Path: csiph.com!v102.xanadu-bbs.net!xanadu-bbs.net!goblin3!goblin2!goblin.stu.neva.ru!newsfeed1.swip.net!uio.no!news.tele.dk!news.tele.dk!small.news.tele.dk!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 0.105 X-Spam-Level: * X-Spam-Evidence: '*H*': 0.79; '*S*': 0.00; 'algorithm': 0.04; 'patterns': 0.04; 'preferably': 0.05; 'url:faqs': 0.09; 'cc:addr :python-list': 0.11; 'question.': 0.14; 'random': 0.14; 'compression': 0.16; 'url:catb': 0.16; 'appropriate': 0.16; 'wrote:': 0.18; 'do.': 0.18; 'implementing': 0.19; 'email addr:gmail.com>': 0.22; 'preferred': 0.22; 'cc:addr:python.org': 0.22; 'of.': 0.24; 'question': 0.24; 'cc:2**0': 0.24; 'second': 0.26; 'post': 0.26; 'header:In-Reply- To:1': 0.27; 'correct': 0.29; 'tim': 0.29; 'wonder': 0.29; 'message-id:@mail.gmail.com': 0.30; 'code': 0.31; 'subject:that': 0.31; 'probably': 0.32; 'advice': 0.35; 'but': 0.35; 'received:google.com': 0.35; 'there': 0.35; 'data,': 0.36; 'set.': 0.36; 'possible': 0.36; 'url:org': 0.36; 'searching': 0.37; 'wrong': 0.37; 'turn': 0.37; 'little': 0.38; 'help,': 0.39; 'either': 0.39; 'even': 0.60; 'read': 0.60; 'is.': 0.60; 'truly': 0.60; 'forum': 0.61; 'entire': 0.61; 'course': 0.61; 'simply': 0.61; "you're": 0.61; "you'll": 0.62; "you've": 0.63; 'such': 0.63; 'chance': 0.65; 'to:addr:gmail.com': 0.65; 'reply': 0.66; 'link:': 0.72; 'special': 0.74; 'attention': 0.75; 'completly': 0.84; 'noise,': 0.84; 'good,': 0.91; 'lucky': 0.93; '2013': 0.98 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=EgOMSJN6wnR8D7vxsYrM1DxigYKA1G+cQJzeJ7E5Ph0=; b=ZXfe9wPeXOAulDdyfNTZriGHfvk+zp1E8yHF9uBT2xUvj/p6BkkmPxai1qOeBBQQEg /RVecIgLGylGAxBE74CzUtjHaAVGZrWQVx4/uVRzQJ5IVUf1w4bIupaLKjrM6e98slm4 uvC90m5brUI8PQaSU9Yla6VE0B9qJrfR0Gf3Lrer+bQnSAIlZWn7YrkOiXjbH57pek0E SsDnLqrgCLdU0XdBItH8i0TB2VqJ5pOO499zllCjsK9tnbckiwybY5JP0BDO1DiVT3/M JQc++almWe7iFamJgmhy+tAXw5Pi9tP/mlRH6Pd1w5xa1R59I2CtqdxDRhdPmcqTD969 Ff1w== MIME-Version: 1.0 X-Received: by 10.182.113.195 with SMTP id ja3mr5511187obb.46.1383161759415; Wed, 30 Oct 2013 12:35:59 -0700 (PDT) In-Reply-To: <205bfa4f-29de-43de-be5a-72a12d77d0c9@googlegroups.com> References: <205bfa4f-29de-43de-be5a-72a12d77d0c9@googlegroups.com> Date: Thu, 31 Oct 2013 06:35:59 +1100 Subject: Re: Algorithm that makes maximum compression of completly diffused data. From: Tim Delaney To: jonas.thornvall@gmail.com Content-Type: multipart/alternative; boundary=089e013d0db05644dd04e9fa71fe Cc: Python-List 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: 115 NNTP-Posting-Host: 2001:888:2000:d::a6 X-Trace: 1383161768 news.xs4all.nl 15893 [2001:888:2000:d::a6]:49588 X-Complaints-To: abuse@xs4all.nl Xref: csiph.com comp.lang.python:58097 --089e013d0db05644dd04e9fa71fe Content-Type: text/plain; charset=UTF-8 On 31 October 2013 05:21, wrote: > I am searching for the program or algorithm that makes the best possible > of completly (diffused data/random noise) and wonder what the state of art > compression is. > > I understand this is not the correct forum but since i think i have an > algorithm that can do this very good, and do not know where to turn for > such question i was thinking to start here. > > It is of course lossless compression i am speaking of. > This is not an appropriate forum for this question. If you know it's an inappropriate forum (as you stated) then do not post the question here. Do a search with your preferred search engine and look up compression on lossless Wikipedia. And read and understand the following link: http://www.catb.org/esr/faqs/smart-questions.html paying special attention to the following parts: http://www.catb.org/esr/faqs/smart-questions.html#forum http://www.catb.org/esr/faqs/smart-questions.html#prune http://www.catb.org/esr/faqs/smart-questions.html#courtesy http://www.catb.org/esr/faqs/smart-questions.html#keepcool http://www.catb.org/esr/faqs/smart-questions.html#classic If you have *python* code implementing this algorithm and want help, post the parts you want help with (and preferably post the entire algorithm in a repository). However, having just seen the following from you in a reply to Mark ("I do not follow instructions, i make them accesible to anyone"), I am not not going to give a second chance - fail to learn from the above advice and you'll meet my spam filter. If the data is truly completely random noise, then there is very little that lossless compression can do. On any individual truly random data set you might get a lot of compression, a small amount of compression, or even expansion, depending on what patterns have randomly occurred in the data set. But there is no current lossless compression algorithm that can take truly random data and systematically compress it to be smaller than the original. If you think you have an algorithm that can do this on truly random data, you're probably wrong - either your data is has patterns the algorithm can exploit, or you've simply been lucky with the randomness of your data so far. Tim Delaney --089e013d0db05644dd04e9fa71fe Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
On 3= 1 October 2013 05:21, <jonas.thornvall@gmail.com> w= rote:
I am searching for the program or algorithm that makes the= best possible of completly (diffused data/random noise) and wonder what th= e state of art compression is.

I understand this is not the correct forum but since i think i have an algo= rithm that can do this very good, and do not know where to turn for such qu= estion i was thinking to start here.

It is of course lossless compression i am speaking of.

This is not an appropriate forum for this question. If you = know it's an inappropriate forum (as you stated) then do not post the q= uestion here. Do a search with your preferred search engine and look up com= pression on lossless Wikipedia. And read and understand the following link:=

=
paying special attention to the following parts:

http= ://www.catb.org/esr/faqs/smart-questions.html#prune
http://www.catb.org/esr/faqs/smart-questions.html#courtesy
http://www.catb.org/esr/faqs/smart-questions.html#classic

If you have *python* code implementing this algorithm= and want help, post the parts you want help with (and preferably post the = entire algorithm in a repository).

However, having just seen the following from you i= n a reply to Mark ("I do not follow instructions, i make them accesible to anyone&quo= t;), I am not not going to give a second chance - fail to learn from= the above advice and you'll meet my spam filter.

If the data is truly completely random noise, the= n there is very little that lossless compression can do. On any individual = truly random data set you might get a lot of compression, a small amount of= compression, or even expansion, depending on what patterns have randomly o= ccurred in the data set. But there is no current lossless compression algor= ithm that can take truly random data and systematically compress it to be s= maller than the original.

If you think you have an algorithm that can do this on = truly random data, you're probably wrong - either your data is has patt= erns the algorithm can exploit, or you've simply been lucky with the ra= ndomness of your data so far.

Tim Delaney=C2=A0
--089e013d0db05644dd04e9fa71fe--