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Merge branch 'devel' of github.com:SheffieldML/GPy into devel

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Ricardo 2013-06-05 18:20:43 +01:00
commit 903c8bb123
4 changed files with 24 additions and 20 deletions
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5
GPy/examples/dimensionality_reduction.py
View file

@ -138,6 +138,9 @@ def BGPLVM_oil(optimize=True, N=200, Q=10, num_inducing=15, max_f_eval=4e3, plot
# optimize # optimize
if optimize: if optimize:
m.constrain_fixed('noise')
m.optimize('scg', messages=1, max_f_eval=100, gtol=.05)
m.constrain_positive('noise')
m.optimize('scg', messages=1, max_f_eval=max_f_eval, gtol=.05) m.optimize('scg', messages=1, max_f_eval=max_f_eval, gtol=.05)
if plot: if plot:
@ -295,7 +298,7 @@ def mrd_simulation(optimize=True, plot=True, plot_sim=True, **kw):
if optimize: if optimize:
print "Optimizing Model:" print "Optimizing Model:"
m.optimize('scg', messages=1, max_iters=5e4, max_f_eval=5e4, gtol=.05) m.optimize('scg', messages=1, max_iters=1e3, max_f_eval=1e3, gtol=.1)
if plot: if plot:
m.plot_X_1d("MRD Latent Space 1D") m.plot_X_1d("MRD Latent Space 1D")
m.plot_scales("MRD Scales") m.plot_scales("MRD Scales")

21
GPy/examples/tutorials.py
View file

@ -115,24 +115,25 @@ def tuto_kernel_overview():
# Create GP regression model # Create GP regression model
m = GPy.models.GPRegression(X, Y, Kanova) m = GPy.models.GPRegression(X, Y, Kanova)
pb.figure(figsize=(5,5)) fig = pb.figure(figsize=(5,5))
m.plot() ax = fig.add_subplot(111)
m.plot(ax=ax)
pb.figure(figsize=(20,3)) pb.figure(figsize=(20,3))
pb.subplots_adjust(wspace=0.5) pb.subplots_adjust(wspace=0.5)
pb.subplot(1,5,1) axs = pb.subplot(1,5,1)
m.plot() m.plot(ax=axs)
pb.subplot(1,5,2) pb.subplot(1,5,2)
pb.ylabel("= ",rotation='horizontal',fontsize='30') pb.ylabel("= ",rotation='horizontal',fontsize='30')
pb.subplot(1,5,3) axs = pb.subplot(1,5,3)
m.plot(which_parts=[False,True,False,False]) m.plot(ax=axs, which_parts=[False,True,False,False])
pb.ylabel("cst +",rotation='horizontal',fontsize='30') pb.ylabel("cst +",rotation='horizontal',fontsize='30')
pb.subplot(1,5,4) axs = pb.subplot(1,5,4)
m.plot(which_parts=[False,False,True,False]) m.plot(ax=axs, which_parts=[False,False,True,False])
pb.ylabel("+ ",rotation='horizontal',fontsize='30') pb.ylabel("+ ",rotation='horizontal',fontsize='30')
pb.subplot(1,5,5) axs = pb.subplot(1,5,5)
pb.ylabel("+ ",rotation='horizontal',fontsize='30') pb.ylabel("+ ",rotation='horizontal',fontsize='30')
m.plot(which_parts=[False,False,False,True]) m.plot(ax=axs, which_parts=[False,False,False,True])
return(m) return(m)

2
GPy/models/mrd.py
View file

@ -78,7 +78,7 @@ class MRD(Model):
self.NQ = self.num_data * self.input_dim self.NQ = self.num_data * self.input_dim
self.MQ = self.num_inducing * self.input_dim self.MQ = self.num_inducing * self.input_dim
model.__init__(self) # @UndefinedVariable super(MRD, self).__init__()
self._set_params(self._get_params()) self._set_params(self._get_params())
@property @property

16
doc/tuto_kernel_overview.rst
View file

@ -230,19 +230,19 @@ The submodels can be represented with the option ``which_function`` of ``plot``:
pb.figure(figsize=(20,3)) pb.figure(figsize=(20,3))
pb.subplots_adjust(wspace=0.5) pb.subplots_adjust(wspace=0.5)
pb.subplot(1,5,1) axs = pb.subplot(1,5,1)
m.plot() m.plot(ax=axs)
pb.subplot(1,5,2) pb.subplot(1,5,2)
pb.ylabel("= ",rotation='horizontal',fontsize='30') pb.ylabel("= ",rotation='horizontal',fontsize='30')
pb.subplot(1,5,3) axs = pb.subplot(1,5,3)
m.plot(which_parts=[False,True,False,False]) m.plot(ax=axs, which_parts=[False,True,False,False])
pb.ylabel("cst +",rotation='horizontal',fontsize='30') pb.ylabel("cst +",rotation='horizontal',fontsize='30')
pb.subplot(1,5,4) axs = pb.subplot(1,5,4)
m.plot(which_parts=[False,False,True,False]) m.plot(ax=axs, which_parts=[False,False,True,False])
pb.ylabel("+ ",rotation='horizontal',fontsize='30') pb.ylabel("+ ",rotation='horizontal',fontsize='30')
pb.subplot(1,5,5) axs = pb.subplot(1,5,5)
pb.ylabel("+ ",rotation='horizontal',fontsize='30') pb.ylabel("+ ",rotation='horizontal',fontsize='30')
m.plot(which_parts=[False,False,False,True]) m.plot(ax=axs, which_parts=[False,False,False,True])
.. pb.savefig('tuto_kern_overview_mANOVAdec.png',bbox_inches='tight') .. pb.savefig('tuto_kern_overview_mANOVAdec.png',bbox_inches='tight')