def plotAgainstGFP_hist2d(self):
fig1 = pylab.figure(figsize = (20, 15))
print len(self.GFP)
for i in xrange(min(len(data.cat), 4)):
print len(self.GFP[self.categories == i])
vect = []
pylab.subplot(2,2,i+1)
pop = self.GFP[self.categories == i]
print "cat", i, "n pop", len(self.GFP[(self.categories == i) & (self.GFP > -np.log(12.5))])
H, xedges, yedges = np.histogram2d(self.angles[self.categories == i], self.GFP[self.categories == i], bins = 10)
hist = pylab.hist2d(self.GFP[self.categories == i], self.angles[self.categories == i], bins = 10, cmap = pylab.cm.Reds, normed = True)
pylab.clim(0.,0.035)
pylab.colorbar()
pylab.title(data.cat[i])
pylab.xlabel('GFP score')
pylab.ylabel('Angle (degree)')
pylab.xlim([-4.2, -1])
pylab.show()
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