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Viewing changes to lib/test/t_MarginalTransformationGradient_std.at

  • Committer: Bazaar Package Importer
  • Author(s): Fabrice Coutadeur
  • Date: 2010-05-10 17:27:55 UTC
  • mfrom: (1.1.4 upstream) (5.1.5 sid)
  • Revision ID: james.westby@ubuntu.com-20100510172755-cb5ynskknqqi5rhp
Tags: 0.13.2-2ubuntu1
* Merge with Debian testing. No changes left.
* ubuntu_fix-python-2.6.patch: fix detection of python 2.6 libs, to not use
  LOCALMODLIBS. This pulls a dependency on SSL and makes the package FTBFS.

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Lines of Context:
lib/test/t_MarginalTransformationGradient_std.at
 
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AT_SETUP([MarginalTransformation (gradient)])
 
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AT_KEYWORDS([IsoProbabilisticTransformation MarginalTransformationGradient])
 
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AT_CHECK([t_MarginalTransformationGradient_std],
 
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         [0],
 
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[[transformation=class=MarginalTransformationGradient evaluation=class=MarginalTransformationEvaluation description=[x0,x1,y0,y1] input marginals=[class=Normal name=Normal dimension=1 mean=class=NumericalPoint name=Unnamed dimension=1 values=[1] sigma=class=NumericalPoint name=Unnamed dimension=1 values=[2.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1],class=Gamma name=Gamma dimension=1 k=1.5 lambda=3 gamma=0] output marginals=[class=Uniform name=Uniform dimension=1 a=0 b=1,class=Uniform name=Uniform dimension=1 a=0 b=1]
 
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transformation.gradient(class=NumericalPoint name=Unnamed dimension=2 values=[-0.686224,0.202089])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.127111,0,0,1.43751]
 
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finite difference gradient(class=NumericalPoint name=Unnamed dimension=2 values=[-0.686224,0.202089])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.127111,0,0,1.43751]
 
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transformation.gradient(class=NumericalPoint name=Unnamed dimension=2 values=[2.68622,0.684724])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.127111,0,0,0.621984]
 
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finite difference gradient(class=NumericalPoint name=Unnamed dimension=2 values=[2.68622,0.684724])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.127111,0,0,0.621984]
 
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input dimension=2
 
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output dimension=2
 
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transformation=class=MarginalTransformationGradient evaluation=class=MarginalTransformationEvaluation description=[x0,x1,y0,y1] input marginals=[class=Uniform name=Uniform dimension=1 a=0 b=1,class=Uniform name=Uniform dimension=1 a=0 b=1] output marginals=[class=Normal name=Normal dimension=1 mean=class=NumericalPoint name=Unnamed dimension=1 values=[1] sigma=class=NumericalPoint name=Unnamed dimension=1 values=[2.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1],class=Gamma name=Gamma dimension=1 k=1.5 lambda=3 gamma=0]
 
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transformation.gradient(class=NumericalPoint name=Unnamed dimension=2 values=[0.25,0.25])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[7.86716,0,0,0.695649]
 
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finite difference gradient(class=NumericalPoint name=Unnamed dimension=2 values=[0.25,0.25])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[7.86716,0,0,0.695649]
 
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transformation.gradient(class=NumericalPoint name=Unnamed dimension=2 values=[0.75,0.75])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[7.86716,0,0,1.60776]
 
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finite difference gradient(class=NumericalPoint name=Unnamed dimension=2 values=[0.75,0.75])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[7.86716,0,0,1.60776]
 
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input dimension=2
 
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output dimension=2
 
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transformation=class=MarginalTransformationGradient evaluation=class=MarginalTransformationEvaluation description=[x0,x1,y0,y1] input marginals=[class=Normal name=Normal dimension=1 mean=class=NumericalPoint name=Unnamed dimension=1 values=[1] sigma=class=NumericalPoint name=Unnamed dimension=1 values=[2.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1],class=Gamma name=Gamma dimension=1 k=1.5 lambda=3 gamma=0] output marginals=[class=Gamma name=Gamma dimension=1 k=2.5 lambda=2 gamma=0,class=Normal name=Normal dimension=1 mean=class=NumericalPoint name=Unnamed dimension=1 values=[3] sigma=class=NumericalPoint name=Unnamed dimension=1 values=[1.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]]
 
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transformation.gradient(class=NumericalPoint name=Unnamed dimension=2 values=[-0.686224,0.202089])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.208078,0,0,6.78546]
 
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finite difference gradient(class=NumericalPoint name=Unnamed dimension=2 values=[-0.686224,0.202089])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.208078,0,0,6.78546]
 
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transformation.gradient(class=NumericalPoint name=Unnamed dimension=2 values=[2.68622,0.684724])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.3848,0,0,2.93595]
 
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finite difference gradient(class=NumericalPoint name=Unnamed dimension=2 values=[2.68622,0.684724])=class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.3848,0,0,2.93595]
 
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input dimension=2
 
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output dimension=2
 
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]],
 
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         [ignore])
 
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AT_CLEANUP