How can I use a pre-made color map for my heat map in matplotlib?

Question

I want to use the color map from http://goo.gl/5P4CT for my heat map matplotlib.

I tried to do this:

myHeatMap.imshow(heatMap, extent=ext, cmap=get_cmap(cm.datad["Spectral"])) 

However, the Python interpreter complains

 in get_cmap if name in cmap_d: TypeError: unhashable type: 'dict' 

What is the correct way to use one of these color maps?

Answer 1

It looks like you are simply calling get_cmap incorrectly. Try:

 from pylab import imshow, show, get_cmap from numpy import random Z = random.random((50,50)) # Test data imshow(Z, cmap=get_cmap("Spectral"), interpolation='nearest') show() 

What are the named colormaps?

Code run:

 from pylab import cm print cm.datad.keys() 

Gives a list of color folders, any of which can be replaced with "Spectral" :

 ['Spectral', 'summer', 'RdBu', 'Set1', 'Set2', 'Set3', 'brg_r', 'Dark2', 'hot', 'PuOr_r', 'afmhot_r', 'terrain_r', 'PuBuGn_r', 'RdPu', 'gist_ncar_r', 'gist_yarg_r', 'Dark2_r', 'YlGnBu', 'RdYlBu', 'hot_r', 'gist_rainbow_r', 'gist_stern', 'gnuplot_r', 'cool_r', 'cool', 'gray', 'copper_r', 'Greens_r', 'GnBu', 'gist_ncar', 'spring_r', 'gist_rainbow', 'RdYlBu_r', 'gist_heat_r', 'OrRd_r', 'bone', 'gist_stern_r', 'RdYlGn', 'Pastel2_r', 'spring', 'terrain', 'YlOrRd_r', 'Set2_r', 'winter_r', 'PuBu', 'RdGy_r', 'spectral', 'flag_r', 'jet_r', 'RdPu_r', 'Purples_r', 'gist_yarg', 'BuGn', 'Paired_r', 'hsv_r', 'bwr', 'YlOrRd', 'Greens', 'PRGn', 'gist_heat', 'spectral_r', 'Paired', 'hsv', 'Oranges_r', 'prism_r', 'Pastel2', 'Pastel1_r', 'Pastel1', 'gray_r', 'PuRd_r', 'Spectral_r', 'gnuplot2_r', 'BuPu', 'YlGnBu_r', 'copper', 'gist_earth_r', 'Set3_r', 'OrRd', 'PuBu_r', 'ocean_r', 'brg', 'gnuplot2', 'jet', 'bone_r', 'gist_earth', 'Oranges', 'RdYlGn_r', 'PiYG', 'YlGn', 'binary_r', 'gist_gray_r', 'Accent', 'BuPu_r', 'gist_gray', 'flag', 'seismic_r', 'RdBu_r', 'BrBG', 'Reds', 'BuGn_r', 'summer_r', 'GnBu_r', 'BrBG_r', 'Reds_r', 'RdGy', 'PuRd', 'Accent_r', 'Blues', 'Greys', 'autumn', 'PRGn_r', 'Greys_r', 'pink', 'binary', 'winter', 'gnuplot', 'pink_r', 'prism', 'YlOrBr', 'rainbow_r', 'rainbow', 'PiYG_r', 'YlGn_r', 'Blues_r', 'YlOrBr_r', 'seismic', 'Purples', 'bwr_r', 'autumn_r', 'ocean', 'Set1_r', 'PuOr', 'PuBuGn', 'afmhot'] 

Answer 2

When building with matplotlib you can use cmap=plt.get_cmap('name_of_colormap') For example: plt.pcolormesh(ter_x,ter_y,masked_height.data,cmap=plt.get_cmap('terrain'))

There are many predefined names, all of which are listed here .

However, it’s hard for me to imagine what a 2d plot might look like just by looking at the color bar. Therefore, I created a terrain map with every possible matplotlib color palette, which you can see here here .