NcsSectionsFactory.calc_sample_time(
sampFreq, ncsMemMap["timestamp"][-1], ncsMemMap["nb_valid"][-1]
)
n_samples = NcsSection._RECORD_SIZE * (ncsMemMap.size - 1) + ncsMemMap["nb_valid"][-1]
section0 = NcsSection(
startRec=0,
startTime=ncsMemMap["timestamp"][0],
endRec=ncsMemMap.size - 1,
endTime=lastBlkEndTime,
n_samples=n_samples
)
startRec=0,
startTime=ncsMemMap["timestamp"][0],
endRec=ncsMemMap.size - 1,
endTime=lastBlkEndTime,
n_samples=n_samples,
)
ncsSects.sects.append(section0)

else:
# need to parse all data block to detect gaps
# check when the predicted timestamp is outside the tolerance
Expand All @@ -210,19 +212,19 @@ def _buildNcsSections(ncsMemMap, sampFreq, gapTolerance=0):
gap_inds = np.flatnonzero(np.abs(delta - delta_prediction) > gapTolerance)
gap_inds += 1

sections_limits = [ 0 ] + gap_inds.tolist() + [len(ncsMemMap)]
sections_limits = [0] + gap_inds.tolist() + [len(ncsMemMap)]

for i in range(len(gap_inds) + 1):
start = sections_limits[i]
stop = sections_limits[i + 1]
duration = np.uint64(1e6 / sampFreq * ncsMemMap["nb_valid"][stop-1])
duration = np.uint64(1e6 / sampFreq * ncsMemMap["nb_valid"][stop - 1])
ncsSects.sects.append(
NcsSection(
startRec=start,
startTime=ncsMemMap["timestamp"][start],
endRec=stop-1,
endTime=ncsMemMap["timestamp"][stop-1] + duration,
n_samples=np.sum(ncsMemMap["nb_valid"][start:stop])
endRec=stop - 1,
endTime=ncsMemMap["timestamp"][stop - 1] + duration,
n_samples=np.sum(ncsMemMap["nb_valid"][start:stop]),
)
)

Expand Down Expand Up @@ -274,7 +276,6 @@ def build_for_ncs_file(ncsMemMap, nlxHdr, gapTolerance=None, strict_gap_mode=Tru
# quarter of paquet size is tolerate
gapTolerance = round(0.25 * NcsSection._RECORD_SIZE * 1e6 / freq)
ncsSects = NcsSectionsFactory._buildNcsSections(ncsMemMap, freq, gapTolerance=gapTolerance)


# take longer data block to compute reaal sampling rate
# ind_max = np.argmax([section.n_samples for section in ncsSects.sects])
Expand All @@ -292,7 +293,6 @@ def build_for_ncs_file(ncsMemMap, nlxHdr, gapTolerance=None, strict_gap_mode=Tru
ncsSects.sampFreqUsed = sampFreqUsed
ncsSects.microsPerSampUsed = NcsSectionsFactory.get_micros_per_samp_for_freq(sampFreqUsed)


elif acqType == "BML" or acqType == "ATLAS":
# BML & ATLAS style with fractional frequency and micros per samp
if strict_gap_mode:
Expand All @@ -305,7 +305,6 @@ def build_for_ncs_file(ncsMemMap, nlxHdr, gapTolerance=None, strict_gap_mode=Tru
ncsSects.sampFreqUsed = freq
ncsSects.microsPerSampUsed = NcsSectionsFactory.get_micros_per_samp_for_freq(freq)


else:
raise TypeError("Unknown Ncs file type from header.")

Expand Down
12 changes: 8 additions & 4 deletions neo/rawio/neuralynxrawio/neuralynxrawio.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,11 +87,11 @@ class NeuralynxRawIO(BaseRawIO):
Otherwise set 0 of time to first time in dataset
strict_gap_mode: bool, default: True
Detect gaps using strict mode or not.
* strict_gap_mode = True then a gap is consider when timstamp difference between two
* strict_gap_mode = True then a gap is consider when timstamp difference between two
consequtive data packet is more than one sample interval.
* strict_gap_mode = False then a gap has an increased tolerance. Some new system with different clock need this option
otherwise, too many gaps are detected

Notes
-----
* This IO supports NCS, NEV, NSE and NTT file formats (not NVT or NRD yet)
Expand Down Expand Up @@ -131,7 +131,9 @@ class NeuralynxRawIO(BaseRawIO):
("samples", "int16", (NcsSection._RECORD_SIZE)),
]

def __init__(self, dirname="", filename="", exclude_filename=None, keep_original_times=False, strict_gap_mode=True, **kargs):
def __init__(
self, dirname="", filename="", exclude_filename=None, keep_original_times=False, strict_gap_mode=True, **kargs
):

if dirname != "":
self.dirname = dirname
Expand Down Expand Up @@ -797,7 +799,9 @@ def scan_stream_ncs_files(self, ncs_filenames):

verify_sec_struct = NcsSectionsFactory._verifySectionsStructure
if not chanSectMap or (not verify_sec_struct(data, chan_ncs_sections)):
chan_ncs_sections = NcsSectionsFactory.build_for_ncs_file(data, nlxHeader, strict_gap_mode=self.strict_gap_mode)
chan_ncs_sections = NcsSectionsFactory.build_for_ncs_file(
data, nlxHeader, strict_gap_mode=self.strict_gap_mode
)

# register file section structure for all contained channels
for chan_uid in zip(nlxHeader["channel_names"], np.asarray(nlxHeader["channel_ids"], dtype=str)):
Expand Down
4 changes: 2 additions & 2 deletions neo/test/rawiotest/test_neuralynxrawio.py
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Original file line number Diff line number Diff line change
Expand Up @@ -228,7 +228,7 @@ def test_build_given_actual_frequency(self):
ncsBlocks = NcsSections()
ncsBlocks.sampFreqUsed = 1 / (35e-6)
ncsBlocks.microsPerSampUsed = 35

ncsBlocks = NcsSectionsFactory._buildNcsSections(data0, ncsBlocks.sampFreqUsed)

self.assertEqual(len(ncsBlocks.sects), 1)
Expand Down Expand Up @@ -324,7 +324,7 @@ class TestNcsSections(TestNeuralynxRawIO, unittest.TestCase):
"""
Test building NcsBlocks for files of different revisions.
"""

entities_to_test = []

def test_equality(self):
Expand Down