RE 7091 bias data in splatterplot

Initial version.  Now sorts lists of boxes in
decreasing order and takes points in order from the
ordered list of boxes.  If a large number of points
are requested, the number of points actually used
may be much smaller.  The code steps along the list
trying to get the AVERAGE number of points per box,
from each non-empty box, with a minimum of of one
point per box.

refs #7901
RE 7091 bias data in splatterplot

Comment out a couple of un-used variables so it compiles cleanly.
The variables will be used for testing other strategies.

refs #7091
Refs #7091. Adding threshold parameter for top percentile.
Refs #7091. Changing default value for number of points.
RE 7091 bias data in splatterplot

Removed a couple of variables intended for an alternate
biasing strategy that won't be used.  Put cout statements
in if (VERBOSE) structure that was originally present in the
code.  Tried an alternate biasing strategy that used points
from the boxes above the threshold, based on the number of points
in the box.  For example, if the number of points requested was
equal to 1/2 the total number of points in boxes above the
threshold, then 1/2 of the points from each box would be used.
This alternate strategy emphasized bright peaks much more
than the weaker peaks and required many more points to see the
full lattice.  Also, it was more difficult to get a good
view of scattering between the main Bragg peaks in TOPAZ 7424
or of the diffuse scattering in TOPAZ 7238, with the alternate
strategy.

refs #7091
RE 7091_bias data in splatterplot

Added some additional comments in the code on the strategy being used.
Basically, the average number of points to use per box is calculated
as the number of points in the boxes above the threshold, divided by
the number of boxes above the threshold.  The list of boxes is then
processed in decreasing order, taking at least one point from each
box, up to max(average_points_per_box,number_in_box), until all boxes
have been processed or the requested number of points has been used.
This strategy seems to work quite well and both high and low level
features in a run such as TOPAZ 7424 can be seen.

refs #7901
Merge branch 'feature/7091_bias_data_in_splatterplot' into develop