Rank Normalization

[Peter]

needs #439

This a normalization that works on 1D containers, for example, a Vector.

The short story is to replace each value with its rank, i.e., the smallest value is replaced with 0, the next smallest is replaced with 1/N (where N is number of elements in the Container), et cetera.

In the weighted case, the rank naturally translates to sum(w_i)/sum(w) where the first sum runs over elements for which x_i<x. Possibly one could add half the values of the weights corresponding to x_i=x just for symmetry reasons (and make the corresponding modification in the unweighted case)

[Peter]

well I actually need this now... I'll call the class normalization::Spearman

[Peter]

(In [1496]) unweighted version of the Spearman Normalization. refs #437.

[Peter]

(In [1507]) preparing for weighted version - refs #437

[Peter]

(In [1508]) refs #437

[Peter]

(In [1509]) fixes #437 and added support for having known issues in test::Suite

[Peter]

I think we should add half the equal weights as mentioned in description. This will cost some speed, but I think it is worth it. See this weighted example in which the NaNs? have w=0

1  2
2  NaN
4  NaN

that currently is transformed to

0    0
1/3  NaN
2/3  NaN

but with in modified version we will get

1/6  1/2
1/2  NaN
5/6  NaN

which I think makes more sense, because the only value in second column should not be biased to lower (or upper) end.

[Peter]

(In [1511]) refs #437 modified test to reflect new spec

[Peter]

fixed in [1512]