Colorbar frame and color not aligned

Question

I have a vexing issue with a colorbar and even after vigorous research I cannot find the question even being asked. I have a plot where I overlay a contour and a pcolormesh and I would like a colorbar to indicate values. That works fine except for one thing: The colorbar frame and color are offset

The colorbar frame and the actual bar are offset such that below you have a white bit in the frame and on top the color is poking out. While the frame is aligned with the axis as desired, the colorbar is offset.

Here is a working example that emulates the situation I was in, i.e. multiple plots with insets.

import matplotlib.gridspec as gridspec
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

figheight = 4.2 - (2.1 - 49.519 / 25.4)
matplotlib.rcParams['figure.figsize'] = (5.25, figheight)
matplotlib.rcParams['axes.linewidth'] = 0.5

fig = plt.figure()
grid = gridspec.GridSpec(2, 1, height_ratios=[49.519 / 25.4 / figheight, 2.1 / figheight])
ax0 = plt.subplot(grid[0, 0])
ax1 = plt.subplot(grid[1, 0])

plt.tight_layout()

###############################################################################################
#
#           Define position of inset
#
    ###############################################################################################

ax1.axis('off')
pos1 = ax1.get_position()
pos2 = matplotlib.transforms.Bbox([[pos1.x0, pos1.y0],
                                    [.8*pos1.x1,
                                     0.8*pos1.height + pos1.y0]])
left, bottom, width, height = [pos2.x0, pos2.y0, pos2.width, pos2.height]

ax2 = fig.add_axes([left, bottom, width, height])

###############################################################################################
#
#           ax2 (inset) plot
#
###############################################################################################

pos2 = ax2.get_position()
ax2.axis('on')

x = np.linspace(0,5)
z = (np.outer(np.sin(x), np.cos(x))+1)*0.5

im = ax2.pcolormesh(z)
c  = ax2.contour(z, linewidths=7)

ax2pos = ax2.get_position()

cbar_axis = fig.add_axes([ax2pos.x1+0.05,ax2pos.y0, .02, ax2pos.height])
colorbar = fig.colorbar(im, ax = ax2,
                    cax = cbar_axis, ticks = [0.1, .5, .9])
colorbar.outline.set_visible(True)

plot = 'Minimal.pdf'

fig.savefig(plot)

plt.close()

The problem persists in both the inline display and the saved .pdf if 'Inline' graphics backend is chosen. Using tight layout or not changes how badly the offset is depending on the size of the bar - same with using PyQT5 rather than inline graphics backend. I thought it was gone when I was changing between the various combinations, but I just realized it's still there.

I would appreciate any input.

---

As suggested by ImportanceOfBeingErnest I have tried using np.round on the figsize and that didn't change things. While you can fiddle around with sizes to make it look okay, it always stands over on one or the other side by some amount. When I change the graphics backend on Spyder 3 from 'Inline' to 'QT5' the problem becomes less severe with or without rounding. A summary of this is in this picture Colorbar overlap cases. Note that with not rounded and PyQT5 the problem still occurs, but is not as severe.

Answer 1

On inspection, it is clear that the colorbar is not only bleeding out over the top of its axes, but it's also positioned slightly to the left. So, the problem here appears to be a conflict between the position of the colorbar axis and the colorbar itself when rasterization occurs. You can find more details on this issue in matplotlib's github repository, but I'll summarize what's going on here.

Colorbars are rasterized when the output is produced, so as to avoid artifacting issues during rendering. The position of the colorbar is snapped to the nearest integer pixels during the rasterization process, while the axis is kept where it is supposed to be. Then, when the output is produced, the colorbar falls within borders of fixed pixels of the image, despite the fact that the image is, itself, vectorized. Thus, there are two strategies that can be employed to avoid this mishap.

Use a finer DPI

The conversion from vectorized coordinates to rasterized coordinates takes place assuming a given DPI on the image. By default, this is set to be 72. However, by using more DPI, the overall shift induced by the rasterization process will be smaller, as the closest pixel the colorbar will snap to will be much nearer. Here, we change the output to have fig.savefig(plot,dpi=4000), and the problem goes away: Note, however, that on my machine, the output size changed from 62 KB to 78 KB due to this change (although the DPI adjustment was also, admittedly, extreme). If you are worried about file sizes, you should pick a lower DPI that fixes the problem.

Use a different colormap

This rasterization happens when more than 50 colors are in the colorbar. Thus, we can do a quick test, setting our colormap to Pastel1 via im = ax2.pcolormesh(z,cmap='Pastel1'). Here, the colorbar / axis mismatch is mitigated.

As a fallback, adopting a colorbar with fewer than 50 colors should mitigate this problem.

Rasterize the Axis

For completeness, there is also a third option. If you rasterize the colorbar axis, both the axis boundaries and the colormap will be rasterized, and you'll lose the offset. This will also rasterize your labels, and the axis will shift as one, breaking alignment with the nearby axis. For this, you just need to include cbar_axis.set_rasterized(True).

Answer 2

First, a way to overlay a contour and a pcolormesh and create a colorbar would be the following

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np

x = np.linspace(0,5)
z = (np.outer(np.sin(x), np.cos(x))+1)*0.5

fig = plt.figure(figsize=(4, 4))
ax = fig.add_subplot(111)
im = ax.pcolormesh(z)
c  = ax.contour(z, linewidths=7)

divider = make_axes_locatable(ax)
cax = divider.append_axes("right", "5%", pad="3%")
colorbar = fig.colorbar(im, cax=cax, ticks = [0.1, .5, .9])

plt.show()

Now to the problem from the question. It is of course possible to create the axes to put the colorbar in manually. Replacing the colorbar creation with the code from the question still produces a nice image.

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0,5)
z = (np.outer(np.sin(x), np.cos(x))+1)*0.5

fig = plt.figure(figsize=(4, 4))
ax = fig.add_subplot(111)
plt.subplots_adjust(right=0.8)
im = ax.pcolormesh(z)
c  = ax.contour(z, linewidths=7)

ax2pos = ax.get_position()

cbar_axis = fig.add_axes([ax2pos.x1+0.05,ax2pos.y0, .05, ax2pos.height])
colorbar = fig.colorbar(im, ax = ax,
                    cax = cbar_axis, ticks = [0.1, .5, .9])
colorbar.outline.set_visible(True)
plt.show()

Conclusion so far: The issue is not reproducible, at least not without a Minimal, Complete, and Verifiable example.

---

I'm uncertain about the reasons for the behaviour in the example from the question. However, it seems that it can be overcome by rounding the figure size to 3 significant digits

matplotlib.rcParams['figure.figsize'] = (5.25, np.round(figheight,3))