def plotXcorr(qdata,save=False,fname='hmmSortingUnits.pdf'):
unitTimePoints = qdata['unitTimePoints']
samplingRate = qdata.get('samplingRate',30000.0)
units = unitTimePoints.keys()
nunits = len(units)
xsize = max(10,nunits*2)
fig = plt.figure(figsize=(xsize,(6.0/8)*xsize) )
fig.subplots_adjust(left=0.03,right=0.97,bottom=0.03,top=0.97)
i = 1
if not 'XCorr' in qdata:
if isinstance(qdata,dict):
qdata['XCorr'] = {}
else:
qdata.create_group('XCorr')
for k1 in xrange(len(units)-1) :
if not units[k1] in qdata['XCorr']:
qdata['XCorr'].create_group(units[k1])
for k2 in xrange(k1+1,len(units)):
if not units[k2] in qdata['XCorr'][units[k1]]:
T1 = unitTimePoints[units[k1]][:]/(samplingRate/1000)
T2 = unitTimePoints[units[k2]][:]/(samplingRate/1000)
#compute differences less than 50 ms
C = pdist_threshold2(T1,T2,50)
qdata['XCorr'][units[k1]].create_dataset(units[k2],data=C,compression=2,fletcher32=True,shuffle=True)
else:
C = qdata['XCorr'][units[k1]][units[k2]][:]
n,b = np.histogram(C,np.arange(-50,50),normed=True)
ax = Subplot(fig,nunits-1,nunits,k1*nunits+k2)
fig.add_axes(ax)
formatAxis(ax)
ax.plot(b[:-1],n,'k')
ax.fill_betweenx([0,n.max()],-1.0,1.0,color='r',alpha=0.3)
if not (k1 == len(units)-2 and k2 == len(units)-1):
ax.set_xticklabels('')
ax.set_yticklabels('')
if save:
fig.savefig(os.path.expanduser('~/Documents/research/figures/SpikeSorting/hmm/%s' %( fname,)),bbox='tight')
else:
plt.draw()
