def __addEnds(self, obj0SRotmat4, obj1SRotmat4):
"""
add the two ends to the graph
:param obj0SRotmat4:
:param obj1SRotmat4:
:return:
"""
self.regghalf[0].deleteEnd()
self.regghalf[1].deleteEnd()
self.regghalf[0].addEnd(obj0SRotmat4)
self.regghalf[1].addEnd(obj1SRotmat4)
self.regg = nx.compose(self.regghalf[0].graphtpp.regg, self.regghalf[1].graphtpp.regg)
self.__addAssNodes(armname = 'rgt')
self.__addAssNodes(armname = 'lft')
self.__bridgeGraph()
python类compose()的实例源码
def from_depends(subtrees):
G = nx.DiGraph()
root = RootNode()
for subG in subtrees:
self.G = nx.compose(G, subG.G)
self.G.add_edge(root, subG.root)
return InstalledGraph(G, root)
def collect_tasks(path, folders, matrix_base_dir, channels=None, steps=0, test=False,
max_downstream=5, variant_config_files=None):
# runs = ['test']
# not testing means build and test
# if not test:
# runs.insert(0, 'build')
runs = ['build']
task_graph = nx.DiGraph()
config = conda_build.api.Config()
for run in runs:
platforms = parse_platforms(matrix_base_dir, run)
# loop over platforms here because each platform may have different dependencies
# each platform will be submitted with a different label
for platform in platforms:
index_key = '-'.join([platform['platform'], str(platform['arch'])])
config.channel_urls = channels or []
config.variant_config_files = variant_config_files or []
conda_resolve = Resolve(get_build_index(subdir=index_key,
bldpkgs_dir=config.bldpkgs_dir)[0])
# this graph is potentially different for platform and for build or test mode ("run")
g = construct_graph(path, worker=platform, folders=folders, run=run,
matrix_base_dir=matrix_base_dir, conda_resolve=conda_resolve,
config=config)
# Apply the build label to any nodes that need (re)building or testing
expand_run(g, conda_resolve=conda_resolve, worker=platform, run=run,
steps=steps, max_downstream=max_downstream, recipes_dir=path,
matrix_base_dir=matrix_base_dir)
# merge this graph with the main one
task_graph = nx.compose(task_graph, g)
return task_graph
def appendToNode(self, t, rdag):
""" append rdag to self, adding edges from a given node to rdag's roots
Params:
t (SanskritObject) : Node to append to
rdag (SanskritLexicalGraph): Graph to append to node
"""
# t is in our graph
assert t in self.G
self.G = nx.compose(self.G, rdag.G)
for r in rdag.roots:
self.G.add_edge(t, r)
def copy_to_bidirectional(g:nx.DiGraph, weight='weight'):
return nx.compose(g, reverse_weights(g, weight=weight))
