On Fri, Jan 16, 2009 at 10:33 AM, antonv <vasilescu_an...@yahoo.com> wrote: > > I have a series of 18 separate colors to create my cmap but I would like to > convert that to a continuous map which interpolates all the other values in > between my chosen colors. This should be really easy but I am not sure how > can it be solved. Any ideas?
Although the logic of the LinearSegmentedColormap takes some time to get your head around, it is pretty easy. http://matplotlib.sourceforge.net/api/colors_api.html#matplotlib.colors.LinearSegmentedColormap Here is an example: import numpy as np import matplotlib.pyplot as plt import matplotlib.colors as mcolors import matplotlib.cm as cm colors = 'red', 'green', 'blue', 'yellow', 'orange' ncolors = len(colors) vals = np.linspace(0., 1., ncolors) cdict = dict(red=[], green=[], blue=[]) for val, color in zip(vals, colors): r,g,b = mcolors.colorConverter.to_rgb(color) cdict['red'].append((val, r, r)) cdict['green'].append((val, g, g)) cdict['blue'].append((val, b, b)) cmap = mcolors.LinearSegmentedColormap('mycolors', cdict) x = np.arange(10000.).reshape((100,100)) plt.imshow(x, cmap=cmap) plt.show() See also http://matplotlib.sourceforge.net/examples/pylab_examples/custom_cmap.html. I just added a function to svn to support this, so with svn you can do colors = 'red', 'gray', 'green' cmap = mcolors.LinearSegmentedColormap.from_list('mycolors', colors) X, Y = np.meshgrid(np.arange(10), np.arange(10)) plt.imshow(X+Y, cmap=cmap) JDH ------------------------------------------------------------------------------ This SF.net email is sponsored by: SourcForge Community SourceForge wants to tell your story. http://p.sf.net/sfu/sf-spreadtheword _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
