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Merge pull request #30 from ealcobaca/postprocessing
Postprocessing (code coverage)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,162 @@ | ||
| """Module dedicated to framework testing.""" | ||
| import pytest | ||
| import typing as t | ||
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| import numpy as np | ||
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| from pymfe import _internal | ||
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| GNAME = "framework-testing" | ||
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| class MFETestClass: | ||
| """Some generic methods for testing the MFE Framework.""" | ||
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| @classmethod | ||
| def postprocess_return_none(cls, **kwargs) -> None: | ||
| """Postprocess: return None.""" | ||
| return None | ||
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| @classmethod | ||
| def postprocess_return_new_feature( | ||
| cls, | ||
| number_of_lists: int = 3, | ||
| **kwargs | ||
| ) -> t.Tuple[t.List, t.List, t.List]: | ||
| """Postprocess: return Tuple of lists.""" | ||
| return tuple(["test_value"] for _ in range(number_of_lists)) | ||
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| @classmethod | ||
| def postprocess_raise_exception( | ||
| cls, | ||
| raise_exception: bool = False, | ||
| **kwargs) -> None: | ||
| """Posprocess: raise exception.""" | ||
| if raise_exception: | ||
| raise ValueError("Expected exception (postprocess).") | ||
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| return None | ||
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| @classmethod | ||
| def precompute_return_empty(cls, **kwargs) -> t.Dict[str, t.Any]: | ||
| """Precompute: return empty dictionary.""" | ||
| precomp_vals = {} | ||
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| return precomp_vals | ||
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| @classmethod | ||
| def precompute_return_something(cls, **kwargs) -> t.Dict[str, t.Any]: | ||
| """Precompute: return empty dictionary.""" | ||
| precomp_vals = { | ||
| "test_param_1": 0, | ||
| "test_param_2": "euclidean", | ||
| "test_param_3": list, | ||
| "test_param_4": abs, | ||
| } | ||
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| return precomp_vals | ||
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| @classmethod | ||
| def precompute_raise_exception( | ||
| cls, | ||
| raise_exception: bool = False, | ||
| **kwargs) -> t.Dict[str, t.Any]: | ||
| """Precompute: raise exception.""" | ||
| precomp_vals = {} | ||
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| if raise_exception: | ||
| raise ValueError("Expected exception (precompute).") | ||
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| return precomp_vals | ||
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| @classmethod | ||
| def ft_valid_number( | ||
| cls, | ||
| X: np.ndarray, | ||
| y: np.ndarray) -> float: | ||
| """Metafeature: float type.""" | ||
| return 0.0 | ||
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| @classmethod | ||
| def ft_valid_array( | ||
| cls, | ||
| X: np.ndarray, | ||
| y: np.ndarray) -> np.ndarray: | ||
| """Metafeature: float type.""" | ||
| return np.zeros(5) | ||
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| @classmethod | ||
| def ft_raise_expection( | ||
| cls, | ||
| X: np.ndarray, | ||
| y: np.ndarray, | ||
| raise_exception: False) -> float: | ||
| """Metafeature: float type.""" | ||
| if raise_exception: | ||
| raise ValueError("Expected exception (feature).") | ||
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| return -1.0 | ||
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| class TestArchitecture: | ||
| """Tests for the framework architecture.""" | ||
| def test_postprocessing_valid(self): | ||
| """Test valid postprocessing and its automatic detection.""" | ||
| results = [], [], [] | ||
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| _internal.post_processing( | ||
| results=results, | ||
| groups=tuple(), | ||
| custom_class_=MFETestClass) | ||
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| assert all(map(lambda l: len(l) > 0, results)) | ||
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| def test_postprocessing_invalid_1(self): | ||
| """Test exception handling in invalid postprocessing.""" | ||
| results = [], [], [] | ||
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| with pytest.warns(UserWarning): | ||
| _internal.post_processing( | ||
| results=results, | ||
| groups=tuple(), | ||
| custom_class_=MFETestClass, | ||
| raise_exception=True) | ||
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| def test_postprocessing_invalid_2(self): | ||
| """Test incorrect return value in postprocessing methods.""" | ||
| results = [], [], [] | ||
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| with pytest.warns(UserWarning): | ||
| _internal.post_processing( | ||
| results=results, | ||
| groups=tuple(), | ||
| custom_class_=MFETestClass, | ||
| number_of_lists=2) | ||
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| def test_preprocessing_valid(self): | ||
| """Test valid precomputation and its automatic detection.""" | ||
| precomp_args = _internal.process_precomp_groups( | ||
| precomp_groups=tuple(), | ||
| groups=tuple(), | ||
| custom_class_=MFETestClass) | ||
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| assert len(precomp_args) > 0 | ||
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| def test_preprocessing_invalid(self): | ||
| """Test exception handling of precomputation.""" | ||
| with pytest.warns(UserWarning): | ||
| _internal.process_precomp_groups( | ||
| precomp_groups=tuple(), | ||
| groups=tuple(), | ||
| custom_class_=MFETestClass, | ||
| raise_exception=True) | ||
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| def test_feature_detection(self): | ||
| """Test automatic dectection of metafeature extraction method.""" | ||
| name, mtd, groups = _internal.process_features( | ||
| features="all", | ||
| groups=tuple(), | ||
| suppress_warnings=True, | ||
| custom_class_=MFETestClass) | ||
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| assert len(name) == 3 and len(mtd) == 3 and len(groups) == 1 |