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C++ BayesNet::GetSoftMaxOffset方法代码示例

本文整理汇总了C++中BayesNet::GetSoftMaxOffset方法的典型用法代码示例。如果您正苦于以下问题：C++ BayesNet::GetSoftMaxOffset方法的具体用法？C++ BayesNet::GetSoftMaxOffset怎么用？C++ BayesNet::GetSoftMaxOffset使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类BayesNet的用法示例。


在下文中一共展示了BayesNet::GetSoftMaxOffset方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。

示例1: TestSetDistributionSoftMax

void TestSetDistributionSoftMax()
{
    BayesNet *net = SimpleSoftMaxModel();

    if (net->GetGaussianMean("node0")[0].FltValue() != 0.1f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node0 : Setting or getting gaussian parameters is wrong");
    }
        if (net->GetGaussianMean("node1")[0].FltValue() != 0.2f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node1 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianMean("node2")[0].FltValue() != 0.3f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node2 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianCovar("node0")[0].FltValue() != 0.9f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node0 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianCovar("node1")[0].FltValue() != 0.8f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node1 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianCovar("node2")[0].FltValue() != 0.7f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node2 : Setting or getting gaussian parameters is wrong");
    }

    if ((net->GetSoftMaxOffset("node5")[0].FltValue(0).fl != 0.1f)||
        (net->GetSoftMaxOffset("node5")[0].FltValue(1).fl != 0.1f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    };

    TokArr node5= net->GetSoftMaxWeights("node5");
    float val0 = node5[0].FltValue(0).fl;
    float val1 = node5[0].FltValue(1).fl;
    float val2 = node5[0].FltValue(2).fl;
    float val3 = node5[0].FltValue(3).fl;
    float val4 = node5[0].FltValue(4).fl;
    float val5 = node5[0].FltValue(5).fl;

    if ((node5[0].FltValue(0).fl != 0.3f)||
        (node5[0].FltValue(1).fl != 0.4f)||
	(node5[0].FltValue(2).fl != 0.5f)||
        (node5[0].FltValue(3).fl != 0.6f)||
        (node5[0].FltValue(4).fl != 0.7f)||
        (node5[0].FltValue(5).fl != 0.8f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    };

    delete net;
	std::cout << "TestSetDistributionSoftMax is completed successfully" << std::endl;

}
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:57，代码来源:TestSoftMax.cpp

示例2: TestSetDistributionSevenNodesModel

void TestSetDistributionSevenNodesModel()
{
    BayesNet *net = SevenNodesModel();
    if (net->GetGaussianMean("node0")[0].FltValue() != 0.5f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node0 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianMean("node1")[0].FltValue() != 0.5f)
    {
        PNL_THROW(pnl::CAlgorithmicException, "node1 : Setting or getting gaussian parameters is wrong");
    }
    
    if (net->GetGaussianCovar("node0")[0].FltValue() != 1.0f)
    {
        PNL_THROW(pnl::CAlgorithmicException, "node0 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianCovar("node1")[0].FltValue() != 1.0f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node1 : Setting or getting gaussian parameters is wrong");
    }

    float val12 = net->GetPTabular("node2")[0].FltValue();
    float val22 = net->GetPTabular("node2")[1].FltValue();

    if ((net->GetPTabular("node2")[0].FltValue() != 0.7f)||
        (net->GetPTabular("node2")[1].FltValue() != 0.3f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node2 : Setting or getting tabular parameters is wrong");
    };

    TokArr off5True = net->GetSoftMaxOffset("node3", "node2^True");
    
    if ((off5True[0].FltValue(0).fl != 0.3f)||
        (off5True[0].FltValue(1).fl != 0.5f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node3 : Setting or getting softmax parameters is wrong");
    };

    TokArr off5False = net->GetSoftMaxOffset("node3", "node2^False");

    float val1off = off5False[0].FltValue(0).fl;
    float val2off = off5False[0].FltValue(1).fl;
    if ((off5False[0].FltValue(0).fl != 0.3f)||
        (off5False[0].FltValue(1).fl != 0.5f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node3 : Setting or getting softmax parameters is wrong");
    };

    TokArr node5True = net->GetSoftMaxWeights("node3", "node2^True");
    
    if ((node5True[0].FltValue(0).fl != 0.5f)||
        (node5True[0].FltValue(1).fl != 0.1f)||
	(node5True[0].FltValue(2).fl != 0.5f)||
        (node5True[0].FltValue(3).fl != 0.7f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node3 : Setting or getting softmax parameters is wrong");
    };

    TokArr node5False = net->GetSoftMaxWeights("node3", "node2^False");
    float val0 = node5False[0].FltValue(0).fl;
    float val1 = node5False[0].FltValue(1).fl;
    float val2 = node5False[0].FltValue(2).fl;
    float val3 = node5False[0].FltValue(3).fl;

    if ((node5False[0].FltValue(0).fl != 0.5f)||
        (node5False[0].FltValue(1).fl != 0.4f)||
	(node5False[0].FltValue(2).fl != 0.5f)||
        (node5False[0].FltValue(3).fl != 0.7f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node3 : Setting or getting softmax parameters is wrong");
    };

    float val40 = net->GetPTabular("node4", "node3^False")[0].FltValue();
    float val41 = net->GetPTabular("node4", "node3^False")[1].FltValue();
    float val42 = net->GetPTabular("node4", "node3^True")[0].FltValue() ;
    float val43 = net->GetPTabular("node4", "node3^True")[1].FltValue() ;

    if ((net->GetPTabular("node4", "node3^False")[0].FltValue() != 0.7f)||
        (net->GetPTabular("node4", "node3^False")[1].FltValue() != 0.3f)||
        (net->GetPTabular("node4", "node3^True")[0].FltValue() != 0.2f)||
        (net->GetPTabular("node4", "node3^True")[1].FltValue() != 0.8f))
    {
        PNL_THROW(pnl::CAlgorithmicException, "node4 : Setting or getting tabular parameters is wrong");
    };

    if ((net->GetGaussianMean("node5", "node3^True")[0].FltValue() != 0.5f)||
        (net->GetGaussianMean("node5", "node3^False")[0].FltValue() != 1.0f))
    {
        PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    }
    
    if ((net->GetGaussianCovar("node5", "node3^True")[0].FltValue() != 0.5f)||
        (net->GetGaussianCovar("node5", "node3^False")[0].FltValue() != 1.0f))
    {
        PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    }
    
    TokArr off6True = net->GetSoftMaxOffset("node6", "node4^True");
    
    if ((off6True[0].FltValue(0).fl != 0.1f)||
//.........这里部分代码省略.........
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:101，代码来源:TestSoftMax.cpp

示例3: TestSetDistributionCondSoftMax

void TestSetDistributionCondSoftMax()
{
    BayesNet *net = SimpleCondSoftMaxModel();
    if (net->GetGaussianMean("node0")[0].FltValue() != 0.1f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node0 : Setting or getting gaussian parameters is wrong");
    }
        if (net->GetGaussianMean("node1")[0].FltValue() != 0.2f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node1 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianMean("node2")[0].FltValue() != 0.3f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node2 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianCovar("node0")[0].FltValue() != 0.9f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node0 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianCovar("node1")[0].FltValue() != 0.8f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node1 : Setting or getting gaussian parameters is wrong");
    }
    if (net->GetGaussianCovar("node2")[0].FltValue() != 0.7f)
    {
         PNL_THROW(pnl::CAlgorithmicException, "node2 : Setting or getting gaussian parameters is wrong");
    }

    if ((net->GetPTabular("node6")[0].FltValue() != 0.3f)||
        (net->GetPTabular("node6")[1].FltValue() != 0.7f)||
	(net->GetPTabular("node6")[2].FltValue() != 0.5f)||
        (net->GetPTabular("node6")[3].FltValue() != 0.5f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node6 : Setting or getting gaussian parameters is wrong");
    };

    TokArr off5True = net->GetSoftMaxOffset("node5", "node3^True");
    
    if ((off5True[0].FltValue(0).fl != 0.1f)||
        (off5True[0].FltValue(1).fl != 0.1f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    };

    TokArr off5False = net->GetSoftMaxOffset("node5", "node3^False");

    float val1off = off5False[0].FltValue(0).fl;
    float val2off = off5False[0].FltValue(1).fl;
    if ((off5False[0].FltValue(0).fl != 0.21f)||
        (off5False[0].FltValue(1).fl != 0.21f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    };

    TokArr node5True = net->GetSoftMaxWeights("node5", "node3^True");
    
    if ((node5True[0].FltValue(0).fl != 0.3f)||
        (node5True[0].FltValue(1).fl != 0.4f)||
	(node5True[0].FltValue(2).fl != 0.5f)||
        (node5True[0].FltValue(3).fl != 0.6f)||
        (node5True[0].FltValue(4).fl != 0.7f)||
        (node5True[0].FltValue(5).fl != 0.8f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    };

    TokArr node5False = net->GetSoftMaxWeights("node5", "node3^False");
    float val0 = node5False[0].FltValue(0).fl;
    float val1 = node5False[0].FltValue(1).fl;
    float val2 = node5False[0].FltValue(2).fl;
    float val3 = node5False[0].FltValue(3).fl;
    float val4 = node5False[0].FltValue(4).fl;
    float val5 = node5False[0].FltValue(5).fl;

    if ((node5False[0].FltValue(0).fl != 0.23f)||
        (node5False[0].FltValue(1).fl != 0.24f)||
	(node5False[0].FltValue(2).fl != 0.25f)||
        (node5False[0].FltValue(3).fl != 0.26f)||
        (node5False[0].FltValue(4).fl != 0.27f)||
        (node5False[0].FltValue(5).fl != 0.28f))
    {
	PNL_THROW(pnl::CAlgorithmicException, "node5 : Setting or getting gaussian parameters is wrong");
    };

    delete net;
	std::cout << "TestSetDistributionCondSoftMax is completed successfully" << std::endl;
}
开发者ID:JacobCWard，项目名称:PyPNL，代码行数:87，代码来源:TestSoftMax.cpp


注：本文中的BayesNet::GetSoftMaxOffset方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。