code stringlengths 3 6.57k |
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np.asarray(good) |
set_good(self, good) |
list(self.neurons) |
np.all([ nid in nids for nid in good ]) |
np.setdiff1d(nids, good) |
property(get_good, set_good) |
get_stream(self) |
set_stream(self, stream=None) |
type(stream) |
type(oldstream) |
type(oldstream) |
type(stream) |
type(stream.probe) |
type(oldstream.probe) |
type(oldstream.probe) |
type(stream.probe) |
if (stream.fname not in oldstream.fname) |
and (oldstream.fname not in stream.fname) |
print('Bound stream %r to sort %r' % (stream.fname, self.fname) |
self.calc_twts_twi() |
property(get_stream, set_stream) |
calc_twts_twi(self) |
np.arange(tw[0], tw[1], tres) |
intround(twts[0] / tres) |
intround(twts[-1] / tres) |
info('twi = %s' % (self.twi,) |
update_tw(self, tw) |
SpykeWindow.update_spiketw() |
self.calc_twts_twi() |
np.asarray(tw) |
np.asarray(oldtw) |
intround(dtw[0] / self.tres) |
self.neurons.values() |
neuron.update_wave() |
print('WARNING: all spike waveforms need to be reloaded!') |
get_tres(self) |
property(get_tres) |
__getstate__(self) |
self.__dict__.copy() |
are (potentially) |
get_nspikes(self) |
len(self.spikes) |
property(get_nspikes) |
update_usids(self) |
np.where(nids == 0) |
get_spikes_sortedby(self, attr='id') |
vals.argsort() |
get_wave(self, sid) |
np.arange(t0, t1, self.tres) |
WaveForm(data=wavedata, ts=ts, chans=chans, tres=self.tres) |
get_maxchan_wavedata(self, sid=None, nid=None) |
np.where(neuron.chans == neuron.chan) |
len(chani) |
get_mean_wave(self, sids, nid=None) |
len(sids) |
get_mean_wave() |
print(s) |
len(sids) |
zip(chanss, nchanss) |
np.concatenate(chanslist) |
np.unique(chanpopulation) |
len(groupchans) |
np.zeros((maxnchans, nt) |
np.zeros((maxnchans, 1) |
zip(chanslist, wavedata) |
groupchans.searchsorted(chans) |
len(chans) |
time.time() |
np.zeros((maxnchans, nt) |
zip(chanslist, wavedata) |
groupchans.searchsorted(chans) |
len(chans) |
np.sqrt(var) |
list(groupchans) |
np.histogram(chanpopulation, bins=bins) |
groupchans.searchsorted(chans) |
WaveForm(data=data, std=std, chans=chans) |
check_ISIs(self, nids='good') |
print('Checking inter-spike intervals') |
sorted(self.neurons) |
spikets.sort() |
np.diff(spikets) |
sum() |
spikes (given DEFMINISI=%d us) |
RuntimeError(msg) |
check_wavealign(self, nids='good', maxdti=1) |
print('Checking neuron mean waveform alignment') |
sorted(self.neurons) |
self.get_maxchan_wavedata(nid=nid) |
len(wd) |
scipy.signal.find_peaks(wd) |
scipy.signal.find_peaks(-wd) |
argmax() |
argmin() |
abs(nmax) |
print("n%d: dti=%d" % (nid, dti) |
abs(dti) |
self.converter.AD2uV(wd[peak1i]) |
intround(self.tres*(peak1i-alignti) |
peak (%+d uV @ t=%d us) |
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