Coloc 2: Add Kendall's Tau-b rank correlation

Kendall's Tau-b rank correlation is said to be a better measure than
Spearman's rank correlation, and the latter was only preferred for a long
time because the former needs substantially more computational resources.

This implementation is very dumb and inefficient -- O(n^2) -- and is here
only for correctness.

A subsequent commit will replace it by an efficient method.

Signed-off-by: Johannes Schindelin <johannes.schindelin@gmx.de>
Introduce the PairIterator

For many measures, it should actually not be necessary to localize the
position or know about the mask. Therefore, let's abstract out an
interface for an iterator that returns pairs of values, and nothing else.

This will also make it substantially easier to test things, as one does no
longer need to construct full-blown image data structures just to test
an algorithm.

Signed-off-by: Johannes Schindelin <johannes.schindelin@gmx.de>
Add a test for the Kendall Tau-b algorithm

Signed-off-by: Johannes Schindelin <johannes.schindelin@gmx.de>
Add some documentation to the implementation of Kendall's Tau-b

Signed-off-by: Johannes Schindelin <johannes.schindelin@gmx.de>
Test more conditions of Kendall's Tau-b

Signed-off-by: Johannes Schindelin <johannes.schindelin@gmx.de>