Groups | Search | Server Info | Keyboard shortcuts | Login | Register [http] [https] [nntp] [nntps]


Groups > comp.lang.python > #36728

Re: Multiple disjoint sample sets?

Path csiph.com!v102.xanadu-bbs.net!xanadu-bbs.net!feeder.erje.net!eu.feeder.erje.net!newsfeed.freenet.ag!news2.euro.net!newsgate.cistron.nl!newsgate.news.xs4all.nl!post.news.xs4all.nl!not-for-mail
Return-Path <python-python-list@m.gmane.org>
X-Original-To python-list@python.org
Delivered-To python-list@mail.python.org
X-Spam-Status OK 0.000
X-Spam-Evidence '*H*': 1.00; '*S*': 0.00; 'skip:[ 20': 0.03; 'none:': 0.05; 'badly': 0.07; 'repeated': 0.07; 'received:80.91': 0.09; 'received:80.91.229': 0.09; 'received:gmane.org': 0.09; 'received:list': 0.09; 'satisfy': 0.09; 'second.': 0.09; 'def': 0.10; 'index': 0.13; 'resulting': 0.13; 'overwriting': 0.16; 'received:80.91.229.3': 0.16; 'received:dip.t-dialin.net': 0.16; 'received:plane.gmane.org': 0.16; 'received:t-dialin.net': 0.16; 'repetitions': 0.16; 'roy': 0.16; 'set)': 0.16; 'subject:sample': 0.16; 'true:': 0.16; 'values:': 0.16; 'wrote:': 0.17; 'items.': 0.17; 'typical': 0.17; 'yield': 0.17; 'bit': 0.21; 'assuming': 0.22; 'sets': 0.23; 'split': 0.23; 'seems': 0.23; 'header:User- Agent:1': 0.26; '(which': 0.26; 'values': 0.26; 'order.': 0.27; 'header:X-Complaints-To:1': 0.28; 'skip:( 20': 0.28; 'initial': 0.28; 'though.': 0.29; 'way?': 0.29; 'array': 0.29; 'expect': 0.31; 'code': 0.31; 'could': 0.32; 'to:addr:python-list': 0.33; 'another': 0.33; 'list': 0.35; 'subject:?': 0.35; 'there': 0.35; 'list.': 0.35; 'received:org': 0.36; 'but': 0.36; '(i.e.': 0.36; 'should': 0.36; 'uses': 0.37; 'item': 0.37; 'subject:: ': 0.38; 'some': 0.38; 'sure': 0.38; 'instead': 0.39; 'to:addr:python.org': 0.39; 'header:Received:5': 0.40; 'your': 0.60; 'first': 0.61; 'between': 0.63; 'skip:n 10': 0.63; 'more': 0.63; 'population': 0.65; 'smith': 0.71; 'destructive': 0.84; 'lost,': 0.84; '100,000': 0.91
X-Injected-Via-Gmane http://gmane.org/
To python-list@python.org
From Peter Otten <__peter__@web.de>
Subject Re: Multiple disjoint sample sets?
Date Sun, 13 Jan 2013 11:16:03 +0100
Organization None
References <roy-7E69C0.09152911012013@news.panix.com>
Mime-Version 1.0
Content-Type text/plain; charset="ISO-8859-1"
Content-Transfer-Encoding 7Bit
X-Gmane-NNTP-Posting-Host p5084ad4a.dip.t-dialin.net
User-Agent KNode/4.7.3
X-BeenThere python-list@python.org
X-Mailman-Version 2.1.15
Precedence list
List-Id General discussion list for the Python programming language <python-list.python.org>
List-Unsubscribe <http://mail.python.org/mailman/options/python-list>, <mailto:python-list-request@python.org?subject=unsubscribe>
List-Archive <http://mail.python.org/pipermail/python-list/>
List-Post <mailto:python-list@python.org>
List-Help <mailto:python-list-request@python.org?subject=help>
List-Subscribe <http://mail.python.org/mailman/listinfo/python-list>, <mailto:python-list-request@python.org?subject=subscribe>
Newsgroups comp.lang.python
Message-ID <mailman.464.1358072165.2939.python-list@python.org> (permalink)
Lines 57
NNTP-Posting-Host 2001:888:2000:d::a6
X-Trace 1358072165 news.xs4all.nl 6921 [2001:888:2000:d::a6]:45434
X-Complaints-To abuse@xs4all.nl
Xref csiph.com comp.lang.python:36728

Show key headers only | View raw


Roy Smith wrote:

> I have a list of items.  I need to generate n samples of k unique items
> each.  I not only want each sample set to have no repeats, but I also
> want to make sure the sets are disjoint (i.e. no item repeated between
> sets).
> 
> random.sample(items, k) will satisfy the first constraint, but not the
> second.  Should I just do random.sample(items, k*n), and then split the
> resulting big list into n pieces?  Or is there some more efficient way?
> 
> Typical values:
> 
> len(items) = 5,000,000
> n = 10
> k = 100,000

I would expect that your simple approach is more efficient than shuffling 
the whole list. 

Assuming there is a sample_iter(population) that generates unique items from 
the population (which has no repetitions itself) you can create the samples 
with

g = sample_iter(items)
samples = [list(itertools.islice(g, k) for _ in xrange(n)]

My ideas for such a sample_iter():

def sample_iter_mark(items):
    n = len(items)
    while True:
        i = int(random()*n)
        v = items[i]
        if v is not None:
            yield v
            items[i] = None

This is destructive and will degrade badly as the number of None items 
increases. For your typical values it seems to be OK though. You can make 
this non-destructive by adding a bit array or a set (random.Random.sample() 
has code that uses a set) to keep track of the seen items.

Another sample_iter() (which is also part of the random.Random.sample() 
implementation):

def sample_iter_replace(items):
    n = len(items)
    for k in xrange(n):
        i = int(random()*(n-k))
        yield items[i]
        items[i] = items[n-k-1]

You can micro-optimise that a bit to avoid the index calculation. Also, 
instead of overwriting items you could swap them, so that no values would be 
lost, only their initial order.

Back to comp.lang.python | Previous | NextPrevious in thread | Find similar | Unroll thread


Thread

Multiple disjoint sample sets? Roy Smith <roy@panix.com> - 2013-01-11 09:15 -0500
  Re: Multiple disjoint sample sets? MRAB <python@mrabarnett.plus.com> - 2013-01-11 14:36 +0000
  Re: Multiple disjoint sample sets? Dave Angel <d@davea.name> - 2013-01-11 10:14 -0500
  Re: Multiple disjoint sample sets? Peter Otten <__peter__@web.de> - 2013-01-13 11:16 +0100

csiph-web