Elena [service address] wrote:
Mmm... really, why didn't I think of that before ?! Unless having duplicate SAMPLE_IDs in the ti3 might lead to some unpredictable side effect...
The Sample_ID is ignored by colprof.
Yes, but since I see that colprof generates shaper curves that aren't quite linear (see attached image) when channels are targeted at linear density, I was wondering if my idea could improve things furtherly. No more than one of my academical fixations :)
I wouldn't be to concerned. The curves are relatively smooth, and don't deviate very much at the 50% mark. The important thing is that the resulting per channel output is visually progressive, and roughly even. (There is only so much that per channel curves can do anyway.)
always playing with xicclu K curves, I am a bit disappointed that a predicted plot doesn't completely reflect what colprof will actually generate.
They are not exact, no, but typically they do at least resemble each other. You need to keep in mind that the B2A table is an sampled version of the fine grained plot you get out xicclu -g, with some tweaks to make it more like a least squares fit to the underlying inverse. The finite resolution of the B2A table means that it tends to smooth the underlying curve out. This may be good or bad. It's better of course if the underlying curve is smooth to start with.
xicclu -v -g -fif -ir -kp 0 0 1 .2 .5 -L100 -l300 test5.icm the plot: http://www.elenadomain.it/pub/argyll/predicted.png
xicclu -v -g -fb -ir test5.icm the plot: http://www.elenadomain.it/pub/argyll/actual.png
They seem an excellent match - very pleasing. Graeme Gill.