Exemplo n.º 1
0
    def test_transformers_not_modified(self):
        # given
        mock = self.DataTransformerMock1()
        p = Pipeline([mock], copy=True)

        # when
        p.transform(constant_timeseries(1, 10))

        # then
        self.assertFalse(mock.transform_called)
Exemplo n.º 2
0
    def test_inverse_transform(self):
        # given
        data = constant_timeseries(0., 3)

        transformers = [self.PlusTenTransformer(), self.TimesTwoTransformer()]
        p = Pipeline(transformers)

        # when
        transformed = p.transform(data)
        back = p.inverse_transform(transformed)

        # then
        self.assertEqual(data, back)
Exemplo n.º 3
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    def test_transform(self):
        # given
        mock1 = self.DataTransformerMock1()
        mock2 = self.DataTransformerMock2()
        data = constant_timeseries(0, 3)
        transformers = [mock1] * 10 + [mock2] * 10
        p = Pipeline(transformers)
        # when
        p.fit(data)
        transformed = p.transform(data)

        # then
        self.assertEqual(63, len(transformed))
        self.assertEqual([0] * 3 + [1] * 30 + [2] * 30,
                         list(transformed.values()))
        for t in transformers:
            self.assertTrue(t.transform_called)
            self.assertFalse(t.inverse_transform_called)
Exemplo n.º 4
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    def test_multi_ts(self):

        series1 = constant_timeseries(0., 3)
        series2 = constant_timeseries(1., 3)

        data = [series1, series2]

        mapper1 = InvertibleMapper(fn=lambda x: x + 10,
                                   inverse_fn=lambda x: x - 10)
        mapper2 = InvertibleMapper(fn=lambda x: x * 10,
                                   inverse_fn=lambda x: x / 10)

        transformers = [mapper1, mapper2]
        p = Pipeline(transformers)

        # when
        transformed = p.transform(data)
        back = p.inverse_transform(transformed)

        # then
        self.assertEqual(data, back)
Exemplo n.º 5
0
    def test_pipeline_partial_inverse(self):
        series = constant_timeseries(0., 3)

        def plus_ten(x):
            return x + 10

        mapper = Mapper(fn=plus_ten)
        mapper_inv = InvertibleMapper(fn=lambda x: x + 2,
                                      inverse_fn=lambda x: x - 2)

        series_plus_ten = mapper.transform(series)

        pipeline = Pipeline([mapper, mapper_inv])

        transformed = pipeline.transform(series)

        # should fail, since partial is False by default
        with self.assertRaises(ValueError):
            pipeline.inverse_transform(transformed)

        back = pipeline.inverse_transform(transformed, partial=True)

        # while the +/- 2 is inverted, the +10 operation is not
        self.assertEqual(series_plus_ten, back)