def _parse_roi(self, raw_roi_dict):
"""Extract the vector animation parameters from the ROI.
This includes the position and size at the given timepoints.
Args:
raw_roi_dict: dictionary of raw roi metadata
Returns:
dict: the parsed ROI metadata
"""
number_of_timepoints = raw_roi_dict[six.b('m_vectAnimParams_Size')]
roi_dict = {
"timepoints": [],
"positions": [],
"sizes": [],
"shape": parse_roi_shape(raw_roi_dict[six.b('m_sInfo')][six.b('m_uiShapeType')]),
"type": parse_roi_type(raw_roi_dict[six.b('m_sInfo')][six.b('m_uiInterpType')])
}
for i in range(number_of_timepoints):
roi_dict = self._parse_vect_anim(roi_dict, raw_roi_dict[six.b('m_vectAnimParams_%d' % i)])
# convert to NumPy arrays
roi_dict["timepoints"] = np.array(roi_dict["timepoints"], dtype=np.float)
roi_dict["positions"] = np.array(roi_dict["positions"], dtype=np.float)
roi_dict["sizes"] = np.array(roi_dict["sizes"], dtype=np.float)
return roi_dict
def test_parse_roi_shape(self):
self.assertEqual(parse_roi_shape(3), 'rectangle')
self.assertEqual(parse_roi_shape(9), 'circle')
self.assertIsNone(parse_roi_shape(-1))
