analyzeAngle.py 文件源码

def bootstrap(self, nBoot, nbins = 20):
        pops = np.zeros((nBoot, nbins))
        #medianpop = [[] for i in data.cat]
        pylab.figure(figsize = (20,14))
        for i in xrange(3):
            pylab.subplot(1,3,i+1)
            #if  i ==0:
                #pylab.title("Bootstrap on medians", fontsize = 20.)
            pop = self.angles[(self.categories == i)]# & (self.GFP > 2000)]
            for index in xrange(nBoot):
                newpop = np.random.choice(pop, size=len(pop), replace=True)
                #medianpop[i].append(np.median(newpop))
                newhist, binedges = np.histogram(newpop, bins = nbins)
                pops[index,:] = newhist/1./len(pop)
            #pylab.hist(medianpop[i], bins = nbins, label = "{2} median {0:.1f}, std {1:.1f}".format(np.median(medianpop[i]), np.std(medianpop[i]), data.cat[i]), color = data.colors[i], alpha =.2, normed = True)

            meanpop = np.sum(pops, axis = 0)/1./nBoot
            stdY = np.std(pops, axis = 0)
            print "width", binedges[1] - binedges[0]
            pylab.bar(binedges[:-1], meanpop, width = binedges[1] - binedges[0], label = "mean distribution", color = data.colors[i], alpha = 0.6)
            pylab.fill_between((binedges[:-1]+binedges[1:])/2., meanpop-stdY, meanpop+stdY, alpha = 0.3)
            pylab.legend()
            pylab.title(data.cat[i])
            pylab.xlabel("Angle(degree)", fontsize = 15)
            pylab.ylim([-.01, 0.23])

        pylab.savefig("/users/biocomp/frose/frose/Graphics/FINALRESULTS-diff-f3/distrib_nBootstrap{0}_bins{1}_GFPsup{2}_{3}.png".format(nBoot, nbins, 'all', randint(0,999)))