Re: [QUIZ] Distinct Sets (#225)

On Fri, Nov 20, 2009 at 9:23 PM, Daniel Moore <yahivin@gmail.com> wrote:
>
> ## Distinct Sets (#225)
>
> Aloha Rubyists,
>
> This week's quiz comes from Ruby Quiz Suggestions MVP Martin DeMello[1].
>
> [based on a surprisingly tricky stackoverflow problem]
>
> You have an list of sets, which you want to transform by the following
> method: if any two sets have a common element, merge them into a
> single set. You will be left with a reduced list partitioning all the
> elements into sets where every set is disjoint from every other.

$ ruby -v 225.rb
ruby 1.8.2 (2004-12-25) [powerpc-darwin8.0]
Loaded suite 225
Started

On Nov 21, 2009, at 11:50 AM, brabuhr@gmail.com wrote:

> On Fri, Nov 20, 2009 at 9:23 PM, Daniel Moore <yahivin@gmail.com>
> wrote:
>>
>> ## Distinct Sets (#225)
>>
>> Aloha Rubyists,
>>
>> This week's quiz comes from Ruby Quiz Suggestions MVP Martin
>> DeMello[1].
>>
>> [based on a surprisingly tricky stackoverflow problem]
>>
>> You have an list of sets, which you want to transform by the
>> following
>> method: if any two sets have a common element, merge them into a
>> single set. You will be left with a reduced list partitioning all the
>> elements into sets where every set is disjoint from every other.
>
> $ ruby -v 225.rb
> ruby 1.8.2 (2004-12-25) [powerpc-darwin8.0]
> Loaded suite 225
> Started
> .
> Finished in 0.059557 seconds.
>
> 1 tests, 10 assertions, 0 failures, 0 errors
>
> But, I cheated a bit in my assertions; sorting the expected and actual
> values before asserting them equal:

I'm sure that there's a better way than mine, but it seems to work well.

ruby -v -rubygems distinct_sets_test.rb
ruby 1.8.6 (2008-08-11 patchlevel 287) [universal-darwin9.0]
/Library/Ruby/Gems/1.8/gems/thoughtbot-shoulda-2.9.1/lib/shoulda/
context.rb:4: warning: method redefined; discarding old contexts
Loaded suite distinct_sets_test
Started
....................
Finished in 0.018326 seconds.

20 tests, 148 assertions, 0 failures, 0 errors

This includes all the tests given in the original quiz description and
all the tests from brabuhr@gmail.com, but using Shoulda and splitting
the one "tests" method with 10 assertions into 4 separate methods with
one assertion each and eliminating the duplicates.

http://gist.github.com/240457

I'm guessing the speed difference is due more to 1.8.2 v. 1.8.6 and
the actual machines than any significant difference in our algorithms.

-Rob

Rob Biedenharn http://agileconsultingllc.com
Rob@AgileConsultingLLC.com

> http://gist.github.com/240457

Both of your tests use rather small input sets. It would be
interesting to know how the solutions deal with input that contains
many (10, 50, 100, ....) sets and/or many different signs (not just
letters).

On Nov 22, 2009, at 1:51 AM, lith wrote:

>> http://gist.github.com/240457
>
> Both of your tests use rather small input sets. It would be
> interesting to know how the solutions deal with input that contains
> many (10, 50, 100, ....) sets and/or many different signs (not just
> letters).

I accept your challenge! The gist has been updated with sets that use
numbers and symbols as well as strings. There are also some tests of
large sets (which worked fine, but getting the test setup by hand was
nasty).

ruby -rubygems distinct_sets_test.rb
Loaded suite distinct_sets_test
Started
..........................
Finished in 1.237836 seconds.

26 tests, 202 assertions, 0 failures, 0 errors


The only change that I has to make was in how I sorted the final array
to account for symbols or mixed contents: Numerics compare "naturally"
with <=> and non-numeric or mixed are compared using the #to_s
representation.

-Rob

P.S. I could add my solution to the gist, too, but I'll give everyone
a chance to try the new tests first.

Rob Biedenharn http://agileconsultingllc.com
Rob@AgileConsultingLLC.com

On Mon, Nov 23, 2009 at 11:10 AM, Rob Biedenharn
<Rob@agileconsultingllc.com> wrote:
> On Nov 22, 2009, at 1:51 AM, lith wrote:
>>> http://gist.github.com/240457
>>
>> Both of your tests use rather small input sets. It would be
>> interesting to know how the solutions deal with input that contains
>> many (10, 50, 100, ....) sets and/or many different signs (not just
>> letters).
>
> I accept your challenge! =A0The gist has been updated with sets that use
> numbers and symbols as well as strings. =A0There are also some tests of l=
arge
> sets (which worked fine, but getting the test setup by hand was nasty).

Thanks.

> ruby1.8 -v -rubygems distinct_sets_test.rb
ruby 1.8.7 (2009-06-12 patchlevel 174) [i486-linux]
/var/lib/gems/1.8/gems/shoulda-2.10.2/lib/shoulda/context.rb:4:
warning: method redefined; discarding old contexts
Loaded suite distinct_sets_test
Started
..................EEE.....
Finished in 3.424045 seconds.

1) Error:
test: non-uniform contents should handle matching on symbols.
(DistinctSetsTest):
ArgumentError: comparison of String with :bill failed
./distinct_sets.rb:7:in `sort'

2) Error:
test: non-uniform contents should handle mix of strings and symbols
(matching on string). (DistinctSetsTest):
ArgumentError: comparison of String with :bill failed
./distinct_sets.rb:7:in `sort'

3) Error:
test: non-uniform contents should handle mix of strings, numbers, and
symbols. (DistinctSetsTest):
ArgumentError: comparison of Fixnum with :emergency failed
./distinct_sets.rb:7:in `sort'

26 tests, 175 assertions, 0 failures, 3 errors

> The only change that I has to make was in how I sorted the final array to
> account for symbols or mixed contents: Numerics compare "naturally" with =
<=3D>
> and non-numeric or mixed are compared using the #to_s representation.

Simply not sorting:

26 tests, 202 assertions, 17 failures, 0 errors

Simply sort_by{to_s}:

26 tests, 202 assertions, 3 failures, 0 errors

More complex sort{}:

26 tests, 202 assertions, 0 failures, 0 errors

[Note: parts of this message were removed to make it a legal post.]

Hey Rubyists!

I think I got quite a fast solution, using 1.9.

Here is my test file : http://pastie.org/711737
You just need to change METHOD and require your own file

So here is my best result for the 19tests:

Finished in 0.222688 seconds.
1 tests, 19 assertions, 0 failures, 0 errors, 0 skips

Without sorting(I just had to change the order of some tests of Rob)

Maye I should also say I'm using a 64bit ruby 1.9.2 ? Anyway I think this
method is far faster than my others(about 100 times) and probably some of
yours.

Enjoy the quiz,
Benoit

2009/11/23 <brabuhr@gmail.com>

> On Mon, Nov 23, 2009 at 11:10 AM, Rob Biedenharn
> <Rob@agileconsultingllc.com> wrote:
> > On Nov 22, 2009, at 1:51 AM, lith wrote:
> >>> http://gist.github.com/240457
> >>
> >> Both of your tests use rather small input sets. It would be
> >> interesting to know how the solutions deal with input that contains
> >> many (10, 50, 100, ....) sets and/or many different signs (not just
> >> letters).
> >
> > I accept your challenge! The gist has been updated with sets that use
> > numbers and symbols as well as strings. There are also some tests of
> large
> > sets (which worked fine, but getting the test setup by hand was nasty).
>
> Thanks.
>
> > ruby1.8 -v -rubygems distinct_sets_test.rb
> ruby 1.8.7 (2009-06-12 patchlevel 174) [i486-linux]
> /var/lib/gems/1.8/gems/shoulda-2.10.2/lib/shoulda/context.rb:4:
> warning: method redefined; discarding old contexts
> Loaded suite distinct_sets_test
> Started
> ..................EEE.....
> Finished in 3.424045 seconds.
>
> 1) Error:
> test: non-uniform contents should handle matching on symbols.
> (DistinctSetsTest):
> ArgumentError: comparison of String with :bill failed
> ./distinct_sets.rb:7:in `sort'
>
> 2) Error:
> test: non-uniform contents should handle mix of strings and symbols
> (matching on string). (DistinctSetsTest):
> ArgumentError: comparison of String with :bill failed
> ./distinct_sets.rb:7:in `sort'
>
> 3) Error:
> test: non-uniform contents should handle mix of strings, numbers, and
> symbols. (DistinctSetsTest):
> ArgumentError: comparison of Fixnum with :emergency failed
> ./distinct_sets.rb:7:in `sort'
>
> 26 tests, 175 assertions, 0 failures, 3 errors
>
> > The only change that I has to make was in how I sorted the final array to
> > account for symbols or mixed contents: Numerics compare "naturally" with
> <=>
> > and non-numeric or mixed are compared using the #to_s representation.
>
> Simply not sorting:
>
> 26 tests, 202 assertions, 17 failures, 0 errors
>
> Simply sort_by{to_s}:
>
> 26 tests, 202 assertions, 3 failures, 0 errors
>
> More complex sort{}:
>
> 26 tests, 202 assertions, 0 failures, 0 errors
>
>

Here's my not-fast solution:

require 'set'

class Set
def intersect?(other)
other.each { |o| return true if include?(o) }
false
end
end

def distinct_sets(array_of_arrays)
set_of_sets = array_of_arrays.map{|a|
a.to_set
}.to_set

set_of_sets.divide{|i, j|
i.intersect?(j)
}.map{|s|
s.flatten.to_a
}
end

Adding the intersect? method to Set was primarily motivated by
readability, but also provided a noticeable speed improvement over my
original alternative (intersection.size.>).

[Note: parts of this message were removed to make it a legal post.]

I must admit is a very elegant solution.
And it's not so slow, 0.36s with my tests and adding .map { |s|
s.flatten.to_a*.sort*
}, it pass all the tests without sorting.
Awesome for a Ruby-based class! A nice exemple of using forgot methods like
divide.

2009/11/23 <brabuhr@gmail.com>

> Here's my not-fast solution:
>
> require 'set'
>
> class Set
> def intersect?(other)
> other.each { |o| return true if include?(o) }
> false
> end
> end
>
> def distinct_sets(array_of_arrays)
> set_of_sets = array_of_arrays.map{|a|
> a.to_set
> }.to_set
>
> set_of_sets.divide{|i, j|
> i.intersect?(j)
> }.map{|s|
> s.flatten.to_a
> }
> end
>
> Adding the intersect? method to Set was primarily motivated by
> readability, but also provided a noticeable speed improvement over my
> original alternative (intersection.size.>).
>
>

> And it's not so slow,

I wrote a small approximative benchmark for that runs the script with
different set configurations.
http://pastie.org/711915

It might be interesting to compare the runtime behaviour of your
script with other solutions.

On Tue, Nov 24, 2009 at 1:20 AM, lith <minilith@gmail.com> wrote:
>> And it's not so slow,
>
> I wrote a small approximative benchmark for that runs the script with
> different set configurations.
> http://pastie.org/711915

> cat /proc/cpuinfo | fgrep name
model name : Intel(R) Pentium(R) M processor 1.60GHz
> uname -a
Linux eXist 2.6.31-14-generic #48-Ubuntu SMP Fri Oct 16 14:04:26 UTC
2009 i686 GNU/Linux
> ruby1.8 -v 711915.rb 225.rb
ruby 1.8.7 (2009-06-12 patchlevel 174) [i486-linux]
user system
total real
elements * sets: 1 * 5 => 1 * 1 0.010000 0.000000
0.010000 ( 0.010348)
elements * sets: 1 * 5 => 2 * 1 0.010000 0.000000
0.010000 ( 0.008285)
elements * sets: 2 * 5 => 3 * 1 0.010000 0.000000
0.010000 ( 0.015534)
elements * sets: 2 * 5 => 4 * 1 0.020000 0.000000
0.020000 ( 0.020882)
elements * sets: 2 * 5 => 5 * 1 0.020000 0.010000
0.030000 ( 0.023482)
elements * sets: 3 * 5 => 6 * 1 0.020000 0.000000
0.020000 ( 0.021767)
elements * sets: 3 * 5 => 7 * 1 0.040000 0.000000
0.040000 ( 0.035285)
elements * sets: 3 * 5 => 8 * 1 0.020000 0.010000
0.030000 ( 0.028141)
elements * sets: 4 * 5 => 9 * 1 0.020000 0.000000
0.020000 ( 0.028562)
elements * sets: 4 * 5 => 10 * 1 0.020000 0.010000
0.030000 ( 0.029465)
elements * sets: 18 * 255 => 1 * 51 0.780000 0.140000
0.920000 ( 0.922092)
elements * sets: 35 * 255 => 2 * 51 1.330000 0.190000
1.520000 ( 1.526110)
elements * sets: 52 * 255 => 3 * 51 1.110000 0.220000
1.330000 ( 1.338236)
elements * sets: 69 * 255 => 4 * 51 1.670000 0.280000
1.950000 ( 1.942574)
elements * sets: 86 * 255 => 5 * 51 1.440000 0.320000
1.760000 ( 1.763389)
elements * sets: 103 * 255 => 6 * 51 1.820000 0.330000
2.150000 ( 2.147160)
elements * sets: 120 * 255 => 7 * 51 1.720000 0.430000
2.150000 ( 2.165951)
elements * sets: 137 * 255 => 8 * 51 2.300000 0.480000
2.780000 ( 2.774613)
elements * sets: 154 * 255 => 9 * 51 2.180000 0.390000
2.570000 ( 2.571221)
elements * sets: 171 * 255 => 10 * 51 2.430000 0.500000
2.930000 ( 2.921943)
elements * sets: 34 * 505 => 1 * 101 2.550000 0.650000
3.200000 ( 3.199823)
elements * sets: 68 * 505 => 2 * 101 4.540000 1.000000
5.540000 ( 5.547267)
elements * sets: 102 * 505 => 3 * 101 3.980000 0.740000
4.720000 ( 4.744038)
elements * sets: 135 * 505 => 4 * 101 5.890000 1.210000
7.100000 ( 7.099683)
elements * sets: 169 * 505 => 5 * 101 5.170000 1.120000
6.290000 ( 6.288145)
elements * sets: 203 * 505 => 6 * 101 6.660000 1.510000
8.170000 ( 11.120129)
elements * sets: 236 * 505 => 7 * 101 6.470000 1.360000
7.830000 ( 7.843291)
elements * sets: 270 * 505 => 8 * 101 8.390000 1.830000
10.220000 ( 10.233364)
elements * sets: 304 * 505 => 9 * 101 7.750000 1.630000
9.380000 ( 9.377075)
elements * sets: 337 * 505 => 10 * 101 8.730000 2.000000
10.730000 ( 10.752132)


And another one-off benchmark I had run:

per
sets set user system total real
10, 1 0.000000 0.000000 0.000000 ( 0.005441)
10, 10 0.010000 0.000000 0.010000 ( 0.006944)
10, 100 0.040000 0.010000 0.050000 ( 0.044136)
10, 1000 0.310000 0.060000 0.370000 ( 0.372266)
10, 10000 1.620000 0.090000 1.710000 ( 1.718613)
10, 100000 18.700000 1.020000 19.720000 ( 19.869159)
user system total real
1, 10 0.000000 0.000000 0.000000 ( 0.002515)
10, 10 0.010000 0.000000 0.010000 ( 0.006701)
100, 10 0.370000 0.080000 0.450000 ( 0.454811)
1000, 10 36.210000 8.340000 44.550000 ( 44.798496)
user system total real
1, 1 0.000000 0.000000 0.000000 ( 0.000435)
10, 10 0.010000 0.000000 0.010000 ( 0.006239)
100, 100 2.900000 0.750000 3.650000 ( 3.762373)

(Sets were filled with random integers.)

> =A0 set_of_sets.divide{|i, j|
> =A0 =A0 i.intersect?(j)
> =A0 }

I didn't know the Set#divide method. Interesting.

Here is a graph-based approach:
http://pastie.org/714759

Regards,
Tom

On Wed, Nov 25, 2009 at 11:59 AM, lith <minilith@gmail.com> wrote:
> Here is a graph-based approach:
> http://pastie.org/714759

Running the small approximative benchmark:

> fgrep name /proc/cpuinfo
model name : Intel(R) Pentium(R) M processor 1.60GHz
> uname -a
Linux eXist 2.6.31-14-generic #48-Ubuntu SMP Fri Oct 16 14:04:26 UTC
2009 i686 GNU/Linux
> ruby1.8 -v 711915.rb 714759.rb
ruby 1.8.7 (2009-06-12 patchlevel 174) [i486-linux]
user system
total real
elements * sets: 1 * 5 => 1 * 1 0.000000 0.000000
0.000000 ( 0.003731)
elements * sets: 1 * 5 => 2 * 1 0.000000 0.000000
0.000000 ( 0.002467)
elements * sets: 2 * 5 => 3 * 1 0.000000 0.000000
0.000000 ( 0.003154)
elements * sets: 2 * 5 => 4 * 1 0.010000 0.000000
0.010000 ( 0.004540)
elements * sets: 2 * 5 => 5 * 1 0.000000 0.000000
0.000000 ( 0.005251)
elements * sets: 3 * 5 => 6 * 1 0.010000 0.000000
0.010000 ( 0.004601)
elements * sets: 3 * 5 => 7 * 1 0.000000 0.000000
0.000000 ( 0.006505)
elements * sets: 3 * 5 => 8 * 1 0.000000 0.010000
0.010000 ( 0.008302)
elements * sets: 4 * 5 => 9 * 1 0.000000 0.000000
0.000000 ( 0.008121)
elements * sets: 4 * 5 => 10 * 1 0.010000 0.010000
0.020000 ( 0.008174)
elements * sets: 18 * 255 => 1 * 51 0.070000 0.000000
0.070000 ( 0.068440)
elements * sets: 35 * 255 => 2 * 51 0.120000 0.020000
0.140000 ( 0.145098)
elements * sets: 52 * 255 => 3 * 51 0.220000 0.030000
0.250000 ( 0.253006)
elements * sets: 69 * 255 => 4 * 51 0.310000 0.060000
0.370000 ( 0.375845)
elements * sets: 86 * 255 => 5 * 51 0.450000 0.070000
0.520000 ( 0.516071)
elements * sets: 103 * 255 => 6 * 51 0.580000 0.090000
0.670000 ( 0.680203)
elements * sets: 120 * 255 => 7 * 51 0.740000 0.130000
0.870000 ( 0.864627)
elements * sets: 137 * 255 => 8 * 51 0.920000 0.160000
1.080000 ( 1.082008)
elements * sets: 154 * 255 => 9 * 51 1.190000 0.130000
1.320000 ( 1.319013)
elements * sets: 171 * 255 => 10 * 51 1.380000 0.190000
1.570000 ( 1.569024)
elements * sets: 34 * 505 => 1 * 101 0.140000 0.010000
0.150000 ( 0.151603)
elements * sets: 68 * 505 => 2 * 101 0.260000 0.060000
0.320000 ( 0.336318)
elements * sets: 102 * 505 => 3 * 101 0.490000 0.060000
0.550000 ( 0.537813)
elements * sets: 135 * 505 => 4 * 101 0.700000 0.090000
0.790000 ( 0.802585)
elements * sets: 169 * 505 => 5 * 101 0.950000 0.160000
1.110000 ( 1.106535)
elements * sets: 203 * 505 => 6 * 101 1.240000 0.220000
1.460000 ( 1.456670)
elements * sets: 236 * 505 => 7 * 101 1.590000 0.260000
1.850000 ( 1.850735)
elements * sets: 270 * 505 => 8 * 101 2.030000 0.260000
2.290000 ( 2.294973)
elements * sets: 304 * 505 => 9 * 101 2.350000 0.430000
2.780000 ( 2.784864)
elements * sets: 337 * 505 => 10 * 101 2.860000 0.470000
3.330000 ( 3.335518)


And a little one-off benchmark (sets of random integers):

per
sets set user system total real
10, 1 0.000000 0.000000 0.000000 ( 0.000776)
10, 10 0.000000 0.000000 0.000000 ( 0.005667)
10, 100 0.350000 0.030000 0.380000 ( 0.384304)
10, 1000 Timeout::Error - execution expired (> 3 minutes)
user system total real
1, 10 0.000000 0.000000 0.000000 ( 0.000743)
10, 10 0.000000 0.000000 0.000000 ( 0.009329)
100, 10 0.040000 0.010000 0.050000 ( 0.056932)
1000, 10 5.180000 0.070000 5.250000 ( 7.455180)
10000, 10 8.460000 0.510000 8.970000 ( 12.744708)
100000, 10 Timeout::Error - execution expired (> 3 minutes)
user system total real
1, 1 0.010000 0.000000 0.010000 ( 0.003573)
10, 10 0.010000 0.000000 0.010000 ( 0.008709)
100, 100 28.750000 0.350000 29.100000 ( 42.588412)
1000, 1000 Timeout::Error - execution expired (> 3 minutes)

<brabuhr@gmail.com>:
>> Here's my not-fast solution:
Benoit Daloze <eregontp@gmail.com>:
> I must admit is a very elegant solution.

Here's a fresh non-elegant solution:

def distinct_sets(sets)
sets = sets.dup
h1 = {}; h2 = {}
sets.each{|s| h1[s.object_id] = s.dup; s.each{|e| (h2[e] ||= []) <<
s.object_id}}
merges = h2.select{|_, ids| ids.size > 1}.map{|_, ids| ids}
return sets.sort.uniq if merges.size == 0
flag = true
while flag
flag = false
merges = h1.keys.map{|id|
merges.select{|m| m.include?(id)}.tap{|m| flag = true if m.size
> 1}.flatten.uniq
}.uniq
end
result = []
merges.each{|m| result << m.map{|id| s = h1[id]; h1.delete(id);
s}.flatten.sort.uniq }
(result + h1.values).sort.uniq
end

Slight bug in this version, (sometimes) adds an empty set to "result", e.g.:
[ [], ["B", "C", "D", "F", "G", "J", "K", "L", "M", "N", "Q"], ["E", "H"] ]


ruby 1.8.7 (2009-06-12 patchlevel 174) [i486-linux]
user system
total real
elements * sets: 1 * 5 => 1 * 1 0.010000 0.000000
0.010000 ( 0.008809)
elements * sets: 1 * 5 => 2 * 1 0.000000 0.000000
0.000000 ( 0.008136)
elements * sets: 2 * 5 => 3 * 1 0.010000 0.000000
0.010000 ( 0.007661)
elements * sets: 2 * 5 => 4 * 1 0.010000 0.000000
0.010000 ( 0.007797)
elements * sets: 2 * 5 => 5 * 1 0.010000 0.000000
0.010000 ( 0.008351)
elements * sets: 3 * 5 => 6 * 1 0.010000 0.000000
0.010000 ( 0.008181)
elements * sets: 3 * 5 => 7 * 1 0.010000 0.000000
0.010000 ( 0.011584)
elements * sets: 3 * 5 => 8 * 1 0.010000 0.000000
0.010000 ( 0.011224)
elements * sets: 4 * 5 => 9 * 1 0.010000 0.000000
0.010000 ( 0.011744)
elements * sets: 4 * 5 => 10 * 1 0.020000 0.000000
0.020000 ( 0.014110)
elements * sets: 18 * 255 => 1 * 51 0.630000 0.100000
0.730000 ( 0.752032)
elements * sets: 35 * 255 => 2 * 51 1.760000 0.230000
1.990000 ( 2.104564)
elements * sets: 52 * 255 => 3 * 51 2.230000 0.330000
2.560000 ( 2.578473)
elements * sets: 69 * 255 => 4 * 51 2.760000 0.400000
3.160000 ( 3.179041)
elements * sets: 86 * 255 => 5 * 51 3.230000 0.520000
3.750000 ( 3.770260)
elements * sets: 103 * 255 => 6 * 51 3.740000 0.560000
4.300000 ( 4.326179)
elements * sets: 120 * 255 => 7 * 51 4.250000 0.630000
4.880000 ( 4.919036)
elements * sets: 137 * 255 => 8 * 51 4.870000 0.700000
5.570000 ( 5.998519)
elements * sets: 154 * 255 => 9 * 51 5.350000 0.710000
6.060000 ( 6.334980)
elements * sets: 171 * 255 => 10 * 51 5.960000 0.700000
6.660000 ( 6.852846)
elements * sets: 34 * 505 => 1 * 101 2.200000 0.310000
2.510000 ( 2.528937)
elements * sets: 68 * 505 => 2 * 101 6.230000 0.860000
7.090000 ( 7.158239)
elements * sets: 102 * 505 => 3 * 101 8.130000 1.290000
9.420000 ( 10.024654)
elements * sets: 135 * 505 => 4 * 101 10.190000 1.370000
11.560000 ( 12.229713)
elements * sets: 169 * 505 => 5 * 101 12.060000 1.710000
13.770000 ( 14.657392)
elements * sets: 203 * 505 => 6 * 101 13.870000 2.060000
15.930000 ( 16.317533)
elements * sets: 236 * 505 => 7 * 101 15.860000 2.310000
18.170000 ( 18.707348)
elements * sets: 270 * 505 => 8 * 101 17.610000 2.750000
20.360000 ( 20.495151)
elements * sets: 304 * 505 => 9 * 101 19.780000 2.880000
22.660000 ( 23.630379)
elements * sets: 337 * 505 => 10 * 101 22.020000 2.980000
25.000000 ( 26.895880)

per
set set user system total real
10, 1 0.000000 0.000000 0.000000 ( 0.000205)
10, 10 0.000000 0.000000 0.000000 ( 0.000565)
10, 100 0.010000 0.000000 0.010000 ( 0.004842)
10, 1000 0.070000 0.000000 0.070000 ( 0.069138)
10, 10000 0.770000 0.100000 0.870000 ( 0.872998)
10, 100000 18.600000 1.130000 19.730000 ( 19.776977)
user system total real
1, 10 0.000000 0.000000 0.000000 ( 0.000126)
10, 10 0.000000 0.000000 0.000000 ( 0.000569)
100, 10 0.010000 0.000000 0.010000 ( 0.007341)
1000, 10 1.360000 0.040000 1.400000 ( 1.419874)
10000, 10 (> 3 minutes)
user system total real
1, 1 0.000000 0.000000 0.000000 ( 0.000044)
10, 10 0.000000 0.000000 0.000000 ( 0.000587)
100, 100 0.080000 0.010000 0.090000 ( 0.077950)
1000, 1000 (> 3 minutes)

<brabuhr@gmail.com>:
>>> Here's my not-fast solution:
Benoit Daloze <eregontp@gmail.com>:
>> I must admit is a very elegant solution.
<brabuhr@gmail.com> wrote:
> Here's a fresh non-elegant solution:

Had an epiphany while thinking about the last one I had sent :-)
The last half of the previous one can be applied directly to the input
array of arrays of items instead of to the intermediate array of
arrays of object ids:

def distinct_sets(sets)
sets = sets.dup
values = sets.flatten.sort.uniq
flag = true
while flag
flag = false
sets = values.map{|v|
sets.select{|s|
s.include?(v)
}.tap{|s|
flag = true if s.size > 1
}.flatten.sort.uniq
}.uniq
end
sets
end

Easier code, but generally scales more poorly than the previous more
complex version:

ruby 1.8.7 (2009-06-12 patchlevel 174) [i486-linux]
user system
total real
elements * sets: 1 * 5 => 1 * 1 0.000000 0.000000
0.000000 ( 0.001928)
elements * sets: 1 * 5 => 2 * 1 0.000000 0.000000
0.000000 ( 0.002136)
elements * sets: 2 * 5 => 3 * 1 0.000000 0.000000
0.000000 ( 0.003218)
elements * sets: 2 * 5 => 4 * 1 0.000000 0.000000
0.000000 ( 0.003926)
elements * sets: 2 * 5 => 5 * 1 0.010000 0.000000
0.010000 ( 0.007761)
elements * sets: 3 * 5 => 6 * 1 0.010000 0.000000
0.010000 ( 0.012438)
elements * sets: 3 * 5 => 7 * 1 0.010000 0.000000
0.010000 ( 0.009863)
elements * sets: 3 * 5 => 8 * 1 0.010000 0.000000
0.010000 ( 0.015234)
elements * sets: 4 * 5 => 9 * 1 0.020000 0.000000
0.020000 ( 0.022202)
elements * sets: 4 * 5 => 10 * 1 0.020000 0.000000
0.020000 ( 0.025353)
elements * sets: 18 * 255 => 1 * 51 0.400000 0.120000
0.520000 ( 0.514576)
elements * sets: 35 * 255 => 2 * 51 0.970000 0.180000
1.150000 ( 1.280102)
elements * sets: 52 * 255 => 3 * 51 1.690000 0.210000
1.900000 ( 2.260107)
elements * sets: 69 * 255 => 4 * 51 2.310000 0.390000
2.700000 ( 2.888354)
elements * sets: 86 * 255 => 5 * 51 3.220000 0.460000
3.680000 ( 4.250457)
elements * sets: 103 * 255 => 6 * 51 4.090000 0.590000
4.680000 ( 4.723892)
elements * sets: 120 * 255 => 7 * 51 5.200000 0.600000
5.800000 ( 6.258614)
elements * sets: 137 * 255 => 8 * 51 6.330000 0.700000
7.030000 ( 7.694748)
elements * sets: 154 * 255 => 9 * 51 7.470000 0.870000
8.340000 ( 8.730147)
elements * sets: 171 * 255 => 10 * 51 8.970000 0.820000
9.790000 ( 9.871180)
elements * sets: 34 * 505 => 1 * 101 1.720000 0.250000
1.970000 ( 2.331276)
elements * sets: 68 * 505 => 2 * 101 3.620000 0.750000
4.370000 ( 4.983125)
elements * sets: 102 * 505 => 3 * 101 6.110000 0.920000
7.030000 ( 7.258356)
elements * sets: 135 * 505 => 4 * 101 8.730000 1.460000
10.190000 ( 10.912860)
elements * sets: 169 * 505 => 5 * 101 12.130000 1.630000
13.760000 ( 14.714311)
elements * sets: 203 * 505 => 6 * 101 15.280000 2.040000
17.320000 ( 17.556731)
elements * sets: 236 * 505 => 7 * 101 19.090000 2.490000
21.580000 ( 22.005613)
elements * sets: 270 * 505 => 8 * 101 23.430000 2.620000
26.050000 ( 26.366511)
elements * sets: 304 * 505 => 9 * 101 28.090000 3.020000
31.110000 ( 32.421622)
elements * sets: 337 * 505 => 10 * 101 33.270000 3.550000
36.820000 ( 39.281699)

per
set set user system total real
10, 1 0.000000 0.000000 0.000000 ( 0.000338)
10, 10 0.010000 0.000000 0.010000 ( 0.006647)
10, 100 0.320000 0.000000 0.320000 ( 0.326307)
10, 1000 (>3 minutes)
user system total real
1, 10 0.000000 0.000000 0.000000 ( 0.000311)
10, 10 0.010000 0.000000 0.010000 ( 0.006137)
100, 10 0.290000 0.020000 0.310000 ( 0.305198)
1000, 10 77.240000 8.000000 85.240000 ( 90.868828)
10000, 10 (>3 minutes)
user system total real
1, 1 0.000000 0.000000 0.000000 ( 0.000052)
10, 10 0.000000 0.000000 0.000000 ( 0.006212)
100, 100 84.440000 1.080000 85.520000 ( 91.856640)
1000, 1000 (>3 minutes)

Sorry for all the posts :-) I think I'm done now. I refined the
complex, non-elegant solution a bit more; so, to make it easy to
reference later, here are my three main solutions:

First:

require 'set'

class Set
def intersect?(other)
other.each { |o| return true if include?(o) }
false
end
end

def distinct_sets(array_of_arrays)
set_of_sets = array_of_arrays.map{|a|
a.to_set
}.to_set

set_of_sets.divide{|i, j|
i.intersect?(j)
}.map{|s|
s.flatten.to_a.sort
}
end

Third:

def distinct_sets(sets)
sets = sets.dup
values = sets.flatten.sort.uniq
flag = true
while flag
flag = false
sets = values.map{|v|
sets.select{|s|
s.include?(v)
}.tap{|s|
flag = true if s.size > 1
}.flatten.sort.uniq
}.uniq
end
sets
end

Second (from the earlier post):

def distinct_sets(sets)
sets = sets.dup
h1 = {}; h2 = {}
sets.each{|s|
h1[s.object_id] = s.dup
s.each{|e| (h2[e] ||= []) << s.object_id}
}
merges = h2.select{|_, ids|
ids.size > 1
}.map{|_, ids| ids}
return sets.sort.uniq if merges.size == 0
flag = true
while flag
flag = false
merges = h1.keys.map{|id|
merges.select{|m|
m.include?(id)
}.tap{|m|
flag = true if m.size > 1
}.flatten.uniq
}.uniq
end
result = []
merges.each{|m|
result << m.map{|id|
s = h1[id]; h1.delete(id); s
}.flatten.sort.uniq
}
(result + h1.values).sort.uniq
end

Second (refined version):

def distinct_sets(sets)
sets = sets.dup
h1 = {}; h2 = {}
sets.each{|s|
h1[s.object_id] = s.dup
s.each{|e| (h2[e] ||= []) << s.object_id}
}
merges = h2.values.sort.uniq
flag = true
while flag
flag = false
merges = h1.keys.map{|id|
merges.select{|m|
m.include?(id)
}.tap{|m|
flag = true if m.size > 1
}.flatten.sort.uniq
}.sort.uniq
end
merges.map{|m|
m.map{|id|
s = h1[id]; h1.delete(id); s
}.flatten.sort.uniq
}
end