def build(self):
g1 = self.g1
g2 = self.g2
# We will assume integer weights only.
g1.add_edge('A', 'B', color='green', weight=0, size=.5)
g1.add_edge('A', 'B', color='red', weight=1, size=.35)
g1.add_edge('A', 'B', color='red', weight=2, size=.65)
g2.add_edge('C', 'D', color='green', weight=1, size=.5)
g2.add_edge('C', 'D', color='red', weight=0, size=.45)
g2.add_edge('C', 'D', color='red', weight=2, size=.65)
if g1.is_multigraph():
self.em = iso.numerical_multiedge_match('weight', 1)
self.emc = iso.categorical_multiedge_match('color', '')
self.emcm = iso.categorical_multiedge_match(['color', 'weight'],
['', 1])
self.emg1 = iso.generic_multiedge_match('color', 'red', eq)
self.emg2 = iso.generic_multiedge_match(
['color', 'weight', 'size'], ['red', 1, .5],
[eq, eq, iso.matchhelpers.close])
else:
self.em = iso.numerical_edge_match('weight', 1)
self.emc = iso.categorical_edge_match('color', '')
self.emcm = iso.categorical_edge_match(['color', 'weight'],
['', 1])
self.emg1 = iso.generic_multiedge_match('color', 'red', eq)
self.emg2 = iso.generic_edge_match(
['color', 'weight', 'size'], ['red', 1, .5],
[eq, eq, iso.matchhelpers.close])
def build(self):
g1 = self.g1
g2 = self.g2
# We will assume integer weights only.
g1.add_edge('A', 'B', color='green', weight=0, size=.5)
g1.add_edge('A', 'B', color='red', weight=1, size=.35)
g1.add_edge('A', 'B', color='red', weight=2, size=.65)
g2.add_edge('C', 'D', color='green', weight=1, size=.5)
g2.add_edge('C', 'D', color='red', weight=0, size=.45)
g2.add_edge('C', 'D', color='red', weight=2, size=.65)
if g1.is_multigraph():
self.em = iso.numerical_multiedge_match('weight', 1)
self.emc = iso.categorical_multiedge_match('color', '')
self.emcm = iso.categorical_multiedge_match(['color', 'weight'], ['', 1])
self.emg1 = iso.generic_multiedge_match('color', 'red', eq)
self.emg2 = iso.generic_multiedge_match(['color', 'weight', 'size'], ['red', 1, .5], [eq, eq, iso.matchhelpers.close])
else:
self.em = iso.numerical_edge_match('weight', 1)
self.emc = iso.categorical_edge_match('color', '')
self.emcm = iso.categorical_edge_match(['color', 'weight'], ['', 1])
self.emg1 = iso.generic_multiedge_match('color', 'red', eq)
self.emg2 = iso.generic_edge_match(['color', 'weight', 'size'], ['red', 1, .5], [eq, eq, iso.matchhelpers.close])
def build(self):
g1 = self.g1
g2 = self.g2
# We will assume integer weights only.
g1.add_edge("A", "B", color="green", weight=0, size=0.5)
g1.add_edge("A", "B", color="red", weight=1, size=0.35)
g1.add_edge("A", "B", color="red", weight=2, size=0.65)
g2.add_edge("C", "D", color="green", weight=1, size=0.5)
g2.add_edge("C", "D", color="red", weight=0, size=0.45)
g2.add_edge("C", "D", color="red", weight=2, size=0.65)
if g1.is_multigraph():
self.em = iso.numerical_multiedge_match("weight", 1)
self.emc = iso.categorical_multiedge_match("color", "")
self.emcm = iso.categorical_multiedge_match(["color", "weight"],
["", 1])
self.emg1 = iso.generic_multiedge_match("color", "red", eq)
self.emg2 = iso.generic_multiedge_match(
["color", "weight", "size"],
["red", 1, 0.5],
[eq, eq, iso.matchhelpers.close],
)
else:
self.em = iso.numerical_edge_match("weight", 1)
self.emc = iso.categorical_edge_match("color", "")
self.emcm = iso.categorical_edge_match(["color", "weight"],
["", 1])
self.emg1 = iso.generic_multiedge_match("color", "red", eq)
self.emg2 = iso.generic_edge_match(
["color", "weight", "size"],
["red", 1, 0.5],
[eq, eq, iso.matchhelpers.close],
)
def edge_iso_match(attr, attr_default, op):
"""
Returns an edge_match function that can be used in find_sub_iso()
Args:
- attr: the name (or list of names) of attributes to consider.
- attr_default: default value (or list of values) for attributes
- op: a callable boolean function.
Note: This function in its current form is just a wrapper around networkx.isomorphism.generic_edge_match()
"""
em = isomorphism.generic_edge_match(attr, attr_default, op)
return em
"e3": "b2",
"e4": "b3",
"e5": "b2",
"e6": "b3"
}
TARGET_MAP = {
"e1": "b2",
"e2": "b4",
"e3": "b3",
"e4": "b2",
"e5": "b4",
"e6": "b4"
}
WEIGHT_MAP = {"e1": 6, "e2": 1, "e3": 10, "e4": 10, "e5": 12, "e6": 8}
DEEP_CYCLES = [{"e3", "e4"}, {"e4", "e5", "e6"}]
EM = generic_edge_match(["weight", "label"], [0, "b1"], [close, eq])
_ATTR_LABEL = "label"
_ATTR = "weight"
@pytest.fixture(scope="module")
def dg() -> nx.MultiDiGraph:
"""Init a case from page 237 in [camerini1980ranking]_ ."""
res = nx.MultiDiGraph()
res.add_edge("b1", "b2", label="e1", weight=6)
res.add_edge("b1", "b4", label="e2", weight=1)
res.add_edge("b2", "b3", label="e3", weight=10)
res.add_edge("b3", "b2", label="e4", weight=10)
res.add_edge("b2", "b4", label="e5", weight=12)
res.add_edge("b4", "b3", label="e6", weight=8)
return res