def test_04_05_get_measurement_scales(self): workspace, module = self.make_workspace( dict(image=numpy.zeros((20, 10), bool)), dict(image=numpy.zeros((20, 10), bool))) scales = module.get_measurement_scales( workspace.pipeline, cellprofiler.measurement.IMAGE, cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP, cellprofiler.modules.measureimageoverlap.FTR_RAND_INDEX, None) self.assertEqual(len(scales), 0)
def test_04_05_get_measurement_scales(self): workspace, module = self.make_workspace( dict(image=numpy.zeros((20, 10), bool)), dict(image=numpy.zeros((20, 10), bool))) module.obj_or_img.value = cellprofiler.modules.measureimageoverlap.O_OBJ module.object_name_GT.value = GROUND_TRUTH_OBJ module.object_name_ID.value = ID_OBJ scales = module.get_measurement_scales( workspace.pipeline, cellprofiler.measurement.IMAGE, cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP, cellprofiler.modules.measureimageoverlap.FTR_RAND_INDEX, None) self.assertEqual(len(scales), 1) self.assertEqual(scales[0], "_".join((GROUND_TRUTH_OBJ, ID_OBJ))) module.obj_or_img.value = cellprofiler.modules.measureimageoverlap.O_IMG scales = module.get_measurement_scales( workspace.pipeline, cellprofiler.measurement.IMAGE, cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP, cellprofiler.modules.measureimageoverlap.FTR_RAND_INDEX, None) self.assertEqual(len(scales), 0)
def test_04_05_get_measurement_scales(self): workspace, module = self.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, cellprofiler.measurement.IMAGE, cellprofiler.modules.measureobjectoverlap.C_IMAGE_OVERLAP, cellprofiler.modules.measureobjectoverlap.FTR_RAND_INDEX, None) self.assertEqual(len(scales), 1) self.assertEqual(scales[0], "_".join((GROUND_TRUTH_OBJ, ID_OBJ)))
def test_04_05_get_measurement_scales(self): workspace, module = self.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, cellprofiler.measurement.IMAGE, cellprofiler.modules.measureobjectoverlap.C_IMAGE_OVERLAP, cellprofiler.modules.measureobjectoverlap.FTR_RAND_INDEX, None ) self.assertEqual(len(scales), 1) self.assertEqual(scales[0], "_".join((GROUND_TRUTH_OBJ, ID_OBJ)))
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, cellprofiler.measurement.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 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 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()) 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, )