def test_dimensionality(): feature_list = [ (features.StrokeCount(), 1), ( features.ConstantPointCoordinates(strokes=4, points_per_stroke=20, fill_empty_with=0), 160, ), ( features.ConstantPointCoordinates(strokes=0, points_per_stroke=20, fill_empty_with=0), 60, ), ( features.ConstantPointCoordinates(strokes=0, points_per_stroke=20, pen_down=False), 40, ), (features.AspectRatio(), 1), (features.Width(), 1), (features.Height(), 1), (features.Time(), 1), (features.CenterOfMass(), 2), ] for feat, dimension in feature_list: assert feat.get_dimension() == dimension
def test_execution(): """ Test if analyze_data.filter_label and analyze_data.analyze_feature are executable at all. """ analyze_data.filter_label("\\dag", replace_by_similar=True) analyze_data.filter_label("\\diameter", replace_by_similar=True) analyze_data.filter_label("\\degree", replace_by_similar=True) analyze_data.filter_label("\\alpha", replace_by_similar=True) raw_datasets = testhelper.get_raw_datasets() feature = features.AspectRatio() filename = "aspect_ratio.csv" analyze_data.analyze_feature(raw_datasets, feature, filename)
def simple_execution_test(): algorithms = [ features.ConstantPointCoordinates(), features.ConstantPointCoordinates(strokes=0), features.FirstNPoints(), # features.Bitmap(), features.Ink(), features.AspectRatio(), features.Width(), features.Time(), features.CenterOfMass(), features.StrokeCenter(), features.StrokeCenter(8), features.StrokeIntersections(), features.ReCurvature() ] for algorithm in algorithms: recording = testhelper.get_symbol_as_handwriting(292934) algorithm(recording)
def print_featurelist_test(): """Test features.print_featurelist.""" feature_list = [ features.StrokeCount(), features.ConstantPointCoordinates(strokes=4, points_per_stroke=20, fill_empty_with=0), features.ConstantPointCoordinates(strokes=0, points_per_stroke=20, fill_empty_with=0), features.ConstantPointCoordinates(strokes=0, points_per_stroke=20, pen_down=False), features.AspectRatio(), features.Width(), features.Height(), features.Time(), features.CenterOfMass() ] features.print_featurelist(feature_list)