[Matplotlib-users] defining a custom RGB colormap

[Michael R. <raw...@ya...>]

How does one define a range of colors for a custom user-defined colormap?  I'm fairly new to matplotlib and have been using standard colormaps.  Below is a sample program that makes a color bar based on the hot colormap.  I'd like to have a colormap like hot, but that starts at, say, orange (near 14%), and runs to black (40%).



'''
Make a colorbar as a separate figure.
'''

from matplotlib import pyplot, mpl
import sys,getopt
from mpl_toolkits.basemap import Basemap, shiftgrid, cm 
#from netCDF3 import Dataset as NetCDFFile 
from mpl_toolkits.basemap import  NetCDFFile
from pylab import *

usemaprev=True

# Make a figure and axes with dimensions as desired.
fig = pyplot.figure(figsize=(8,3))
ax1 = fig.add_axes([0.05, 0.4, 0.9, 0.14])

# Set the colormap and norm to correspond to the data for which
# the colorbar will be used.
cmap = mpl.cm.cool
norm = mpl.colors.Normalize(vmin=0, vmax=40)   # here set colorbar min/max

# alter a matplotlib color table, 
# cm.jet is very useful scheme, but reversed colors are better for drought 
colordict=cm.jet._segmentdata.copy() # dictionary ('blue', 'green', 'red') of nested tuples

#  autumn scheme is yellow to red
colordict=cm.hot._segmentdata.copy() 

#mycolormap=cm.jet
mycolormap=cm.hot

for k in colordict.keys():
	colordict[k]=[list(q) for q in colordict[k]] #convert nested tuples to nested list
	for a in colordict[k]: 
		a[0]=1.-a[0] #in inner list, change normalized value to 1 - value.
	colordict[k].reverse() #reverse order of outer list
maprev = cm.colors.LinearSegmentedColormap("maprev",  colordict)
#map = cm.colors.LinearSegmentedColormap("map", colordict)

if usemaprev:
	mycolormap=maprev
	print "using reverse of defined colormap"

#ax1 = fig.add_axes([0.05, 0.65, 0.9, 0.15])
#cax = axes([0.85, 0.1, 0.05, 0.7]) # setup colorbar axes
#colorbar(format='%d') # draw colorbar

# ColorbarBase derives from ScalarMappable and puts a colorbar
# in a specified axes, so it has everything needed for a
# standalone colorbar.  There are many more kwargs, but the
# following gives a basic continuous colorbar with ticks
# and labels.
#cb1 = mpl.colorbar.ColorbarBase(ax1, cmap=jetrev,
#                                   norm=norm,
#                                   orientation='horizontal')
cb1 = mpl.colorbar.ColorbarBase(ax1, cmap=mycolormap,
                                   norm=norm,
                                   orientation='horizontal')
cb1.set_label('percent')

#pyplot.show()
plt.savefig('colormap.png')