def do_unit_ISI_plot(session, area, unit,
INFOXPOS = 70, LABELSIZE=8, NBINS=20, FMAX = 250):
cla()
spikes = []
for trial in get_good_trials(session):
spikes.append(cgid.spikes.get_spikes_event(
session,area,unit,trial,6,-1000,0))
spikes.append(cgid.spikes.get_spikes_event(
session,area,unit,trial,8,-1000,0))
ISI_events = array(list(flatten(map(diff,spikes))))
SNR = get_unit_SNR(session,area,unit)
histc,edges = histogram(ISI_events, bins = linspace(0,FMAX,NBINS+1))
dx = diff(edges)[0]
bar(edges[:-1]+dx*0.1,histc,width=dx*0.8,color=GATHER[-1],edgecolor=(0,)*4)
allisi = array(ISI_events)
K = 20
x,y = kdepeak(log(K+allisi[allisi>0]))
x = exp(x)-K
y = y/(K+x)
y = y*len(allisi)*dx
plot(x,y,color=RUST,lw=1.5)
mean_rate = sum(map(len,spikes))/float(len(get_good_trials(session))*2)
ISI_cv = std(allisi)/mean(allisi)
burstiness = sum(allisi<5)/float(len(allisi))*100
ll = 1./mean(allisi)
expected_short_isi = (1.0-exp(-ll*10))*100
mode = modefind(allisi)
residual_burstiness = burstiness-expected_short_isi
LH = LABELSIZE+4
text(INFOXPOS,ylim()[1]-pixels_to_yunits(20 ),'Mean rate = %d Hz'%mean_rate,
horizontalalignment='left',
verticalalignment ='bottom',fontsize=LABELSIZE)
text(INFOXPOS,ylim()[1]-pixels_to_yunits(20+LH*1),'ISI CV = %0.2f'%ISI_cv,
horizontalalignment='left',
verticalalignment ='bottom',fontsize=LABELSIZE)
text(INFOXPOS,ylim()[1]-pixels_to_yunits(20+LH*2),'SNR = %0.1f'%SNR,
horizontalalignment='left',
verticalalignment ='bottom',fontsize=LABELSIZE)
text(INFOXPOS,ylim()[1]-pixels_to_yunits(20+LH*3),'Mode freq. = %0.1f'%mode,
horizontalalignment='left',
verticalalignment ='bottom',fontsize=LABELSIZE)
axvline(mode,lw=2,color=TURQUOISE)
xlabel('ms',fontsize=LABELSIZE)
ylabel('No. Events',fontsize=LABELSIZE)
fudgey(10)
fudgex(5)
xlim(0,FMAX)
nicex()
nicey()
title('Monkey %s area %s\nsession %s unit %s'%(session[0],area,session[-2:],unit),loc='center',fontsize=7)
return mean_rate,ISI_cv,SNR,mode
def unit_ISI_plot(session,area,unit,epoch=((6,-1000,0),(8,-1000,0)),INFOXPOS=70,LABELSIZE=8,NBINS=20,TMAX=300,INFOYSTART=0,BURST=10):
cla()
spikes = []
for trial in get_good_trials(session):
try:
e,a,b = epoch
spikes.append(cgid.spikes.get_spikes_event(session,area,unit,trial,e,a,b))
except:
for e,a,b in epoch:
spikes.append(cgid.spikes.get_spikes_event(session,area,unit,trial,e,a,b))
ISI_events = array(list(flatten(map(diff,spikes))))
SNR = cgid.spikes.get_unit_SNR(session,area,unit)
histc,edges = histogram(ISI_events, bins = linspace(0,TMAX,NBINS+1))
dx = diff(edges)[0]
bar(edges[:-1]+dx*0.1,histc,width=dx*0.8,color=GATHER[-1],edgecolor=(0,)*4)
allisi = array(ISI_events)
K = 20
x,y = kdepeak(log(K+allisi[allisi>0]))
x = exp(x)-K
y = y/(K+x)
y = y*len(allisi)*dx
plot(x,y,color=RUST,lw=1.5)
mean_rate = sum(map(len,spikes))/float(len(get_good_trials(session))*2)
noburst = allisi[allisi>BURST]
ISI_cv = std(noburst)/mean(noburst)
burstiness = sum(allisi<BURST)/float(len(allisi))*100
ll = 1./mean(allisi)
expected_short_isi = (1.0-exp(-ll*10))*100
residual_burstiness = burstiness-expected_short_isi
LH = LABELSIZE+4
text(INFOXPOS,ylim()[1]-pixels_to_yunits(INFOYSTART ),'Mean rate = %d Hz'%mean_rate,
horizontalalignment='left',
verticalalignment ='bottom',fontsize=LABELSIZE)
text(INFOXPOS,ylim()[1]-pixels_to_yunits(INFOYSTART+LH*1),'ISI CV = %0.2f'%ISI_cv,
horizontalalignment='left',
verticalalignment ='bottom',fontsize=LABELSIZE)
text(INFOXPOS,ylim()[1]-pixels_to_yunits(INFOYSTART+LH*2),'SNR = %0.1f'%SNR,
horizontalalignment='left',
verticalalignment ='bottom',fontsize=LABELSIZE)
xlabel('ms',fontsize=LABELSIZE)
ylabel('No. Events',fontsize=LABELSIZE)
fudgey(10)
fudgex(5)
xlim(0,TMAX)
nicex()
nicey()
simpleaxis()
title('Monkey %s area %s\nsession %s unit %s'%(session[0],area,session[-2:],unit),loc='center',fontsize=7)
