Tight Layout guide

How to use tight-layout to fit plots within your figure cleanly.

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.

An alternative to tight_layout is constrained_layout.

Simple Example

In matplotlib, the location of axes (including subplots) are specified in
normalized figure coordinates. It can happen that your axis labels or
titles (or sometimes even ticklabels) go outside the figure area, and are thus
clipped.

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# sphinx_gallery_thumbnail_number = 7

import matplotlib.pyplot as plt
import numpy as np

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)

sphx_glr_tight_layout_guide_001

To prevent this, the location of axes needs to be adjusted. For
subplots, this can be done by adjusting the subplot params
(Move the edge of an axes to make room for tick labels). Matplotlib v1.1 introduces a new
command tight_layout() that does this
automatically for you.

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fig, ax = plt.subplots()
example_plot(ax, fontsize=24)
plt.tight_layout()

sphx_glr_tight_layout_guide_002

Note that matplotlib.pyplot.tight_layout() will only adjust the
subplot params when it is called. In order to perform this adjustment each
time the figure is redrawn, you can call fig.set_tight_layout(True), or,
equivalently, set the figure.autolayout rcParam to True.

When you have multiple subplots, often you see labels of different
axes overlapping 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)

sphx_glr_tight_layout_guide_003

tight_layout() will also adjust spacing between
subplots to minimize the overlaps.

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

sphx_glr_tight_layout_guide_004

tight_layout() can take keyword arguments of
pad, w_pad and h_pad. These control the extra padding around the
figure border and between subplots. The pads are specified in fraction
of fontsize.

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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)
example_plot(ax1)
example_plot(ax2)
example_plot(ax3)
example_plot(ax4)
plt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)

sphx_glr_tight_layout_guide_005

tight_layout() will work even if the sizes of
subplots are different as far as their grid specification is
compatible. In the example below, ax1 and ax2 are subplots of a 2x2
grid, while ax3 is of a 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()

sphx_glr_tight_layout_guide_006

It works with subplots created with
subplot2grid(). In general, subplots created
from the gridspec (Customizing Figure Layouts Using GridSpec and Other Functions) 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()

sphx_glr_tight_layout_guide_007

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()

sphx_glr_tight_layout_guide_008

Caveats

  • tight_layout() only considers ticklabels, axis
    labels, and titles. Thus, other artists 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 where 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 tight_layout() also works).

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import matplotlib.gridspec as gridspec

plt.close('all')
fig = plt.figure()

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)

sphx_glr_tight_layout_guide_009

You may provide an optional rect parameter, which specifies the bounding box
that the subplots will be fit inside. The coordinates must be in normalized
figure coordinates and the default is (0, 0, 1, 1).

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fig = plt.figure()

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, rect=[0, 0, 0.5, 1])

sphx_glr_tight_layout_guide_010

For example, this can be used for a figure with multiple gridspecs.

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fig = plt.figure()

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, rect=[0, 0, 0.5, 1])

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 ::
top = min(gs1.top, gs2.top)
bottom = max(gs1.bottom, gs2.bottom)

gs1.update(top=top, bottom=bottom)
gs2.update(top=top, bottom=bottom)
plt.show()

sphx_glr_tight_layout_guide_011

While this should be mostly good enough, adjusting top and bottom
may require adjustment of hspace also. To update hspace & vspace, we
call tight_layout() again with updated
rect argument. Note that the rect argument specifies the area including the
ticklabels, etc. Thus, we will increase the bottom (which is 0 for the normal
case) by the difference between the bottom from above and the bottom of each
gridspec. Same thing for the top.

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fig = plt.gcf()

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, rect=[0, 0, 0.5, 1])

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)

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

gs1.update(top=top, bottom=bottom)
gs2.update(top=top, bottom=bottom)

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)

sphx_glr_tight_layout_guide_012

Legends and Annotations

Pre Matplotlib 2.2, legends and annotations were excluded from the bounding
box calculations that decide the layout. Subsequently these artists were
added to the calculation, but sometimes it is undesirable to include them.
For instance in this case it might be good to have the axes shring a bit
to make room for the legend:

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fig, ax = plt.subplots(figsize=(4, 3))
lines = ax.plot(range(10), label='A simple plot')
ax.legend(bbox_to_anchor=(0.7, 0.5), loc='center left',)
fig.tight_layout()
plt.show()

sphx_glr_tight_layout_guide_013

However, sometimes this is not desired (quite often when using
fig.savefig('outname.png', bbox_inches='tight')). In order to
remove the legend from the bounding box calculation, we simply set its
bounding leg.set_in_layout(False) and the legend will be ignored.

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fig, ax = plt.subplots(figsize=(4, 3))
lines = ax.plot(range(10), label='B simple plot')
leg = ax.legend(bbox_to_anchor=(0.7, 0.5), loc='center left',)
leg.set_in_layout(False)
fig.tight_layout()
plt.show()

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Use with AxesGrid1

While limited, the axes_grid1 toolkit is also supported.

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from mpl_toolkits.axes_grid1 import Grid

plt.close('all')
fig = plt.figure()
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()

sphx_glr_tight_layout_guide_015

Colorbar

If you create a colorbar with the colorbar()
command, the created colorbar is an instance of Axes, not Subplot, so
tight_layout does not work. With Matplotlib v1.1, you may create a
colorbar as a subplot using the gridspec.

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plt.close('all')
arr = np.arange(100).reshape((10, 10))
fig = plt.figure(figsize=(4, 4))
im = plt.imshow(arr, interpolation="none")

plt.colorbar(im, use_gridspec=True)

plt.tight_layout()

sphx_glr_tight_layout_guide_016

Another option is to use AxesGrid1 toolkit to
explicitly create an axes for colorbar.

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from mpl_toolkits.axes_grid1 import make_axes_locatable

plt.close('all')
arr = np.arange(100).reshape((10, 10))
fig = plt.figure(figsize=(4, 4))
im = plt.imshow(arr, interpolation="none")

divider = make_axes_locatable(plt.gca())
cax = divider.append_axes("right", "5%", pad="3%")
plt.colorbar(im, cax=cax)

plt.tight_layout()

sphx_glr_tight_layout_guide_017

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