def getLFPData(probeBase, syncDataset, num_channels=384):
probeTTLDir = os.path.join(probeBase, r'events\\Neuropix-PXI-100.0\\TTL_1')
lfp_data_dir = os.path.join(probeBase, r'continuous\\Neuropix-PXI-100.1')
lfp_data_file = os.path.join(lfp_data_dir, 'continuous.dat')
if not os.path.exists(lfp_data_file):
print('Could not find LFP data at ' + lfp_data_file)
return None, None
lfp_data = np.memmap(lfp_data_file, dtype='int16', mode='r')
lfp_data_reshape = np.reshape(lfp_data,
[int(lfp_data.size / num_channels), -1])
time_stamps = np.load(os.path.join(lfp_data_dir, 'lfp_timestamps.npy'))
bRising, bFalling = get_sync_line_data(syncDataset, channel=0)
bs_t, bs = ecephys.extract_barcodes_from_times(bRising, bFalling)
channel_states = np.load(os.path.join(probeTTLDir, 'channel_states.npy'))
event_times = np.load(os.path.join(probeTTLDir, 'event_timestamps.npy'))
beRising = event_times[channel_states > 0] / 30000.
beFalling = event_times[channel_states < 0] / 30000.
be_t, be = ecephys.extract_barcodes_from_times(beRising, beFalling)
#Compute time shift between ephys and sync
shift, p_sampleRate, m_endpoints = ecephys.get_probe_time_offset(
bs_t, bs, be_t, be, 0, 30000)
time_stamps_shifted = (time_stamps / p_sampleRate) - shift
return lfp_data_reshape, time_stamps_shifted
def plot_barcode_interval_hist(probe_dirs,
syncDataset,
FIG_SAVE_DIR,
prefix=''):
for ip, probe in enumerate(probe_dirs):
p_name = probe.split('_')[-2][-1]
base = os.path.join(probe, r'events\\Neuropix-PXI-100.0\\TTL_1')
channel_states_file = glob_file(base, 'channel_states.npy')
event_times_file = glob_file(base, 'event_timestamps.npy')
if channel_states_file and event_times_file:
#get barcode intervals from probe events file
channel_states = np.load(channel_states_file)
event_times = np.load(event_times_file)
beRising = event_times[channel_states > 0] / 30000.
beFalling = event_times[channel_states < 0] / 30000.
be_t, be = ecephys.extract_barcodes_from_times(beRising, beFalling)
barcode_intervals = np.diff(be_t)
#get intervals from sync file for comparison
bRising, bFalling = get_sync_line_data(syncDataset, channel=0)
bs_t, bs = ecephys.extract_barcodes_from_times(bRising, bFalling)
sync_barcode_intervals = np.diff(bs_t)
fig, ax = plt.subplots(1, 2)
fig.set_size_inches([8, 4])
bins = np.arange(
np.min([barcode_intervals.min(),
sync_barcode_intervals.min()]) - 1,
np.max([barcode_intervals.max(),
sync_barcode_intervals.max()]) + 1)
ax[0].hist(barcode_intervals, bins)
ax[1].hist(sync_barcode_intervals, bins)
ax[0].axhline(len(be_t) - 1)
ax[1].axhline(len(bs_t) - 1)
ax[0].set_ylim([0.1, len(be_t)])
ax[1].set_ylim([0.1, len(bs_t)])
[a.set_yscale('log') for a in ax]
ax[0].set_title('Probe {} ephys barcode intervals'.format(p_name))
ax[1].set_title('Probe {} sync barcode intervals'.format(p_name))
save_figure(
fig,
os.path.join(
FIG_SAVE_DIR, prefix +
'Probe_{}_barcode_interval_hist.png'.format(p_name)))
def get_ephys_barcodes(probeBase):
probeTTLDir = os.path.join(probeBase, r'events\\Neuropix-PXI-100.0\\TTL_1')
channel_states = np.load(os.path.join(probeTTLDir, 'channel_states.npy'))
event_times = np.load(os.path.join(probeTTLDir, 'event_timestamps.npy'))
beRising = event_times[channel_states > 0] / 30000.
beFalling = event_times[channel_states < 0] / 30000.
be_t, be = ecephys.extract_barcodes_from_times(beRising, beFalling)
return be_t, be
def get_sync_barcodes(sync_dataset, fallback_line=0):
lines = sync_dataset.line_labels
#look for barcodes in labels
bline = fallback_line
for line in lines:
if 'barcode' in line:
bline = line
bRising = sync_dataset.get_rising_edges(bline, units='seconds')
bFalling = sync_dataset.get_falling_edges(bline, units='seconds')
bs_t, bs = ecephys.extract_barcodes_from_times(bRising, bFalling)
return bs_t, bs
def getLFPData(dataDir,
pid,
syncDataset,
probePXIDict,
probeGen='3b',
num_channels=384):
if '3a' in probeGen:
lfp_data_dir = glob.glob(
os.path.join(dataDir, '*probe' + pid + '_sorted', 'continuous',
'Neuropix-3a-100.1'))[0]
events_dir = glob.glob(
os.path.join(dataDir, '*probe' + pid + '_sorted', 'events',
'Neuropix-3a-100.0', 'TTL_1'))[0]
elif '3b' in probeGen:
probeDirName = 'Neuropix-PXI-' + probePXIDict[pid]
lfp_data_dir = os.path.join(dataDir, probeDirName + '-LFP')
events_dir = os.path.join(dataDir, 'events', probeDirName, 'TTL_1')
elif probeGen == 'pipeline':
baseString = os.path.basename(dataDir)
probeBase = os.path.join(dataDir,
baseString + '_probe' + pid + '_sorted')
lfp_data_dir = os.path.join(probeBase,
r'continuous\\\Neuropix-PXI-100.1')
events_dir = os.path.join(probeBase,
r'events\\Neuropix-PXI-100.0\\TTL_1')
lfp_data_file = os.path.join(lfp_data_dir, 'continuous.dat')
if not os.path.exists(lfp_data_file):
print('Could not find LFP data at ' + lfp_data_file)
return None, None
lfp_data = np.memmap(lfp_data_file, dtype='int16', mode='r')
lfp_data_reshape = np.reshape(lfp_data,
[int(lfp_data.size / num_channels), -1])
time_stamps = np.load(os.path.join(lfp_data_dir, 'lfp_timestamps.npy'))
#Get barcodes from sync file
if 'barcode' in syncDataset.line_labels:
bRising, bFalling = get_sync_line_data(syncDataset, 'barcode')
elif 'barcodes' in syncDataset.line_labels:
bRising, bFalling = get_sync_line_data(syncDataset, 'barcodes')
bs_t, bs = ecephys.extract_barcodes_from_times(bRising, bFalling)
#Get barcodes from ephys data
if '03122019' in dataDir and 'slot3' in events_dir:
#files on slot3 for this day saved extra bytes at beginning, must skip them to get the right time stamps
channel_states = np.load(
r"Z:\03122019_416656\events\Neuropix-PXI-slot2-probe1\TTL_1\channel_states.npy"
)
event_times_file = open(
os.path.join(events_dir, 'event_timestamps.npy'), 'rb')
event_times_file.seek(8 * 22 + 1)
event_times = np.fromfile(event_times_file,
dtype='<u8')[:channel_states.size]
lfp_data_reshape = lfp_data_reshape[:time_stamps.size]
elif '06122019' in dataDir:
good_channel_states = np.load(
r"Z:\06122019_423745\events\Neuropix-PXI-slot3-probe1\TTL_1\channel_states.npy"
)
good_event_times = np.load(
r"Z:\06122019_423745\events\Neuropix-PXI-slot3-probe1\TTL_1\event_timestamps.npy"
)
channel_states = np.load(os.path.join(
events_dir, 'channel_states.npy'))[:good_channel_states.size]
event_times = np.load(os.path.join(
events_dir, 'event_timestamps.npy'))[:good_event_times.size]
else:
channel_states = np.load(os.path.join(events_dir,
'channel_states.npy'))
event_times = np.load(os.path.join(events_dir, 'event_timestamps.npy'))
beRising = event_times[channel_states > 0] / 30000.
beFalling = event_times[channel_states < 0] / 30000.
be_t, be = ecephys.extract_barcodes_from_times(beRising, beFalling)
if '03212019' in dataDir:
be_t = be_t[5:]
be = be[5:]
#Compute time shift between ephys and sync
shift, p_sampleRate, m_endpoints = ecephys.get_probe_time_offset(
bs_t, bs, be_t, be, 0, 30000)
if '03212019' in dataDir:
shift = -3.6950408520530686
time_stamps_shifted = (time_stamps / p_sampleRate) - shift
return lfp_data_reshape, time_stamps_shifted
def getUnitData(dataDir, syncDataset, probeID, probePXIDict, probeGen='3b'):
if probeGen == '3a':
probeDir = glob.glob(
os.path.join(dataDir, '*Probe' + probeID + '_sorted'))[0]
probeTTLDir = os.path.join(probeDir,
'events\\Neuropix-3a-100.0\\TTL_1')
probeSpikeDir = os.path.join(probeDir, 'continuous\\Neuropix-3a-100.0')
elif probeGen == '3b':
eventsDir = os.path.join(dataDir, 'events')
probeTTLDir = os.path.join(
os.path.join(eventsDir, 'Neuropix-PXI-' + probePXIDict[probeID]),
'TTL_1')
probeSpikeDir = os.path.join(
dataDir,
'Neuropix-PXI-' + probePXIDict[probeID] + '-AP_sortingResults')
elif probeGen == 'pipeline':
baseString = os.path.basename(dataDir)
probeBase = os.path.join(dataDir,
baseString + '_probe' + probeID + '_sorted')
probeTTLDir = os.path.join(probeBase,
r'events\\Neuropix-PXI-100.0\\TTL_1')
probeSpikeDir = os.path.join(probeBase,
r'continuous\\Neuropix-PXI-100.0')
print(probeTTLDir)
print(probeSpikeDir)
#Get barcodes from sync file
if 'barcode' in syncDataset.line_labels:
bRising, bFalling = get_sync_line_data(syncDataset, 'barcode')
elif 'barcodes' in syncDataset.line_labels:
bRising, bFalling = get_sync_line_data(syncDataset, 'barcodes')
bs_t, bs = ecephys.extract_barcodes_from_times(bRising, bFalling)
#Get barcodes from ephys data
if '03122019' in dataDir and 'slot3' in probeTTLDir:
#files on slot3 for this day saved extra bytes at beginning, must skip them to get the right time stamps
channel_states = np.load(
r"Z:\03122019_416656\events\Neuropix-PXI-slot2-probe1\TTL_1\channel_states.npy"
)
event_times_file = open(
os.path.join(probeTTLDir, 'event_timestamps.npy'), 'rb')
event_times_file.seek(8 * 22 + 1)
event_times = np.fromfile(event_times_file,
dtype='<u8')[:channel_states.size]
elif '06122019' in dataDir:
good_channel_states = np.load(
r"Z:\06122019_423745\events\Neuropix-PXI-slot3-probe1\TTL_1\channel_states.npy"
)
good_event_times = np.load(
r"Z:\06122019_423745\events\Neuropix-PXI-slot3-probe1\TTL_1\event_timestamps.npy"
)
channel_states = np.load(
os.path.join(probeTTLDir,
'channel_states.npy'))[:good_channel_states.size]
event_times = np.load(os.path.join(
probeTTLDir, 'event_timestamps.npy'))[:good_event_times.size]
else:
channel_states = np.load(
os.path.join(probeTTLDir, 'channel_states.npy'))
event_times = np.load(os.path.join(probeTTLDir,
'event_timestamps.npy'))
beRising = event_times[channel_states > 0] / 30000.
beFalling = event_times[channel_states < 0] / 30000.
be_t, be = ecephys.extract_barcodes_from_times(beRising, beFalling)
if '03212019' in dataDir:
be_t = be_t[5:]
be = be[5:]
#Compute time shift between ephys and sync
shift, p_sampleRate, m_endpoints = ecephys.get_probe_time_offset(
bs_t, bs, be_t, be, 0, 30000)
if '03212019' in dataDir:
shift = -3.6950408520530686
#be_t_shifted = (be_t/(p_sampleRate/30000)) - shift #just to check that the shift and scale are right
#Get unit spike times
units = load_spike_info(probeSpikeDir, p_sampleRate, shift)
return units
ax.set_ylabel('uV')
if i == len(channelsToPlot) - 1:
ax.set_xlabel('Sample')
ax.set_title('ch ' + str(ch))
plt.tight_layout()
# sync data
syncDataset = sync.Dataset(syncFile)
probeEventsDir = os.path.join(
os.path.join(probeDataDir, 'events',
'Neuropix-PXI-' + pxiDict[probeLabel]), 'TTL_1')
# get barcodes from sync file
bRising, bFalling = get_sync_line_data(syncDataset, 'barcode')
bs_t, bs = ecephys.extract_barcodes_from_times(bRising, bFalling)
# get barcodes from ephys data
channel_states = np.load(os.path.join(probeEventsDir, 'channel_states.npy'))
event_times = np.load(os.path.join(probeEventsDir, 'event_timestamps.npy'))
beRising = event_times[channel_states > 0] / 30000.
beFalling = event_times[channel_states < 0] / 30000.
be_t, be = ecephys.extract_barcodes_from_times(beRising, beFalling)
# compute time shift between ephys and sync
probeShift, probeSampleRate, m_endpoints = ecephys.get_probe_time_offset(
bs_t, bs, be_t, be, 0, 30000)
# unit data
kilosortData = {
