On 10/28/11 12:14 AM, Luc Maisonobe wrote:
> Le 28/10/2011 08:27, Sébastien Brisard a écrit :
>
> Hi Sébastien,
>
>> 2011/10/27 Gilles Sadowski <gil...@harfang.homelinux.org>:
>>>>>> The BOBYQA optimizer takes simple bound contraints into account:
>>>>>> lowerBound(i) <= p(i) <= upperBound(i) 0 <= i < n
>>>>>> where "n" is the problem dimension.
>>>>>>
>>>>>> The parent class ("BaseMultivariateRealOptimizer") currently mandates the
>>>>>> following "optimize" method:
>>>>>> ---CUT---
>>>>>> RealPointValuePair optimize(int maxEval,
>>>>>> FUNC f,
>>>>>> GoalType goalType,
>>>>>> double[] startPoint);
>>>>>> ---CUT---
>>>>>>
>>>>>> I think that the bounds are arguments that should be passed through that
>>>>>> method. The current method definition is a special case: no bound
>>>>>> constraints (or, equivalently, all lower bounds = -infinity, all upper
>>>>>> bounds = +infinity).
>>>>>>
>>>>>> Thus, it seems that adding the following to the API
>>>>>> ---CUT---
>>>>>> RealPointValuePair optimize(int maxEval,
>>>>>> FUNC f,
>>>>>> GoalType goalType,
>>>>>> double[] startPoint,
>>>>>> double[] lowerBounds,
>>>>>> double[] upperBounds);
>>>>>> ---CUT---
>>>>>> is all there is to do in order to accomodate algorithms like BOBYQA.
>>>>> [...]
>>>> It sounds like a useful addition, which raises one question I'd like
>>>> to ask all of you. I guess all three double[] arrays should have the
>>>> same size, which must be checked, and also documented in the javadoc.
>>>>
>>>> In order to avoid this, what I tend to do at the moment is to define a
>>>> new class --say, BoundedPoint-- which would hold three double:s an
>>>> initial value, a lower bound and an upper bound. Then I would just
>>>> provide the method with the corresponding array of BoundedPoint,
>>>> instead of three arrays of doubles. Then no dimension mismatch can
>>>> occur, and no additional information needs be provided in the javadoc.
>>>> Of course, the price to pay is that you have to construct a few
>>>> BoundedPoint. As I said, this is what I tend to do at the moment, but
>>>> I have mixed feelings about this solution vs. passing 3 double[]. Any
>>>> thoughts about this side question?
>>> On the principle, you are right of course.
>>> But I'm not sure that we gain much by adding this layer of data
>>> encapsulation, because having a single array (instead of three) is not
>>> enough to prevent a dimensionality error: indeed, the arrays dimension must
>>> match the expected argument of the function, and this possible mismatch can
>>> only be detected later, when the function is called (within the "doOptimize"
>>> method).
>>>
>> OK, that's a fair point.
>>
>>> To be completely safe, we would have to introduce an additional method
>>> ("getDimension") in the "MultivariateFunction" interface. [But this has
>>> the drawback that it reduces the generality of this interface.]
>>>
>> I'm certainly not claiming that such a method *should* be added, but
>> may I ask why you think it reduces generality? I guess you are
>> thinking of generic multivariate functions, with unspecified number of
>> arguments (like sum(), product(), ...), but this could be handled by
>> returning eg a negative value. Again, I'm not claiming anything, I'm
>> just wondering (actually, wondering if what I did was wrong --or not
>> so good--, in a project I'm working on at work...).
> Both ways can be used and both are either good or bad depending on
> context. We probably all have this kind of problems all the time. As
> Apache Commons Math is a rather low level component in a complete
> software stack, as many users are still used to non-object languages
> (Fortran and C mostly), and as it is a library with many different users
> and use cases, using very generic primitive arrays seems fair at this
> level. For a dedicated application, using specific objects is better.
>
> One reason I prefer primitive objects for low level components is that
> most of the time you already need to do some mapping from your
> domain-specific objects. With primitive arrays, you may simply rely on
> passing references to existing internal data structures and avoid
> copying them back and forth all the time, which is cumbersome, adds
> management code, and may impact performance in iterative algorithms.
+1
Phil
>
> However, there is nothing against using several separate arguments in
> high level applications even if they should be kept consistent with each
> other, and there is nothing against using objects in low level
> libraries. We may well change our mind in a few releases, this would not
> be the end of the world.
>
>
>>> Also, keeping it simple (although not totally safe) by using (arrays of)
>>> primitive type makes the interface closer to what people are accustomed to
>>> coming from e.g. the C language. This approach is also used in the
>>> "...VectorialOptimizer" classes (see "BaseAbstractVectorialOptimizer" where
>>> a check is done to verify that the "target" and "weight" arrays have the
>>> same length).
>>>
>>> That said, I agree that it would be nicer to have a completely uniform and
>>> integrated set of interfaces. The current design is already quite a rework
>>> of the previous state of affairs (see versions 2.1 and 2.2) with much of the
>>> inconsistency and code duplication corrected. However, similarly to other
>>> design issues raised during the last months, it is not clear that the
>>> obvious solution at this point will lead to a clear improvement in the
>>> overall design. I mean that the code might in fact need a more thorough
>>> refactoring, not some patch here and there. But that work would be for the
>>> next++ major release. :-)
>>>
>>>
>>> Best,
>>> Gilles
>>>
>> I'm too new to this project to make any statement... We'll talk about
>> that in a few years...
> No, nobody is too new. Everybody can express their concerns and propose
> something different.
>
> best regards,
> Luc
>
>> Best regards,
>> Sébastien
>>
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