def print_stats(g,name='',prefix=''):
'''
computes, prints, and returns
mode
mean
median
'''
mode = modefind.modefind(g,0)
mn = np.mean(g)
md = np.median(g)
print(prefix,'mode %s\t%0.4f'%(name,mode))
print(prefix,'mean %s\t%0.4f'%(name,mn))
print(prefix,'median %s\t%0.4f'%(name,md))
return mode,mn,md
def get_isi_stats(spikes,epoch,FS=1000,BURST_CUTOFF_MS=10,MIN_NISI=100):
'''
Computes a statistical summary of an ISI distribution.
Accepts a list of lists of spike times
return burstiness, ISI_cv, mean_rate, KS, mode, burst_free_ISI_cv, burst_free_mean_rate, burst_free_mode
'''
event,start,stop = epoch
duration = (stop-start)/float(FS)
ISI_events = list(flatten(map(diff,spikes)))
allisi = np.array(ISI_events)
if len(ISI_events)<MIN_NISI: return None
mode = FS/modefind(allisi)
mean_rate = (sum(map(len,spikes))) / float(len(spikes)) / duration
ISI_cv = np.std(allisi)/np.mean(allisi)
KS = poisson_KS(allisi)
burstiness = sum(allisi<BURST_CUTOFF_MS)/float(len(allisi))*100
burst_free_spikes = remove_bursts(spikes, duration=BURST_CUTOFF_MS)
burst_free_ISI_events = list(flatten(map(diff,burst_free_spikes)))
burst_free_allisi = np.array(burst_free_ISI_events)
burst_free_mode = FS/modefind(burst_free_allisi)
burst_free_mean_rate = (sum(map(len,burst_free_spikes))) / float(len(burst_free_spikes)) / duration
burst_free_ISI_cv = np.std(burst_free_allisi)/np.mean(burst_free_allisi)
return burstiness, ISI_cv, mean_rate, KS, mode, burst_free_ISI_cv, burst_free_mean_rate, burst_free_mode
