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()
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