def test_04_02_get_categories(self):
workspace, module = self.make_workspace(
dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)))
categories = module.get_categories(workspace.pipeline, "Foo")
self.assertEqual(len(categories), 0)
categories = module.get_categories(workspace.pipeline, cellprofiler.measurement.IMAGE)
self.assertEqual(len(categories), 1)
self.assertEqual(categories[0], cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP)
def test_04_02_get_categories(self):
workspace, module = self.make_workspace(
dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)))
categories = module.get_categories(workspace.pipeline, "Foo")
self.assertEqual(len(categories), 0)
categories = module.get_categories(workspace.pipeline, cellprofiler.measurement.IMAGE)
self.assertEqual(len(categories), 1)
self.assertEqual(categories[0], cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP)
def test_get_categories():
workspace, module = make_workspace(dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)))
categories = module.get_categories(workspace.pipeline, "Foo")
assert len(categories) == 0
categories = module.get_categories(workspace.pipeline,
cellprofiler.measurement.IMAGE)
assert len(categories) == 1
assert categories[
0] == cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP
def test_get_categories_other(self):
module = cellprofiler.module.ImageSegmentation()
module.x_name.value = "Image"
actual = module.get_categories(None, "foo")
expected = []
assert actual == expected
def test_get_categories_other(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, "foo")
expected = []
assert actual == expected
def test_get_categories_other(self):
module = cellprofiler.module.ImageSegmentation()
module.x_name.value = "Image"
actual = module.get_categories(None, "foo")
expected = []
assert actual == expected
def test_get_categories_other(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, "foo")
expected = []
assert actual == expected
def test_get_categories_image(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, cellprofiler.measurement.IMAGE)
expected = [cellprofiler.measurement.C_COUNT]
assert actual == expected
def test_get_categories_image(self):
module = cellprofiler.module.ImageSegmentation()
module.x_name.value = "Image"
actual = module.get_categories(None, cellprofiler.measurement.IMAGE)
expected = [cellprofiler.measurement.C_COUNT]
assert actual == expected
def test_get_categories_input_object(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, "Objects")
expected = [cellprofiler.measurement.C_CHILDREN]
assert actual == expected
def test_get_categories_image(self):
module = cellprofiler.module.ImageSegmentation()
module.x_name.value = "Image"
actual = module.get_categories(None, cellprofiler.measurement.IMAGE)
expected = [
cellprofiler.measurement.C_COUNT
]
assert actual == expected
def test_get_categories_image(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, cellprofiler.measurement.IMAGE)
expected = [
cellprofiler.measurement.C_COUNT
]
assert actual == expected
def test_get_categories_input_object(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, "Objects")
expected = [
cellprofiler.measurement.C_CHILDREN
]
assert actual == expected
def test_get_categories_output_object(self):
module = cellprofiler.module.ImageSegmentation()
module.x_name.value = "Image"
actual = module.get_categories(None, "ImageSegmentation")
expected = [
cellprofiler.measurement.C_LOCATION,
cellprofiler.measurement.C_NUMBER,
]
assert actual == expected
def test_get_categories_output_object(self):
module = cellprofiler.module.ImageSegmentation()
module.x_name.value = "Image"
actual = module.get_categories(None, "ImageSegmentation")
expected = [
cellprofiler.measurement.C_LOCATION,
cellprofiler.measurement.C_NUMBER
]
assert actual == expected
def test_get_categories_output_object(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, "ObjectProcessing")
expected = [
cellprofiler.measurement.C_LOCATION,
cellprofiler.measurement.C_NUMBER,
cellprofiler.measurement.C_PARENT,
]
assert actual == expected
def test_get_categories_output_object(self):
module = cellprofiler.module.ObjectProcessing()
module.x_name.value = "Objects"
actual = module.get_categories(None, "ObjectProcessing")
expected = [
cellprofiler.measurement.C_LOCATION,
cellprofiler.measurement.C_NUMBER,
cellprofiler.measurement.C_PARENT
]
assert actual == expected
def test_01_get_measurements():
module = (cellprofiler.modules.measureobjectintensitydistribution.
MeasureObjectIntensityDistribution())
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
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 [x.image_name.value for x in module.images]:
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,
)
