def clustering_api(engines, api=None, optionables=None, prefix="clustering"):
def clustering_engine(optionables):
""" Return a default engine over a lexical graph
"""
# setup
engine = Engine("gbuilder", "clustering", "labelling")
engine.gbuilder.setup(in_name="request", out_name="graph", hidden=True)
engine.clustering.setup(in_name="graph", out_name="clusters")
engine.labelling.setup(in_name="clusters", out_name="clusters", hidden=True)
engine.gbuilder.set(engines.edge_subgraph)
engine.clustering.set(*optionables)
## Labelling
from cello.clustering.labelling.model import Label
from cello.clustering.labelling.basic import VertexAsLabel, TypeFalseLabel, normalize_score_max
def _labelling(graph, cluster, vtx):
return Label(vtx["uuid"], score=1, role="default")
labelling = VertexAsLabel( _labelling ) | normalize_score_max
engine.labelling.set(labelling)
return engine
if api is None:
api = ReliureAPI(name,expose_route = False)
## Clustering
from cello.graphs.transform import EdgeAttr
from cello.clustering.common import Infomap, Walktrap
# weighted
walktrap = Walktrap(weighted=True)
walktrap.name = "Walktrap"
infomap = Infomap(weighted=True)
infomap.name = "Infomap"
DEFAULTS = [walktrap, infomap]
if optionables == None : optionables = DEFAULTS
view = EngineView(clustering_engine(optionables))
view.set_input_type(EdgeList())
view.add_output("clusters", export_clustering, vertex_id_attr='uuid')
api.register_view(view, url_prefix=prefix)
return api
def clustering_api(graphdb,
engines,
api=None,
optionables=None,
prefix="clustering"):
def clustering_engine(optionables):
""" Return a default engine over a lexical graph
"""
# setup
engine = Engine("gbuilder", "clustering")
engine.gbuilder.setup(in_name="request", out_name="graph", hidden=True)
engine.clustering.setup(in_name="graph", out_name="clusters")
engine.gbuilder.set(engines.edge_subgraph)
engine.clustering.set(*optionables)
return engine
if api is None:
api = ReliureAPI(name, expose_route=False)
## Clustering
from cello.graphs.transform import EdgeAttr
from cello.clustering.common import Infomap, Walktrap
# weighted
walktrap = Walktrap(weighted=True)
walktrap.name = "Walktrap"
infomap = Infomap(weighted=True)
infomap.name = "Infomap"
DEFAULTS = [walktrap, infomap]
if optionables == None: optionables = DEFAULTS
from pdgapi.explor import EdgeList
view = EngineView(clustering_engine(optionables))
view.set_input_type(EdgeList())
view.add_output("clusters", export_clustering, vertex_id_attr='uuid')
api.register_view(view, url_prefix=prefix)
# cluster labels
view = EngineView(clusters_labels_engine(graphdb))
view.set_input_type(Clusters())
view.add_output("labels", lambda e: e)
api.register_view(view, url_prefix="labels")
return api