From f627c0b1cd66cd9689562d90eb4fac8a3c505f87 Mon Sep 17 00:00:00 2001 From: Mike Croucher Date: Fri, 6 Mar 2015 14:48:19 +0000 Subject: [PATCH] 2to3 itertools fixer --- GPy/models/mrd.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/GPy/models/mrd.py b/GPy/models/mrd.py index 0028078f..f6e8c408 100644 --- a/GPy/models/mrd.py +++ b/GPy/models/mrd.py @@ -139,7 +139,7 @@ class MRD(BayesianGPLVMMiniBatch): self.bgplvms = [] - for i, n, k, l, Y, im, bs in itertools.izip(itertools.count(), Ynames, kernels, likelihoods, Ylist, self.inference_method, batchsize): + for i, n, k, l, Y, im, bs in zip(itertools.count(), Ynames, kernels, likelihoods, Ylist, self.inference_method, batchsize): assert Y.shape[0] == self.num_data, "All datasets need to share the number of datapoints, and those have to correspond to one another" md = np.isnan(Y).any() spgp = BayesianGPLVMMiniBatch(Y, input_dim, X, X_variance, @@ -166,7 +166,7 @@ class MRD(BayesianGPLVMMiniBatch): self._log_marginal_likelihood = 0 self.Z.gradient[:] = 0. self.X.gradient[:] = 0. - for b, i in itertools.izip(self.bgplvms, self.inference_method): + for b, i in zip(self.bgplvms, self.inference_method): self._log_marginal_likelihood += b._log_marginal_likelihood self.logger.info('working on im <{}>'.format(hex(id(i)))) @@ -197,7 +197,7 @@ class MRD(BayesianGPLVMMiniBatch): elif init in "PCA_single": X = np.zeros((Ylist[0].shape[0], self.input_dim)) fracs = [] - for qs, Y in itertools.izip(np.array_split(np.arange(self.input_dim), len(Ylist)), Ylist): + for qs, Y in zip(np.array_split(np.arange(self.input_dim), len(Ylist)), Ylist): x,frcs = initialize_latent('PCA', len(qs), Y) X[:, qs] = x fracs.append(frcs)