Пример #1
0
    def test_observer_aware_subjective_model(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling()

        self.assertAlmostEquals(np.sum(result['observer_bias']),
                                -0.090840910829083799,
                                places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']),
                                0.089032585621095089,
                                places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']),
                                15.681766163430936,
                                places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']),
                                0.012565584832977776,
                                places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']),
                                280.31447815213642,
                                places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']),
                                1.4355485462027884,
                                places=4)
Пример #2
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    def test_observer_aware_subjective_model_use_log(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(use_log=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']),
                                -0.082429594509296211,
                                places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']),
                                0.089032585621095089,
                                places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']),
                                15.681766163430936,
                                places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']),
                                0.012565584832977776,
                                places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']),
                                280.2889206910113,
                                places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']),
                                1.4355485462027884,
                                places=4)
Пример #3
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    def test_observer_aware_subjective_model_with_dscoring(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(dscore_mode=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']),
                                -0.090840910829083799,
                                places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']),
                                0.089032585621095089,
                                places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']),
                                15.681766163430936,
                                places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']),
                                0.012565584832977776,
                                places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']),
                                298.35293969059796,
                                places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']),
                                1.4163670233392607,
                                places=4)
Пример #4
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    def test_observer_aware_subjective_model(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling()

        self.assertAlmostEquals(np.sum(result['observer_bias']), -0.090840910829083799, places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']), 0.089032585621095089, places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']), 15.681766163430936, places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']), 0.012565584832977776, places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']), 280.31447815213642, places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']), 1.4355485462027884, places=4)
Пример #5
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    def test_observer_aware_subjective_model_use_log(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(use_log=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']), -0.082429594509296211, places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']), 0.089032585621095089, places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']), 15.681766163430936, places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']), 0.012565584832977776, places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']), 280.2889206910113, places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']), 1.4355485462027884, places=4)
Пример #6
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    def test_observer_aware_subjective_model_with_dscoring_and_zscoring(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(dscore_mode=True, zscore_mode=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']), 0.0, places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']), 11.628499078069273, places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']), 0.0082089371266301642, places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']), 0.80806512456121071, places=4)
Пример #7
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    def test_observer_aware_subjective_model_with_zscoring(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(zscore_mode=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']), 0.0, places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']), 11.568205661696393, places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']), 0.0079989301785523791, places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']), 0.80942484781493518, places=4)
Пример #8
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    def test_observer_aware_subjective_model_with_dscoring(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(dscore_mode=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']), -0.090840910829083799, places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']), 0.089032585621095089, places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']), 15.681766163430936, places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']), 0.012565584832977776, places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']), 298.35293969059796, places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']), 1.4163670233392607, places=4)
Пример #9
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    def test_observer_aware_subjective_model_with_dscoring_and_zscoring(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(dscore_mode=True, zscore_mode=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']), 0.0, places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']), 11.628499078069273, places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']), 0.0082089371266301642, places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']), 0.80806512456121071, places=4)
Пример #10
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    def test_observer_aware_subjective_model_with_zscoring(self):
        subjective_model = MaximumLikelihoodEstimationModelReduced.from_dataset_file(
            self.dataset_filepath)
        result = subjective_model.run_modeling(zscore_mode=True)

        self.assertAlmostEquals(np.sum(result['observer_bias']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['observer_bias']), 0.0, places=4)

        self.assertAlmostEquals(np.sum(result['observer_inconsistency']), 11.568205661696393, places=4)
        self.assertAlmostEquals(np.var(result['observer_inconsistency']), 0.0079989301785523791, places=4)

        self.assertAlmostEquals(np.sum(result['quality_scores']), 0.0, places=4)
        self.assertAlmostEquals(np.var(result['quality_scores']), 0.80942484781493518, places=4)