Adding a new script "decimate" which attempts to reduce a large data set down to something much smaller without significantly impacting the quality of the data for fitting The idea relies mainly on the assumption that the data is (and the model) smooth between the nearby samples.  These are then blended together where a straight line is a good fit to fewer points, preserving the line-fit, and the second derivative of the likelihood (vs that line). The fit runs over the data in progressive passes considering shortening segment lengths as it proceeds.  Various levels of agression seem to provide for from x10 reduction with minimal (few percent) reduction of the lens region, ranging to reduction by x200, without losing important parts of the shape.
Adding a new script "decimate" which attempts to reduce
a large data set down to something much smaller without
significantly impacting the quality of the data for fitting
The idea relies mainly on the assumption that the data is
(and the model) smooth between the nearby samples.  These
are then blended together where a straight line is a good
fit to fewer points, preserving the line-fit, and the
second derivative of the likelihood (vs that line).
The fit runs over the data in progressive passes considering
shortening segment lengths as it proceeds.  Various levels
of agression seem to provide for from x10 reduction with
minimal (few percent) reduction of the lens region, ranging
to reduction by x200, without losing important parts of the
shape.

JohnGBaker/gleam,JohnGBaker/gleam