#18811: Boost Clustering Coefficient
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Reporter: borassi | Owner:
Type: enhancement | Status: needs_review
Priority: major | Milestone: sage-6.8
Component: graph theory | Resolution:
Keywords: Local clustering | Merged in:
coefficient, Boost | Reviewers:
Authors: Michele Borassi | Work issues:
Report Upstream: N/A | Commit:
Branch: | 283c61be9357902ff555843b27c0ffed6fed6ea4
u/borassi/boost_clustering_coefficient| Stopgaps:
Dependencies: 18564 |
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Changes (by {'newvalue': u'Michele Borassi', 'oldvalue': ''}):
* status: new => needs_review
* author: => Michele Borassi
* cc: dcoudert (added)
* component: PLEASE CHANGE => graph theory
* dependencies: => 18564
* keywords: => Local clustering coefficient, Boost
* commit: => 283c61be9357902ff555843b27c0ffed6fed6ea4
* type: PLEASE CHANGE => enhancement
Old description:
New description:
Apply Boost algorithm for computing the clustering coefficient, using the
interface of Ticket !#18564.
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Comment:
Hello!
I have implemented the computation of the local clustering coefficient
through Boost. The improvement is not as striking as the edge
connectivity, but it is still a 10x improvement, more or less. Some
benchmarks:
{{{
sage: g = graphs.RandomGNM(20000,100000)
sage: %timeit g.clustering_coeff(implementation='boost')
10 loops, best of 3: 258 ms per loop
sage: %timeit g.clustering_coeff(implementation='networkx')
1 loops, best of 3: 3.99 s per loop
}}}
{{{
sage: g = graphs.CompleteGraph(300)
sage: %timeit g.clustering_coeff(implementation='boost')
1 loops, best of 3: 6.14 s per loop
sage: %timeit g.clustering_coeff(implementation='networkx')
1 loops, best of 3: 1min 3s per loop
}}}
{{{
sage: g = graphs.RandomGNM(10000,1000000)
sage: %timeit
g.clustering_coeff(implementation='networkx',nodes=range(30))
1 loops, best of 3: 13.1 s per loop
sage: %timeit g.clustering_coeff(implementation='boost',nodes=range(30))
1 loops, best of 3: 1.55 s per loop
}}}
I hope you like it!
--
Ticket URL: <http://trac.sagemath.org/ticket/18811#comment:3>
Sage <http://www.sagemath.org>
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