(I know this is an old question but…) Colorbars require a matplotlib.cm.ScalarMappable, plt.plot produces lines which are not scalar mappable, therefore, in order to make a colorbar, we are going to need to make a scalar mappable. Ok. So the constructor of a ScalarMappable takes a cmap and a norm instance. (norms scale data to … Read more
Sometimes it can be useful to retrieve a colorbar even if it was not held in a variable. In this case, it is possible to retrieve the colorbar from the plot with: # Create an example image and colourbar img = np.arange(20).reshape(5,4) plt.imshow(img) plt.colorbar() # Get the current axis ax = plt.gca() # Get the … Read more
Aha! Found the answer here: cbar.ax.tick_params(labelsize=10) P.S. Upvote that answer and give Paul some love!
I think all that you’re missing is a call to caxis to specify the minimum and maximum values to map the color range to: caxis([18 23]); Note that the following line… cb.Limits = [18 23]; … only changes the tick limits displayed on the colorbar, but doesn’t change anything about how the data is mapped … Read more
I think the problem is that with del you cancel the variable, but not the referenced object colorbar. If you want the colorbar to be removed from plot and disappear, you have to use the method remove of the colorbar instance and to do this you need to have the colorbar in a variable, for … Read more
Here a step by step explanation. First consider the following example: [X,Y,Z1] = peaks; figure(1) [~,h1] = contourf(X,Y,Z1,20); a1 = colorbar; colormap(jet) caxis([-6,6]) which will give you the following plot: It has linear data and a linear colormap. Now I want to scale the Z-Data to get it non-linear like in your case. I chose … Read more
This can be easily solved with the the utility make_axes_locatable. I provide a minimal example that shows how this works and should be readily adaptable: import matplotlib.pyplot as plt from mpl_toolkits.axes_grid1 import make_axes_locatable import numpy as np m1 = np.random.rand(3, 3) m2 = np.arange(0, 3*3, 1).reshape((3, 3)) fig = plt.figure(figsize=(16, 12)) ax1 = fig.add_subplot(121) im1 … Read more
While I’m not sure how to do this specifically using an ArtistAnimation, using a FuncAnimation is fairly straightforward. If I make the following modifications to your “naive” version 1 it works. Modified Version 1 import numpy as np import matplotlib.pyplot as plt import matplotlib.animation as animation from mpl_toolkits.axes_grid1 import make_axes_locatable fig = plt.figure() ax = … Read more
You could use colorbar‘s format parameter: import matplotlib.pyplot as plt import numpy as np import matplotlib.ticker as ticker img = np.random.randn(300,300) myplot = plt.imshow(img) def fmt(x, pos): a, b = ‘{:.2e}’.format(x).split(‘e’) b = int(b) return r’${} \times 10^{{{}}}$’.format(a, b) plt.colorbar(myplot, format=ticker.FuncFormatter(fmt)) plt.show()
Not to steal @ianilis’s answer, but I wanted to add an example… There are multiple ways, but the simplest is just to specify the vmin and vmax kwargs to imshow. Alternately, you can make a matplotlib.cm.Colormap instance and specify it, but that’s more complicated than necessary for simple cases. Here’s a quick example with a … Read more