"""Dump the population spike histogram values."""

with open('{}_psth_{}_{}ms_window_{}ms_bins.csv'.format(outprefix, celltype, window*1e3, binwidth*1e3), 'wb') as fd:

writer = csv.writer(fd, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)

dbcnt_flist = get_dbcnt_dict(ffname)

bins = np.arange(-window / 2.0, window / 2.0 + 0.5 * binwidth, binwidth)

writer.writerow(['dbcount', 'filename'] + list(np.asarray(np.round(bins[1:]*1e3), dtype=int)))

for dbcnt, flist in dbcnt_flist.items():

for fname in flist:

data = TraubData(makepath(fname))

pop_train_list = []

bgtimes, probetimes = get_stim_times(data, correct_tcr=True)

if (len(bgtimes) == 0) and (len(probetimes) == 0):

print 'EE: {} has no TCR spiking on stimulus.'.format(fname)

continue

stim_times = np.concatenate((bgtimes, probetimes))

stim_times.sort()

# print '###', stim_times

for cell, train in data.spikes.items():

if cell.startswith(celltype):

pop_train_list.append(train)

pop_train = np.concatenate(pop_train_list)

pop_train.sort()

bgpsth, b = psth(pop_train, stim_times, window=window, bins=bins)

bgpsth /= (data.cellcounts._asdict()[celltype] * binwidth)