def _export_review_skeleton(project_id=None, skeleton_id=None, format=None):
treenodes = Treenode.objects.filter(skeleton_id=skeleton_id).values_list(
'id', 'location', 'parent_id', 'reviewer_id')
g = nx.DiGraph()
reviewed = set()
for t in treenodes:
loc = Double3D.from_str(t[1])
# While at it, send the reviewer ID, which is useful to iterate fwd
# to the first unreviewed node in the segment.
g.add_node(t[0], {
'id': t[0],
'x': loc.x,
'y': loc.y,
'z': loc.z,
'rid': t[3]
})
if -1 != t[3]:
reviewed.add(t[0])
if t[2]: # if parent
g.add_edge(t[2], t[0]) # edge from parent to child
else:
root_id = t[0]
# Create all sequences, as long as possible and always from end towards root
distances = edge_count_to_root(
g, root_node=root_id) # distance in number of edges from root
seen = set()
sequences = []
# Iterate end nodes sorted from highest to lowest distance to root
endNodeIDs = (nID for nID in g.nodes() if 0 == len(g.successors(nID)))
for nodeID in sorted(endNodeIDs, key=distances.get, reverse=True):
sequence = [g.node[nodeID]]
parents = g.predecessors(nodeID)
while parents:
parentID = parents[0]
sequence.append(g.node[parentID])
if parentID in seen:
break
seen.add(parentID)
parents = g.predecessors(parentID)
if len(sequence) > 1:
sequences.append(sequence)
segments = []
for sequence in sorted(sequences, key=len, reverse=True):
segments.append({
'id':
len(segments),
'sequence':
sequence,
'status':
'%.2f' %
(100.0 * sum(1 for node in sequence if node['id'] in reviewed) /
len(sequence)),
'nr_nodes':
len(sequence)
})
return segments
def _export_review_skeleton(project_id=None, skeleton_id=None, format=None):
""" Returns a list of segments for the requested skeleton. Each segment
contains information about the review status of this part of the skeleton.
"""
# Get all treenodes of the requested skeleton
treenodes = Treenode.objects.filter(skeleton_id=skeleton_id).values_list('id', 'location', 'parent_id')
# Get all reviews for the requested skeleton
reviews = get_treenodes_to_reviews(skeleton_ids=[skeleton_id])
# Add each treenode to a networkx graph and attach reviewer information to
# it.
g = nx.DiGraph()
reviewed = set()
for t in treenodes:
loc = Double3D.from_str(t[1])
# While at it, send the reviewer IDs, which is useful to iterate fwd
# to the first unreviewed node in the segment.
g.add_node(t[0], {'id': t[0], 'x': loc.x, 'y': loc.y, 'z': loc.z, 'rids': reviews[t[0]]})
if reviews[t[0]]:
reviewed.add(t[0])
if t[2]: # if parent
g.add_edge(t[2], t[0]) # edge from parent to child
else:
root_id = t[0]
# Create all sequences, as long as possible and always from end towards root
distances = edge_count_to_root(g, root_node=root_id) # distance in number of edges from root
seen = set()
sequences = []
# Iterate end nodes sorted from highest to lowest distance to root
endNodeIDs = (nID for nID in g.nodes() if 0 == len(g.successors(nID)))
for nodeID in sorted(endNodeIDs, key=distances.get, reverse=True):
sequence = [g.node[nodeID]]
parents = g.predecessors(nodeID)
while parents:
parentID = parents[0]
sequence.append(g.node[parentID])
if parentID in seen:
break
seen.add(parentID)
parents = g.predecessors(parentID)
if len(sequence) > 1:
sequences.append(sequence)
# Calculate status
segments = []
for sequence in sorted(sequences, key=len, reverse=True):
segments.append({
'id': len(segments),
'sequence': sequence,
'status': '%.2f' % (100.0 * sum(1 for node in sequence if node['id'] in reviewed) / len(sequence)),
'nr_nodes': len(sequence)
})
return segments
def export_review_skeleton(request, project_id=None, skeleton_id=None, format=None):
"""
Export the skeleton as a list of sequences of entries, each entry containing
an id, a sequence of nodes, the percent of reviewed nodes, and the node count.
"""
treenodes = Treenode.objects.filter(skeleton_id=skeleton_id).values_list('id', 'location', 'parent_id', 'reviewer_id')
g = nx.DiGraph()
reviewed = set()
for t in treenodes:
loc = Double3D.from_str(t[1])
# While at it, send the reviewer ID, which is useful to iterate fwd
# to the first unreviewed node in the segment.
g.add_node(t[0], {'id': t[0], 'x': loc.x, 'y': loc.y, 'z': loc.z, 'rid': t[3]})
if -1 != t[3]:
reviewed.add(t[0])
if t[2]: # if parent
g.add_edge(t[2], t[0]) # edge from parent to child
else:
root_id = t[0]
# Create all sequences, as long as possible and always from end towards root
distances = edge_count_to_root(g, root_node=root_id) # distance in number of edges from root
seen = set()
sequences = []
# Iterate end nodes sorted from highest to lowest distance to root
endNodeIDs = (nID for nID in g.nodes() if 0 == len(g.successors(nID)))
for nodeID in sorted(endNodeIDs, key=distances.get, reverse=True):
sequence = [g.node[nodeID]]
parents = g.predecessors(nodeID)
while parents:
parentID = parents[0]
sequence.append(g.node[parentID])
if parentID in seen:
break
seen.add(parentID)
parents = g.predecessors(parentID)
if len(sequence) > 1:
sequences.append(sequence)
segments = []
for sequence in sorted(sequences, key=len, reverse=True):
segments.append({
'id': len(segments),
'sequence': sequence,
'status': '%.2f' % (100.0 * sum(1 for node in sequence if node['id'] in reviewed) / len(sequence)),
'nr_nodes': len(sequence)
})
return HttpResponse(json.dumps(segments))
def format_node_data(node):
'''
Formats node data for our json output.
When we start using Django 1.4, we can use prefetch_related instead of using
.values('treenode__xxx'), and will then be able to access a proper location
object.
'''
location = Double3D.from_str(node['treenode__location'])
return {
'id': node['treenode'],
'x': int(location.x),
'y': int(location.y),
'z': int(location.z),
'skid': node['treenode__skeleton']}
