Graeme,
Thank for the clarification and if I may suggest, English is not my
first language and I would never have thought "Average deviation of
device+instrument readings as a percentage" meant the degree of
regularization or better yet "smoothing" maybe you can add something to
that effect in the documentation.
Are there other parameters that affect the "interpolation", you mention
"more possibilities" below, just curious?
Thanks,
Yves
On 12/10/2019 8:41 PM, Graeme Gill wrote:
Yves Gauvreau wrote:
Maybe I don't understand what you mean but I would believe a more robust approach then a patch by patch one, would be to measure all the patches several times and use "average(.exe)" to sort out which of these measure we will actually use (average, median or a Geometric Median). This should improve our chance of obtaining a measure that is closer to the real thing.
That's one end of a continuum. The regularization (AKA smoothing) used by Argyll's
interpolation allows more possibilities though. If multiple sets of measurements
are combined and there are multiple readings of the same patch, then the measurements
will be averaged. But you could also just use more overall patches, which combines
sampling the device space in more detail with averaging out reproduction and
measurement uncertainty. There is a degree of control over this by changing the
colprof -r parameter.
Cheers,
Graeme Gill.