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)