def sampleWang(X,cp,parameters=modelParameters): Z = list(np.zeros(len(X))) sampler = DP.sampleDPMM(X,Z,cp, DP.gaussianMarginalLikelihood, DP.gaussianMAPPostPred, parameters, iterations=2000, burn=1000, thin=5, cpSampler=DP.sampleCP) posteriorSamples = sampler.wangSUGS() return posteriorSamples
def sampleClusters(X,cp): Z = list(np.zeros(len(X))) sampler = DP.sampleDPMM(X,Z,cp, DP.gaussianMarginalLikelihood, DP.gaussianPostPred, modelParameters, iterations=2000, burn=1000, thin=5, cpSampler=DP.sampleCP) posteriorSamples = sampler.gibbs() return posteriorSamples