Python ExpectedColumnNamesValidator Examples

Example #1

File: test_validators.py Project: schelv/evalutils

def test_expected_columns_ok():
    validator = ExpectedColumnNamesValidator(expected=(
        'foo',
        'bar',
    ))
    df = DataFrame(columns=['foo', 'bar'])
    validator.validate(df=df)

Example #2

File: test_validators.py Project: schelv/evalutils

def test_expected_columns_overdefined():
    validator = ExpectedColumnNamesValidator(expected=(
        'foo',
        'bar',
    ))
    df = DataFrame(columns=['foo', 'bar', 'baz'])
    with pytest.raises(ValidationError):
        validator.validate(df=df)

Example #3

 def __init__(self):
     super().__init__(
         file_loader=CSVLoader(),
         validators=(
             ExpectedColumnNamesValidator(
                 expected=('image_id', 'x', 'y', 'score')
             ),
         ),
         join_key='image_id',
         ground_truth_path=(
             Path(__file__).parent /
             'resources' /
             'detection' /
             'reference'
         ),
         predictions_path=(
             Path(__file__).parent /
             'resources' /
             'detection' /
             'submission'
         ),
         output_file=Path('/tmp/metrics.json'),
     )
     self.detection_threshold = 0.5
     self.detection_radius = 1.0

Example #4

 def __init__(self):
     super().__init__(
         file_loader=CSVLoader(),
         ground_truth_path=(Path(__file__).parent / 'resources' /
                            'classification' / 'reference'),
         predictions_path=(Path(__file__).parent / 'resources' /
                           'classification' / 'submission'),
         output_file=Path('/tmp/metrics.json'),
         join_key='case',
         validators=(ExpectedColumnNamesValidator(expected=(
             'case',
             'class',
         )), ),
     )

Example #5

 def __init__(self):
     super().__init__(
         file_loader=CSVLoader(),
         validators=(ExpectedColumnNamesValidator(expected=(
             "image_id_roi_id",
             "pixel_size",
             "x",
             "y",
             "score",
         )), ),
         join_key="image_id_roi_id",
     )
     self.detection_threshold = 0.0
     self.detection_radius = 4 / 0.24309392273426056

Example #6

File: test_detection_evaluation.py Project: comic/evalutils

 def __init__(self, outdir):
     super().__init__(
         file_loader=CSVLoader(),
         validators=(ExpectedColumnNamesValidator(expected=("image_id", "x",
                                                            "y",
                                                            "score")), ),
         join_key="image_id",
         ground_truth_path=(Path(__file__).parent / "resources" /
                            "detection" / "reference"),
         predictions_path=(Path(__file__).parent / "resources" /
                           "detection" / "submission"),
         output_file=Path(outdir) / "metrics.json",
         detection_threshold=0.5,
         detection_radius=1.0,
     )

Example #7

File: test_classification_evaluation.py Project: sjoerdk/evalutils

 def __init__(self, outdir):
     super().__init__(
         file_loader=CSVLoader(),
         ground_truth_path=(
             Path(__file__).parent
             / "resources"
             / "classification"
             / "reference"
         ),
         predictions_path=(
             Path(__file__).parent
             / "resources"
             / "classification"
             / "submission"
         ),
         output_file=Path(outdir) / "metrics.json",
         join_key="case",
         validators=(
             ExpectedColumnNamesValidator(expected=("case", "class")),
         ),
     )

Example #8

File: test_validators.py Project: comic/evalutils

def test_expected_columns_ok():
    validator = ExpectedColumnNamesValidator(expected=("foo", "bar"))
    df = DataFrame(columns=["foo", "bar"])
    validator.validate(df=df)

Example #9

File: test_validators.py Project: comic/evalutils

def test_expected_columns_overdefined():
    validator = ExpectedColumnNamesValidator(expected=("foo", "bar"))
    df = DataFrame(columns=["foo", "bar", "baz"])
    with pytest.raises(ValidationError):
        validator.validate(df=df)

Example #10

File: test_validators.py Project: comic/evalutils

def test_expected_columns_creation():
    with pytest.raises(ValueError):
        # noinspection PyTypeChecker
        ExpectedColumnNamesValidator(expected=())