def _parse_mnu_roi(self, columns):
"""Parses out ROI from OmeroTables columns for 'MNU' datasets."""
log.debug("Parsing %s MNU ROIs..." % (len(columns[0].values)))
image_ids = columns[self.IMAGE_COL].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = FileAnnotationI(self.file_annotation.id.val, False)
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
values = columns[3].values
shape.cx = rdouble(float(values[i]))
values = columns[2].values
shape.cy = rdouble(float(values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
if len(rois) == self.ROI_UPDATE_LIMIT:
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
self.thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns[self.ROI_COL].values += batches[k]
def _parse_neo_roi(self, columns):
"""Parses out ROI from OmeroTables columns for 'NEO' datasets."""
log.debug("Parsing %s NEO ROIs..." % (len(columns[0].values)))
image_ids = columns[self.IMAGE_COL].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = \
self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = \
FileAnnotationI(self.file_annotation.id.val, False)
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
roi = RoiI()
shape = EllipseI()
values = columns[6].values
diameter = rdouble(float(values[i]))
shape.theZ = rint(0)
shape.theT = rint(0)
values = columns[4].values
shape.cx = rdouble(float(values[i]))
values = columns[3].values
shape.cy = rdouble(float(values[i]))
shape.rx = diameter
shape.ry = diameter
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
if len(rois) == self.ROI_UPDATE_LIMIT:
self.thread_pool.add_task(
self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
self.thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns[self.ROI_COL].values += batches[k]
def parse_and_populate_roi(self, columns_as_list):
# First sanity check our provided columns
names = [column.name for column in columns_as_list]
log.debug('Parsing columns: %r' % names)
cells_expected = [name in names for name in self.CELLS_CG_EXPECTED]
nuclei_expected = [name in names for name in self.NUCLEI_CG_EXPECTED]
if (False in cells_expected) and (False in nuclei_expected):
log.warn("Missing CGs for InCell dataset: %r" % names)
log.warn('Removing resultant empty ROI column.')
for column in columns_as_list:
if RoiColumn == column.__class__:
columns_as_list.remove(column)
return
# Reconstruct a column name to column map
columns = dict()
for column in columns_as_list:
columns[column.name] = column
image_ids = columns['Image'].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = \
self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = \
FileAnnotationI(self.file_annotation.id.val, False)
# Parse and append ROI
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
if False in nuclei_expected:
# Cell centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Cell: cgX'].values[i]))
shape.cy = rdouble(float(columns['Cell: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
elif False in cells_expected:
# Nucleus centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Nucleus: cgX'].values[i]))
shape.cy = rdouble(float(columns['Nucleus: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
else:
raise MeasurementError('Not a nucleus or cell ROI')
if len(rois) == self.ROI_UPDATE_LIMIT:
thread_pool.add_task(self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
thread_pool.add_task(self.update_rois, rois, batches, batch_no)
thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns['ROI'].values += batches[k]
def test_save_rois(self, conn, django_client):
"""Save new ROIs to an Image"""
image = self.make_image(client=conn.c)
roi = RoiI()
roi.name = rstring("roi_name")
roi.setImage(ImageI(image.id.val, False))
point = PointI()
point.x = rdouble(1)
point.y = rdouble(2)
encoder = get_encoder(point.__class__)
point_json = encoder.encode(point)
unsaved_id = "-1:-1"
point_json['oldId'] = unsaved_id
persist_url = reverse('omero_iviewer_persist_rois')
data = {
'imageId': image.id.val,
'rois': {
'count': 1,
'new': [point_json]
}
}
rsp = post_json(django_client, persist_url, data)
print('rsp', rsp)
# {"ids": {"-1:-1": "225504:416603"}}
assert "ids" in rsp
new_ids = rsp["ids"].values()
assert len(new_ids) == 1
new_id = rsp["ids"][unsaved_id]
roi_id = int(new_id.split(':')[0])
shape_id = int(new_id.split(':')[1])
# Add Tag to ROI and Shape
tag = TagAnnotationWrapper(conn)
tag.setValue("ROI/Shape Tag")
tag.save()
roi = conn.getObject("Roi", roi_id)
roi.linkAnnotation(tag)
shape = conn.getObject("Shape", shape_id)
shape.linkAnnotation(tag)
# check...
assert len(list(conn.getAnnotationLinks(
"Shape", parent_ids=[shape_id]))) == 1
# Load Shape
rois_url = reverse('api_rois', kwargs={'api_version': 0})
rois_url += '?image=%s' % image.id.val
rsp = get_json(django_client, rois_url)
assert len(rsp['data']) == 1
# Edit Shape
point_json = rsp['data'][0]['shapes'][0]
point_json["X"] = 100
point_json["Y"] = 200
# iviewer wants to know ROI:Shape ID
point_json["oldId"] = new_id
# Unload details
del point_json["omero:details"]
data = {
'imageId': image.id.val,
'rois': {
'count': 1,
'modified': [point_json]
}
}
rsp = post_json(django_client, persist_url, data)
# IDs shouldn't have changed, e.g.
# {"ids": {"225504:416603": "225504:416603"}}
print('post rsp', rsp)
assert rsp["ids"][new_id] == new_id
# Check annotations not lost
roi = conn.getObject("Roi", roi_id)
assert len(list(roi.listAnnotations())) == 1
assert len(list(conn.getAnnotationLinks(
"Shape", parent_ids=[shape_id]))) == 1
def parse_and_populate_roi(self, columns_as_list):
# First sanity check our provided columns
names = [column.name for column in columns_as_list]
log.debug('Parsing columns: %r' % names)
cells_expected = [name in names for name in self.CELLS_CG_EXPECTED]
nuclei_expected = [name in names for name in self.NUCLEI_CG_EXPECTED]
if (False in cells_expected) and (False in nuclei_expected):
log.warn("Missing CGs for InCell dataset: %r" % names)
log.warn('Removing resultant empty ROI column.')
for column in columns_as_list:
if RoiColumn == column.__class__:
columns_as_list.remove(column)
return
# Reconstruct a column name to column map
columns = dict()
for column in columns_as_list:
columns[column.name] = column
image_ids = columns['Image'].values
rois = list()
# Save our file annotation to the database so we can use an unloaded
# annotation for the saveAndReturnIds that will be triggered below.
self.file_annotation = \
self.update_service.saveAndReturnObject(self.file_annotation)
unloaded_file_annotation = \
FileAnnotationI(self.file_annotation.id.val, False)
# Parse and append ROI
batch_no = 1
batches = dict()
for i, image_id in enumerate(image_ids):
unloaded_image = ImageI(image_id, False)
if False in nuclei_expected:
# Cell centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Cell: cgX'].values[i]))
shape.cy = rdouble(float(columns['Cell: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
elif False in cells_expected:
# Nucleus centre of gravity
roi = RoiI()
shape = PointI()
shape.theZ = rint(0)
shape.theT = rint(0)
shape.cx = rdouble(float(columns['Nucleus: cgX'].values[i]))
shape.cy = rdouble(float(columns['Nucleus: cgY'].values[i]))
roi.addShape(shape)
roi.image = unloaded_image
roi.linkAnnotation(unloaded_file_annotation)
rois.append(roi)
else:
raise MeasurementError('Not a nucleus or cell ROI')
if len(rois) == self.ROI_UPDATE_LIMIT:
self.thread_pool.add_task(
self.update_rois, rois, batches, batch_no)
rois = list()
batch_no += 1
self.thread_pool.add_task(self.update_rois, rois, batches, batch_no)
self.thread_pool.wait_completion()
batch_keys = batches.keys()
batch_keys.sort()
for k in batch_keys:
columns['ROI'].values += batches[k]
