python - Matplotlib colorbar with fixed aspect ratio - Stack Overflow

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I have a grid (say 2x2) of subplots with constrained layout and I want to have a colorbar of the total height of the figure right next to it as follows:

fig, axes = plt.subplots(nrows=2,ncols=2,layout='constrained')

for ax in axes.flat:

    stuff = ax.pcolormesh(np.random.randn(20, 20), cmap='viridis')
    
#    ax.set_box_aspect(1/2)

fig1.colorbar(stuff,ax= axes.ravel().tolist())  # add a color legend

plt.show()

This looks fine and exactly how I want it. However, as soon as I uncomment the line where I set the (box) aspect, the colorbar is too high.

I tried different things like inset_axis which is suggested in the tutorial (.html#manual-placement-of-colorbars) but as I want the colorbar to extend over two axes, this doesn't work.

Any help?

I have a grid (say 2x2) of subplots with constrained layout and I want to have a colorbar of the total height of the figure right next to it as follows:

fig, axes = plt.subplots(nrows=2,ncols=2,layout='constrained')

for ax in axes.flat:

    stuff = ax.pcolormesh(np.random.randn(20, 20), cmap='viridis')
    
#    ax.set_box_aspect(1/2)

fig1.colorbar(stuff,ax= axes.ravel().tolist())  # add a color legend

plt.show()

This looks fine and exactly how I want it. However, as soon as I uncomment the line where I set the (box) aspect, the colorbar is too high.

I tried different things like inset_axis which is suggested in the tutorial (https://matplotlib.org/stable/users/explain/axes/colorbar_placement.html#manual-placement-of-colorbars) but as I want the colorbar to extend over two axes, this doesn't work.

Any help?

• python
• matplotlib
• colorbar

Share Improve this question Follow asked Nov 21, 2024 at 13:43 Eduard TetzlaffEduard Tetzlaff 4955 bronze badges 1

• Use layout="compressed" instead of "constrained". Compressed layout is a special case of constrained layout, designed specifically for fixed aspect ratio axes. – RuthC Commented Nov 21, 2024 at 16:43

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1 Answer 1

Sorted by: Reset to default 1

You can use ImageGrid from mpl_toolkits.axes_grid1

from mpl_toolkits.axes_grid1 import ImageGrid

I used random data:

# Example data
Z = np.random.rand(10, 10)
extent = (-10, 10, -10, 10)

# Define aspect ratio (width-to-height)
aspect_ratio = .5  # Width is twice the height

Create the figure

fig = plt.figure(figsize=(10, 8))  

# Create a 2x2 grid of images with a single colorbar on the right
grid = ImageGrid(
    fig, 111,  # Position in the figure
    nrows_ncols=(2, 2),  
    axes_pad=(0.1, 0.4),  
    label_mode="L",  
    share_all=True,  # Share axes limits
    cbar_location="right",  # Place the colorbar on the right
    cbar_mode="single",  # One colorbar for all plots
    cbar_size="3%",  # Slimmer colorbar
    cbar_pad=0.2,  # Padding between grid and colorbar
)

Add images to the grid and control the aspect ratio

for ax in grid:
    im = ax.imshow(Z, extent=extent, cmap="viridis", aspect=1/aspect_ratio)

Add the colorbar

grid.cbar_axes[0].colorbar(im)

Configure ticks and axes labels

for cax in grid.cbar_axes:
    cax.tick_params(labelright=True)  # Show ticks on the right
grid.axes_llc.set(xticks=[-10, 0, 10], yticks=[-10, 0, 10])

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