def test_get_measurement_scales():
workspace, module = make_workspace(dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)))
scales = module.get_measurement_scales(
workspace.pipeline,
"Image",
cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP,
cellprofiler.modules.measureimageoverlap.FTR_RAND_INDEX,
None,
)
assert len(scales) == 0
def test_get_measurement_scales():
workspace, module = make_obj_workspace(
numpy.zeros((0, 3), int),
numpy.zeros((0, 3), int),
dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)),
)
scales = module.get_measurement_scales(
workspace.pipeline,
"Image",
cellprofiler.modules.measureobjectoverlap.C_IMAGE_OVERLAP,
cellprofiler.modules.measureobjectoverlap.FTR_RAND_INDEX,
None,
)
assert len(scales) == 1
assert scales[0] == "_".join((GROUND_TRUTH_OBJ, ID_OBJ))
def test_02_get_zernike_measurements():
module = (cellprofiler.modules.measureobjectintensitydistribution.
MeasureObjectIntensityDistribution())
for wants_zernikes, ftrs in (
(
cellprofiler.modules.measureobjectintensitydistribution.
Z_MAGNITUDES,
(cellprofiler.modules.measureobjectintensitydistribution.
FF_ZERNIKE_MAGNITUDE, ),
),
(
cellprofiler.modules.measureobjectintensitydistribution.
Z_MAGNITUDES_AND_PHASE,
(
cellprofiler.modules.measureobjectintensitydistribution.
FF_ZERNIKE_MAGNITUDE,
cellprofiler.modules.measureobjectintensitydistribution.
FF_ZERNIKE_PHASE,
),
),
):
module.wants_zernikes.value = wants_zernikes
module.zernike_degree.value = 2
module.images_list.value = "DNA, Cytoplasm, Actin"
for i, object_name, center_name in (
(0, "Nucleii", None),
(1, "Cells", "Nucleii"),
(2, "Cytoplasm", "Nucleii"),
):
if i:
module.add_object()
module.objects[i].object_name.value = object_name
if center_name is None:
module.objects[i].center_choice.value = (
cellprofiler.modules.measureobjectintensitydistribution.
C_SELF)
else:
module.objects[i].center_choice.value = (
cellprofiler.modules.measureobjectintensitydistribution.
C_CENTERS_OF_OTHER)
module.objects[i].center_object_name.value = center_name
for object_name in "Nucleii", "Cells", "Cytoplasm":
result = module.get_measurements(
None,
object_name,
cellprofiler.modules.measureobjectintensitydistribution.
M_CATEGORY,
)
for ftr in ftrs:
assert ftr in result
iresult = module.get_measurement_images(
None,
object_name,
cellprofiler.modules.measureobjectintensitydistribution.
M_CATEGORY,
ftr,
)
for image in "DNA", "Cytoplasm", "Actin":
assert image in iresult
sresult = module.get_measurement_scales(
None,
object_name,
cellprofiler.modules.
measureobjectintensitydistribution.M_CATEGORY,
ftr,
image,
)
for n, m in ((0, 0), (1, 1), (2, 0), (2, 2)):
assert "%d_%d" % (n, m) in sresult
def test_01_get_measurements():
module = (cellprofiler.modules.measureobjectintensitydistribution.
MeasureObjectIntensityDistribution())
module.images_list.value = "DNA, Cytoplasm, Actin"
for i, object_name, center_name in (
(0, "Nucleii", None),
(1, "Cells", "Nucleii"),
(2, "Cytoplasm", "Nucleii"),
):
if i:
module.add_object()
module.objects[i].object_name.value = object_name
if center_name is None:
module.objects[i].center_choice.value = (
cellprofiler.modules.measureobjectintensitydistribution.C_SELF)
else:
module.objects[i].center_choice.value = (
cellprofiler.modules.measureobjectintensitydistribution.
C_CENTERS_OF_OTHER)
module.objects[i].center_object_name.value = center_name
for i, bin_count in ((0, 4), (0, 5), (0, 6)):
if i:
module.add_bin_count()
module.bin_counts[i].bin_count.value = bin_count
for object_name in [x.object_name.value for x in module.objects]:
assert tuple(module.get_categories(None, object_name)) == (
cellprofiler.modules.measureobjectintensitydistribution.M_CATEGORY,
)
for feature in cellprofiler.modules.measureobjectintensitydistribution.F_ALL:
assert feature in module.get_measurements(
None,
object_name,
cellprofiler.modules.measureobjectintensitydistribution.
M_CATEGORY,
)
for image_name in module.images_list.value:
for (
feature
) in cellprofiler.modules.measureobjectintensitydistribution.F_ALL:
assert image_name in module.get_measurement_images(
None,
object_name,
cellprofiler.modules.measureobjectintensitydistribution.
M_CATEGORY,
feature,
)
for bin_count in [x.bin_count.value for x in module.bin_counts]:
for bin in range(1, bin_count + 1):
for (
feature
) in cellprofiler.modules.measureobjectintensitydistribution.F_ALL:
assert "%dof%d" % (
bin,
bin_count,
) in module.get_measurement_scales(
None,
object_name,
cellprofiler.modules.
measureobjectintensitydistribution.M_CATEGORY,
feature,
image_name,
)
