>>> """
==================================
Scatter Histogram (Locatable Axes)
==================================

Show the marginal distributions of a scatter as histograms at the sides of
the plot.

For a nice alignment of the main axes with the marginals, the axes positions
are defined by a ``Divider``, produced via `.make_axes_locatable`.

An alternative method to produce a similar figure is shown in the
:doc:`/gallery/lines_bars_and_markers/scatter_hist` example. The advantage of
the locatable axes method shown below is that the marginal axes follow the
fixed aspect ratio of the main axes.
"""
... 
... import numpy as np
... import matplotlib.pyplot as plt
... from mpl_toolkits.axes_grid1 import make_axes_locatable
... 
... # Fixing random state for reproducibility
... np.random.seed(19680801)
... 
... # the random data
... x = np.random.randn(1000)
... y = np.random.randn(1000)
... 
... 
... fig, ax = plt.subplots(figsize=(5.5, 5.5))
... 
... # the scatter plot:
... ax.scatter(x, y)
... 
... # Set aspect of the main axes.
... ax.set_aspect(1.)
... 
... # create new axes on the right and on the top of the current axes
... divider = make_axes_locatable(ax)
... # below height and pad are in inches
... ax_histx = divider.append_axes("top", 1.2, pad=0.1, sharex=ax)
... ax_histy = divider.append_axes("right", 1.2, pad=0.1, sharey=ax)
... 
... # make some labels invisible
... ax_histx.xaxis.set_tick_params(labelbottom=False)
... ax_histy.yaxis.set_tick_params(labelleft=False)
... 
... # now determine nice limits by hand:
... binwidth = 0.25
... xymax = max(np.max(np.abs(x)), np.max(np.abs(y)))
... lim = (int(xymax/binwidth) + 1)*binwidth
... 
... bins = np.arange(-lim, lim + binwidth, binwidth)
... ax_histx.hist(x, bins=bins)
... ax_histy.hist(y, bins=bins, orientation='horizontal')
... 
... # the xaxis of ax_histx and yaxis of ax_histy are shared with ax,
... # thus there is no need to manually adjust the xlim and ylim of these
... # axis.
... 
... ax_histx.set_yticks([0, 50, 100])
... ax_histy.set_xticks([0, 50, 100])
... 
... plt.show()
... 
... #############################################################################
... #
... # .. admonition:: References
... #
... #    The use of the following functions, methods, classes and modules is shown
... #    in this example:
... #
... #    - `mpl_toolkits.axes_grid1.axes_divider.make_axes_locatable`
... #    - `matplotlib.axes.Axes.set_aspect`
... #    - `matplotlib.axes.Axes.scatter`
... #    - `matplotlib.axes.Axes.hist`
...