Path: csiph.com!v102.xanadu-bbs.net!xanadu-bbs.net!feeder.erje.net!eu.feeder.erje.net!newsfeed.xs4all.nl!newsfeed3a.news.xs4all.nl!xs4all!post.news.xs4all.nl!not-for-mail Return-Path: X-Original-To: python-list@python.org Delivered-To: python-list@mail.python.org X-Spam-Status: OK 0.021 X-Spam-Evidence: '*H*': 0.96; '*S*': 0.00; 'received:80.91': 0.09; 'received:80.91.229': 0.09; 'received:gmane.org': 0.09; 'received:list': 0.09; 'python': 0.11; "'from": 0.16; '100;': 0.16; 'itertools': 0.16; 'received:80.91.229.3': 0.16; 'received:dip0.t-ipconnect.de': 0.16; 'received:plane.gmane.org': 0.16; 'received:t-ipconnect.de': 0.16; 'subject:skip:m 10': 0.16; 'wrote:': 0.18; 'normally': 0.19; 'import': 0.22; 'header:User- Agent:1': 0.23; 'header:X-Complaints-To:1': 0.27; 'array': 0.29; 'compared': 0.30; 'operations': 0.35; 'but': 0.35; 'subject:?': 0.36; 'expected': 0.38; 'to:addr:python-list': 0.38; 'to:addr:python.org': 0.39; 'received:org': 0.40; 'new': 0.61; 'further': 0.61; 'such': 0.63; 'skip:n 10': 0.64; 'dear': 0.65; 'yes': 0.68; '100': 0.79; 'picture.': 0.84; 'subject:space': 0.84 X-Injected-Via-Gmane: http://gmane.org/ To: python-list@python.org From: Peter Otten <__peter__@web.de> Subject: Re: Pythonic way to iterate through multidimensional space? Date: Wed, 06 Aug 2014 14:39:36 +0200 Organization: None References: <53E1E180.6070308@gmail.com> Mime-Version: 1.0 Content-Type: text/plain; charset="ISO-8859-1" Content-Transfer-Encoding: 7Bit X-Gmane-NNTP-Posting-Host: p57bdb941.dip0.t-ipconnect.de User-Agent: KNode/4.13.2 X-BeenThere: python-list@python.org X-Mailman-Version: 2.1.15 Precedence: list List-Id: General discussion list for the Python programming language List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Newsgroups: comp.lang.python Message-ID: Lines: 26 NNTP-Posting-Host: 2001:888:2000:d::a6 X-Trace: 1407328796 news.xs4all.nl 2901 [2001:888:2000:d::a6]:39974 X-Complaints-To: abuse@xs4all.nl Xref: csiph.com comp.lang.python:75796 Gayathri J wrote: > Dear Peter > > Yes the f[t] or f[:,:,:] might give a marginal increase, The speedup compared itertools.product() is significant: $ python -m timeit -s 'from itertools import product; from numpy.random import rand; N = 100; a = rand(N, N, N); r = range(N)' 'for x in product(r, repeat=3): a[x] = 0.0' 10 loops, best of 3: 290 msec per loop $ python -m timeit -s 'from itertools import product; from numpy.random import rand; N = 100; a = rand(N, N, N); r = range(N)' 'a[:,:,:] = 0.0' 100 loops, best of 3: 3.58 msec per loop But normally you'd just make a new array with numpy.zeros(). > but then i need > to do further operations using the indices, in which case this wouldnt > help Which is expected and also the crux of such micro-benchmarks. They distract from big picture.