def skeleton_graph(request, project_id=None):
compute_risk = 1 == int(request.POST.get("risk", 0))
if compute_risk:
# TODO port the last bit: computing the synapse risk
from graph import skeleton_graph as slow_graph
return slow_graph(request, project_id=project_id)
project_id = int(project_id)
skeleton_ids = set(int(v) for k, v in request.POST.iteritems() if k.startswith("skeleton_list["))
confidence_threshold = min(int(request.POST.get("confidence_threshold", 0)), 5)
bandwidth = float(request.POST.get("bandwidth", 0)) # in nanometers
cable_spread = float(request.POST.get("cable_spread", 2500)) # in nanometers
path_confluence = int(request.POST.get("path_confluence", 10)) # a count
expand = set(int(v) for k, v in request.POST.iteritems() if k.startswith("expand["))
return HttpResponse(
json.dumps(
_skeleton_graph(
project_id,
skeleton_ids,
confidence_threshold,
bandwidth,
expand,
compute_risk,
cable_spread,
path_confluence,
)
)
)
def skeleton_graph(request, project_id=None):
compute_risk = 1 == int(request.POST.get('risk', 0))
if compute_risk:
# TODO port the last bit: computing the synapse risk
from graph import skeleton_graph as slow_graph
return slow_graph(request, project_id=project_id)
project_id = int(project_id)
skeleton_ids = set(int(v) for k,v in request.POST.iteritems() if k.startswith('skeleton_list['))
confidence_threshold = min(int(request.POST.get('confidence_threshold', 0)), 5)
bandwidth = float(request.POST.get('bandwidth', 0)) # in nanometers
cable_spread = float(request.POST.get('cable_spread', 2500)) # in nanometers
path_confluence = int(request.POST.get('path_confluence', 10)) # a count
expand = set(int(v) for k,v in request.POST.iteritems() if k.startswith('expand['))
return HttpResponse(json.dumps(_skeleton_graph(project_id, skeleton_ids, confidence_threshold, bandwidth, expand, compute_risk, cable_spread, path_confluence)))
def skeleton_graph(request, project_id=None):
"""Get a synaptic graph between skeletons compartmentalized by confidence.
Given a set of skeletons, retrieve presynaptic-to-postsynaptic edges
between them, annotated with count. If a confidence threshold is
supplied, compartmentalize the skeletons at edges in the arbor
below that threshold and report connectivity based on these
compartments.
When skeletons are split into compartments, nodes in the graph take an
string ID like ``{skeleton_id}_{compartment #}``.
---
parameters:
- name: skeleton_ids[]
description: IDs of the skeletons to graph
required: true
type: array
items:
type: integer
paramType: form
- name: confidence_threshold
description: Confidence value below which to segregate compartments
type: integer
paramType: form
- name: bandwidth
description: Bandwidth in nanometers
type: number
- name: cable_spread
description: Cable spread in nanometers
type: number
- name: expand[]
description: IDs of the skeletons to expand
type: array
items:
type: integer
- name: link_types[]
description: IDs of link types to respect
type: array
items:
type: string
models:
skeleton_graph_edge:
id: skeleton_graph_edge
properties:
- description: ID of the presynaptic skeleton or compartment
type: integer|string
required: true
- description: ID of the postsynaptic skeleton or compartment
type: integer|string
required: true
- description: number of synapses constituting this edge
$ref: skeleton_graph_edge_count
required: true
skeleton_graph_edge_count:
id: skeleton_graph_edge_count
properties:
- description: Number of synapses with confidence 1
type: integer
required: true
- description: Number of synapses with confidence 2
type: integer
required: true
- description: Number of synapses with confidence 3
type: integer
required: true
- description: Number of synapses with confidence 4
type: integer
required: true
- description: Number of synapses with confidence 5
type: integer
required: true
skeleton_graph_intraedge:
id: skeleton_graph_intraedge
properties:
- description: ID of the presynaptic skeleton or compartment
type: integer|string
required: true
- description: ID of the postsynaptic skeleton or compartment
type: integer|string
required: true
type:
edges:
type: array
items:
$ref: skeleton_graph_edge
required: true
nodes:
type: array
items:
type: integer|string
required: false
intraedges:
type: array
items:
$ref: skeleton_graph_intraedge
required: false
branch_nodes:
type: array
items:
type: integer|string
required: false
"""
compute_risk = 1 == int(request.POST.get('risk', 0))
if compute_risk:
# TODO port the last bit: computing the synapse risk
from graph import skeleton_graph as slow_graph
return slow_graph(request, project_id)
project_id = int(project_id)
skeleton_ids = set(int(v) for k,v in request.POST.items() if k.startswith('skeleton_ids['))
confidence_threshold = min(int(request.POST.get('confidence_threshold', 0)), 5)
bandwidth = float(request.POST.get('bandwidth', 0)) # in nanometers
cable_spread = float(request.POST.get('cable_spread', 2500)) # in nanometers
path_confluence = int(request.POST.get('path_confluence', 10)) # a count
expand = set(int(v) for k,v in request.POST.items() if k.startswith('expand['))
with_overall_counts = get_request_bool(request.POST, 'with_overall_counts', False)
expand = set(int(v) for k,v in request.POST.items() if k.startswith('expand['))
link_types = get_request_list(request.POST, 'link_types', None)
graph = _skeleton_graph(project_id, skeleton_ids,
confidence_threshold, bandwidth, expand, compute_risk, cable_spread,
path_confluence, with_overall_counts, link_types=link_types)
if not graph:
raise ValueError("Could not compute graph")
return JsonResponse(graph)
def skeleton_graph(request, project_id=None):
"""Get a synaptic graph between skeletons compartmentalized by confidence.
Given a set of skeletons, retrieve presynaptic-to-postsynaptic edges
between them, annotated with count. If a confidence threshold is
supplied, compartmentalize the skeletons at edges in the arbor
below that threshold and report connectivity based on these
compartments.
When skeletons are split into compartments, nodes in the graph take an
string ID like ``{skeleton_id}_{compartment #}``.
---
parameters:
- name: skeleton_ids[]
description: IDs of the skeletons to graph
required: true
type: array
items:
type: integer
paramType: form
- name: confidence_threshold
description: Confidence value below which to segregate compartments
type: integer
paramType: form
- name: bandwidth
description: Bandwidth in nanometers
type: number
- name: cable_spread
description: Cable spread in nanometers
type: number
- name: expand[]
description: IDs of the skeletons to expand
type: array
items:
type: integer
- name: link_types[]
description: IDs of link types to respect
type: array
items:
type: string
models:
skeleton_graph_edge:
id: skeleton_graph_edge
properties:
- description: ID of the presynaptic skeleton or compartment
type: integer|string
required: true
- description: ID of the postsynaptic skeleton or compartment
type: integer|string
required: true
- description: number of synapses constituting this edge
$ref: skeleton_graph_edge_count
required: true
skeleton_graph_edge_count:
id: skeleton_graph_edge_count
properties:
- description: Number of synapses with confidence 1
type: integer
required: true
- description: Number of synapses with confidence 2
type: integer
required: true
- description: Number of synapses with confidence 3
type: integer
required: true
- description: Number of synapses with confidence 4
type: integer
required: true
- description: Number of synapses with confidence 5
type: integer
required: true
skeleton_graph_intraedge:
id: skeleton_graph_intraedge
properties:
- description: ID of the presynaptic skeleton or compartment
type: integer|string
required: true
- description: ID of the postsynaptic skeleton or compartment
type: integer|string
required: true
type:
edges:
type: array
items:
$ref: skeleton_graph_edge
required: true
nodes:
type: array
items:
type: integer|string
required: false
intraedges:
type: array
items:
$ref: skeleton_graph_intraedge
required: false
branch_nodes:
type: array
items:
type: integer|string
required: false
"""
compute_risk = 1 == int(request.POST.get('risk', 0))
if compute_risk:
# TODO port the last bit: computing the synapse risk
from graph import skeleton_graph as slow_graph
return slow_graph(request, project_id)
project_id = int(project_id)
skeleton_ids = set(int(v) for k,v in request.POST.items() if k.startswith('skeleton_ids['))
confidence_threshold = min(int(request.POST.get('confidence_threshold', 0)), 5)
bandwidth = float(request.POST.get('bandwidth', 0)) # in nanometers
cable_spread = float(request.POST.get('cable_spread', 2500)) # in nanometers
path_confluence = int(request.POST.get('path_confluence', 10)) # a count
expand = set(int(v) for k,v in request.POST.items() if k.startswith('expand['))
with_overall_counts = get_request_bool(request.POST, 'with_overall_counts', False)
expand = set(int(v) for k,v in request.POST.items() if k.startswith('expand['))
link_types = get_request_list(request.POST, 'link_types', None)
graph = _skeleton_graph(project_id, skeleton_ids,
confidence_threshold, bandwidth, expand, compute_risk, cable_spread,
path_confluence, with_overall_counts, link_types=link_types)
if not graph:
raise ValueError("Could not compute graph")
return JsonResponse(graph)