Python DiscreteKLDivergence示例

示例#1

文件： test_kl_divergence.py 项目： sdv-dev/SDMetrics

    def test_bad(self):
        output = DiscreteKLDivergence.compute(self.real(), self.bad())
        normalized = DiscreteKLDivergence.normalize(output)

        assert 0 <= output < 0.5
        assert 0 <= normalized < 0.5

示例#2

文件： test_kl_divergence.py 项目： sdv-dev/SDMetrics

    def test_awful(self):
        output = DiscreteKLDivergence.compute(self.ones(), self.zeros())
        normalized = DiscreteKLDivergence.normalize(output)

        assert 0.0 <= output < 0.1
        assert 0.0 <= normalized < 0.1

示例#3

文件： test_kl_divergence.py 项目： sdv-dev/SDMetrics

    def test_good(self):
        output = DiscreteKLDivergence.compute(self.real(), self.good())
        normalized = DiscreteKLDivergence.normalize(output)

        assert 0.5 < output <= 1
        assert 0.5 < normalized <= 1

示例#4

文件： test_kl_divergence.py 项目： sdv-dev/SDMetrics

    def test_perfect(self):
        output = DiscreteKLDivergence.compute(self.ones(), self.ones())
        normalized = DiscreteKLDivergence.normalize(output)

        assert output == 1
        assert normalized == 1

示例#5

    def test_bad(self):
        output = DiscreteKLDivergence.compute(self.real(), self.bad())

        assert 0 <= output < 0.5

示例#6

    def test_good(self):
        output = DiscreteKLDivergence.compute(self.real(), self.good())

        assert 0.5 < output <= 1

示例#7

    def test_awful(self):
        output = DiscreteKLDivergence.compute(self.ones(), self.zeros())

        assert 0.0 <= output < 0.1

示例#8

    def test_perfect(self):
        output = DiscreteKLDivergence.compute(self.ones(), self.ones())

        assert output == 1