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Add a few igraph algorithms to run via scripts/bench.py
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973fb1c
Add a few igraph algorithms to run via `scripts/bench.py`
eriknw ec81bd1
clustering in igraph
eriknw 4bcc817
Add `--min-n` command line option to `scripts/bench.py`
eriknw 8e58900
oops run pre-commit
eriknw 76ab622
Merge branch 'main' into bench_igraph
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -14,6 +14,7 @@ | |
| import scipy.sparse | ||
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| import graphblas_algorithms as ga | ||
| import igraph_impl | ||
| import scipy_impl | ||
| from graphblas_algorithms.interface import Dispatcher | ||
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@@ -56,13 +57,20 @@ def readfile(filepath, is_symmetric, backend): | |
| return ga.Graph(A) | ||
| return ga.DiGraph(A) | ||
| a = scipy.io.mmread(filepath) | ||
| if backend == "networkx": | ||
| if backend in {"networkx", "igraph"}: | ||
| create_using = nx.Graph if is_symmetric else nx.DiGraph | ||
| return nx.from_scipy_sparse_array(a, create_using=create_using) | ||
| G = nx.from_scipy_sparse_array(a, create_using=create_using) | ||
| if backend == "networkx": | ||
| return G | ||
| if backend == "igraph": | ||
| # TODO: is there a better way for igraph to read MM files or scipy.sparse arrays? | ||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more.
You can use There is no direct support for reading MM files in igraph. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Just what I was looking for, thanks! |
||
| import igraph | ||
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||
| return igraph.Graph.from_networkx(G) | ||
| if backend == "scipy": | ||
| return scipy.sparse.csr_array(a) | ||
| raise ValueError( | ||
| f"Backend {backend!r} not understood; must be 'graphblas', 'networkx', or 'scipy'" | ||
| f"Backend {backend!r} not understood; must be 'graphblas', 'networkx', 'igraph', or 'scipy'" | ||
| ) | ||
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@@ -126,6 +134,8 @@ def getfunction(functionname, backend): | |
| return getattr(Dispatcher, functionname) | ||
| if backend == "scipy": | ||
| return getattr(scipy_impl, functionname) | ||
| if backend == "igraph": | ||
| return getattr(igraph_impl, functionname) | ||
| if functionname in functionpaths: | ||
| func = nx | ||
| for attr in functionpaths[functionname].split("."): | ||
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@@ -149,7 +159,15 @@ def getgraph(dataname, backend="graphblas", functionname=None): | |
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| def main( | ||
| dataname, backend, functionname, time=3.0, n=None, extra=None, display=True, enable_gc=False | ||
| dataname, | ||
| backend, | ||
| functionname, | ||
| time=3.0, | ||
| n=None, | ||
| min_n=None, | ||
| extra=None, | ||
| display=True, | ||
| enable_gc=False, | ||
| ): | ||
| G = getgraph(dataname, backend, functionname) | ||
| func = getfunction(functionname, backend) | ||
|
|
@@ -193,6 +211,8 @@ def main( | |
| n = 1 | ||
| elif n is None: | ||
| n = 2 ** max(0, int(np.ceil(np.log2(time / first_time)))) | ||
| if min_n is not None: | ||
| n = max(n, min_n) | ||
| if display: | ||
| print("Number of runs:", n) | ||
| print("first: ", stime(first_time)) | ||
|
|
@@ -222,7 +242,7 @@ def main( | |
| description=f"Example usage: python {sys.argv[0]} -b graphblas -f pagerank -d amazon0302" | ||
| ) | ||
| parser.add_argument( | ||
| "-b", "--backend", choices=["graphblas", "networkx", "scipy"], default="graphblas" | ||
| "-b", "--backend", choices=["graphblas", "networkx", "scipy", "igraph"], default="graphblas" | ||
| ) | ||
| parser.add_argument( | ||
| "-t", "--time", type=float, default=3.0, help="Target minimum time to run benchmarks" | ||
|
|
@@ -232,6 +252,11 @@ def main( | |
| type=int, | ||
| help="The number of times to run the benchmark (the default is to run according to time)", | ||
| ) | ||
| parser.add_argument( | ||
| "--min-n", | ||
| type=int, | ||
| help="The minimum number of times to run the benchmark", | ||
| ) | ||
| parser.add_argument( | ||
| "-d", | ||
| "--data", | ||
|
|
@@ -260,6 +285,7 @@ def main( | |
| args.func, | ||
| time=args.time, | ||
| n=args.n, | ||
| min_n=args.min_n, | ||
| extra=args.extra, | ||
| display=not args.json, | ||
| enable_gc=args.gc, | ||
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||
51 changes: 51 additions & 0 deletions
scripts/igraph_impl.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,51 @@ | ||
| def overall_reciprocity(G): | ||
| return G.reciprocity() | ||
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| def pagerank( | ||
| G, | ||
| alpha=0.85, | ||
| personalization=None, | ||
| max_iter=100, | ||
| tol=1e-06, | ||
| nstart=None, | ||
| weight="weight", | ||
| dangling=None, | ||
| *, | ||
| vertices=None, | ||
| directed=True, | ||
| arpack_options=None, | ||
| implementation="prpack", | ||
| ): | ||
| if personalization is not None: | ||
| raise NotImplementedError | ||
|
||
| if nstart is not None: | ||
| raise NotImplementedError | ||
| if dangling is not None: | ||
| raise NotImplementedError | ||
|
||
| rv = G.pagerank( | ||
| vertices=vertices, | ||
| directed=directed, | ||
| damping=alpha, | ||
| weights=weight, | ||
| arpack_options=arpack_options, | ||
| implementation=implementation, | ||
| ) | ||
| return rv | ||
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| def transitivity(G): | ||
| return G.transitivity_undirected() | ||
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| def average_clustering(G, nodes=None, weight=None, count_zeros=True): | ||
| if nodes is not None: | ||
| raise NotImplementedError | ||
| # TODO: check results when `count_zeros=False` | ||
| mode = "zero" if count_zeros else "nan" | ||
|
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| return G.transitivity_avglocal_undirected(mode=mode, weights=weight) | ||
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| def clustering(G, nodes=None, weight=None): | ||
| mode = "zero" # or "nan" | ||
| return G.transitivity_local_undirected(vertices=nodes, mode=mode, weights=weight) | ||
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