def test_polygon_merger(self):
"""Test Polygon_merger.run()."""
# init and run polygon merger on masks grid
pm = Polygon_merger(maskpaths=maskpaths,
GTCodes_df=GTCodes_df,
discard_nonenclosed_background=True,
verbose=1)
contours_df = pm.run()
# make sure it is what we expect
self.assertTupleEqual(contours_df.shape, (17, 13))
self.assertSetEqual(
set(contours_df.loc[:, 'group']), {
'roi', 'mostly_tumor', 'mostly_stroma',
'mostly_lymphocytic_infiltrate'
})
# deleting existing annotations in target slide (if any)
delete_annotations_in_slide(gc, SAMPLE_SLIDE_ID)
# get list of annotation documents
annotation_docs = get_annotation_documents_from_contours(
contours_df.copy(),
separate_docs_by_group=True,
docnamePrefix='test',
verbose=False,
monitorPrefix=SAMPLE_SLIDE_ID + ": annotation docs")
# post annotations to slide -- make sure it posts without errors
for annotation_doc in annotation_docs:
resp = gc.post("/annotation?itemId=" + SAMPLE_SLIDE_ID,
json=annotation_doc)
self.assertTrue('annotation' in resp.keys())
def cellularity_detection_workflow(gc,
cdo,
slide_id,
monitorPrefix='',
destination_folder_id=None,
keep_existing_annotations=False):
"""Run cellularity detection for single slide.
The cellularity detection algorithm can either be
Cellularity_detector_superpixels or Cellularity_detector_thresholding.
Arguments
-----------
gc : object
girder client object
cdo : object
Cellularity_detector object instance. Can either be
Cellularity_detector_superpixels() or
Cellularity_detector_thresholding(). The thresholding-based workflow
seems to be more robust, despite being simpler.
slide_id : str
girder id of slide on which workflow is done
monitorPrefix : str
this will set the cds monitorPrefix attribute
destination_folder_id : str or None
if not None, copy slide to this girder folder and post results
there instead of original slide.
keep_existing_annotations : bool
keep existing annotations in slide when posting results?
"""
cdo.monitorPrefix = monitorPrefix
# copy slide to target folder, otherwise work in-place
if destination_folder_id is not None:
cdo._print1("%s: copying slide to destination folder" % monitorPrefix)
resp = gc.post(
"/item/%s/copy?folderId=%s©Annotations=%s" %
(slide_id, destination_folder_id, keep_existing_annotations))
slide_id = resp['_id']
elif not keep_existing_annotations:
cdo._print1("%s: deleting existing annotations" % monitorPrefix)
delete_annotations_in_slide(gc, slide_id)
# run cds for this slide
cdo.slide_id = slide_id
cdo.run()
return slide_id
def test_polygon_merger_tiled_masks(self, girderClient): # noqa
"""Test Polygon_merger.run()."""
# read GTCodes dataframe
gtcodePath = getTestFilePath('sample_GTcodes.csv')
GTCodes_df = read_csv(gtcodePath)
GTCodes_df.index = GTCodes_df.loc[:, 'group']
# This is where masks for adjacent rois are saved
mask_loadpath = getTestFilePath(
os.path.join('annotations_and_masks', 'polygon_merger_roi_masks'))
maskpaths = [
os.path.join(mask_loadpath, j) for j in os.listdir(mask_loadpath)
if j.endswith('.png')
]
# init and run polygon merger on masks grid
pm = Polygon_merger(maskpaths=maskpaths,
GTCodes_df=GTCodes_df,
discard_nonenclosed_background=True,
verbose=1)
contours_df = pm.run()
# make sure it is what we expect
assert contours_df.shape == (13, 13)
assert set(contours_df.loc[:, 'group']) == {
'roi', 'mostly_tumor', 'mostly_stroma',
'mostly_lymphocytic_infiltrate'
}
# deleting existing annotations in target slide (if any)
sampleSlideItem = girderClient.resourceLookup(
'/user/admin/Public/TCGA-A2-A0YE-01Z-00-DX1.8A2E3094-5755-42BC-969D-7F0A2ECA0F39.svs'
) # noqa
sampleSlideId = str(sampleSlideItem['_id'])
delete_annotations_in_slide(girderClient, sampleSlideId)
# get list of annotation documents
annotation_docs = get_annotation_documents_from_contours(
contours_df.copy(),
separate_docs_by_group=True,
docnamePrefix='test',
verbose=False,
monitorPrefix=sampleSlideId + ": annotation docs")
# post annotations to slide -- make sure it posts without errors
for annotation_doc in annotation_docs:
resp = girderClient.post("/annotation?itemId=" + sampleSlideId,
json=annotation_doc)
assert 'annotation' in resp.keys()
def test_get_tissue_boundary_annotation_documents(self):
"""Test get_tissue_boundary_annotation_documents()."""
labeled = imread(os.path.join(savepath, 'tissue_binmask.png'))
annotation_docs = get_tissue_boundary_annotation_documents(
gc, slide_id=SAMPLE_SLIDE_ID, labeled=labeled)
self.assertTrue('elements' in annotation_docs[0].keys())
self.assertEqual(len(annotation_docs[0]['elements']), 9)
# deleting existing annotations in target slide (if any)
delete_annotations_in_slide(gc, SAMPLE_SLIDE_ID)
# post annotations to slide
for doc in annotation_docs:
_ = gc.post("/annotation?itemId=" + SAMPLE_SLIDE_ID, json=doc)
def test_get_tissue_boundary_annotation_documents(self):
"""Test get_tissue_boundary_annotation_documents()."""
annotation_docs = get_tissue_boundary_annotation_documents(
cfg.gc, slide_id=cfg.iteminfo['_id'], labeled=cfg.labeled)
assert 'elements' in annotation_docs[0].keys()
assert len(annotation_docs[0]['elements']) == 9
# test delete existing annotations in slide
delete_annotations_in_slide(cfg.gc, cfg.iteminfo['_id'])
# check that it posts without issues
resps = [
cfg.gc.post("/annotation?itemId=" + cfg.iteminfo['_id'], json=doc)
for doc in annotation_docs
]
assert all(['annotation' in resp for resp in resps])
def test_Cellularity_detector_superpixels(self):
"""Test Cellularity_detector_superpixels()."""
# deleting existing annotations in target slide (if any)
delete_annotations_in_slide(gc, SAMPLE_SLIDE_ID)
# run cellularity detector
cds = Cellularity_detector_superpixels(
gc,
slide_id=SAMPLE_SLIDE_ID,
MAG=3.0,
compactness=0.1,
spixel_size_baseMag=256 * 256,
max_cellularity=40,
visualize_spixels=True,
visualize_contiguous=True,
get_tissue_mask_kwargs={
'deconvolve_first': False,
'n_thresholding_steps': 2,
'sigma': 1.5,
'min_size': 500,
},
verbose=2,
monitorPrefix='test',
logging_savepath=logging_savepath)
# cds.set_color_normalization_values(
# mu=cnorm_thumbnail['mu'],
# sigma=cnorm_thumbnail['sigma'], what='thumbnail')
cds.set_color_normalization_values(mu=cnorm_main['mu'],
sigma=cnorm_main['sigma'],
what='main')
tissue_pieces = cds.run()
# check
self.assertEqual(len(tissue_pieces), 2)
self.assertTrue(
all([
j in tissue_pieces[0].__dict__.keys()
for j in ('tissue_mask', 'ymin', 'xmin', 'ymax', 'xmax',
'spixel_mask', 'fdata', 'cluster_props')
]))
self.assertEqual(len(tissue_pieces[0].cluster_props), 5)
# cleanup
shutil.rmtree(logging_savepath)
def test_get_annotation_documents_from_contours(self,
girderClient): # noqa
"""Test get_contours_from_bin_mask()."""
self._setup()
sampleSlideItem = girderClient.resourceLookup(
'/user/admin/Public/TCGA-A2-A0YE-01Z-00-DX1.8A2E3094-5755-42BC-969D-7F0A2ECA0F39.svs'
) # noqa
sampleSlideId = str(sampleSlideItem['_id'])
# get list of annotation documents
annprops = {
'X_OFFSET': self.X_OFFSET,
'Y_OFFSET': self.Y_OFFSET,
'opacity': 0.2,
'lineWidth': 4.0,
}
annotation_docs = get_annotation_documents_from_contours(
self.CONTOURS_DF.copy(),
separate_docs_by_group=True,
annots_per_doc=10,
docnamePrefix='test',
annprops=annprops,
verbose=False,
monitorPrefix=self.MASKNAME[:12] + ": annotation docs")
# make sure its what we expect
assert len(annotation_docs) == 8
assert {j['name']
for j in annotation_docs} == {
'test_blood_vessel-0', 'test_exclude-0',
'test_mostly_lymphocytic_infiltrate-0',
'test_mostly_stroma-0', 'test_mostly_tumor-0',
'test_mostly_tumor-1', 'test_normal_acinus_or_duct-0',
'test_roi-0'
}
# deleting existing annotations in target slide (if any)
delete_annotations_in_slide(girderClient, sampleSlideId)
# post annotations to slide -- make sure it posts without errors
resp = girderClient.post("/annotation?itemId=" + sampleSlideId,
json=annotation_docs[0])
assert 'annotation' in resp.keys()
def test_polygon_merger_v2(self):
"""Test Polygon_merger_v2.run()."""
# init & run polygon merger
pm = Polygon_merger_v2(contours_df, verbose=1)
pm.unique_groups.remove("roi")
pm.run()
# make sure it is what we expect
self.assertTupleEqual(pm.new_contours.shape, (16, 13))
self.assertSetEqual(
set(pm.new_contours.loc[:, 'group']),
{'mostly_tumor', 'mostly_stroma', 'mostly_lymphocytic_infiltrate'})
# add colors (aesthetic)
for group in pm.unique_groups:
cs = contours_df.loc[contours_df.loc[:, "group"] == group, "color"]
pm.new_contours.loc[pm.new_contours.loc[:, "group"] == group,
"color"] = cs.iloc[0]
# get rid of nonenclosed stroma (aesthetic)
pm.new_contours = _discard_nonenclosed_background_group(
pm.new_contours, background_group="mostly_stroma")
# deleting existing annotations in target slide (if any)
delete_annotations_in_slide(gc, POST_SLIDE_ID)
# get list of annotation documents
annotation_docs = get_annotation_documents_from_contours(
pm.new_contours.copy(),
separate_docs_by_group=True,
docnamePrefix='test',
verbose=False,
monitorPrefix=POST_SLIDE_ID + ": annotation docs")
# post annotations to slide -- make sure it posts without errors
for annotation_doc in annotation_docs:
resp = gc.post("/annotation?itemId=" + POST_SLIDE_ID,
json=annotation_doc)
self.assertTrue('annotation' in resp.keys())
def test_get_annotation_documents_from_contours(self):
"""Test get_contours_from_bin_mask()."""
# get list of annotation documents
annprops = {
'X_OFFSET': X_OFFSET,
'Y_OFFSET': Y_OFFSET,
'opacity': 0.2,
'lineWidth': 4.0,
}
annotation_docs = get_annotation_documents_from_contours(
CONTOURS_DF.copy(),
separate_docs_by_group=True,
annots_per_doc=10,
docnamePrefix='test',
annprops=annprops,
verbose=False,
monitorPrefix=MASKNAME[:12] + ": annotation docs")
# make sure its what we expect
self.assertTrue(len(annotation_docs) == 8)
self.assertSetEqual(
{j['name']
for j in annotation_docs},
{
'test_blood_vessel-0', 'test_exclude-0',
'test_mostly_lymphocytic_infiltrate-0', 'test_mostly_stroma-0',
'test_mostly_tumor-0', 'test_mostly_tumor-1',
'test_normal_acinus_or_duct-0', 'test_roi-0'
})
# deleting existing annotations in target slide (if any)
delete_annotations_in_slide(gc, SAMPLE_SLIDE_ID)
# post annotations to slide -- make sure it posts without errors
resp = gc.post("/annotation?itemId=" + SAMPLE_SLIDE_ID,
json=annotation_docs[0])
self.assertTrue('annotation' in resp.keys())
