Hi Jim,

I guess you'd have to write a custom palette dictionnary do to that. If you already have a GMT file, check the link

You could also take a cpt file you like, see for example

http://pdfb.wiredworkplace.net/cpt-city/www/cb/seq/index.html

tweak it to fit your needs and use the script below to convert it to a format matplotlib will understand. See the example in the docstring.

David

def cpt2seg(file_name, sym=False, discrete=False):
"""Reads a .cpt palette and returns a segmented colormap.

sym : If True, the returned colormap contains the palette and a mirrored copy.
For example, a blue-red-green palette would return a blue-red-green-green-red-blue colormap.

discrete : If true, the returned colormap has a fixed number of uniform colors.
That is, colors are not interpolated to form a continuous range.

Example :
>>> _palette_data = cpt2seg('palette.cpt')
>>> palette = matplotlib.colors.LinearSegmentedColormap ('palette',
_palette_data, 100)
>>> imshow(X, cmap=palette)

Licence: MIT
Author: David Huard, 2006
"""

dic = {}
f = open(file_name, 'r')
rgb = rgb/255.
s = shape(rgb)
colors = ['red', 'green', 'blue']
for c in colors:
i = colors.index(c)
x = rgb[:, i+1]

if discrete:
if sym:
dic[c] = zeros((2*s[0]+1, 3), float)
dic[c][:,0] = linspace(0,1,2*s[0]+1)
vec = concatenate((x ,x[::-1]))
else:
dic[c] = zeros((s[0]+1, 3), float)
dic[c][:,0] = linspace(0,1,s[0]+1)
vec = x
dic[c][1:, 1] = vec
dic[c][:-1,2] = vec

else:
if sym:
dic[c] = zeros((2*s[0], 3), float)
dic[c][:,0] = linspace(0,1,2*s[0])
vec = concatenate((x ,x[::-1]))
else:
dic[c] = zeros((s[0], 3), float)
dic[c][:,0] = linspace(0,1,s[0])
vec = x
dic[c][:, 1] = vec
dic[c][:, 2] = vec

return dic

2006/6/29, James Boyle <boyle5@llnl.gov >:
I am interested in producing a color map and accompanying colorbar with
non-linear (arbitrary) spacing.  My intent is like the attached color
bar in which the increments are monotonic but vary in size. There might
be an easy way to do this but it is not apparent to me.

--Jim

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