Date: Sun, 7 Mar 2004 01:54:11 -0500 (GMT-05:00) From: Zach Message-ID: <23613898.1078641828630.JavaMail.root..at..wamui10.slb.atl.earthlink.net> Date: Sun, 7 Mar 2004 01:43:48 -0500 (GMT-05:00) From: Zach Reply-To: Zach To: chemistry..at..ccl.net Subject: CCL: TINKER Question Message: Hello to all, I am using TINKERversion 4.0 to do some minimizations and dynamics. In several opportunities I have submited energy minimization jobs and obtained the following output: Variable-Mode Truncated-Newton Conjugate-Gradient Optimization : Algorithm : auto Preconditioning : auto RMS Grad : 0.25D+00 TN Iter F Value G RMS F Move X Move CG Iter Solve FG Call 0 -0.1120D+07 0.4562D+06 1 TNCG -- Normal Termination due to SmallFct Final Function Value : -1120344.2138 Final RMS Gradient : 456235.9873 Final Gradient Norm : 23218781.3035 That is, the minimization is aborted with the message Normal Termination. Given the value of the gradient this structure cannot be minimized. This happens often when I am submitting jobs involving more or less large proteins (the above output came from a 10000+ system). Why is the minimization stopping at this point? Please help. Thanks a lot. Zach From chemistry-request@ccl.net Sun Mar 7 07:55:27 2004 Received: from spearnet.net (mail.spearnet.net [65.219.158.32]) by server.ccl.net (8.12.8/8.12.8) with ESMTP id i27CtQjs006967 for ; Sun, 7 Mar 2004 07:55:26 -0500 Received: from cornell.edu [67.193.134.13] by spearnet.net with ESMTP (SMTPD32-6.06) id A4E1B37004E; Sun, 07 Mar 2004 07:34:25 -0600 Date: Sun, 7 Mar 2004 07:57:10 -0500 Subject: Re: CCL:software evaluation / validation Content-Type: text/plain; charset=US-ASCII; format=flowed Mime-Version: 1.0 (Apple Message framework v552) From: Richard Gillilan To: chemistry..at..ccl.net Content-Transfer-Encoding: 7bit In-Reply-To: <404A1AB4.1EB5B3DB..at..ccdc.cam.ac.uk> Message-Id: X-Mailer: Apple Mail (2.552) X-Spam-Status: No, hits=3.3 required=7.0 tests=RCVD_IN_DYNABLOCK, RCVD_IN_NJABL,RCVD_IN_NJABL_DIALUP,RCVD_IN_SORBS autolearn=no version=2.61 X-Spam-Level: *** X-Spam-Checker-Version: SpamAssassin 2.61 (1.212.2.1-2003-12-09-exp) on servernd.ccl.net On Saturday, March 6, 2004, at 01:38 PM, Jacco van de Streek wrote: > Andras.Borosy..at..givaudan.com wrote: >> I agree with the first part, which is indeed a _VERY_ important point: >> "The main criterion of scientific work is reproducibility." >> However, my question about this would be: >> How is it possible to reproduce scientific results obtained by >> commercial >> _OR_ academic software which relies on _RANDOM_ methods ? > > Hi, > > I happen to work on a program that uses random numbers (to solve > crystal > structures from X-ray powder data) and I think that reproducibility is > not an > issue, at least not in the sense you are referring to. > > Because it is a random process, users of such programs would not run > them just > once, as the single outcome of a random event is meaningless. Instead, > our > program by default runs the simulated annealing run ten times (with > different > seeds for the random number generators). It is now the reproducibility > (the > statistical distribution of solutions) itself that should be > reproducible. > Glad, somebody mentioned random number seeds. Even a random number stream should be reproducible when you use the same seed and same algorithm. I suspect this should be true across platforms when you have a well-implemented algorithm, anyone ever tested this? I can't think of many instances when it was actually necessary to do this, but I am always bothered by programs that just draw a seed > from the time clock or some other system variable. This is a level of reproducibility that "could" be possible in computation, but in practice, is probably not necessary given that it is the solution of the underlying model that is sought (within statistical error) rather than the particular route of convergence. I don't know how many folks have had the experience of actually trying to numerically reproduce computational results from a paper alone, but I've done it on several occasions over the years and have learned a lot about numerical error in the process ... something I rarely ever see discussed. It is important. Just compare energy values of several different implementations of the same exact empirical forcefield (even "official" versions done by the author of the FF) ... the differences are sometimes surprising. Still, it is a great tribute to the scientific integrity of the originator of a method if one can reproduce the results from the published work without the actual code. As much as I like open source code, and as much as I hate property claims being staked on anything and everything possible the human mind can conceive of, it is good to force scientists to reproduce a few things once in a while as long as it does not slow progress due to needless redundancy. Richard Gillilan MacCHESS, Cornell