Well, with the help of Graeme and Alastair, I have the feeling I'm getting somewhere with Argyll -- I never doubt it. But I'm all excited to find interesting questions as I go along, little nuggets of color management knowledge. Here's the comments from a profile session: >>profile -v test_with_stats > Total ink limit being used is 390% > No black ink limit being used > No of test patches = 182 > Estimating white point > Approximate White point XYZ = 0.814167 0.842132 0.744550, Lab = 93.543000 > 0.423000 -4.416000 > > Creating optimised per channel curves > Initial White Point XYZ 0.814167 0.842132 0.744550, Lab 93.543000 0.423000 > -4.41 6000 > > About to optimise temporary matrix > ..................... > About to optimise input curves and matrix > .............................................................................. > .............................................................................. > .............................................................................. > .......................................................... > > About to optimise output curves and matrix > ...................................... > About to optimise input curves and matrix again > About to optimise input, matrix and output together > ..................... > About to adjust a and b output curves for white point > About to create grid position input curves > > Create final clut from scattered data > > ****************************************************************************** > ****************************************************************************** > > Doing White point fine tune: > > Before fine tune, WP = XYZ 0.000000 0.000000 0.000000, Lab 99.786657 -0.259466 > 0.309300 > > Creating fast inverse input lookups > Compensate scattered data for input curves > White point XYZ = 0.808475 0.837511 0.743901, Lab = 93.342285 0.184253 > -4.705911 > > Find black point > K only value (Lab) = 8.856753 1.517002 0.394401 > Black point XYZ = 0.007579 0.007461 0.005880, Lab = 6.739928 1.551594 0.519903 > > Done A to B table creation > > Creating B to A tables > 100% > > Done B to A tables > > Creating gamut boundary table > 100% > > Done gamut boundary table > profile check complete, peak err = 4.363131, avg err = 0.961138 OK. How I just love this stuff. My question comes from what I was doing with the cctiff converted to Lab file. You see, I want my students to verify for themselves that when they point to a patch in the Lab version IT8.7/3 Basic they can compare with the actual EyeOnePro measurement, since I ordered cctiff to convert AbsCol. A quick comparison turns out a very good fitting of the device data by Argyll. Very good. For example, for the 100C patch, the EyeOnePro measured 51.499 -34.625 -57.789 whereas the TIFF file opened up in Photoshop shows 52 -35 -57. I understand Photoshop rounds off the data for the Info palette. To me, that's an excellent result. So I continue with the 100M patch. This time the EyeOnePro reported 40.705 77.134 -7.750 while Photoshop showed this one at 41 79 -10. Not quite as close as on the Cyan. I continue my comparison and, in most cases, the fitting is excellent -- good math and modeling, Graeme! But then I turn to the comments by profile and I think to myself, maybe there are some profile generation statistics I missed that would tell me how good was the fitting of the colorimetric data by the profile? And the only thing I can think of is the very last line: > profile check complete, peak err = 4.363131, avg err = 0.961138 My thinking is, I would like to demonstrate to the students the effect of using a larger device sample in modeling its behavior. So, if I use something like an IT8.7/3 928 sample set (as opposed to my lowly 182 sample set) or an ECI2002 or an IT8.7/4 or, something like 3000 patches by Argyll, can I reasonably expect those two statistics to go down? Or is that a sign of the device ill-behavior? This is from an Epson printer, by the way. Linearized by a CMYK RIP. Just curious... Roger