James Boyle wrote:

I wish to make a color filled plot with the colors defined for discrete, non-uniform intervals. Something like:

0.0 -0.001 0.001-0.05 0.05-0.2 0.2-0.4 0.4-0.8 0.8-1.0

red blue green magenta yellow cyan

with the colorbar labeled appropriately.

I have seen discussions and solutions for discrete colors but not for non-uniform intervals + discrete.

The last post I saw regarding this type of issue was august 2005 - and a solution was not resolved at that time.

However, Eric has done a huge amount of work in the intervening time and a smarter person than myself might have a solution now.

Note that I do not wish just to make contours - although that would be good - but to have a general mapping code that joins allows the color rmapping to be passed to colorbar.

maybe some sub-class of scalarMappable that could work.

This is very easy for contourf, and is illustrated in the second figure made by examples/contourf_demo.py. For your case above, it would be something like

levs = [0, 0.001, 0.05, 0.2, 0.4, 0.8, 1]

colors = ['r', 'b', 'g', 'm', 'y', 'c']

contourf(z, levs, colors=colors)

colorbar()

Unfortunately, although it *should* be just as easy for imshow or pcolor, it is not at present; it can be done, probably in several ways, but not in such a transparent way. Attached is a quick attempt at something that might be close to what you need. The right way to do this is to make some changes and additions to colors.py and colorbar.py; I might get to that in a few days, or, more likely, it might be a few weeks.

Eric

Thanks for any help.

--Jim

import pylab as P

import numpy

from matplotlib import colors

class BoundaryNorm(colors.Normalize):

def __init__(self, boundaries):

self.vmin = boundaries[0]

self.vmax = boundaries[-1]

self.boundaries = boundaries

self.N = len(self.boundaries)

def __call__(self, x, clip=False):

x = numpy.asarray(x)

ret = numpy.zeros(x.shape, dtype=numpy.int)

for i, b in enumerate(self.boundaries):

ret[numpy.greater_equal(x, b)] = i

ret[numpy.less(x, self.vmin)] = -1

ret = numpy.ma.asarray(ret / float(self.N-1))

return ret

bounds = [0, 0.1, 0.5, 1]

cm = colors.ListedColormap(['r', 'g', 'b'])

z = (numpy.arange(5)[:,None] * numpy.arange(8)[None,:]).astype(numpy.float)

z = z / z.max()

P.pcolor(z, cmap=cm, norm=BoundaryNorm(bounds))

P.colorbar(boundaries=bounds)

P.show()