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_normalize_features_one(): """Test create_ffiles._normalize_features with one point.""" feature_list = [features.Width(), features.Height()] prepared = [([123], 1)] is_traindata = True out = create_ffiles._normalize_features(feature_list, prepared, is_traindata) assert out == [([0.0], 1)]
def normalize_features_one_test(): """Test create_ffiles._normalize_features with one point.""" feature_list = [features.Width(), features.Height()] prepared = [([123], 1)] is_traindata = True out = create_ffiles._normalize_features(feature_list, prepared, is_traindata) nose.tools.assert_equal(out, [([0.0], 1)])
def test_normalize_features_two_classes(): """Test create_ffiles._normalize_features with two classes.""" feature_list = [features.Width(), features.Height()] prepared = [([123], 1), ([100], 1), ([500], 2)] is_traindata = True out = create_ffiles._normalize_features(feature_list, prepared, is_traindata) # Mean: 241; Range: 400 assert out == [([-0.295], 1), ([-0.3525], 1), ([0.6475], 2)]
def test_normalize_features_two_feats2(): """Test create_ffiles._normalize_features with two points.""" feature_list = [features.Width(), features.Height()] prepared = [([123, 123], 1), ([100, 100], 1)] is_traindata = True out = create_ffiles._normalize_features(feature_list, prepared, is_traindata) # Mean: 111.5; Range: 23 assert out == [([0.5, 0.5], 1), ([-0.5, -0.5], 1)] # Now the other set prepared = [([111.5, 146], 1), ([146, 111.5], 1), ([54, 54], 1)] is_traindata = False out = create_ffiles._normalize_features(feature_list, prepared, is_traindata) assert out == [([0.0, 1.5], 1), ([1.5, 0.0], 1), ([-2.5, -2.5], 1)]
def test_normalize_features_two(): """Test create_ffiles._normalize_features with two points.""" feature_list = [features.Width(), features.Height()] prepared = [([123], 1), ([100], 1)] is_traindata = True out = create_ffiles._normalize_features(feature_list, prepared, is_traindata) # Mean: 111.5; Range: 23 assert out == [([0.5], 1), ([-0.5], 1)] # Now the other set prepared = [([111.5], 1), ([90], 1), ([180], 1)] is_traindata = False out = create_ffiles._normalize_features(feature_list, prepared, is_traindata) assert out == [([0.0], 1), ([-0.93478260869565222], 1), ([2.9782608695652173], 1)]
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)
def height_test(): feature_list = [features.Height()] a = testhelper.get_symbol_as_handwriting(97705) # TODO: Check if this is correct nose.tools.assert_equal(a.feature_extraction(feature_list), [263.0])
def test_height(): feature_list = [features.Height()] a = testhelper.get_symbol_as_handwriting(97705) # TODO: Check if this is correct assert a.feature_extraction(feature_list) == [263.0]