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bug fix for mcmc sampler and add test case
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2 changed files with 18 additions and 5 deletions
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@ -37,16 +37,14 @@ class Metropolis_Hastings(object):
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def sample(self, Ntotal=10000, Nburn=1000, Nthin=10, tune=True, tune_throughout=False, tune_interval=400):
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current = self.model.optimizer_array
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fcurrent = self.model.log_likelihood() + self.model.log_prior() + \
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self.model._log_det_jacobian()
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fcurrent = self.model.log_likelihood() + self.model.log_prior()
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accepted = np.zeros(Ntotal,dtype=np.bool)
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for it in range(Ntotal):
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print("sample %d of %d\r"%(it,Ntotal),end="\t")
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print("sample %d of %d\r"%(it+1,Ntotal),end="")
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sys.stdout.flush()
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prop = np.random.multivariate_normal(current, self.cov*self.scale*self.scale)
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self.model.optimizer_array = prop
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fprop = self.model.log_likelihood() + self.model.log_prior() + \
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self.model._log_det_jacobian()
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fprop = self.model.log_likelihood() + self.model.log_prior()
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if fprop>fcurrent:#sample accepted, going 'uphill'
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accepted[it] = True
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@ -64,6 +64,21 @@ class HMCSamplerTest(unittest.TestCase):
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hmc = GPy.inference.mcmc.HMC(m,stepsize=1e-2)
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s = hmc.sample(num_samples=3)
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class MCMCSamplerTest(unittest.TestCase):
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def test_sampling(self):
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np.random.seed(1)
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x = np.linspace(0.,2*np.pi,100)[:,None]
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y = -np.cos(x)+np.random.randn(*x.shape)*0.3+1
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m = GPy.models.GPRegression(x,y)
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m.kern.lengthscale.set_prior(GPy.priors.Gamma.from_EV(1.,10.))
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m.kern.variance.set_prior(GPy.priors.Gamma.from_EV(1.,10.))
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m.likelihood.variance.set_prior(GPy.priors.Gamma.from_EV(1.,10.))
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mcmc = GPy.inference.mcmc.Metropolis_Hastings(m)
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mcmc.sample(Ntotal=100, Nburn=10)
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if __name__ == "__main__":
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unittest.main()
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