def test_01_get_measurement_columns():
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 enumerate((4, 5, 6)):
if i:
module.add_bin_count()
module.bin_counts[i].bin_count.value = bin_count
module.bin_counts[2].wants_scaled.value = False
columns = module.get_measurement_columns(None)
column_dictionary = {}
for object_name, feature, coltype in columns:
key = (object_name, feature)
assert not (key in column_dictionary)
assert coltype == cellprofiler_core.measurement.COLTYPE_FLOAT
column_dictionary[key] = (object_name, feature, coltype)
for object_name in [x.object_name.value for x in module.objects]:
for image_name in module.images_list.value:
for bin_count, wants_scaled in [
(x.bin_count.value, x.wants_scaled.value) for x in module.bin_counts
]:
for bin in range(1, bin_count + (1 if wants_scaled else 2)):
for feature_fn in (
feature_frac_at_d,
feature_mean_frac,
feature_radial_cv,
):
measurement = feature_fn(bin, bin_count, image_name)
key = (object_name, measurement)
assert key in column_dictionary
del column_dictionary[key]
assert len(column_dictionary) == 0
def test_02_get_zernike_columns():
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
for i, image_name in ((0, "DNA"), (1, "Cytoplasm"), (2, "Actin")):
if i:
module.add_image()
module.images[i].image_name.value = image_name
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
columns = module.get_measurement_columns(None)
for image_name in "DNA", "Cytoplasm", "Actin":
for object_name in "Nucleii", "Cells", "Cytoplasm":
for n, m in ((0, 0), (1, 1), (2, 0), (2, 2)):
for ftr in ftrs:
name = "_".join((
cellprofiler.modules.
measureobjectintensitydistribution.M_CATEGORY,
ftr,
image_name,
str(n),
str(m),
))
col = (
object_name,
name,
cellprofiler_core.measurement.COLTYPE_FLOAT,
)
assert col in columns
def test_default_heatmap_values():
module = (cellprofiler.modules.measureobjectintensitydistribution.
MeasureObjectIntensityDistribution())
module.add_heatmap()
module.heatmaps[0].image_name.value = IMAGE_NAME
module.heatmaps[0].object_name.value = OBJECT_NAME
module.heatmaps[0].bin_count.value = 10
module.images_list.value = "Bar"
module.objects[0].object_name.value = "Foo"
module.bin_counts[0].bin_count.value = 2
assert module.heatmaps[0].image_name.get_image_name() == "Bar"
assert not module.heatmaps[0].image_name.is_visible()
assert module.heatmaps[0].object_name.get_objects_name() == "Foo"
assert not module.heatmaps[0].object_name.is_visible()
assert module.heatmaps[0].get_number_of_bins() == 2
module.images_list.value = "Bar, MoreBar"
assert module.heatmaps[0].image_name.is_visible()
assert module.heatmaps[0].image_name.get_image_name() == IMAGE_NAME
module.add_object()
assert module.heatmaps[0].object_name.is_visible()
assert module.heatmaps[0].object_name.get_objects_name() == OBJECT_NAME
module.add_bin_count()
assert module.heatmaps[0].get_number_of_bins() == 10
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,
)
