Create a color map with white centered around zero

Question

I must admit that understanding how to create or manipulate matplotlib color maps is not easy. So I'm looking for a little help in explaining and setting up a color map that goes from blue (negative) to red (positive) and has a white one centered around zero. Then I would like to use this cmap in contourf :

• This works, but the colors are reversed.

   cs = plt.contourf(longrid, latgrid, ar[window-1]-bkgrd, levels, cmap = cm.get_cmap('BuRd', len(levels)-1)) 

• The problem is that BuRd_r removes white around zero

   cs = plt.contourf(longrid, latgrid, ar[window-1]-bkgrd, levels, cmap = cm.get_cmap('BuRd_r', len(levels)-1)) 

I would appreciate any help with this.

Here is the function and data for checking the color map:

 def PlotAnomalyCF(ar,hgrid,latgrid,longrid,outfile,levels,units): window = 1 tsize = 8 plt.close() plt.figure(figsize=(11.7,4.3) ) plt.clf() plt.cla() bkgrd = bn.nanmean(ar[:],0) for v in hgrid:OA plt.subplot(1,len(hgrid),window) plt.title(v,fontsize=tsize) plt.subplots_adjust(left=0.07,bottom=0.75, right=0.98, top=0.92, wspace=0.12,hspace=0.98) cs = plt.contourf(longrid,latgrid, ar[window-1]-bkgrd,levels, cmap=cm.get_cmap('BuRd_r',len(levels)-1)) cs.cmap.set_over('r') plt.grid(True) plt.axis('off') window += 1 ax = plt.gca() pos = ax.get_position() l,b,w,h = pos.bounds print l,b,w,h cax = plt.axes([l-0.848,b-0.05,0.91,0.02]) # setup colorbar axes cbar = plt.colorbar(cs,cax=cax,orientation='horizontal') cl = plt.getp(cbar.ax, 'xticklabels') plt.setp(cl, fontsize=8) # Add units text plt.figtext(0.012,0.83,units,fontsize=tsize+1) print 'outfile.',outfile plt.savefig(outfile,dpi=900,orientation='landscape',format='pdf') plt.show() # Data hgrid = array([-18, -15, -12, -9, -6, -3, 0, 3, 6, 9, 12, 15, 18]) latgrid = array([ 5.61402391, 4.91227095, 4.21051798, 3.508765 , 2.80701201, 2.10525902, 1.40350602, 0.70175301, 0. , -0.70175302, -1.40350604, -2.10525907, -2.8070121 , -3.50876514, -4.21051818, -4.91227122, -5.61402427]) longrid = array([-5.625 , -4.921875, -4.21875 , -3.515625, -2.8125 , -2.109375, -1.40625 , -0.703125, 0. , 0.703125, 1.40625 , 2.109375, 2.8125 , 3.515625, 4.21875 , 4.921875, 5.625 ]) levels = array([-20, -19, -18, -17, -16, -15, -14, -13, -12, -11, -10, -9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]) units ='$\mathrm{CC_{200}\,[\%]}$' ar = shape is (13, 17, 17) with max = 82.4 and min = 45.5. It would be easier to just generate some random data within these intervals. Alternatively just copy one of the array: ar[1] = array([[ 46.91224792, 46.21374984, 46.86130719, 47.01021234, 46.72626813, 46.2288305 , 46.43835451, 45.79325437, 45.58271668, 46.35872217, 48.08725987, 48.44553638, 47.76519316, 47.6366742 , 48.40425078, 48.77756577, 49.33566712], [ 46.83599932, 46.84286989, 47.33453309, 46.55030976, 46.80566458, 46.53292035, 47.02261763, 47.41084421, 47.38724565, 47.91122826, 49.21117552, 49.45223641, 49.97629913, 50.44165439, 51.08080398, 50.79600723, 49.968034 ], [ 47.42288313, 47.07674124, 46.7167639 , 46.11959218, 46.95814111, 46.88763807, 47.79510368, 48.50213272, 49.14340301, 50.0550682 , 50.96554707, 51.70960776, 52.76304827, 53.13428506, 53.01955687, 52.57951586, 51.91245273], [ 47.71067291, 47.48154219, 47.40131211, 47.45929857, 48.46118424, 48.65199823, 49.38156691, 49.86137507, 50.55394084, 51.96604309, 52.60579898, 53.69096203, 54.22750101, 54.37757099, 54.31517398, 53.47697773, 53.41809044], [ 48.20779565, 48.58856851, 48.75880829, 49.40822878, 50.03355014, 51.44922083, 52.00567831, 52.99485667, 53.69339127, 53.58208129, 53.88588998, 55.24096208, 55.24137628, 55.38338399, 55.30856415, 55.0329081 , 54.58041914], [ 49.20063728, 49.81223264, 50.2145489 , 50.54749112, 51.44252761, 53.1708726 , 54.48141824, 55.1337493 , 55.86338227, 55.80719304, 56.1060897 , 56.15050406, 56.10404113, 56.82550383, 57.12370494, 56.79250814, 57.21656741], [ 50.17222332, 50.78494993, 51.47036476, 51.78513471, 54.07329312, 55.12136894, 56.63202678, 56.77587861, 57.60688855, 57.31874243, 57.86532727, 58.38753463, 58.52204736, 58.8451274 , 59.17282185, 58.93137673, 58.90977463], [ 51.50642331, 51.51055372, 52.44746806, 53.37696513, 54.86775802, 56.68992167, 57.90624404, 58.76394172, 59.64662899, 59.80540837, 59.98355254, 60.05761821, 59.95848562, 60.54540623, 60.4776266 , 60.11749116, 59.74209418], [ 51.40396463, 51.48043239, 52.89530187, 53.73500868, 55.39612502, 56.70178532, 58.07064267, 59.56644298, 60.47288049, 60.59095081, 61.26474813, 61.20278944, 61.43807574, 61.1942828 , 60.40014922, 59.78371327, 59.50410992], [ 51.89656984, 52.18725649, 52.57764233, 54.39502415, 55.61672911, 57.04180061, 58.54357871, 59.76354498, 60.24155861, 60.59473182, 60.65985503, 60.92762915, 60.76726905, 60.47166256, 60.42044548, 60.04043031, 60.06031171], [ 51.69698671, 52.39494994, 52.71685017, 53.65488505, 54.52480831, 56.33091376, 57.87811829, 58.36719736, 59.31479758, 59.61329074, 59.81807224, 59.44053305, 59.25522337, 59.5309563 , 59.68850776, 59.54046914, 58.60604327], [ 50.81523448, 51.5690217 , 51.81382216, 52.88514118, 53.27394887, 54.6941369 , 55.81938471, 56.85401174, 57.10874072, 58.55074569, 58.45869901, 57.67496274, 57.3895956 , 58.05319653, 58.83009123, 57.90678384, 56.97717781], [ 49.61355365, 49.92298625, 50.56281781, 51.22117266, 51.98020374, 53.0328832 , 53.76602714, 54.94396421, 55.16849545, 55.83033544, 56.19720112, 56.9382048 , 57.20669361, 56.76351885, 56.93632305, 56.16428665, 54.7570241 ], [ 49.17250426, 49.14663096, 49.86504335, 50.24394193, 50.84671744, 51.21785439, 51.72667942, 52.8287256 , 53.65550669, 53.81801262, 54.62490542, 54.88045696, 55.27367041, 54.89234901, 54.51005786, 53.57284022, 52.53966996], [ 48.55125023, 48.99467099, 49.80237362, 49.67943854, 49.45569362, 49.3387854 , 50.129718 , 49.94784906, 51.03357894, 51.73021167, 52.0211617 , 52.55805334, 52.22956095, 51.88844202, 50.87410618, 50.39506101, 49.72117909], [ 48.37551433, 48.30812683, 48.45300884, 48.50818535, 47.76798967, 47.21965588, 47.60764424, 48.21327283, 48.52370448, 49.95221655, 49.7608777 , 50.1178807 , 50.15020093, 49.4369175 , 49.16839811, 49.31254753, 48.03208233], [ 46.91675497, 46.45280928, 46.37122283, 46.69881125, 45.95493853, 46.33296801, 46.15091804, 46.09862998, 46.31676066, 46.6199912 , 47.60040926, 48.34096053, 47.78005438, 48.0951173 , 48.15291404, 47.21140107, 46.28884057]]) 

Answer 1

Instead of using cmap, I will carefully work out my own production.

As you already noticed, in order to have absolute control over colors (without going through an array of colors) when using cmaps, the number of colors in cmap should be equal to the number of levels - 1.

We can easily demonstrate this in the following example. Let's make a color code with three primary colors in:

 import matplotlib.pyplot as plt import matplotlib.colors as mcolors import numpy data = numpy.arange(12).reshape(3, 4) cmap = mcolors.ListedColormap([(0, 0, 1), (0, 1, 0), (1, 0, 0)]) 

However, when we start using with anything other than 3 + 1 levels, we get results that you cannot expect:

 plt.subplot(121) plt.contourf(data, cmap=cmap, levels=[1, 4, 8, 10]) plt.subplot(122) plt.contourf(data, cmap=cmap, levels=[1, 4, 8]) plt.show() 

So, I showed that your levels should have length n_colors-1 , but since we want to have 3 colors, and the average color is always shown, we also need to have an even number of levels.

Ok, now we have some basic rules, let's create a LinearSegmentedColormap, which is essentially just a ListedColormap interpolated to N colors:

 levs = range(12) assert len(levs) % 2 == 0, 'N levels must be even.' cmap = mcolors.LinearSegmentedColormap.from_list(name='red_white_blue', colors =[(0, 0, 1), (1, 1., 1), (1, 0, 0)], N=len(levs)-1, ) plt.contourf(data, cmap=cmap, levels=levs) plt.show() 

We can verify that the normal cmap is white as the middle color programmatically:

 >>> print cmap(0.5) (1.0, 1.0, 1.0, 1.0) 

I hope this will give you all the information you need to be able to make any color map that you like and successfully use it in contouring.