       Re: Re: Finding Clusters

```Szabolcs Horvát wrote:
> On 2009.11.04. 7:34, Fred Simons wrote:
>
>> Here is a very short, very fast but not very simple solution:
>>
>> components[lst_List] := Module[{f},
>>    Do[Set @@ f /@ pair, {pair, lst}];   GatherBy[Union @@ lst, f]]
>>
>>
>
> I enjoyed Fred Simons's solution tremendously.
>
> I tried to speed it up a bit.
>
> I compared the speed of components[] with the speed of WeakComponents
> (from the GraphUtilities package) for random graphs (e.g.
> RandomInteger[50000, {30000, 2}]).  It seems that components[] is faster
> than WeakComponents for as long as the graph doesn't have very large
> connected components.  However, as soon as large connected components
> appear, components[] slows down a lot.
>
> I looked into the source of WeakComponents to find out how it works, but
> it turns out it uses undocumented functions, such as
> SparseArray`StronglyConnectedComponents
>
> The reason for the slowdown of components[] when large connected
> components are present is that the f[] function needs to be evaluated in
> several steps.  E.g. for the graph {{1,2},{2,3},{3,4}}, the definition
> of f will include f=f, f=f, f=f, so the evaluation of
> f will take 3 steps.
>
> I tried to remedy this by changing f so that it re-defines itself each
> time the left-hand-side of a particular definition can be evaluated
> further.  With the above example, evaluating f would cause the
> definition of f to change from f=f to f=f (as f
> evaluates to f).  Here's the solution:
>
> setSpecial[lhs_, rhs_] /; rhs =!= lhs :=
>    (lhs := With[{val = #1}, lhs := #0[val]; val] &[rhs])
>
> components2[lst_List] :=
>   Module[{f},
>    Do[setSpecial @@ f /@ pair, {pair, lst}];
>    GatherBy[Union @@ lst, f]
>   ]
>
> This modified components2[] seems to be faster than WeakComponents[]
> even for single-component random graphs, however, it is limited by
> \$RecursionLimit (which can't be increased indefinitely without risking a
> crash)
>
> Szabolcs
>
> P.S. Here's the code I used to compare the speed of components[] and
> WeakComponents[].  For 'a' greater than about 0.5 components[] gets slow.
>
> a = 0.7;
>
> tw = Table[
>    g = RandomInteger[n, {Ceiling[a n], 2}];
>    {n, First@Timing[WeakComponents[Rule @@@ g]]},
>    {n, 2^Range[11, 16]}
>    ]
>
> tc = Table[
>    g = RandomInteger[n, {Ceiling[a n], 2}];
>    {n, First@Timing[components[g]]},
>    {n, 2^Range[11, 16]}
>    ]
>
> tc2 = Table[
>    g = RandomInteger[n, {Ceiling[a n], 2}];
>    {n, First@Timing[components2[g]]},
>    {n, 2^Range[11, 16]}
>    ]
>
> ListLogLogPlot[{tw, tc, tc2}, Joined -> True,
>   PlotMarkers -> Automatic]
>
>
Another late to the party post. I think this topic was discussed back in
2005, and I think the quickest solution then was found in my post:*

http://tinyurl.com/ylon3hr*

Anyway, the solution was:

aggs[n_, pairs_] := Module[{sp, t},
sp = SparseArray[Thread[pairs -> 1], {n, n}];
t = Sign[sp + Transpose[sp]];
SparseArray`StronglyConnectedComponents[t]]

Here, the pairs argument needs to be a list of pairs of positive
integers, and n is the maximum of these integers. A quick comparison
with components2 follows:

In:= g = RandomInteger[{1, 10^4}, {7000, 2}];

r1 = components2[g]; // Timing
r2 = aggs[10^4, g]; // Timing

Sort[Sort /@ DeleteCases[r1, {_}]] ===  Sort[Sort /@ DeleteCases[r2, {_}]]

Out= {0.499, Null}

Out= {0.016, Null}

Out= True

So, about 30 times faster.

Carl Woll
Wolfram Research

```

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