>> >> Several times I brought out some problems and ideas about the package and it >> seems the only person who has an opinion is Gilles. >> >> I will list what I consider to be major problems >> 1) The OO design is bad, too much inheritance which could be handled better >> by interfaces, > We may have gone too far in favoring abstract classes over > interfaces. What led to this historically was getting "locked in" > to incomplete interface designs due to their immutability wrt > backward compatibility. >> the structure has no relation to the actual way parts of optimizers can be >> mixed and matched. Input functions should also have clear inheritance >> structure and should return both the value, gradient, hessian in one >> function call. >> 2) Incorrect handling of constraints. There are only something like 5 >> possible constraints possible in optimization, with each implementation of >> the solver handling some but not all. There is no need to this runtime >> approach, which creates incredible amount of confusion. All the possible >> constraints should be explicitly given in the parameters to a function call, >> there are only 5. In addition, constraints should be pre-processed a priori! >> So they should be an input to the constructor not to the optimization >> function call. >> 3) Linear algebra package should be used as an interface and internally to >> increase performance for larger datasets. Data copying should be avoided as >> much as possible. > > Can you provide a little more detail and maybe some sample code > illustrating above?
Are you referring to the linear algebra comment? I have no examples. I was talking in general terms. For example the covariance matrix is typically sparse, as I think would be its inverse (?). That means its possible to actually provide an option of a general weight matrix, if we used the linear algebra framework. The user could simply create a sparse matrix instead of a RealMatrix, and pass it on to the solver. The code inside the optimizer would naturally take advantage its sparsity due to inheritance and speedup its inversion as well as its multiplication by other matrices. This would also help with sparse Jacobians in the least-squares method. Diagonal matrix is a special case of sparse matrix, so we could actually create a class for that. That was the general code can remain, and both Matrix and vector weights would be automatically handled efficiently. >> 4) Testing should be done on larger problems. > +1 - I think it would be great to add some test classes not executed > on each build to test large problems. Do you have some we can use? > I don't know much about testing libraries, only know that standard benchmarks exist. I would assume it's not hard to create a larger inverse problem by simply randomly generating several examples. But standard benchmarks would be better. > Phil >> I know the response is that I am free to go implemented, but I think we >> should at least agree on design principles instead of pushing through your >> own ideas because the other person is too busy. The only discussion we ever >> had on this was between me and Gilles, everyone else disappeared. >> >> Thanks, >> Konstantin >> >> On Dec 28, 2012, at 11:27 AM, Phil Steitz <phil.ste...@gmail.com> wrote: >> >>> On 12/28/12 8:12 AM, Dimitri Pourbaix wrote: >>>> Luc, >>>> >>>>> So in order to make sure I understand your point, you would be OK >>>>> if I >>>>> deprecate the non-diagonal weights, in which case users needing this >>>>> would have to implement it themselves by premultiplication (as >>>>> both you >>>>> and Konstantin seem to propose)? >>>> Yes, exactly. >>>> >>>>> Sure, but for the record the feature was also a last minute >>>>> change. This >>>>> was discussed on the list, and the final decision was to add this >>>>> feature despite the release was close. No wonder we failed to >>>>> test it >>>>> thoroughsly. >>>> Last minute? I have been discussing this with Gilles for several >>>> months. >>> Relevant project discussion happens *on this list* >>>>> We don't expect our releases to be perfect. We do our best, with the >>>>> resources we have. >>>> I perfectly understand this but focusing those resources less on >>>> rules >>>> and more on real cases might help. >>> As stated before, you are more than welcome to *become* one of these >>> resources. >>> >>> Phil >>>> Regards, >>>> Dim. >>>> ---------------------------------------------------------------------------- >>>> >>>> Dimitri Pourbaix * Don't worry, be happy >>>> Institut d'Astronomie et d'Astrophysique * and CARPE DIEM. >>>> CP 226, office 2.N4.211, building NO * >>>> Universite Libre de Bruxelles * Tel : +32-2-650.35.71 >>>> Boulevard du Triomphe * Fax : +32-2-650.42.26 >>>> B-1050 Bruxelles * NAC: HBZSC RG2Z6 >>>> http://sb9.astro.ulb.ac.be/~pourbaix * >>>> mailto:pourb...@astro.ulb.ac.be >>>> >>>> --------------------------------------------------------------------- >>>> 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
