Dense Layout Guidelines
original: Tight Layout guide Translator: flying dragon protocol: CC BY-NC-SA 4.0
tight_layout will automatically adjust the parameters of the subimage to fill the entire image area. This is an experimental feature and may not work in some cases. It only checks the axis labels, tick labels and title parts.
simple example
In matplotlib, the location of axes (including subplots) is specified in normalized figure coordinates. What can happen is that your axis labels or titles (and sometimes even tick labels) will extend beyond the graph area and thus get cut off.
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 avoid it, the position of the axes needs to be adjusted. For subgraphs, this can be done by adjusting the subgraph parameters ( Move one side of the axes to make room for the tick labels ). Matplotlib v1.1 introduced a new command, tight_layout(), which automatically takes care of this for you.
copyplt.tight_layout()
When you have multiple subplots, you will often see labels for different axes stacked together.
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() also adjusts the spacing between subplots to reduce stacking.
tight_layout() can accept keyword arguments pad , w_pad , or h_pad which are extra margins between image borders and subplots. Margins are specified in font size units.
copyplt.tight_layout(pad=0.4, w_pad=0.5, h_pad=1.0)
tight_layout() will work even if the subplots are of different sizes, as long as the grid specifications are compatible. In the example below, ax1 and ax2 are subplots of a 2x2 grid, but ax3 is a 1x2 grid.
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 for subplots created with subplot2grid(). In general, from the gridspec ( Use GridSpec to customize the position of sub-layouts ) also works fine.
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 looks like it also works for subplots with aspect not auto (e.g. axes with images).
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()
warn
- tight_layout() only considers tick labels, axis labels and titles. Therefore, other artists may be truncated and overlapped as well.
- It assumes that the extra space required for tick labels, axis labels and titles has nothing to do with the original position of the axes. This is usually true, but not in rare cases.
- pad=0 cuts some text by a few pixels. This may be a bug or limitation of the current algorithm, and it's not clear why it happens. Also, an interval greater than at least 0.3 is recommended.
Used with GridSpec
GridSpec has its own tight_layout() method (tight_layout() of the pyplot API also works).
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 can provide an optional rect parameter specifying the bounding box to be filled by the subplot. The coordinates must be normalized graphics coordinates, the default value is (0, 0, 1, 1).
copygs1.tight_layout(fig, rect=[0, 0, 0.5, 1])
For example, this can be used for graphs with multiple gridspecs.
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 can try to match the top and bottom of the two grids.
copytop = min(gs1.top, gs2.top) bottom = max(gs1.bottom, gs2.bottom) gs1.update(top=top, bottom=bottom) gs2.update(top=top, bottom=bottom)
While this should be good enough, adjusting the top and bottom may require adjusting the hspace as well. To update hspace and vspace, we call tight_layout() again with the updated rect parameter. Note that the area specified by the rect parameter includes the tick labels. So we increment the bottom (normally 0) by the difference between the bottom of each gridspec. Same goes for the top.
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)
Used with AxesGrid1
Although limited, the axes_grid1 toolkit is also supported
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()
color bar
If you create a colorbar using the colorbar command, the created colorbar is an instance of Axes instead of Subplot, so tight_layout has no effect. In Matplotlib v1.1 you can use gridspec to create colorbars as subplots.
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()![])http://matplotlib.org/_images/tight_layout_guide-14.png
Another option is to explicitly create an axes for the colorbar, using the AxesGrid1 toolkit:
plt.close('all')
arr = np.arange(100).reshape((10,10))
fig = plt.figure(figsize=(4, 4))
im = plt.imshow(arr, interpolation="none")
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(plt.gca())
cax = divider.append_axes("right", "5%", pad="3%")
plt.colorbar(im, cax=cax)
plt.tight_layout()