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 or will you do both at the same time? 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
