Le 29/12/2012 12:34, Gilles Sadowski a écrit : > On Sat, Dec 29, 2012 at 10:43:11AM +0100, Luc Maisonobe wrote: >> Le 29/12/2012 10:08, Luc Maisonobe a écrit : >>> Le 29/12/2012 04:09, Gilles Sadowski a écrit : >>>> Hi. >>> >>> Hi Gilles, >>> >>>> >>>>> [...] >>>> >>>>>> third is just bug-fix. Does the fix for the issue that started this >>>>>> thread change the API? If so, we would need to cut 3.2 in any case. >>>> >>>> The current fix does change the usage (one needs to call optimize with an >>>> argument of a different type). IIUC, it also silently removes the handling >>>> of uncorrelated observations. >>>> >>>>> Yes, this fixes the issue. I have created/resolved the issue (MATH-924) >>>>> and committed the fix as of r1426616. >>>>> >>>>> Could someone please review what I have done? >>>> >>>> I don't like the fix... >>> >>> Thanks for reviewing. >>> >>>> >>>> Handling weighted observations must take correlations into account, i.e. >>>> use >>>> a _matrix_. >>>> There is the _practical_ problem of memory. Solving it correctly is by >>>> using >>>> a sparse implementation (and this is actually an implementation _detail_). >>> >>> Yes. >>> >>>> If we _need_ such an implementation to solve the practical problem, I >>>> strongly suggest that we focus on creating it (or fixing what CM already >>>> has, or accept that some inconsistency will be present), rather than >>>> reducing the code applicability (i.e. allowing only uncorrelated data). >>>> If the observations are not correlated, the matrix is a diagonal matrix, >>>> not >>>> a vector. >>> >>> It's fine with me. I simply thought it wouldn't be that easy. You proved >>> me wrong. >>> >>>> CM also lacks implementations for symmetric, triangular, and diagonal >>>> matrix, >>>> which all would go some way to solving several practical problems of the >>>> same >>>> kind as the current one without sacrificing generality. >>> >>> Yes, we have known that for years. >>> >>>> >>>> Now, and several years ago, it was noticed that CM does not _have_ to >>>> provide the "weights" feature because users can handle this before they >>>> call CM code. [IIRC, no CM unit test actually use weights different from >>>> 1.] >>>> IMO, the other valid option is thus to have a simpler version of the >>>> algorithm, but still a correct one. >>>> This would also have the advantage that we won't have the urgent need to >>>> keep the sparse matrix implementation. >>>> [Then, if at some point we include helper code to handle weights >>>> (_including_ correlations), we should also do it in a "preprocessing" step, >>>> without touching the optimization algorithms.] >>> >>> So what do you suggest: keep the current support (with proper handling >>> as you did) or drop it? >>> >>> Since several people asked for removing it (Dimitri, Konstantin and now >>> you), we can do that. Unitl now, this feature was a convenience that was >>> really useful for some cases, and it was simple. There were some errors >>> in it and Dimitri solved them in 2010, but no other problems appeared >>> since them, so it made sense simply keeping it as is. Now we are hit by >>> a second problem, and it seems it opens a can of worm. Dropping it >>> completely as a not so useful convenience which is tricky to set up >>> right would be fair. >>> >>>> >>>>> I also think (but did not test it), that there may be a problem with >>>>> missing OptimizationData. If someone call the optimizer but forget to >>>>> set the weight (or the target, or some other mandatory parameters), then >>>>> I'm not sure we fail with an appropriate error. Looking for example at >>>>> the private checkParameters method in the MultivariateVectorOptimizer >>>>> abstract class, I guess we may have a NullPointer Exception if either >>>>> Target or Weight/NonCorrelatedWeight has not been parsed in the >>>>> parseOptimizationData method. Could someone confirm this? >>>> >>>> Yes. >>>> And this (not checking for missing data) _could_ be considered a feature, >>>> as >>>> I stressed several times on this ML, and in the code documentation >>>> (eliciting zero constructive comment). >>>> We also _agreed_ that users not passing needed data will result in NPE. >>>> [I imagined that applications would check that valid and complete input is >>>> passed to the lower level "optimize(OptimizationData ...)" methods.] >>> >>> Yes, abd I agree with that. However, I found the javadoc to be >>> ambiguous. It says "The following data will be looked for:" followed by >>> a list. There is no distinction between optional and required >>> parameters. As an example, simple bounds are optional whereas initial >>> guess or weight are required, but there is nothing to tell it to user. >>> So in this case, either we should provide proper exception or proper >>> documentation. I am OK with both. >>> >>>> >>>> It is however straightforward to add a "checkParameters()" method that >>>> would >>>> raise more specific exceptions. [Although that would contradict the >>>> conclusion of the previous discussion about NPE in CM. And restart it, >>>> without even getting a chance to go forward with what had been decided!] >>> >>> As long as we identify the parameters that are optional (and hence user >>> can deduce the other one are mandatory and will raise an NPE), this >>> would be fine. I don't ask to restart this tiring discussion, just make >>> sure users have the proper way to understand why they get an NPE when >>> the forget weight and why they don't get one when the forget simple bounds. >>> >>> Also weight should really be optional and have a fallback to identity >>> matrix, but this is another story. >>> >>>> >>>> >>>> Hence, to summarize: >>>> * The fix, in a 3.2 release, should be to replace the matrix >>>> implementation >>>> with one that does not exhaust the memory, e.g. "OpenMapRealMatrix"[1] >>>> or >>>> "DiagonalMatrix" (see my patch for MATH-924), but not change the API. >>> >>> +1 >> >> I forgot to ask: do you want me to first revert my change before you >> commit yours > > Yes, please.
Done as of r1426751. > >> or will you do both at the same time? > > I wouldn't know how to do that. > What is the svn command to revert a list a files to their state in a given > revision? I don't know. I now use git-svn to connect to our subversion repository while using git commands locally. Luc > > Thanks, > Gilles > >> >> Luc >> >>> >>>> * We must decide wether to deprecate the weights feature in that release >>>> (and thus remove it in 4.0) or to keep it in its general form (and thus >>>> un-deprecate "OpenMapRealMatrix"[2]). >>> >>> +1 to deprecate. >>> >>> best regards >>> Luc >>> >>>> >>>> >>>> Best regards, >>>> Gilles >>>> >>>> [1] The inconsistencies that led to the deprecation will have no bearing >>>> on usage within the optimizers. >>>> [2] The latter option seems likely to entail a fair amount of work to >>>> improve the performance of "OpenMapRealMatrix" (which is quite poor >>>> for some operations, e.g. "multiply"). >>>> >>>> --------------------------------------------------------------------- >>>> To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org >>>> For additional commands, e-mail: dev-h...@commons.apache.org >>>> >>>> >>> >>> >>> --------------------------------------------------------------------- >>> To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org >>> For additional commands, e-mail: dev-h...@commons.apache.org >>> >>> >> >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org >> For additional commands, e-mail: dev-h...@commons.apache.org >> > > --------------------------------------------------------------------- > To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org > For additional commands, e-mail: dev-h...@commons.apache.org > > --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
