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2to3 itertools fixer

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This commit is contained in:
Mike Croucher 2015-03-06 14:48:19 +00:00
parent 3e25098710
commit f627c0b1cd
1 changed files with 3 additions and 3 deletions
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6
GPy/models/mrd.py
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@ -139,7 +139,7 @@ class MRD(BayesianGPLVMMiniBatch):
self.bgplvms = [] 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" 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() md = np.isnan(Y).any()
spgp = BayesianGPLVMMiniBatch(Y, input_dim, X, X_variance, spgp = BayesianGPLVMMiniBatch(Y, input_dim, X, X_variance,
@ -166,7 +166,7 @@ class MRD(BayesianGPLVMMiniBatch):
self._log_marginal_likelihood = 0 self._log_marginal_likelihood = 0
self.Z.gradient[:] = 0. self.Z.gradient[:] = 0.
self.X.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._log_marginal_likelihood += b._log_marginal_likelihood
self.logger.info('working on im <{}>'.format(hex(id(i)))) self.logger.info('working on im <{}>'.format(hex(id(i))))
@ -197,7 +197,7 @@ class MRD(BayesianGPLVMMiniBatch):
elif init in "PCA_single": elif init in "PCA_single":
X = np.zeros((Ylist[0].shape[0], self.input_dim)) X = np.zeros((Ylist[0].shape[0], self.input_dim))
fracs = [] 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,frcs = initialize_latent('PCA', len(qs), Y)
X[:, qs] = x X[:, qs] = x
fracs.append(frcs) fracs.append(frcs)