Path: csiph.com!newsfeed.hal-mli.net!feeder3.hal-mli.net!newsfeed.hal-mli.net!feeder1.hal-mli.net!newsfeed.xs4all.nl!newsfeed5.news.xs4all.nl!xs4all!newsgate.cistron.nl!newsgate.news.xs4all.nl!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 0.010 X-Spam-Evidence: '*H*': 0.98; '*S*': 0.00; '"""': 0.05; 'ascii': 0.07; 'bytes)': 0.09; 'received:mail-qc0-f174.google.com': 0.09; 'cc:addr:python-list': 0.10; 'stored': 0.10; 'assume': 0.11; '"""\\': 0.16; 'arrays.': 0.16; 'benjamin': 0.16; 'inputs': 0.16; 'numpy': 0.16; 'oct': 0.16; 'processed.': 0.16; 'repetitions': 0.16; 'sequential': 0.16; 'written.': 0.16; 'wrote:': 0.17; 'variables': 0.17; 'input': 0.18; 'written': 0.20; 'import': 0.21; 'finally,': 0.22; 'example': 0.23; 'external': 0.24; 'cc:2**1': 0.24; 'cc:addr:python.org': 0.25; 'header:In-Reply-To:1': 0.25; '---': 0.26; '(e.g.': 0.27; 'question': 0.27; 'message- id:@mail.gmail.com': 0.27; 'thus,': 0.29; 'performing': 0.30; 'file': 0.32; 'print': 0.32; 'ram': 0.33; 'received:google.com': 0.34; 'saved': 0.35; 'pm,': 0.35; 'received:209.85': 0.35; 'data.': 0.36; "i'll": 0.36; 'subject: (': 0.36; 'october': 0.37; 'being': 0.37; 'rather': 0.37; 'received:209': 0.37; 'received:209.85.216': 0.37; 'data': 0.37; 'subject:: ': 0.38; 'perform': 0.38; 'files': 0.38; 'some': 0.38; 'several': 0.39; 'subject:-': 0.40; 'header:Received:5': 0.40; 'save': 0.61; 'first': 0.61; 'mentioned': 0.63; 'series': 0.63; 'skip:n 10': 0.63; 'reverse': 0.65; 'forward': 0.66; 'manner': 0.74; 'dimensional': 0.84; 'oscar': 0.84; 'subject:Fast': 0.84; 'subject:read': 0.84; 'subject:write': 0.84 DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20120113; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :cc:content-type; bh=s8voWtOHZH6oBYkK+7ZHBxCyAGxqRDGpoXARrE6NPdM=; b=l8NV/YiZJeWS78bwIXBCXzHU5XsRYD/bShfT3+PAPB35CI9NRYZkLzaC6fLUpklA3W 8wrEjqOXE6yCSjp+cVMGSCOoK/zUEm8U3baeFHb1ZoTLqHKThOPen6seX2iVfStCPDxT 5aw7wxIt5CNAI+r6H2/UPVjZueMiuPfLki3zVx52nqyydN14rFE1qrEcDO6uz10aXPLi 3PDrdbZLNeqz5zsK+HgdyXGZqMk97owqzjATrdPD2TjkuvfBNlbQTUqKOkb+kuS2fku2 LKWSuCtlzmFJ9NHUeXvoeI9j+CKJs31s4uytXYbrRhTgNqyIY7hzL20JU/jDrECVbMS5 xZoA== MIME-Version: 1.0 In-Reply-To: References: <5086AA35.4000509@it.uu.se> Date: Tue, 23 Oct 2012 22:29:09 -0400 Subject: Re: Fast forward-backward (write-read) From: David Hutto To: Oscar Benjamin Content-Type: text/plain; charset=ISO-8859-1 Cc: "python-list@python.org" 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: 75 NNTP-Posting-Host: 2001:888:2000:d::a6 X-Trace: 1351045752 news.xs4all.nl 6960 [2001:888:2000:d::a6]:60247 X-Complaints-To: abuse@xs4all.nl Xref: csiph.com comp.lang.python:31983 On Tue, Oct 23, 2012 at 8:06 PM, Oscar Benjamin wrote: > On 23 October 2012 15:31, Virgil Stokes wrote: >> I am working with some rather large data files (>100GB) that contain time >> series data. The data (t_k,y(t_k)), k = 0,1,...,N are stored in ASCII >> format. I perform various types of processing on these data (e.g. moving >> median, moving average, and Kalman-filter, Kalman-smoother) in a sequential >> manner and only a small number of these data need be stored in RAM when >> being processed. When performing Kalman-filtering (forward in time pass, k = >> 0,1,...,N) I need to save to an external file several variables (e.g. 11*32 >> bytes) for each (t_k, y(t_k)). These are inputs to the Kalman-smoother >> (backward in time pass, k = N,N-1,...,0). Thus, I will need to input these >> variables saved to an external file from the forward pass, in reverse order >> --- from last written to first written. >> >> Finally, to my question --- What is a fast way to write these variables to >> an external file and then read them in backwards? > > You mentioned elsewhere that you are using numpy. I'll assume that the > data you want to read/write are numpy arrays. If that is the case always timeit. The following is an example of 3 functions, with repetitions of time that give an average: import timeit #3 dimensional matrix x_dim = -1 y_dim = -1 z_dim = -1 s = """\ x_dim = -1 y_dim = -1 z_dim = -1 dict_1 = {} for i in xrange(0,6): x_dim = 1 y_dim = 1 z_dim = 1 dict_1['%s' % (i) ] = ['x = %i' % (x_dim), 'y = %i' % (y_dim), 'z = %i' % (z_dim)] """ t = """\ import numpy numpy.array([[ 1., 0., 0.], [ 0., 1., 2.]]) """ u = """\ list_count = 0 an_array = [] for i in range(0,10): if list_count > 3: break if i % 3 != 0: an_array.append(i) if i % 3 == 0: list_count += 1 """ print timeit.timeit(stmt=s, number=100000) print timeit.timeit(stmt=t, number=100000) print timeit.timeit(stmt=u, number=100000) -- Best Regards, David Hutto CEO: http://www.hitwebdevelopment.com