On 02/09/2014 12:46 AM, Thomas Neidhart wrote:
> On 02/08/2014 10:16 PM, Gilles wrote:
>> Hi.
>>
>>>
>>> I think we are very close to releasing 3.3.
>>> Looking through the issues, the following should/need to be resolved:
>>>
>>> [...]
>>>
>>>  * [MATH-923] Kohonen's SOFM: can it be considered finished?
>>
>> Done.
>>
>>>  * [MATH-928] Alternative approach to matrix implementations:
>>>
>>>    postpone to 4.0?
>>
>> Done.
>>
>>>
>>>  * [MATH-990] Improve performance of MathArrays.sortInPlace:
>>>
>>>    finished for 3.3?
>>
>> Done.
>>
>>>
>>>
>>> Other issues to be discussed:
>>>
>>>  * [MATH-1008]
>>>
>>>    a new package has been created o.a.c.m.fitting.leastsquares which
>>>    contains some interface for the new fluent API but they are also
>>>    used elsewhere so I guess it would be more logical to put them in a
>>>    more general place, e.g. WithMaxEvaluations should be moved to
>>>    o.a.c.m.optim. WDYT?
>>
>> Strictly speaking, these have potential use outside the "o.a.c.m.optim"
>> package.
> 
> Yes, it is now already used by the AbstractOptimizer in the optim
> package, thats why I thought it would be better to place it in a more
> general package.
> 
>> Also, further improvements were postponed since the alternate proposal
>> looked quite promising:
>>   https://issues.apache.org/jira/browse/MATH-1026
> 
> Ah, I forgot about this, thanks for the pointer. It is then probably
> better that we take the time and review / cleanup this before the release.
> 
> I will really take a look tomorrow!

Ok, I started to review his contribution, and I think it goes in the
right direction. When doing some test with the SimplexSolver, I actually
did go in the same direction (but much simpler for my purposes) by
creating a Problem class specific for the optimization problem at hand.

I will play around with the code next week and see if we can get it into
a releasable state within 1-2 weeks.

Another thing to be concerned of: right now we have already *3* places
in the library where e.g. the GaussNewtonOptimizer resides:

 * optimization.general
 * optim.nonlinear.vector.jacobian
 * fitting.leastsquares

two of them deprecated. This is kind of crazy ;-).

Thomas

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