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# Legend Demo

Plotting legends in Matplotlib.

There are many ways to create and customize legends in Matplotlib. Below we’ll show a few examples for how to do so.

First we’ll show off how to make a legend for specific lines.

    from __future__ import (absolute_import, division,
                            print_function, unicode_literals)

    import matplotlib.pyplot as plt
    import numpy as np
    from matplotlib.legend_handler import (HandlerLineCollection,
                                           HandlerTuple)
    import matplotlib.collections as mcol
    from matplotlib.lines import Line2D

    t1 = np.arange(0.0, 2.0, 0.1)
    t2 = np.arange(0.0, 2.0, 0.01)

    fig, ax = plt.subplots()

    # note that plot returns a list of lines.  The "l1, = plot" usage
    # extracts the first element of the list into l1 using tuple
    # unpacking.  So l1 is a Line2D instance, not a sequence of lines
    l1, = ax.plot(t2, np.exp(-t2))
    l2, l3 = ax.plot(t2, np.sin(2 * np.pi * t2), '--o', t1, np.log(1 + t1), '.')
    l4, = ax.plot(t2, np.exp(-t2) * np.sin(2 * np.pi * t2), 's-.')

    ax.legend((l2, l4), ('oscillatory', 'damped'), loc='upper right', shadow=True)
    ax.set_xlabel('time')
    ax.set_ylabel('volts')
    ax.set_title('Damped oscillation')
    plt.show()

Next we’ll demonstrate plotting more complex labels.

    x = np.linspace(0, 1)

    fig, (ax0, ax1) = plt.subplots(2, 1)

    # Plot the lines y=x**n for n=1..4.
    for n in range(1, 5):
        ax0.plot(x, x**n, label="n={0}".format(n))
    leg = ax0.legend(loc="upper left", bbox_to_anchor=[0, 1],
                     ncol=2, shadow=True, title="Legend", fancybox=True)
    leg.get_title().set_color("red")

    # Demonstrate some more complex labels.
    ax1.plot(x, x**2, label="multi\nline")
    half_pi = np.linspace(0, np.pi / 2)
    ax1.plot(np.sin(half_pi), np.cos(half_pi), label=r"$\frac{1}{2}\pi$")
    ax1.plot(x, 2**(x**2), label="$2^{x^2}$")
    ax1.legend(shadow=True, fancybox=True)

    plt.show()

Here we attach legends to more complex plots.

    fig, axes = plt.subplots(3, 1)
    top_ax, middle_ax, bottom_ax = axes

    top_ax.bar([0, 1, 2], [0.2, 0.3, 0.1], width=0.4, label="Bar 1",
               align="center")
    top_ax.bar([0.5, 1.5, 2.5], [0.3, 0.2, 0.2], color="red", width=0.4,
               label="Bar 2", align="center")
    top_ax.legend()

    middle_ax.errorbar([0, 1, 2], [2, 3, 1], xerr=0.4, fmt="s", label="test 1")
    middle_ax.errorbar([0, 1, 2], [3, 2, 4], yerr=0.3, fmt="o", label="test 2")
    middle_ax.errorbar([0, 1, 2], [1, 1, 3], xerr=0.4, yerr=0.3, fmt="^",
                       label="test 3")
    middle_ax.legend()

    bottom_ax.stem([0.3, 1.5, 2.7], [1, 3.6, 2.7], label="stem test")
    bottom_ax.legend()

    plt.subplots_adjust(hspace=0.7)
    plt.show()

Now we’ll showcase legend entries with more than one legend key.

    fig, (ax1, ax2) = plt.subplots(2, 1)

    # First plot: two legend keys for a single entry
    p1 = ax1.scatter([1], [5], c='r', marker='s', s=100)
    p2 = ax1.scatter([3], [2], c='b', marker='o', s=100)
    # `plot` returns a list, but we want the handle - thus the comma on the left
    p3, = ax1.plot([1, 5], [4, 4], 'm-d')

    # Assign two of the handles to the same legend entry by putting them in a tuple
    # and using a generic handler map (which would be used for any additional
    # tuples of handles like (p1, p3)).
    l = ax1.legend([(p1, p3), p2], ['two keys', 'one key'], scatterpoints=1,
                   numpoints=1, handler_map={tuple: HandlerTuple(ndivide=None)})

    # Second plot: plot two bar charts on top of each other and change the padding
    # between the legend keys
    x_left = [1, 2, 3]
    y_pos = [1, 3, 2]
    y_neg = [2, 1, 4]

    rneg = ax2.bar(x_left, y_neg, width=0.5, color='w', hatch='///', label='-1')
    rpos = ax2.bar(x_left, y_pos, width=0.5, color='k', label='+1')

    # Treat each legend entry differently by using specific `HandlerTuple`s
    l = ax2.legend([(rpos, rneg), (rneg, rpos)], ['pad!=0', 'pad=0'],
                   handler_map={(rpos, rneg): HandlerTuple(ndivide=None),
                                (rneg, rpos): HandlerTuple(ndivide=None, pad=0.)})

    plt.show()

Finally, it is also possible to write custom objects that define how to stylize legends.

    class HandlerDashedLines(HandlerLineCollection):
        """
        Custom Handler for LineCollection instances.
        """
        def create_artists(self, legend, orig_handle,
                           xdescent, ydescent, width, height, fontsize, trans):
            # figure out how many lines there are
            numlines = len(orig_handle.get_segments())
            xdata, xdata_marker = self.get_xdata(legend, xdescent, ydescent,
                                                 width, height, fontsize)
            leglines = []
            # divide the vertical space where the lines will go
            # into equal parts based on the number of lines
            ydata = ((height) / (numlines + 1)) * np.ones(xdata.shape, float)
            # for each line, create the line at the proper location
            # and set the dash pattern
            for i in range(numlines):
                legline = Line2D(xdata, ydata * (numlines - i) - ydescent)
                self.update_prop(legline, orig_handle, legend)
                # set color, dash pattern, and linewidth to that
                # of the lines in linecollection
                try:
                    color = orig_handle.get_colors()[i]
                except IndexError:
                    color = orig_handle.get_colors()[0]
                try:
                    dashes = orig_handle.get_dashes()[i]
                except IndexError:
                    dashes = orig_handle.get_dashes()[0]
                try:
                    lw = orig_handle.get_linewidths()[i]
                except IndexError:
                    lw = orig_handle.get_linewidths()[0]
                if dashes[0] is not None:
                    legline.set_dashes(dashes[1])
                legline.set_color(color)
                legline.set_transform(trans)
                legline.set_linewidth(lw)
                leglines.append(legline)
            return leglines

    x = np.linspace(0, 5, 100)

    fig, ax = plt.subplots()
    colors = plt.rcParams['axes.prop_cycle'].by_key()['color'][:5]
    styles = ['solid', 'dashed', 'dashed', 'dashed', 'solid']
    lines = []
    for i, color, style in zip(range(5), colors, styles):
        ax.plot(x, np.sin(x) - .1 * i, c=color, ls=style)

    # make proxy artists
    # make list of one line -- doesn't matter what the coordinates are
    line = [[(0, 0)]]
    # set up the proxy artist
    lc = mcol.LineCollection(5 * line, linestyles=styles, colors=colors)
    # create the legend
    ax.legend([lc], ['multi-line'], handler_map={type(lc): HandlerDashedLines()},
              handlelength=2.5, handleheight=3)

    plt.show()

Total running time of the script: ( 0 minutes 0.271 seconds)

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