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[yak shaving]

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Max Zwiessele 2015-09-18 16:21:31 +01:00
parent ba813edd07
commit 637be86369
3 changed files with 14 additions and 6 deletions
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4
GPy/core/parameterization/parameterized.py
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@ -314,8 +314,8 @@ class Parameterized(Parameterizable):
if name in pnames: if name in pnames:
param = self.parameters[pnames.index(name)] param = self.parameters[pnames.index(name)]
param[:] = val; return param[:] = val; return
except AttributeError: except AttributeError as a:
pass raise
return object.__setattr__(self, name, val); return object.__setattr__(self, name, val);
#=========================================================================== #===========================================================================

2
GPy/inference/mcmc/samplers.py
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@ -14,7 +14,7 @@ except ImportError:
import pickle import pickle
class Metropolis_Hastings: class Metropolis_Hastings(object):
def __init__(self,model,cov=None): def __init__(self,model,cov=None):
"""Metropolis Hastings, with tunings according to Gelman et al. """ """Metropolis Hastings, with tunings according to Gelman et al. """
self.model = model self.model = model

14
GPy/util/initialization.py
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@ -5,15 +5,23 @@ Created on 24 Feb 2014
''' '''
import numpy as np import numpy as np
from GPy.util.pca import PCA from ..util.pca import PCA
def initialize_latent(init, input_dim, Y): def initialize_latent(init, input_dim, Y):
Xr = np.asfortranarray(np.random.randn(Y.shape[0], input_dim)) Xr = np.asfortranarray(np.random.normal(0, 1, (Y.shape[0], input_dim)))
if init == 'PCA': if 'PCA' in init:
p = PCA(Y) p = PCA(Y)
PC = p.project(Y, min(input_dim, Y.shape[1])) PC = p.project(Y, min(input_dim, Y.shape[1]))
Xr[:PC.shape[0], :PC.shape[1]] = PC Xr[:PC.shape[0], :PC.shape[1]] = PC
var = .1*p.fracs[:input_dim] var = .1*p.fracs[:input_dim]
elif init in 'empirical_samples':
from ..util.linalg import tdot
from ..util import diag
YYT = tdot(Y)
diag.add(YYT, 1e-6)
EMP = np.asfortranarray(np.random.multivariate_normal(np.zeros(Y.shape[0]), YYT, min(input_dim, Y.shape[1])).T)
Xr[:EMP.shape[0], :EMP.shape[1]] = EMP
var = np.random.uniform(0.5, 1.5, input_dim)
else: else:
var = Xr.var(0) var = Xr.var(0)