def plot_events_in_time(timeStamps,nBins=50,fontsize=8):
'''
Plot histogram of inter-spike interval (in msec, log scale)
Parameters
----------
timeStamps : array (assumed to be integers in microsec)
'''
ax = plt.gca()
timeBinEdges = np.linspace(timeStamps[0],timeStamps[-1],nBins) # in microsec
# FIXME: xLimits depend on the time of the first spike (not of recording)
(nEvents,binEdges) = np.histogram(timeStamps,bins=timeBinEdges)
hp, = plt.plot(1e-6/60 * (binEdges-timeStamps[0]),np.r_[nEvents,0],drawstyle='steps-post')
plt.setp(hp,lw=1,color='k')
plt.xlabel('Time (min)')
plt.axis('tight')
ax.set_yticks(plt.ylim())
extraplots.boxoff(ax)
extraplots.set_ticks_fontsize(ax,fontsize)
return hp
def plot_isi_loghist(timeStamps,nBins=350,fontsize=8):
'''
Plot histogram of inter-spike interval (in msec, log scale)
Parameters
----------
timeStamps : array (assumed to be integers in microsec)
'''
fontsizeLegend = fontsize
xLims = [1e-1,1e4]
ax = plt.gca()
ISI = np.diff(timeStamps)
if np.any(ISI<0):
raise 'Times of events are not ordered (or there is at least one repeated).'
if len(ISI)==0: # Hack in case there is only one spike
ISI = np.array(1)
#if len(timeStamps)<2:
# return (0,0,0) ### FIXME: what to do when only one spike?
logISI = np.log10(ISI)
[ISIhistogram,ISIbinsLog] = np.histogram(logISI,bins=nBins)
ISIbins = 1e-3*(10**ISIbinsLog[:-1]) # Conversion to msec
percentViolation = 100*np.mean(ISI<1e3) # Assumes ISI in usec
percentViolation2 = 100*np.mean(ISI<2e3) # Assumes ISI in usec
hp, = plt.semilogx(ISIbins,ISIhistogram,color='k')
#plt.ylabel('Cluster %d'%SelectedCluster)
plt.setp(hp,lw=0.5,color='k')
yLims = plt.ylim()
plt.xlim(xLims)
plt.text(0.15,0.85*yLims[-1],'N=%d'%len(timeStamps),fontsize=fontsizeLegend,va='top')
#plt.text(0.15,0.7*yLims[-1],'%0.2f%%'%percentViolation,fontsize=fontsizeLegend)
plt.text(0.15,0.6*yLims[-1],'%0.2f%%\n%0.2f%%'%(percentViolation,percentViolation2),
fontsize=fontsizeLegend,va='top')
#'VerticalAlignment','top','HorizontalAlignment','left','FontSize',FontSizeAxes);
ax.xaxis.grid(True)
ax.yaxis.grid(False)
plt.xlabel('Interspike interval (ms)')
ax.set_yticks(plt.ylim())
extraplots.set_ticks_fontsize(ax,fontsize)
return (hp,ISIhistogram,ISIbins)
