pyplot中所有子图的一个图例 [英] One legend for all subplots in pyplot

问题描述

我目前正在绘制相同的数据，但在两个子图中以不同的方式可视化它们(见图):

I am currently plotting the same data but visualizing it differently in two subplots (see figure):

用于生成上图的代码段:

Code snippet used for producing the above figure:

# Figure
plt.figure(figsize=(14,8), dpi=72)
plt.gcf().suptitle(r'Difference between TI and $\lambda$D', size=16)
# Subplot 1
ax1 = plt.subplot2grid((1,3),(0,0),colspan=2)

# Plot scattered data in first subplot
plt.scatter(LE_x, LE_y, s=40, lw=0, color='gold', marker='o', label=r'$\lambda$D')
plt.scatter(MD_x, MD_y, s=40, lw=0, color='blue', marker='^', label=r'TI')

# Subplot 2
ax2 = plt.subplot2grid((1,3),(0,2))

plt.barh(vpos1, LE_hist, height=4, color='gold', label=r'$\lambda$D')
plt.barh(vpos2, MD_hist, height=4, color='blue', label=r'TI')

# Legend
legend = plt.legend()

有什么方法可以使图例同时显示散点和条形?是否也可以按照此处中所述的方法来进行虚拟操作?然后有人可以为此发布一个最小的工作示例，因为我无法解决这个问题.

Is there any way to make the legend show both the scatter dots and the bars? Would this also go per dummy as described here? Could somebody then please post a minimal working example for this, since I'm not able to wrap my head around this.

推荐答案

这对我有用，您基本上可以捕获绘制的每个图形的补丁句柄并在末尾手动创建图例.

This worked for me, you essentially capture the patch handles for each graph plotted and manually create a legend at the end.

import pylab as plt
import numpy as NP

plt.figure(figsize=(14,8), dpi=72)
plt.gcf().suptitle(r'Difference between TI and $\lambda$D', size=16)
# Subplot 1
ax1 = plt.subplot2grid((1,3),(0,0),colspan=2)
N = 100
LE_x = NP.random.rand(N)
LE_y = NP.random.rand(N)
MD_x = NP.random.rand(N)
MD_y = NP.random.rand(N)

# Plot scattered data in first subplot
s1 = plt.scatter(LE_x, LE_y, s=40, lw=0, color='gold', marker='o', label=r'$\lambda$D')
s2 = plt.scatter(MD_x, MD_y, s=40, lw=0, color='blue', marker='^', label=r'TI')

data = NP.random.randn(1000)
LE_hist, bins2 = NP.histogram(data, 50)

data = NP.random.randn(1000)
MD_hist, bins2 = NP.histogram(data, 50)
# Subplot 2
ax2 = plt.subplot2grid((1,3),(0,2))
vpos1 = NP.arange(0, len(LE_hist))
vpos2 = NP.arange(0, len(MD_hist)) + 0.5
h1 = plt.barh(vpos1, LE_hist, height=0.5, color='gold', label=r'$\lambda$D')
h2 = plt.barh(vpos2, MD_hist, height=0.5, color='blue', label=r'TI')

# Legend
#legend = plt.legend()
lgd = plt.legend((s1, s2, h1, h2), (r'$\lambda$D', r'TI', r'$\lambda$D', r'TI'), loc='upper center')
plt.show()

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