Python make_random_sptree Beispiele

Beispiel #1

#!/usr/bin/python
#
# Sprawdzam szybkosc wyznaczania dset.

import timeit
import random
from graphtheory.structures.edges import Edge
from graphtheory.structures.graphs import Graph
from graphtheory.seriesparallel.spnodes import Node
from graphtheory.seriesparallel.sptrees import make_random_sptree
from graphtheory.seriesparallel.spdset import SPTreeDominatingSet
from graphtheory.seriesparallel.spnodes import btree_inorder
from graphtheory.seriesparallel.spnodes import btree_print

V = 10
root = make_random_sptree(V)
E = 0
for tnode in btree_inorder(root):
    if tnode.type == "edge":
        E += 1
#btree_print(root)

algorithm = SPTreeDominatingSet(root)
algorithm.run()
print("dset {}".format(algorithm.dominating_set))
print("cardinality {}".format(algorithm.cardinality))

print("Testing SPTreeDominatingSet ...")
t1 = timeit.Timer(lambda: SPTreeDominatingSet(root).run())
print("{} {} {}".format(V, E, t1.timeit(1)))  # single run

Beispiel #2

Datei: timeit_spmate.py Projekt: ufkapano/graphs-dict

#!/usr/bin/python
#
# Sprawdzam szybkosc wyznaczania matching.

import timeit
import random
from graphtheory.structures.edges import Edge
from graphtheory.structures.graphs import Graph
from graphtheory.seriesparallel.spnodes import Node
from graphtheory.seriesparallel.sptrees import make_random_sptree
from graphtheory.seriesparallel.spmate import SPTreeMatching
from graphtheory.seriesparallel.spnodes import btree_inorder
from graphtheory.seriesparallel.spnodes import btree_print

V = 10
root = make_random_sptree(V)
E = 0
for tnode in btree_inorder(root):
    if tnode.type == "edge":
        E += 1
#btree_print(root)

algorithm = SPTreeMatching(root)
algorithm.run()
print ( "mate_set {}".format( algorithm.mate_set ))
print ( "mate {}".format( algorithm.mate ))
print ( "cardinality {}".format( algorithm.cardinality ))

print ( "Testing SPTreeMatching ..." )
t1 = timeit.Timer(lambda: SPTreeMatching(root).run())
print ( "{} {} {}".format(V, E, t1.timeit(1)) )   # single run