def test_rigid_fill_exceptions(self):
"""
We test the exception raised when the marker SACR does not
exist in Data.
"""
#Test that the marker SACR must exist:
with pytest.raises(Exception):
data = self.data
static = self.static
Pipelines.rigid_fill(data, static)
def test_rigid_fill_transform_from_static(self):
"""
This function tests Pipelines.rigid_fill(Data, static),
where Data is an array of dictionaries of marker data,
and static is an array of dictionaries of static trial data.
Pipelines.rigid_fill() fills gaps for frames with missing data using
the transform functions Pipelines.transform_from_static and
Pipelines.transform_from_mov.
Pipelines.rigid_fill() determines whether to call transform_from_static
or transform_from_mov by determining if there is a previous frame where
all markers in the cluster of the missing marker exist, and can be used
to create an inverse transformation matrix to determine
the position of the missing marker in the current frame. If there is,
transform_from_mov is used. Otherwise, transform_from_static, which uses
static data to reconstruct missing markers, is used.
This function tests that rigid_fill will properly call transform_from_static
by using Pipelines.clearMarker() to clear the value of a given key at all
frames. Since there are no other frames to reconstruct the inverse transform
off of, we expect the function to use transform_from_static.
"""
#The sacrum marker must exist in data to use rigid_fill
#Use data with the LFHD marker cleared from every frame
data = self.data_with_sacrum_clear_marker
static = self.static
#Return value from transform_from_static is mocked
mock_return_val = np.array([1, 2, 3])
with mock.patch.object(Pipelines, 'transform_from_static', return_value=mock_return_val) as mock_transform_from_static:
#Call Pipelines.rigid_fill with the mocked transform_from_static
rigid_fill_data = Pipelines.rigid_fill(data, static)
mock_transform_from_static.assert_called()
result = rigid_fill_data['LFHD'][10]
np.testing.assert_almost_equal(result, np.array([1, 2, 3]), self.rounding_precision)
def test_rigid_fill_transform_from_mov(self):
"""
This function tests that Pipelines.rigid_fill() will properly call transform_from_mov
by clearing the value of a marker at only one frame. We expect transform_from_mov
to be called in this case since there are previous markers to create the
inverse transform matrix from.
"""
#Use data with all markers
data = self.data_with_sacrum
static = self.static
#Clear marker LFHD from frame 10
data['LFHD'][10] = np.array([np.nan, np.nan, np.nan])
#Return value from transform_from_mov is mocked
mock_return_val = np.array([1, 2, 3])
with mock.patch.object(Pipelines, 'transform_from_mov', return_value=mock_return_val) as mock_transform_from_mov:
#Call Pipelines.rigid_fill with the mocked transform_from_static
rigid_fill_data = Pipelines.rigid_fill(data, static)
mock_transform_from_mov.assert_called()
result = rigid_fill_data['LFHD'][10]
np.testing.assert_almost_equal(result, np.array([1, 2, 3]), self.rounding_precision)