def test_02_03_default_heatmap_values(self):
module = M.MeasureObjectRadialDistribution()
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[0].image_name.value = "Bar"
module.objects[0].object_name.value = "Foo"
module.bin_counts[0].bin_count.value = 2
self.assertEqual(module.heatmaps[0].image_name.get_image_name(), "Bar")
self.assertFalse(module.heatmaps[0].image_name.is_visible())
self.assertEqual(module.heatmaps[0].object_name.get_objects_name(),
"Foo")
self.assertFalse(module.heatmaps[0].object_name.is_visible())
self.assertEqual(module.heatmaps[0].get_number_of_bins(), 2)
module.add_image()
self.assertTrue(module.heatmaps[0].image_name.is_visible())
self.assertEqual(module.heatmaps[0].image_name.get_image_name(),
IMAGE_NAME)
module.add_object()
self.assertTrue(module.heatmaps[0].object_name.is_visible())
self.assertEqual(module.heatmaps[0].object_name.get_objects_name(),
OBJECT_NAME)
module.add_bin_count()
self.assertEqual(module.heatmaps[0].get_number_of_bins(), 10)
def run_module(self, image, labels, center_labels = None, bin_count = 4):
'''Run the module, returning the measurements
image - matrix representing the image to be analyzed
labels - labels matrix of objects to be analyzed
center_labels - labels matrix of alternate centers or None for self
centers
bin_count - # of radial bins
'''
module = M.MeasureObjectRadialDistribution()
module.images[0].image_name.value = IMAGE_NAME
module.objects[0].object_name.value = OBJECT_NAME
object_set = cpo.ObjectSet()
main_objects = cpo.Objects()
main_objects.segmented = labels
object_set.add_objects(main_objects, OBJECT_NAME)
if center_labels is None:
module.objects[0].center_choice.value = M.C_SELF
else:
module.objects[0].center_choice.value = M.C_OTHER
module.objects[0].center_object_name.value = CENTER_NAME
center_objects = cpo.Objects()
center_objects.segmented = center_labels
object_set.add_objects(center_objects, CENTER_NAME)
module.bin_counts[0].bin_count.value = bin_count
pipeline = cpp.Pipeline()
measurements = cpmeas.Measurements()
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
img = cpi.Image(image)
image_set.add(IMAGE_NAME, img)
workspace = cpw.Workspace(pipeline, module, image_set, object_set,
measurements, image_set_list)
module.run(workspace)
return measurements
def run_module(self, image, labels, center_labels = None,
center_choice = M.C_CENTERS_OF_OTHER,
bin_count = 4,
maximum_radius = 100, wants_scaled = True,
wants_workspace=False):
'''Run the module, returning the measurements
image - matrix representing the image to be analyzed
labels - labels matrix of objects to be analyzed
center_labels - labels matrix of alternate centers or None for self
centers
bin_count - # of radial bins
'''
module = M.MeasureObjectRadialDistribution()
module.images[0].image_name.value = IMAGE_NAME
module.objects[0].object_name.value = OBJECT_NAME
object_set = cpo.ObjectSet()
main_objects = cpo.Objects()
main_objects.segmented = labels
object_set.add_objects(main_objects, OBJECT_NAME)
if center_labels is None:
module.objects[0].center_choice.value = M.C_SELF
else:
module.objects[0].center_choice.value = center_choice
module.objects[0].center_object_name.value = CENTER_NAME
center_objects = cpo.Objects()
center_objects.segmented = center_labels
object_set.add_objects(center_objects, CENTER_NAME)
module.bin_counts[0].bin_count.value = bin_count
module.bin_counts[0].wants_scaled.value = wants_scaled
module.bin_counts[0].maximum_radius.value = maximum_radius
module.add_heatmap()
module.add_heatmap()
module.add_heatmap()
for i, (a, f) in enumerate(
((M.A_FRAC_AT_D, M.F_FRAC_AT_D),
(M.A_MEAN_FRAC, M.F_MEAN_FRAC),
(M.A_RADIAL_CV, M.F_RADIAL_CV))):
module.heatmaps[i].image_name.value = IMAGE_NAME
module.heatmaps[i].object_name.value = OBJECT_NAME
module.heatmaps[i].bin_count.value = str(bin_count)
module.heatmaps[i].wants_to_save_display.value = True
display_name = HEAT_MAP_NAME+f
module.heatmaps[i].display_name.value = display_name
module.heatmaps[i].colormap.value = "gray"
module.heatmaps[i].measurement.value = a
pipeline = cpp.Pipeline()
measurements = cpmeas.Measurements()
image_set_list = cpi.ImageSetList()
image_set = measurements
img = cpi.Image(image)
image_set.add(IMAGE_NAME, img)
workspace = cpw.Workspace(pipeline, module, image_set, object_set,
measurements, image_set_list)
module.run(workspace)
if wants_workspace:
return measurements, workspace
return measurements
def test_02_01_get_measurement_columns(self):
module = M.MeasureObjectRadialDistribution()
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 = M.C_SELF
else:
module.objects[i].center_choice.value = M.C_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)
self.assertFalse(column_dictionary.has_key(key))
self.assertEqual(coltype, cpmeas.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 [x.image_name.value for x in module.images]:
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)
self.assertTrue(column_dictionary.has_key(key))
del column_dictionary[key]
self.assertEqual(len(column_dictionary), 0)
def test_02_02_get_measurements(self):
module = M.MeasureObjectRadialDistribution()
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 = M.C_SELF
else:
module.objects[i].center_choice.value = M.C_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]:
self.assertEqual(tuple(module.get_categories(None, object_name)),
(M.M_CATEGORY, ))
for feature in M.F_ALL:
self.assertTrue(feature in module.get_measurements(
None, object_name, M.M_CATEGORY))
for image_name in [x.image_name.value for x in module.images]:
for feature in M.F_ALL:
self.assertTrue(
image_name in module.get_measurement_images(
None, object_name, M.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 M.F_ALL:
self.assertTrue(
"%dof%d" %
(bin,
bin_count) in module.get_measurement_scales(
None, object_name, M.M_CATEGORY, feature,
image_name))
def test_02_01_get_measurement_columns(self):
module = M.MeasureObjectRadialDistribution()
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 = M.C_SELF
else:
module.objects[i].center_choice.value = M.C_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
columns = module.get_measurement_columns(None)
column_dictionary = {}
for object_name, feature, coltype in columns:
key = (object_name, feature)
self.assertFalse(column_dictionary.has_key(key))
self.assertEqual(coltype, cpmeas.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 [x.image_name.value for x in module.images]:
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 M.F_ALL:
measurement = "_".join((M.M_CATEGORY,
feature,
image_name,
"%dof%d"%(bin, bin_count)))
key = (object_name, measurement)
self.assertTrue(column_dictionary.has_key(key))
del column_dictionary[key]
self.assertEqual(len(column_dictionary), 0)