Hi Michael,
I may be completely off my rocker here, but I think that you can define the
range of Z values that the ramp should be applied to with the Normalize
function.
cmap = matplotlib.colors.LinearSegmentedColormap('my_colormap',cdict,256)
norm = mpl.colors.Normalize(vmin=.0, vmax=1.0)
I'm only guessing though, because at this point I only change vmin and vmax
to alter the colorbar labels.
Roger
--
On Tue, Dec 16, 2008 at 1:15 PM, Michael Hearne <mhea...@usgs.gov> wrote:
> I'm trying to replicate the color-mapping behavior of the GMT package with
> matplotlib/basemap and the imshow() function, and have run into a problem.
>
> Using GMT you can assign colors to ranges of Z values, so that (for
> example), Z values between 0 and 50 are given a color interpolated between
> (0,0,255) (blue) and (255,0,0) (red). There have been various versions of
> a function called gmtColorMap() posted to this list. I did some experiments
> today, and as far as I can tell, this function only reads the _color_ part
> of a GMT .cpt file, ignoring the Z values to which those color ranges are
> assigned. This isn't a problem as long as you have a linear color scale.
> However, if you have (as in my case) a color scale assigned to non-linear
> ranges of values, it becomes a problem.
>
> Is there a way with imshow() to assign ranges of colors to specific ranges
> of Z values?
>
> As a test, I created the attached python script, which reads in the
> attached .cpt file.
>
> For those of you not aware of the GMT color palette file format, in each
> row you define two end points for your Z values, and two corresponding RGB
> triplets. In my simplified example, I have defined 8 ranges, and assigned a
> single color to each range. For example, the first two lines in my color
> palette file looks like this:
>
> 00000 255 255 255 00005 255 255 255
> 00005 255 255 000 00050 255 255 000
>
> which can be interpreted to mean that any values between 0 and 5 (filled in
> with zeros to make the columns line up), should be colored white.
> Similarly, any values between 5 and 50 should be colored yellow.
>
>
>
>
>
>
>
>
> #!/usr/bin/python
>
> from matplotlib.colors import LinearSegmentedColormap,Normalize
> from pylab import *
>
> def gmtColormap(fileName):
> import colorsys
> import numpy as N
> try:
> f = open(fileName)
> except:
> print "file ",fileName, "not found"
> return None
>
> lines = f.readlines()
> f.close()
>
> x = []
> r = []
> g = []
> b = []
> colorModel = "RGB"
> for l in lines:
> ls = l.split()
> if l[0] == "#":
> if ls[-1] == "HSV":
> colorModel = "HSV"
> continue
> else:
> continue
> if ls[0] == "B" or ls[0] == "F" or ls[0] == "N":
> pass
> else:
> x.append(float(ls[0]))
> r.append(float(ls[1]))
> g.append(float(ls[2]))
> b.append(float(ls[3]))
> xtemp = float(ls[4])
> rtemp = float(ls[5])
> gtemp = float(ls[6])
> btemp = float(ls[7])
>
> x.append(xtemp)
> r.append(rtemp)
> g.append(gtemp)
> b.append(btemp)
>
> nTable = len(r)
> x = N.array( x , N.float32)
> r = N.array( r , N.float32)
> g = N.array( g , N.float32)
> b = N.array( b , N.float32)
> if colorModel == "HSV":
> for i in range(r.shape[0]):
> rr,gg,bb = colorsys.hsv_to_rgb(r[i]/360.,g[i],b[i])
> r[i] = rr ; g[i] = gg ; b[i] = bb
> if colorModel == "HSV":
> for i in range(r.shape[0]):
> rr,gg,bb = colorsys.hsv_to_rgb(r[i]/360.,g[i],b[i])
> r[i] = rr ; g[i] = gg ; b[i] = bb
> if colorModel == "RGB":
> r = r/255.
> g = g/255.
> b = b/255.
> xNorm = (x - x[0])/(x[-1] - x[0])
>
> red = []
> blue = []
> green = []
> for i in range(len(x)):
> red.append([xNorm[i],r[i],r[i]])
> green.append([xNorm[i],g[i],g[i]])
> blue.append([xNorm[i],b[i],b[i]])
> colorDict = {"red":red, "green":green, "blue":blue}
> return (colorDict)
>
> colormap = 'popcpt.cpt'
> cdict = gmtColormap(colormap)
> palette = LinearSegmentedColormap('my_colormap',cdict)
>
> f = figure()
> data = array([[2,2,2,2,2],
> [25,25,25,25,25],
> [75,75,75,75,75],
> [250,250,250,250,250],
> [750,750,750,750,750],
> [2500,2500,2500,2500,2500],
> [7500,7500,7500,7500,7500],
> [25000,25000,25000,25000,25000]])
> imshow(data,cmap=palette)
> #draw grid lines around all the cells
> nrows,ncols = data.shape
> for row in range(0,nrows):
> plot([0,ncols],[row,row],'k')
> for col in range(0,ncols):
> plot([col,col],[0,nrows],'k')
> axis([0,ncols-1,0,nrows])
> colorbar()
> savefig('output.png')
> close('all')
>
>
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