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]
