Matplotlib: add color bar to non-displayable
I have a series of lines representing a change to a variable; each with a unique color. For this reason, I want to add a color bar next to the plot. The required output is shown below.
The problem is what plot
is a non-transferable object i.e. the colored bar must be added manually. I find my current solution (below) suboptimal as it includes sizing options that I'm not interested in controlling. I would prefer a similar solution as for the displayable (example below the current solution).
Desired exit
Current solution
import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt x = np.linspace(0, 5, 100) N = 20 cmap = plt.get_cmap('jet',N) fig = plt.figure(figsize=(8,6)) ax1 = fig.add_axes([0.10,0.10,0.70,0.85]) for i,n in enumerate(np.linspace(0,2,N)): y = np.sin(x)*x**n ax1.plot(x,y,c=cmap(i)) plt.xlabel('x') plt.ylabel('y') ax2 = fig.add_axes([0.85,0.10,0.05,0.85]) norm = mpl.colors.Normalize(vmin=0,vmax=2) cb1 = mpl.colorbar.ColorbarBase(ax2,cmap=cmap,norm=norm,orientation='vertical') plt.show()
Desired solution
(obviously replacing imshow
)
fig,ax = plt.subplots() cax = ax.imshow(..) cbar = fig.colorbar(cax,aspect=10) plt.show()
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You can define your own ScalarMappable and use it as if it were present in the plot.
(Note that I changed the colors of numo f to 21 to have nice distances 0.1
)
import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt x = np.linspace(0, 5, 100) N = 21 cmap = plt.get_cmap('jet',N) fig = plt.figure(figsize=(8,6)) ax1 = fig.add_axes([0.10,0.10,0.70,0.85]) for i,n in enumerate(np.linspace(0,2,N)): y = np.sin(x)*x**n ax1.plot(x,y,c=cmap(i)) plt.xlabel('x') plt.ylabel('y') norm = mpl.colors.Normalize(vmin=0,vmax=2) sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm) sm.set_array([]) plt.colorbar(sm, ticks=np.linspace(0,2,N), boundaries=np.arange(-0.05,2.1,.1)) plt.show()
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