def get_descendant_levels(graph, tablename):
#import networkx as nx
import utool as ut
parent_to_children = ut.edges_to_adjacency_list(graph.edges())
to_leafs = ut.path_to_leafs(tablename, parent_to_children)
descendant_levels_ = ut.get_levels(to_leafs)
descendant_levels = ut.longest_levels(descendant_levels_)
return descendant_levels
def get_dependants(depc, tablename):
"""
gets level dependences table to the leaves
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.depends_cache import * # NOQA
>>> depc = testdata_depc()
>>> tablename = 'chip'
>>> result = ut.repr3(depc.get_dependants(tablename), nl=1)
>>> print(result)
[
['chip'],
['keypoint'],
['fgweight', 'descriptor'],
['spam'],
]
Example:
>>> # ENABLE_DOCTEST
>>> from ibeis.depends_cache import * # NOQA
>>> depc = testdata_depc()
>>> tablename = 'spam'
>>> result = ut.repr3(depc.get_dependants(tablename), nl=1)
>>> print(result)
[
['spam'],
]
"""
children_, parents_ = list(zip(*depc.get_edges()))
parent_to_children = ut.group_items(parents_, children_)
to_leafs = {tablename: ut.path_to_leafs(tablename, parent_to_children)}
dependency_levels_ = ut.get_levels(to_leafs)
dependency_levels = ut.longest_levels(dependency_levels_)
return dependency_levels
