Suppose I have a vertical bar plot like this:
MWE per this suggestion:
import numpy as np import matplotlib.pyplot as plt fig, ax = plt.subplots() bar = ax.bar([1,2,3,4,5,6],[4,5,6,3,7,5], bottom=[1,7,4,6,3,2]) def gradientbars(bars): grad = np.atleast_2d(np.linspace(0,1,256)).T ax = bars[0].axes lim = ax.get_xlim()+ax.get_ylim() for bar in bars: bar.set_zorder(1) bar.set_facecolor("none") x,y = bar.get_xy() w, h = bar.get_width(), bar.get_height() ax.imshow(grad, extent=[x,x+w,y,y+h], aspect="auto", zorder=0) ax.axis(lim) gradientbars(bar) plt.show()
Is there an easy way to color the bars with a colormap according to the y-values they actually span (suppose my color bar goes from 1-12 where 1 is represented by yellow and 12 is represented by dark-blue)?
I have tried to adapt this example but wasn’t successful.
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Answer
Here is the code in this post adapted such that each bar shows a corresponding slice of the gradient.
import numpy as np import matplotlib.pyplot as plt fig, ax = plt.subplots() x = np.arange(35) bar = ax.bar(x, 6 - np.sin(x / 10) * 3, bottom=5 - np.cos(x / 10) * 5) plt.xlim(x[0] - 0.5, x[-1] + 0.5) def gradientbars_sliced(bars): ax = bars[0].axes xmin, xmax = ax.get_xlim() ymin, ymax = ax.get_ylim() for bar in bars: bar.set_zorder(1) bar.set_facecolor("none") x, y = bar.get_xy() w, h = bar.get_width(), bar.get_height() grad = np.linspace(y, y + h, 256).reshape(256, 1) ax.imshow(grad, extent=[x, x + w, y, y + h], aspect="auto", zorder=0, origin='lower', vmin=ymin, vmax=ymax, cmap='magma') ax.axis([xmin, xmax, ymin, ymax]) gradientbars_sliced(bar) plt.show()