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https://issues.apache.org/jira/browse/MATH-867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13466308#comment-13466308
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Nikolaus Hansen commented on MATH-867:
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{quote}
Revision 1391840 contains modified "encode" and "decode" functions. Both unit
tests now pass (for "testConstrainedRosen" I had to move the initial guess
closer to the solution).
No change was required for "inputSigma"; I still do not understand why it works
as is (cf. lines 588, 589).
{quote}
to me it makes perfectly sense: luckily enough line 589 performs the same
transformation on inputSigma as the encode function on getStartPoint() (maybe
this should be mentioned in a comment?). As the transformation is linear, the
situations before and after the transformations are mathematically equivalent
(the bug came from loosing digits due to a subtraction, which is now omitted).
As said before it would simplify the code if both transformations were omitted
(but we could leave this to another issue).
{quote}
And I have no idea how to improve the documentation...
{quote}
I'll think about it.
> CMAESOptimizer with bounds fits finely near lower bound and coarsely near
> upper bound.
> ---------------------------------------------------------------------------------------
>
> Key: MATH-867
> URL: https://issues.apache.org/jira/browse/MATH-867
> Project: Commons Math
> Issue Type: Bug
> Reporter: Frank Hess
> Attachments: MATH867_patch, Math867Test.java
>
>
> When fitting with bounds, the CMAESOptimizer fits finely near the lower bound
> and coarsely near the upper bound. This is because it internally maps the
> fitted parameter range into the interval [0,1]. The unit of least precision
> (ulp) between floating point numbers is much smaller near zero than near one.
> Thus, fits have much better resolution near the lower bound (which is mapped
> to zero) than the upper bound (which is mapped to one). I will attach a
> example program to demonstrate.
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