Legenden-Demo

Plotten von Legenden in Matplotlib.

Es gibt viele Möglichkeiten, Legenden in Matplotlib zu erstellen und anzupassen. Im Folgenden zeigen wir einige Beispiele dafür, wie das geht.

Zuerst zeigen wir, wie man eine Legende für bestimmte Linien erstellt.

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

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()

Als Nächstes demonstrieren wir das Plotten komplexerer Beschriftungen.

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()

Hier fügen wir Legenden komplexeren Plots hinzu.

fig, axs = plt.subplots(3, 1, constrained_layout=True)
top_ax, middle_ax, bottom_ax = axs

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.show()

Jetzt zeigen wir Legendeneinträge mit mehr als einem Legendenschlüssel.

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

# 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()

Schließlich ist es auch möglich, benutzerdefinierte Objekte zu schreiben, die definieren, wie Legenden stilisiert werden.

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 = np.full_like(xdata, height / (numlines + 1))
        # 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[1] 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()