public void MP_GetItemGamma()
        {
            InferenceEngine       engine = new InferenceEngine();
            ModelDefinitionMethod meth   = new ModelDefinitionMethod(GetItemGammaModel);
            var ca = engine.Compiler.CompileWithoutParams(
                declaringType, meth.Method, new AttributeRegistry <object, ICompilerAttribute>(true));

            ca.Execute(1);
            Gamma cMarg = ca.Marginal <Gamma>("c");
            DistributionArray <Gamma> dMarg = ca.Marginal <DistributionArray <Gamma> >("d");
        }
        public void MP_VectorGaussian()
        {
            // Need VMP as EP doesn't support random mean
            InferenceEngine       engine = new InferenceEngine(new VariationalMessagePassing());
            ModelDefinitionMethod meth   = new ModelDefinitionMethod(VectorGaussianModel);
            var ca = engine.Compiler.CompileWithoutParams(
                declaringType, meth.Method, new AttributeRegistry <object, ICompilerAttribute>(true));

            ca.Execute(1);
            VectorGaussian cMarg = ca.Marginal <VectorGaussian>("c");
        }
        public void MP_Product()
        {
            InferenceEngine       engine = new InferenceEngine();
            ModelDefinitionMethod meth   = new ModelDefinitionMethod(ProductModel);
            var ca = engine.Compiler.CompileWithoutParams(
                declaringType, meth.Method, new AttributeRegistry <object, ICompilerAttribute>(true));

            ca.Execute(1);
            Gaussian cMarg = ca.Marginal <Gaussian>("c");
            Gaussian dMarg = ca.Marginal <Gaussian>("d");
        }
        public void MP_Logical()
        {
            InferenceEngine       engine = new InferenceEngine();
            ModelDefinitionMethod meth   = new ModelDefinitionMethod(LogicalModel);
            var ca = engine.Compiler.CompileWithoutParams(
                declaringType, meth.Method, new AttributeRegistry <object, ICompilerAttribute>(true));

            ca.Execute(1);
            Bernoulli cMarg = ca.Marginal <Bernoulli>("c");
            Bernoulli dMarg = ca.Marginal <Bernoulli>("d");
            Bernoulli eMarg = ca.Marginal <Bernoulli>("e");
        }
Exemple #5
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 /// <exclude/>
 public IGeneratedAlgorithm Compile <T1, T2, T3, T4, T5, T6, T7, T8, T9, T10>(ModelDefinitionMethod <T1, T2, T3, T4, T5, T6, T7, T8, T9, T10> method)
 {
     return(CompileWithoutParams(method.Method));
 }
Exemple #6
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 /// <exclude/>
 public IGeneratedAlgorithm Compile <T1, T2, T3, T4, T5, T6, T7, T8, T9, T10>(ModelDefinitionMethod <T1, T2, T3, T4, T5, T6, T7, T8, T9, T10> method, T1 arg1, T2 arg2,
                                                                              T3 arg3, T4 arg4, T5 arg5, T6 arg6, T7 arg7, T8 arg8, T9 arg9, T10 arg10)
 {
     return(CompileWithParamArray(method.Method, arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10));
 }
Exemple #7
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 /// <exclude/>
 public IGeneratedAlgorithm Compile <T1, T2, T3, T4, T5, T6>(ModelDefinitionMethod <T1, T2, T3, T4, T5, T6> method, T1 arg1, T2 arg2, T3 arg3, T4 arg4, T5 arg5, T6 arg6)
 {
     return(CompileWithParamArray(method.Method, arg1, arg2, arg3, arg4, arg5, arg6));
 }
Exemple #8
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 /// <exclude/>
 public IGeneratedAlgorithm Compile <T1, T2, T3, T4>(ModelDefinitionMethod <T1, T2, T3, T4> method)
 {
     return(CompileWithoutParams(method.Method));
 }
Exemple #9
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 /// <exclude/>
 public IGeneratedAlgorithm Compile <T1, T2, T3>(ModelDefinitionMethod <T1, T2, T3> method, T1 arg1, T2 arg2, T3 arg3)
 {
     return(CompileWithParamArray(method.Method, arg1, arg2, arg3));
 }
Exemple #10
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 /// <exclude/>
 public IGeneratedAlgorithm Compile <T1>(ModelDefinitionMethod <T1> method, T1 arg1)
 {
     return(CompileWithParamArray(method.Method, arg1));
 }
Exemple #11
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 /// <exclude/>
 public IGeneratedAlgorithm Compile(ModelDefinitionMethod method)
 {
     return(CompileWithParamArray(method.Method));
 }