Using Colormaps to set color of line in matplotlib

Question

How does one set the color of a line in matplotlib with scalar values provided at run time using a colormap (say jet)? I tried a couple of different approaches here and I think I'm stumped. values[] is a storted array of scalars. curves are a set of 1-d arrays, and labels are an array of text strings. Each of the arrays have the same length.

fig = plt.figure() ax = fig.add_subplot(111) jet = colors.Colormap('jet') cNorm  = colors.Normalize(vmin=0, vmax=values[-1]) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) lines = [] for idx in range(len(curves)):     line = curves[idx]     colorVal = scalarMap.to_rgba(values[idx])     retLine, = ax.plot(line, color=colorVal)     #retLine.set_color()     lines.append(retLine) ax.legend(lines, labels, loc='upper right') ax.grid() plt.show() 

Answer 1

The error you are receiving is due to how you define jet. You are creating the base class Colormap with the name 'jet', but this is very different from getting the default definition of the 'jet' colormap. This base class should never be created directly, and only the subclasses should be instantiated.

What you've found with your example is a buggy behavior in Matplotlib. There should be a clearer error message generated when this code is run.

This is an updated version of your example:

import matplotlib.pyplot as plt import matplotlib.colors as colors import matplotlib.cm as cmx import numpy as np  # define some random data that emulates your indeded code: NCURVES = 10 np.random.seed(101) curves = [np.random.random(20) for i in range(NCURVES)] values = range(NCURVES)  fig = plt.figure() ax = fig.add_subplot(111) # replace the next line  #jet = colors.Colormap('jet') # with jet = cm = plt.get_cmap('jet')  cNorm  = colors.Normalize(vmin=0, vmax=values[-1]) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) print scalarMap.get_clim()  lines = [] for idx in range(len(curves)):     line = curves[idx]     colorVal = scalarMap.to_rgba(values[idx])     colorText = (         'color: (%4.2f,%4.2f,%4.2f)'%(colorVal[0],colorVal[1],colorVal[2])         )     retLine, = ax.plot(line,                        color=colorVal,                        label=colorText)     lines.append(retLine) #added this to get the legend to work handles,labels = ax.get_legend_handles_labels() ax.legend(handles, labels, loc='upper right') ax.grid() plt.show() 

Resulting in:

Using a ScalarMappable is an improvement over the approach presented in my related answer: creating over 20 unique legend colors using matplotlib