Le jeu. 20 juil. 2023 à 21:19, Dimitrios Efthymiou
<efthymiou.dimitri...@gmail.com> a écrit :
>
> are you saying that in order to move the ml.clustering classes
> to the new clustering module, I can take all the dependencies to classes
> and their transitive dependencies, copy them to the new clustering module,
> but only keep in them the minimum required code for the new module to
> operate?
To some extent, yes. But the main point is the refactoring. For example,
your wouldn't copy the code from "linear" after seeing that one can do
without it. But also note in this case that exposing a "double[][]" instead
may not be the best choice for a long-term API. As was mentioned, it
would be worth looking at how other libraries provide similar functionality.
The module should solve all issues mentioned in JIRA; it's not just copying
the classes and removing dependencies.
Gilles
>
> On Thu, 20 Jul 2023 at 15:27, Gilles Sadowski <gillese...@gmail.com> wrote:
>
> > Hello.
> >
> > Le mer. 19 juil. 2023 à 12:59, Dimitrios Efthymiou
> > <efthymiou.dimitri...@gmail.com> a écrit :
> > >
> > > [...]
> > > 1-- [...]
> > > 2--As for the atomic refactoring and feature branch, well,
> > > unless someone moves the Variance class (you said that someone
> > > is doing it now) and the distance package and whatever other
> > > dependencies exist within the ml.clustering package,
> > > there can be no moving of the remaining clustering classes
> > > to the new clustering module, right?
> > > 3-- [...]
> > > 4--I don't know how to continue with the clustering modularisation
> > > given all those dependencies. Maybe I shouldn't have started this,
> > > because now I am stuck
> >
> > You aren't.
> >
> > The dependencies found in "o.a.c.math4.legacy.ml.clustering" are
> > (1) "MatrixUtils" and "RealMatrix" (from the "linear" package)
> > (2) "Variance" and "VectorialMean" (from the "stat" package)
> >
> > (1) creates the coupling for a single method ("getMembershipMatrix")
> > that isn't called from anywhere (not even the unit tests). Remove the
> > method and the dependency towards "linear" vanishes.
> >
> > (2) "Variance" can be replaced with a temporary implementation like
> > (untested copy/paste from "SecondMoment" and "FirstMoment"):
> > ---CUT---
> > class Variance {
> > private int n = 0;
> > private double dev = 0;
> > private double nDev = 0;
> > private double m2 = 0;
> > private double m1 = 0;
> >
> > void increment(final double d) {
> > ++n;
> > dev = d - m1;
> > nDev = dev / n;
> > m1 += nDev;
> > m2 += ((double) n - 1) * dev * nDev;
> > }
> >
> > double get() {
> > return m2;
> > }
> > }
> > ---CUT---
> > Then, creating a private copy of class "VectorialMean" (replacing,
> > in the copy, CM exceptions with JDK ones) would complete the
> > removal of the dependency towards the "stat" package.
> >
> > And so on.
> >
> > Regards,
> > Gilles
> >
> > > > > [...]
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