modifying colorbar in matplotlib and seaborn

Question

I'm trying to save an image I generated using seaborn. The image is 4x4 confusion matrix ('confmat' np.array). I learned that when I save the image in vector format, certain viewers have issues resulting in white lines on colorbar, quoting from matplotlib reference:

It is known that some vector graphics viewer (svg and pdf) renders white gaps between segments of the colorbar. This is due to bugs in the viewers not matplotlib. As a workaround the colorbar can be rendered with overlapping segments:

cbar = colorbar()

cbar.solids.set_edgecolor("face")

draw()

However, I have trouble doing what is suggested.

Here is what I did:

import seaborn as sns
import matplotlib.pyplot as plt

cmap=plt.cm.Blues

fig, ax = plt.subplots()
    
ax = sns.heatmap(confmat, annot=True, cmap=cmap)
ax.set_title('title')
ax.tick_params(
    axis='both',          # changes apply to the x-axis
    which='both',      # both major and minor ticks are affected
    bottom='off',      # ticks along the bottom edge are off
    top='off',         # ticks along the top edge are off
    labelbottom='off',  # labels along the bottom edge are off
    labelleft='off',
    right='off')

fig.savefig('confusion_matrix.svg', format='svg')

I tried to get colorbar using

cbar = ax.colorbar()

But get an error AttributeError: 'AxesSubplot' object has no attribute 'colorbar'.

I searched for solution and found a few questions here that suggest using plt.imshow() to get the colorbar object, but I'm completely confused about what I'm doing by now. Can someone suggest, and if possible, explain why, the solution for implementing what matplotlib documentation has offered for colorbar?

mwaskom · Accepted Answer · 2015-11-11 17:01:10Z

6

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

x = np.random.randn(10, 10)

f, ax = plt.subplots()
sns.heatmap(x)
cbar_ax = f.axes[-1]
cbar_solids = cbar_ax.collections[0]
cbar_solids.set_edgecolor("face")
f.savefig("heatmap.svg")

answered Nov 11, 2015 at 17:01

mwaskom

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2 Comments

Ed Smith Over a year ago

Much better solution, I couldn't work out how to get the colorbar handle from the figure. Assumed there would be a colorbar object on the second axis but in matplotlib a colorbar seems to be stored as type QuadMesh, which is a little confusing.

Josiah Yoder Over a year ago

I had to use cbar_solids.set_alpha(None) to remove the stripes. set_edgecolor('face') wasn't needed and didn't help in my case.

Ed Smith · Accepted Answer · 2015-11-11 16:41:06Z

Changing a colorbar with cb.solid.set_edgecolor("face") as suggested in the matplotlib docs appears to be a bit of a hack to ensure there are no white lines between elements on the colorbar. I think seaborn is designed assuming you should be able to do everything you need by passing kwargs (cbar_kws in heatmap). For example, you can pass cb_kwargs to the sns.heatmap function cbar_kws={"drawedges": "False"} but unfortunately this doesn't fix the problem.

As the Seaborn Heatmap only returns an axis handle on which the heatplot and the colorbar are plotted, you don't have direct access to the mappable object, cbar in the source code. As a result you can't apply this hack.

One solution is to just plot this using pcolormesh and colorbar. I think seaborn actually redefines matplotlib styles so should look the same,

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

cmap=plt.cm.Blues

fig, ax = plt.subplots()
confmat = np.random.rand(4, 4)

cb = ax.pcolormesh(confmat, cmap=cmap)

ax.set_title('title')
ax.tick_params(
    axis='both',          # changes apply to the x-axis
    which='both',      # both major and minor ticks are affected
    bottom='off',      # ticks along the bottom edge are off
    top='off',         # ticks along the top edge are off
    labelbottom='off',  # labels along the bottom edge are off
    labelleft='off',
    right='off')

cbar = plt.colorbar(cb)
cbar.solids.set_edgecolor("face")
plt.draw()

fig.savefig('confusion_matrix.svg', format='svg')

The result for me looks to be rid of the white lines when you zoom in.

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