def test_labels_frequency(self):
annotations = [[1, 1, 2], [-1, 1, 2]]
nclasses = 4
expected_result = [0., 0.6, 0.4, 0.0]
result = voting.labels_frequency(annotations, nclasses)
#self.assertAlmostEqual(expected_result, list(result)) #AlmostEqual not working on np.arrays but lists
assert_array_almost_equal(expected_result, result) #Probably better
def test_labels_frequency(self):
annotations = [[1, 1, 2], [-1, 1, 2]]
nclasses = 4
expected_result = [0., 0.6, 0.4, 0.0]
result = voting.labels_frequency(annotations, nclasses)
#self.assertAlmostEqual(expected_result, list(result)) #AlmostEqual not working on np.arrays but lists
assert_array_almost_equal(expected_result, result) #Probably better
def test_label_frequency(self):
annotations = [[1, 1, 2], [-1, 1, 2]]
nclasses = 4
expected = np.array([0., 0.6, 0.4, 0.])
result = voting.labels_frequency(annotations, nclasses)
assert_array_almost_equal(expected, result, 2)
def test_label_frequency(self): annotations = [[1, 1, 2], [-1, 1, 2]] nclasses = 4 expected = np.array([ 0. , 0.6, 0.4, 0. ]) result = voting.labels_frequency(annotations, nclasses) assert_array_almost_equal(expected, result, 2)
def test_labels_frequency(self):
annotations = [[1, 2, MV, MV], [MV, MV, 3, 3], [MV, 1, 3, 1],
[MV, MV, MV, MV]]
nclasses = 5
expected = np.array([0., 3., 1., 3., 0.]) / 7.
result = voting.labels_frequency(annotations, nclasses)
np.testing.assert_almost_equal(result, expected)
def test_labels_frequency():
matrix = [
[1, 2, 2, -1],
[2, 2, 2, 2],
[1, 1, 3, 3],
[1, 3, 3, 2],
[-1, 2, 3, 1],
[-1, -1, -1, 3],
]
result = voting.labels_frequency(matrix, 4)
assert np.all([res != None for res in result])
assert len(result) == 4
assert np.all(
voting.labels_frequency([[-1, -1, -1, -1], [-1, -1, -1, -1]], 4) ==
np.zeros(4))
assert np.all([i >= 0 and i <= 1 for i in result])
assert isclose(np.sum(result), 1) or isclose(
np.sum(result), 0, abs_tol=1e-12)
def test_labels_frequency(self):
annotations = [
[ 1, 2, MV, MV],
[MV, MV, 3, 3],
[MV, 1, 3, 1],
[MV, MV, MV, MV]
]
nclasses = 5
expected = np.array([0., 3., 1., 3., 0.]) / 7.
result = voting.labels_frequency(annotations, nclasses)
np.testing.assert_almost_equal(result, expected)
def test_labels_freq(self):
annotations=[[1, 1, 2], [-1, 1, 2]]
nclasses=4
#annotations = [
# [1, 2, MV, MV],
# [MV, MV, 3, 3],
# [MV, 1, 3, 1],
# [MV, MV, MV, MV],
#]
#nclasses = 5
#expected = [0, 3, 1, 3, 0]
expected=[ 0. , 0.6, 0.4, 0. ]
result = voting.labels_frequency(annotations, nclasses)
self.assertAlmostEqual(result, expected,5)
def test_labels_freq(self):
annotations = [[1, 1, 2], [-1, 1, 2]]
nclasses = 4
#annotations = [
# [1, 2, MV, MV],
# [MV, MV, 3, 3],
# [MV, 1, 3, 1],
# [MV, MV, MV, MV],
#]
#nclasses = 5
#expected = [0, 3, 1, 3, 0]
expected = [0., 0.6, 0.4, 0.]
result = voting.labels_frequency(annotations, nclasses)
self.assertAlmostEqual(result, expected, 5)
def test_labels_frequency(self):
result = voting.labels_frequency([[1, 1, 2], [-1, 1, 2]], 4)
expected = np.asarray([0., 0.6, 0.4, 0.])
assert_array_almost_equal(result, expected)
def test_exception_all_missing(self):
with self.assertRaises(PyannoValueError):
result = voting.labels_frequency([[MV, MV, MV], [MV, MV, MV]], 4)
def test_labels_frequency(self):
result = voting.labels_frequency([[1, 1, 2], [-1, 1, 2]], 4)
expected = np.asarray([ 0. , 0.6, 0.4, 0. ])
assert_array_almost_equal(result, expected)
def test_exception_empty_list(self):
with self.assertRaises(PyannoValueError):
result = voting.labels_frequency([], 4)
def test_different_missing_value(self):
annotations = np.array([[1, 1, 2], [MV, 1, 2]])
expected = [0.0, 0.6, 0.4, 0.0]
result = voting.labels_frequency(annotations, 4, MV)
print(result)
np.testing.assert_array_almost_equal(expected, result)
def test_different_missing_value(self):
annotations = np.array([[1, 1, 2], [MV, 1, 2]])
expected = [0., 0.6, 0.4, 0.]
result = voting.labels_frequency(annotations, 4, MV)
print(result)
np.testing.assert_array_almost_equal(expected, result)
def test_exception_empty_list(self):
with self.assertRaises(PyannoValueError):
result = voting.labels_frequency([], 4)
def test_exception_all_missing(self):
with self.assertRaises(PyannoValueError):
result = voting.labels_frequency([[MV, MV, MV], [MV, MV, MV]], 4)