Esempi in Python per DiscreteKLDivergence

Esempio n. 1

File: test_kl_divergence.py Progetto: 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

Esempio n. 2

File: test_kl_divergence.py Progetto: 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

Esempio n. 3

File: test_kl_divergence.py Progetto: 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

Esempio n. 4

File: test_kl_divergence.py Progetto: sdv-dev/SDMetrics

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

        assert output == 1
        assert normalized == 1

Esempio n. 5

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

        assert 0 <= output < 0.5

Esempio n. 6

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

        assert 0.5 < output <= 1

Esempio n. 7

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

        assert 0.0 <= output < 0.1

Esempio n. 8

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

        assert output == 1