Unbounded relative similarity measure for negative values

[mathiskelm]

In the relative similarity measures the data differences are divided by the larger value (for each component) before applying the specified norm. If both values are negative, this selects the one with smaller absolute value, leading to potentially large "normalized" distances.

Exaggeration of this distance may lead not just to activation of micro simulations but by raising the maximal distance also to a relaxation of the refining/coarsening thresholds and solving too few micro simulations.