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Fixed naming to standardized PEP8

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Ricardo 2013-06-05 14:39:32 +01:00
parent b3eeacd956
commit aac4f6a237
7 changed files with 15 additions and 328 deletions
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12
GPy/examples/classification.py
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@ -24,7 +24,7 @@ def crescent_data(seed=default_seed): # FIXME
Y = data['Y']
Y[Y.flatten()==-1] = 0
m = GPy.models.GP_classification(data['X'], Y)
m = GPy.models.GPClassification(data['X'], Y)
m.ensure_default_constraints()
m.update_likelihood_approximation()
m.optimize()
@ -41,7 +41,7 @@ def oil():
Y[Y.flatten()==-1] = 0
# Create GP model
m = GPy.models.GP_classification(data['X'], Y)
m = GPy.models.GPClassification(data['X'], Y)
# Contrain all parameters to be positive
m.constrain_positive('')
@ -66,7 +66,7 @@ def toy_linear_1d_classification(seed=default_seed):
Y[Y.flatten() == -1] = 0
# Model definition
m = GPy.models.GP_classification(data['X'], Y)
m = GPy.models.GPClassification(data['X'], Y)
m.ensure_default_constraints()
# Optimize
@ -95,7 +95,7 @@ def sparse_toy_linear_1d_classification(seed=default_seed):
Y[Y.flatten() == -1] = 0
# Model definition
m = GPy.models.sparse_GP_classification(data['X'], Y)
m = GPy.models.SparseGPClassification(data['X'], Y)
m['.*len']= 2.
m.ensure_default_constraints()
@ -127,7 +127,7 @@ def sparse_crescent_data(inducing=10, seed=default_seed):
Y = data['Y']
Y[Y.flatten()==-1]=0
m = GPy.models.sparse_GP_classification(data['X'], Y)
m = GPy.models.SparseGPClassification(data['X'], Y)
m.ensure_default_constraints()
m['.*len'] = 10.
m.update_likelihood_approximation()
@ -150,7 +150,7 @@ def FITC_crescent_data(inducing=10, seed=default_seed):
Y = data['Y']
Y[Y.flatten()==-1]=0
m = GPy.models.FITC_classification(data['X'], Y)
m = GPy.models.FITCClassification(data['X'], Y)
m.ensure_default_constraints()
m['.*len'] = 10.
m.update_likelihood_approximation()