I removed the neural net test iris2 because I got a failure (arno thinks random params)..he can add back in.
Summary2 creates hidden 1000 bin histogram for finer grain quantile estimate. (hcnt2, with fixed bin size _binsz2)
The existing histogram binning for browser and json response still exists (both filled in parallel)
In addition hcnt2_min and hcnt2_max are created, which are the actual min/max of the values put in that bin.

The actual quantile is computed using the hcnt2_min/max from the bin (if interpolation is needed)

This is nice for integers (you get integer results then, for most datasets)

I believe this passes build.sh junit (1% cars.csv still checks 4 cylinders) and current R run.py (s)