Note
Go to the endto download the full example code.
Bar chart with gradients#
Matplotlib does not natively support gradients. However, we can emulate agradient-filled rectangle by anAxesImage of the right size and coloring.
In particular, we use a colormap to generate the actual colors. It is thensufficient to define the underlying values on the corners of the image andlet bicubic interpolation fill out the area. We define the gradient directionby a unit vectorv. The values at the corners are then obtained by thelengths of the projections of the corner vectors onv.
A similar approach can be used to create a gradient background for an Axes.In that case, it is helpful to use Axes coordinates (extent=(0,1,0,1),transform=ax.transAxes) to be independent of the data coordinates.
importmatplotlib.pyplotaspltimportnumpyasnpnp.random.seed(19680801)defgradient_image(ax,direction=0.3,cmap_range=(0,1),**kwargs):""" Draw a gradient image based on a colormap. Parameters ---------- ax : Axes The Axes to draw on. direction : float The direction of the gradient. This is a number in range 0 (=vertical) to 1 (=horizontal). cmap_range : float, float The fraction (cmin, cmax) of the colormap that should be used for the gradient, where the complete colormap is (0, 1). **kwargs Other parameters are passed on to `.Axes.imshow()`. In particular, *cmap*, *extent*, and *transform* may be useful. """phi=direction*np.pi/2v=np.array([np.cos(phi),np.sin(phi)])X=np.array([[v@[1,0],v@[1,1]],[v@[0,0],v@[0,1]]])a,b=cmap_rangeX=a+(b-a)/X.max()*Xim=ax.imshow(X,interpolation='bicubic',clim=(0,1),aspect='auto',**kwargs)returnimdefgradient_bar(ax,x,y,width=0.5,bottom=0):forleft,topinzip(x,y):right=left+widthgradient_image(ax,extent=(left,right,bottom,top),cmap="Blues_r",cmap_range=(0,0.8))fig,ax=plt.subplots()ax.set(xlim=(0,10),ylim=(0,1))# background imagegradient_image(ax,direction=1,extent=(0,1,0,1),transform=ax.transAxes,cmap="RdYlGn",cmap_range=(0.2,0.8),alpha=0.5)N=10x=np.arange(N)+0.15y=np.random.rand(N)gradient_bar(ax,x,y,width=0.7)plt.show()
Tags:styling: colorplot-type: imshowlevel: intermediatepurpose: showcase