.. _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.

.. plot::
   :include-source:
   :context:

   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.

.. plot::
   :include-source:
   :context:

   plt.tight_layout()

When you have multiple subplots, often you see labels of different
axes overlaps each other.

.. plot::
   :include-source:
   :context:

   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.

.. plot::
   :include-source:
   :context:

   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.

.. plot::
   :include-source:
   :context:

   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.


.. plot::
   :include-source:
   :context:

    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.

.. plot::
   :include-source:
   :context:

    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).


.. plot::
   :include-source:
   :context:

    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).

.. plot::
   :include-source:
   :context:

    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).

.. plot::
   :include-source:
   :context:

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


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

.. plot::
   :include-source:
   :context:

    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)
    

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.

.. plot::
   :include-source:
   :context:

   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.


.. plot::
   :include-source:
   :context:

    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. With Matplotlib v1.1, you may create a
colobar as a subplot using the gridspec.

.. plot::
   :include-source:
   :context:

   plt.close('all')
   fig = plt.figure(figsize=(4, 4))
   im = plt.imshow(arr, interpolation="none")

   plt.colorbar(im, use_gridspec=True)

   plt.tight_layout()

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

.. plot::
   :include-source:
   :context:

   plt.close('all')
   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()