def test_04_02_masked_edge(self):
# Regression test of issue #1115
labels = np.zeros((20, 50), int)
labels[15:25, 15:25] = 1
image = np.random.uniform(size=labels.shape).astype(np.float32)
#
# Mask the edge of the object
#
mask = ~cpmo.outline(labels).astype(bool)
m = cpmeas.Measurements()
m.add(IMAGE_NAME, cpi.Image(image, mask=mask))
object_set = cpo.ObjectSet()
o = cpo.Objects()
o.segmented = labels
object_set.add_objects(o, OBJECT_NAME)
pipeline = P.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, P.RunExceptionEvent))
pipeline.add_listener(callback)
module = MOI.MeasureObjectIntensity()
module.module_num = 1
module.images[0].name.value = IMAGE_NAME
module.objects[0].name.value = OBJECT_NAME
pipeline.add_module(module)
workspace = cpw.Workspace(pipeline, module, m, object_set, m, None)
module.run(workspace)
def test_03_04_quartiles(self):
"""test quartile values on a 250x250 square filled with uniform values"""
labels = np.ones((250, 250), int)
np.random.seed(0)
image = np.random.uniform(size=(250, 250))
ii = II.InjectImage('MyImage', image)
ii.module_num = 1
io = II.InjectObjects('MyObjects', labels)
io.module_num = 2
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.objects[0].name.value = 'MyObjects'
moi.module_num = 3
pipeline = P.Pipeline()
pipeline.add_listener(self.error_callback)
pipeline.add_module(ii)
pipeline.add_module(io)
pipeline.add_module(moi)
m = pipeline.run()
feature_name = '%s_%s_%s' % (MOI.INTENSITY,
MOI.LOWER_QUARTILE_INTENSITY, 'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], .25, 2)
feature_name = '%s_%s_%s' % (MOI.INTENSITY, MOI.MEDIAN_INTENSITY,
'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], .50, 2)
feature_name = '%s_%s_%s' % (MOI.INTENSITY, MOI.MAD_INTENSITY,
'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], 0.25, 2)
feature_name = '%s_%s_%s' % (MOI.INTENSITY,
MOI.UPPER_QUARTILE_INTENSITY, 'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], .75, 2)
def test_04_01_wrong_image_size(self):
'''Regression test of IMG-961 - object and image size differ'''
np.random.seed(41)
labels = np.ones((20, 50), int)
image = np.random.uniform(size=(30, 40)).astype(np.float32)
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
image_set.add('MyImage', cpi.Image(image))
object_set = cpo.ObjectSet()
o = cpo.Objects()
o.segmented = labels
object_set.add_objects(o, "MyObjects")
pipeline = P.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, P.RunExceptionEvent))
pipeline.add_listener(callback)
module = MOI.MeasureObjectIntensity()
module.module_num = 1
module.images[0].name.value = "MyImage"
module.objects[0].name.value = "MyObjects"
pipeline.add_module(module)
workspace = cpw.Workspace(pipeline, module, image_set, object_set,
cpmeas.Measurements(), image_set_list)
module.run(workspace)
feature_name = '%s_%s_%s' % (MOI.INTENSITY, MOI.INTEGRATED_INTENSITY,
"MyImage")
m = workspace.measurements.get_current_measurement(
"MyObjects", feature_name)
self.assertEqual(len(m), 1)
self.assertAlmostEqual(m[0], np.sum(image[:20, :40]), 4)
def test_03_01_01_masked(self):
"""Make sure we can process a completely masked image
Regression test of IMG-971
"""
ii = II.InjectImage('MyImage', np.zeros((10, 10)),
np.zeros((10, 10), bool))
ii.module_num = 1
io = II.InjectObjects('MyObjects', np.ones((10, 10), int))
io.module_num = 2
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.objects[0].name.value = 'MyObjects'
moi.module_num = 3
pipeline = P.Pipeline()
pipeline.add_listener(self.error_callback)
pipeline.add_module(ii)
pipeline.add_module(io)
pipeline.add_module(moi)
m = pipeline.run()
for meas_name in MOI.ALL_MEASUREMENTS:
feature_name = "%s_%s_%s" % (MOI.INTENSITY, meas_name, 'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertEqual(np.product(data.shape), 1)
self.assertTrue(np.all(np.isnan(data) | (data == 0)))
self.features_and_columns_match(m, moi)
def test_03_01_00_zero(self):
"""Make sure we can process a blank image"""
ii = II.InjectImage('MyImage', np.zeros((10, 10)))
ii.module_num = 1
io = II.InjectObjects('MyObjects', np.zeros((10, 10), int))
io.module_num = 2
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.objects[0].name.value = 'MyObjects'
moi.module_num = 3
pipeline = P.Pipeline()
pipeline.add_listener(self.error_callback)
pipeline.add_module(ii)
pipeline.add_module(io)
pipeline.add_module(moi)
m = pipeline.run()
for category, features in ((MOI.INTENSITY, MOI.ALL_MEASUREMENTS),
(MOI.C_LOCATION,
MOI.ALL_LOCATION_MEASUREMENTS)):
for meas_name in features:
feature_name = "%s_%s_%s" % (category, meas_name, 'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertEqual(np.product(data.shape), 0,
"Got data for feature %s" % feature_name)
self.features_and_columns_match(m, moi)
def test_03_03_01_mass_displacement_masked(self):
"""Regression test IMG-766 - mass displacement of a masked image"""
labels = np.array([[0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 1, 1, 1, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 2, 2, 2, 2, 2, 0],
[0, 2, 2, 2, 2, 2, 0],
[0, 2, 2, 2, 2, 2, 0],
[0, 2, 2, 2, 2, 2, 0],
[0, 2, 2, 2, 2, 2, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 3, 3, 3, 3, 3, 0],
[0, 3, 3, 3, 3, 3, 0],
[0, 3, 3, 3, 3, 3, 0],
[0, 3, 3, 3, 3, 3, 0],
[0, 3, 3, 3, 3, 3, 0],
[0, 0, 0, 0, 0, 0, 0]])
image = np.zeros(labels.shape, dtype=float)
#
# image # 1 has a single value in one of the corners
# whose distance is sqrt(8) from the center
#
image[1, 1] = 1
# image # 2 has a single value on the top edge
# and should have distance 2
#
image[7, 3] = 1
# image # 3 has a single value on the left edge
# and should have distance 2
image[15, 1] = 1
mask = np.zeros(image.shape, bool)
mask[labels > 0] = True
ii = II.InjectImage('MyImage', image, mask)
ii.module_num = 1
io = II.InjectObjects('MyObjects', labels)
io.module_num = 2
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.objects[0].name.value = 'MyObjects'
moi.module_num = 3
pipeline = P.Pipeline()
pipeline.add_listener(self.error_callback)
pipeline.add_module(ii)
pipeline.add_module(io)
pipeline.add_module(moi)
m = pipeline.run()
feature_name = '%s_%s_%s' % (MOI.INTENSITY, MOI.MASS_DISPLACEMENT, 'MyImage')
mass_displacement = m.get_current_measurement('MyObjects', feature_name)
self.assertEqual(np.product(mass_displacement.shape), 3)
self.assertAlmostEqual(mass_displacement[0], math.sqrt(8.0))
self.assertAlmostEqual(mass_displacement[1], 2.0)
self.assertAlmostEqual(mass_displacement[2], 2.0)
def test_03_06_quartiles(self):
"""test quartile values on a 250x250 square with 4 objects"""
labels = np.ones((250, 250), int)
labels[125:, :] += 1
labels[:, 125:] += 2
np.random.seed(0)
image = np.random.uniform(size=(250, 250))
#
# Make the distributions center around .5, .25, 1/6 and .125
#
image /= labels.astype(float)
ii = II.InjectImage('MyImage', image)
ii.module_num = 1
io = II.InjectObjects('MyObjects', labels)
io.module_num = 2
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.objects[0].name.value = 'MyObjects'
moi.module_num = 3
pipeline = P.Pipeline()
pipeline.add_listener(self.error_callback)
pipeline.add_module(ii)
pipeline.add_module(io)
pipeline.add_module(moi)
m = pipeline.run()
feature_name = '%s_%s_%s' % (MOI.INTENSITY,
MOI.LOWER_QUARTILE_INTENSITY, 'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], 1.0 / 4.0, 2)
self.assertAlmostEqual(data[1], 1.0 / 8.0, 2)
self.assertAlmostEqual(data[2], 1.0 / 12.0, 2)
self.assertAlmostEqual(data[3], 1.0 / 16.0, 2)
feature_name = '%s_%s_%s' % (MOI.INTENSITY, MOI.MEDIAN_INTENSITY,
'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], 1.0 / 2.0, 2)
self.assertAlmostEqual(data[1], 1.0 / 4.0, 2)
self.assertAlmostEqual(data[2], 1.0 / 6.0, 2)
self.assertAlmostEqual(data[3], 1.0 / 8.0, 2)
feature_name = '%s_%s_%s' % (MOI.INTENSITY,
MOI.UPPER_QUARTILE_INTENSITY, 'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], 3.0 / 4.0, 2)
self.assertAlmostEqual(data[1], 3.0 / 8.0, 2)
self.assertAlmostEqual(data[2], 3.0 / 12.0, 2)
self.assertAlmostEqual(data[3], 3.0 / 16.0, 2)
feature_name = '%s_%s_%s' % (MOI.INTENSITY, MOI.MAD_INTENSITY,
'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertAlmostEqual(data[0], 1.0 / 4.0, 2)
self.assertAlmostEqual(data[1], 1.0 / 8.0, 2)
self.assertAlmostEqual(data[2], 1.0 / 12.0, 2)
self.assertAlmostEqual(data[3], 1.0 / 16.0, 2)
def make_workspace(self, labels, pixel_data, mask=None):
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
image_set.add(IMAGE_NAME, cpi.Image(pixel_data, mask))
object_set = cpo.ObjectSet()
o = cpo.Objects()
o.segmented = labels
object_set.add_objects(o, OBJECT_NAME)
pipeline = P.Pipeline()
module = MOI.MeasureObjectIntensity()
module.images[0].name.value = IMAGE_NAME
module.objects[0].name.value = OBJECT_NAME
module.module_num = 1
pipeline.add_listener(self.error_callback)
pipeline.add_module(module)
workspace = cpw.Workspace(pipeline, module, image_set,
object_set, cpmeas.Measurements(),
image_set_list)
return workspace, module
def test_03_02_00_one(self):
"""Check measurements on a 3x3 square of 1's"""
img = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0]])
ii = II.InjectImage('MyImage', img.astype(float))
ii.module_num = 1
io = II.InjectObjects('MyObjects', img.astype(int))
io.module_num = 2
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.objects[0].name.value = 'MyObjects'
moi.module_num = 3
pipeline = P.Pipeline()
pipeline.add_listener(self.error_callback)
pipeline.add_module(ii)
pipeline.add_module(io)
pipeline.add_module(moi)
m = pipeline.run()
for category, meas_name, value in (
(MOI.INTENSITY, MOI.INTEGRATED_INTENSITY,
9), (MOI.INTENSITY, MOI.MEAN_INTENSITY,
1), (MOI.INTENSITY, MOI.STD_INTENSITY,
0), (MOI.INTENSITY, MOI.MIN_INTENSITY,
1), (MOI.INTENSITY, MOI.MAX_INTENSITY, 1),
(MOI.INTENSITY, MOI.INTEGRATED_INTENSITY_EDGE,
8), (MOI.INTENSITY, MOI.MEAN_INTENSITY_EDGE,
1), (MOI.INTENSITY, MOI.STD_INTENSITY_EDGE,
0), (MOI.INTENSITY, MOI.MIN_INTENSITY_EDGE,
1), (MOI.INTENSITY, MOI.MAX_INTENSITY_EDGE,
1), (MOI.INTENSITY, MOI.MASS_DISPLACEMENT, 0),
(MOI.INTENSITY, MOI.LOWER_QUARTILE_INTENSITY,
1), (MOI.INTENSITY, MOI.MEDIAN_INTENSITY,
1), (MOI.INTENSITY, MOI.UPPER_QUARTILE_INTENSITY,
1), (MOI.C_LOCATION, MOI.LOC_CMI_X,
3), (MOI.C_LOCATION, MOI.LOC_CMI_Y, 2)):
feature_name = "%s_%s_%s" % (category, meas_name, 'MyImage')
data = m.get_current_measurement('MyObjects', feature_name)
self.assertEqual(np.product(data.shape), 1)
self.assertEqual(
data[0], value,
"%s expected %f != actual %f" % (meas_name, value, data[0]))
def test_02_02_get_measurement_columns(self):
'''test the get_measurement_columns method'''
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.add_object()
moi.objects[0].name.value = 'MyObjects1'
moi.objects[1].name.value = 'MyObjects2'
columns = moi.get_measurement_columns(None)
self.assertEqual(len(columns), 2 * len(MOI.ALL_MEASUREMENTS) + 2 * len(MOI.ALL_LOCATION_MEASUREMENTS))
for column in columns:
self.assertTrue(column[0] in ('MyObjects1', 'MyObjects2'))
self.assertEqual(column[2], cpmeas.COLTYPE_FLOAT)
category = column[1].split('_')[0]
self.assertTrue(category in (MOI.INTENSITY, MOI.C_LOCATION))
if category == MOI.INTENSITY:
self.assertTrue(column[1][column[1].find('_') + 1:] in
[m + '_MyImage' for m in MOI.ALL_MEASUREMENTS])
else:
self.assertTrue(column[1][column[1].find('_') + 1:] in
[m + '_MyImage' for m in MOI.ALL_LOCATION_MEASUREMENTS])
def test_02_01_supplied_measurements(self):
"""Test the get_category / get_measurements, get_measurement_images functions"""
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value='MyImage'
moi.add_object()
moi.objects[0].name.value = 'MyObjects1'
moi.objects[1].name.value = 'MyObjects2'
self.assertEqual(tuple(sorted(moi.get_categories(None, 'MyObjects1'))), tuple(sorted([MOI.INTENSITY, MOI.C_LOCATION])))
self.assertEqual(moi.get_categories(None, 'Foo'),[])
measurements = moi.get_measurements(None,'MyObjects1',MOI.INTENSITY)
self.assertEqual(len(measurements),len(MOI.ALL_MEASUREMENTS))
measurements = moi.get_measurements(None,'MyObjects1',MOI.C_LOCATION)
self.assertEqual(len(measurements),len(MOI.ALL_LOCATION_MEASUREMENTS))
self.assertTrue(all([m in MOI.ALL_LOCATION_MEASUREMENTS for m in measurements]))
self.assertTrue(moi.get_measurement_images(None,'MyObjects1',
MOI.INTENSITY,
MOI.MAX_INTENSITY),
['MyImage'])
def test_03_05_quartiles(self):
"""Regression test a bug that occurs in an image with one pixel"""
labels = np.zeros((10, 20))
labels[2:7, 3:8] = 1
labels[5, 15] = 2
np.random.seed(0)
image = np.random.uniform(size=(10, 20))
ii = II.InjectImage('MyImage', image)
ii.module_num = 1
io = II.InjectObjects('MyObjects', labels)
io.module_num = 2
moi = MOI.MeasureObjectIntensity()
moi.images[0].name.value = 'MyImage'
moi.objects[0].name.value = 'MyObjects'
moi.module_num = 3
pipeline = P.Pipeline()
pipeline.add_listener(self.error_callback)
pipeline.add_module(ii)
pipeline.add_module(io)
pipeline.add_module(moi)
# Crashes when pipeline runs in measureobjectintensity.py revision 7146
m = pipeline.run()
