tight_layout_guide.rst

.. _plotting-guide-tight-layout:

Tight Layout guide

*tight_layout* automatically adjusts subplot params so that the

subplot(s) fits in to the figure area. This is an experimental

feature and may not work for some cases. It only checks the extents

of ticklabels, axis labels, and titles.

Simple Example

In matplotlib location of axes (including subplots) are specified in

normalized figure coordinate. It can happen that your axis labels or

titles (or sometimes even ticklabels) go outside the figure area thus

clipped.

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plt.rcParams['savefig.facecolor'] = "0.8"

def example_plot(ax, fontsize=12):

ax.plot([1, 2])

ax.locator_params(nbins=3)

ax.set_xlabel('x-label', fontsize=fontsize)

ax.set_ylabel('y-label', fontsize=fontsize)

ax.set_title('Title', fontsize=fontsize)

plt.close('all')

fig, ax = plt.subplots()

example_plot(ax, fontsize=24)

To prevent this, the location of axes need to be adjusted. For

subplots, this can be done by adjusting the subplot params

(:ref:`howto-subplots-adjust`). Matplotlib v1.1 introduces a new

command :func:`~matplotlib.pyplot.tight_layout` that does this

automatically for you.

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plt.tight_layout()

When you have multiple subplots, often you see labels of different

axes overlaps each other.

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plt.close('all')

fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)

example_plot(ax1)

example_plot(ax2)

example_plot(ax3)

example_plot(ax4)

*tight_layout* will also adjust spacing betweens subplots to minimize

the overlaps.

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plt.tight_layout()

:func:`~matplotlib.pyplot.tight_layout` can take keyword arguments of

*pad*, *w_pad* and *h_pad*. These controls the extra pad around the

figure border and between subplots. The pads are specified in fraction

of fontsize.

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plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)

:func:`~matplotlib.pyplot.tight_layout` will work even if the sizes of

subplot are different as far as their grid specification is

compatible. In the example below, *ax1* and *ax2* are subplots of 2x2

grid, while *ax3* is of 1x2 grid.

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plt.close('all')

fig = plt.figure()

ax1 = plt.subplot(221)

ax2 = plt.subplot(223)

ax3 = plt.subplot(122)

example_plot(ax1)

example_plot(ax2)

example_plot(ax3)

plt.tight_layout()

It works with subplots created with

:func:`~matplotlib.pyplot.subplot2grid`. In general, subplots created

from the gridspec (:ref:`gridspec-guide`) will work.

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plt.close('all')

fig = plt.figure()

ax1 = plt.subplot2grid((3, 3), (0, 0))

ax2 = plt.subplot2grid((3, 3), (0, 1), colspan=2)

ax3 = plt.subplot2grid((3, 3), (1, 0), colspan=2, rowspan=2)

ax4 = plt.subplot2grid((3, 3), (1, 2), rowspan=2)

example_plot(ax1)

example_plot(ax2)

example_plot(ax3)

example_plot(ax4)

plt.tight_layout()

Although not thoroughly tested, it seems to work for subplots with

aspect != "auto" (e.g., axes with images).

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arr = np.arange(100).reshape((10,10))

plt.close('all')

fig = plt.figure(figsize=(5,4))

ax = plt.subplot(111)

im = ax.imshow(arr, interpolation="none")

plt.tight_layout()

Caveats

* *tight_layout* only considers ticklabels, axis labels, and titles. Thus, other atists may be clipped and also may overlap.

* It assumes that the extra space needed for ticklabels, axis labels,

and titles is independent of original location of axes. This is

often True, but there are rare cases it is not.

* pad=0 clips some of the texts by a few pixels. This may be a bug or

a limitation of the current algorithm and it is not clear why it

happens. Meanwhile, use of pad at least larger than 0.3 is

recommended.

Use with GridSpec

GridSpec has its own tight_layout method

(the pyplot api :func:`~matplotlib.pyplot.tight_layout` also works).

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plt.close('all')

fig = plt.figure()

import matplotlib.gridspec as gridspec

gs1 = gridspec.GridSpec(2, 1)

ax1 = fig.add_subplot(gs1[0])

ax2 = fig.add_subplot(gs1[1])

example_plot(ax1)

example_plot(ax2)

gs1.tight_layout(fig)

You may provide an optional *rect* parameter, which specify the bbox

that the subplots will be fit in. The coordinate must be in normalized

figure coordinate and the default is (0, 0, 1, 1).

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gs1.tight_layout(fig, rect=[0, 0, 0.5, 1])

For example, this can be used for a figure with multiple grid_spec's.

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gs2 = gridspec.GridSpec(3, 1)

for ss in gs2:

ax = fig.add_subplot(ss)

example_plot(ax)

ax.set_title("")

ax.set_xlabel("")

ax.set_xlabel("x-label", fontsize=12)

gs2.tight_layout(fig, rect=[0.5, 0, 1, 1], h_pad=0.5)

We may try to match the top and bottom of two grids ::

While this should be mostly good enough, but adjusting top and bottom

may requires adjustment in hspace also. To update hspace & vspace, we

call tight_layout again with updated rect argument. Note the rect

argument specifies area including the ticklabels etc. Thus we will

increase the bottom (which is 0 in normal case) by the difference

between the *bottom* from above and bottom of each gridspec. Same

thing for top.

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top = min(gs1.top, gs2.top)

bottom = max(gs1.bottom, gs2.bottom)

gs1.tight_layout(fig, rect=[None, 0 + (bottom-gs1.bottom),

0.5, 1 - (gs1.top-top)])

gs2.tight_layout(fig, rect=[0.5, 0 + (bottom-gs2.bottom),

None, 1 - (gs2.top-top)],

h_pad=0.5)

Use with AxesGrid1

While limited, axes_grid1 toolkit is also supported.

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plt.close('all')

fig = plt.figure()

from mpl_toolkits.axes_grid1 import Grid

grid = Grid(fig, rect=111, nrows_ncols=(2,2),

axes_pad=0.25, label_mode='L',

)

for ax in grid:

example_plot(ax)

ax.title.set_visible(False)

plt.tight_layout()

Colorbar

If you create colorbar with :func:`~matplotlib.pyplot.colorbar`

command, the created colorbar is an instance of Axes not Subplot, thus

tight_layout does not work. One option is to use AxesGrid1 toolkit to explicitly create an axes for colorbar.

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plt.close('all')

fig = plt.figure(figsize=(4, 4))

ax = plt.subplot(111)

im = plt.imshow(arr, interpolation="none")

from mpl_toolkits.axes_grid1 import make_axes_locatable

divider = make_axes_locatable(ax)

cax = divider.append_axes("right", "5%", pad="3%")

plt.colorbar(im, cax=cax)

plt.tight_layout()