Пример #1
0
    def testRegressionGaia14(self):
        ds = testdata.loadSmallDB()
        ds = transform(ds, 'fixlength')

        to_remove = testdata.TEST_SMALLDB_VARLENGTH
        dsr = transform(ds, 'remove', {'descriptorNames': to_remove})

        self.compareResults(search(dsr, '1_ethno.wav', 5),
                            testdata.SMALL_DB_RAW_RESULTS)

        dsc = transform(dsr, 'cleaner')
        self.compareResults(search(dsc, '1_ethno.wav', 5),
                            testdata.SMALL_DB_CLEAN_RESULTS)

        dsn = transform(dsc, 'normalize')
        self.compareResults(search(dsn, '1_ethno.wav', 5),
                            testdata.SMALL_DB_NORM_RESULTS)

        dspca = transform(dsn, 'pca', {
            'resultName': 'pca30',
            'dimension': 30,
            'descriptorNames': '*'
        })
        self.compareResults(search(dspca, '1_ethno.wav', 5),
                            testdata.SMALL_DB_PCA_RESULTS)
Пример #2
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    def testOwnershipIssues(self):
        # 1: layout of a temp point becomes invalid
        Point().layout().descriptorNames()

        # 2: sample point of a dataset becomes invalid
        ds = testdata.loadSmallDB()
        p = ds.samplePoint()
        del ds
        p.name()
Пример #3
0
    def testOwnershipIssues(self):
        # 1: layout of a temp point becomes invalid
        Point().layout().descriptorNames()

        # 2: sample point of a dataset becomes invalid
        ds = testdata.loadSmallDB()
        p = ds.samplePoint()
        del ds
        p.name()
Пример #4
0
    def testRegressionGaia14(self):
        ds = testdata.loadSmallDB()
        ds = transform(ds, 'fixlength')

        to_remove = testdata.TEST_SMALLDB_VARLENGTH
        dsr = transform(ds, 'remove', { 'descriptorNames': to_remove })

        self.compareResults(search(dsr, '1_ethno.wav', 5), testdata.SMALL_DB_RAW_RESULTS)

        dsc = transform(dsr, 'cleaner')
        self.compareResults(search(dsc, '1_ethno.wav', 5), testdata.SMALL_DB_CLEAN_RESULTS)

        dsn = transform(dsc, 'normalize')
        self.compareResults(search(dsn, '1_ethno.wav', 5), testdata.SMALL_DB_NORM_RESULTS)

        dspca = transform(dsn, 'pca', { 'resultName': 'pca30',
                                        'dimension': 30,
                                        'descriptorNames': '*' })
        self.compareResults(search(dspca, '1_ethno.wav', 5), testdata.SMALL_DB_PCA_RESULTS)