... and for dessert, is there a circular colormap that would work for the colorblind?
My department is practicing presenting-science-for-the-general-public, and the problems 'heat maps' have for the colorblind keep coming up. handy: http://konigi.com/tools/submissions/color-deficit-simulators &C On Nov 8, 2009, at 3:34 AM, Gary Ruben wrote: > Hi Ariel, > > You might find the attached function helpful here. Try creating a > new colormap using the example in the docstring (you could also try > setting high=0.8) - basically this will let you turn down the > saturation which will hopefully solve your problem. You may also > find the plot option useful to see what the individual colour > channels are doing if you decide to make a new colormap of your own > - you just need to ensure that the r, g, and b values match at both > ends. > > Gary > > > Ariel Rokem wrote: >> Hi everyone, >> I am interested in using a circular colormap, in order to represent >> a phase variable, but I don't like 'hsv' (which is circular). In >> particular, I find that it induces perceptual distortion, where >> values in the green/yellow part of the colormap all look the same. >> Are there any circular colormaps except for 'hsv'? If not - how >> would you go about constructing a new circular colormap? Thanks, >> Ariel >> -- >> Ariel Rokem >> Helen Wills Neuroscience Institute >> University of California, Berkeley >> http://argentum.ucbso.berkeley.edu/ariel > import numpy as np > import matplotlib.pyplot as plt > import matplotlib.colors as colors > import matplotlib._cm as _cm > > > def rescale_cmap(cmap_name, low=0.0, high=1.0, plot=False): > ''' > Example 1: > my_hsv = rescale_cmap('hsv', low = 0.3) # equivalent scaling > to cplot_like(blah, l_bias=0.33, int_exponent=0.0) > Example 2: > my_hsv = rescale_cmap(cm.hsv, low = 0.3) > ''' > if type(cmap_name) is str: > cmap = eval('_cm._%s_data' % cmap_name) > else: > cmap = eval('_cm._%s_data' % cmap_name.name) > LUTSIZE = plt.rcParams['image.lut'] > r = np.array(cmap['red']) > g = np.array(cmap['green']) > b = np.array(cmap['blue']) > range = high - low > r[:,1:] = r[:,1:]*range+low > g[:,1:] = g[:,1:]*range+low > b[:,1:] = b[:,1:]*range+low > _my_data = {'red': tuple(map(tuple,r)), > 'green': tuple(map(tuple,g)), > 'blue': tuple(map(tuple,b)) > } > my_cmap = colors.LinearSegmentedColormap('my_hsv', _my_data, > LUTSIZE) > > if plot: > plt.figure() > plt.plot(r[:,0], r[:,1], 'r', g[:,0], g[:,1], 'g', b[:,0], > b[:,1], 'b', lw=3) > plt.axis(ymin=-0.2, ymax=1.2) > > return my_cmap > ------------------------------------------------------------------------------ > Let Crystal Reports handle the reporting - Free Crystal Reports 2008 > 30-Day > trial. Simplify your report design, integration and deployment - and > focus on > what you do best, core application coding. Discover what's new with > Crystal Reports now. > http://p.sf.net/sfu/bobj-july_______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users ------------------------------------------------------------------------------ Let Crystal Reports handle the reporting - Free Crystal Reports 2008 30-Day trial. Simplify your report design, integration and deployment - and focus on what you do best, core application coding. Discover what's new with Crystal Reports now. http://p.sf.net/sfu/bobj-july _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
