Ludwig Schwardt wrote: > Possible solutions: > > - Use colors that are safe for printing and displaying (less saturated > colors?).
Avoid the extreme (255,0,0), (0,255,0), (0,0,255) colors, yes. For reasons which are fairly obvious given the physics, RGB devices do better displaying those than CMYK devices. Blues are especially poorly represented in CMYK media. OS X users can play around with these things using the ColorSync Utility.app program. Click on the "Profiles" button. On the left, there is a tree of profiles. Select "Generic RGB Profile". On the 3D plot, click the triangle in the upper left-hand corner and select "Hold for comparison". Now click the "Generic CMYK Profile". This shows a CMYK color gamut and an RGB color gamut in Lab space. The intersection of these two is the "safe region" where the colors on your screen can be represented in print. Of course, that is only if the printer driver knows about both profiles. > - Use Lab color, which is absolute. This is cumbersome, and RGB is > much more commonplace and well-understood in plotting packages, > including Matlab. Yeah, that's probably not too practical. > - Associate a generic ICC profile with the mpl plot, to attach > absolute color values to the RGB values in the plot in a consistent > way. Maybe this is the default in many graphics file formats and > therefore redundant, or maybe it does make a difference specifying it > explicitly, I'm not sure. It might be reasonable to specify that matplotlib uses the W3C standard sRGB colorspace. It was meant to be good for representability on a wide variety of computer monitors. Some monitors may even be manufactured to match that standard. It is the default colorspace for SVG and PNG. It misses a fair chunk of most the usual CMYK space in the greens and cyans, though. Adobe RGB (1998) would be better for print, but that "wastes" a lot of space on greens that most monitors can't represent. Some journals require figures in Adobe RGB (1998). Really implementing this still requires one to apply calibrated ICC profiles of your viewing device and potential output devices, but it does standardize the files matplotlib outputs. I have some code that wraps the lcms library for applying ICC profiles to numpy arrays. Those who saw my lightning talk at SciPy '07 saw an app I had for showing colormaps in perceptual colorspaces like Lab and with transformations to simulate colorblindness. I'm snowed under work next week, but after that I'll try to clean it up for doing soft-proofs of images. Maybe I'll even get to integrating that soft-proofing with matplotlib such that every interactive plot can be displayed as if it were printed (or seen through my colorblind eyes). -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco ------------------------------------------------------------------------- This SF.net email is sponsored by: Microsoft Defy all challenges. Microsoft(R) Visual Studio 2005. http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
