def atest_eval_sliver_matrics(self):
import volumetry_evaluation as ve
vol1 = np.zeros([20, 21, 22], dtype=np.int8)
vol1[10:15, 10:15, 10:15] = 1
vol2 = np.zeros([20, 21, 22], dtype=np.int8)
vol2[10:15, 10:16, 10:15] = 1
eval1 = ve.compare_volumes(vol1, vol2, [1, 1, 1])
print eval1
def sliver_compare_with_other_volume(self, segmentation_datap):
"""
Compares actual Lisa data with other which are given by
segmentation_datap. That means
segmentation_datap = {
'segmentation': 3d np.array,
'crinfo': information about crop (optional)
}
"""
# if there is no segmentation, data can be stored in data3d. It is the
# way how are data stored in sliver.
if 'segmentation' in segmentation_datap.keys():
segm_key = 'segmentation'
else:
segm_key = 'data3d'
if 'crinfo' in segmentation_datap.keys():
data3d_segmentation = qmisc.uncrop(
segmentation_datap[segm_key],
segmentation_datap['crinfo'],
self.orig_shape)
else:
data3d_segmentation = segmentation_datap[segm_key]
pass
# now we can uncrop actual Lisa data
data3d_segmentation_actual = qmisc.uncrop(
self.segmentation,
self.crinfo,
self.orig_shape)
evaluation = volumetry_evaluation.compare_volumes(
data3d_segmentation_actual,
data3d_segmentation,
self.voxelsize_mm
)
score = volumetry_evaluation.sliver_score_one_couple(evaluation)
segdiff = qmisc.crop(
((data3d_segmentation) - data3d_segmentation_actual),
self.crinfo)
return evaluation, score, segdiff