pyplot在图例中组合了多个线条标签

Question

我有数据导致多行被绘制,我想在我的图例中为这些行添加一个标签.我认为使用下面的例子可以更好地证明这一点,

a = np.array([[ 3.57,  1.76,  7.42,  6.52],
              [ 1.57,  1.2 ,  3.02,  6.88],
              [ 2.23,  4.86,  5.12,  2.81],
              [ 4.48,  1.38,  2.14,  0.86],
              [ 6.68,  1.72,  8.56,  3.23]])

plt.plot(a[:,::2].T, a[:, 1::2].T, 'r', label='data_a')

plt.legend(loc='best')

正如您在Out [23]中看到的那样,该情节产生了5条不同的线条.结果情节看起来像这样

有什么方法可以告诉绘图方法避免多个标签？我不想使用自定义图例(您可以同时指定标签和线条形状)尽可能多.

Answer 1

如果我打算经常这样做,我会亲自制作一个小帮手功能;

from matplotlib import pyplot
import numpy


a = numpy.array([[ 3.57,  1.76,  7.42,  6.52],
                 [ 1.57,  1.2 ,  3.02,  6.88],
                 [ 2.23,  4.86,  5.12,  2.81],
                 [ 4.48,  1.38,  2.14,  0.86],
                 [ 6.68,  1.72,  8.56,  3.23]])


def plotCollection(ax, xs, ys, *args, **kwargs):

  ax.plot(xs,ys, *args, **kwargs)

  if "label" in kwargs.keys():

    #remove duplicates
    handles, labels = pyplot.gca().get_legend_handles_labels()
    newLabels, newHandles = [], []
    for handle, label in zip(handles, labels):
      if label not in newLabels:
        newLabels.append(label)
        newHandles.append(handle)

    pyplot.legend(newHandles, newLabels)

ax = pyplot.subplot(1,1,1)  
plotCollection(ax, a[:,::2].T, a[:, 1::2].T, 'r', label='data_a')
plotCollection(ax, a[:,1::2].T, a[:, ::2].T, 'b', label='data_b')
pyplot.show()

从图例handles和labels图例中删除重复项(比您拥有的)更简单(和IMO更清晰)的方法是:

handles, labels = pyplot.gca().get_legend_handles_labels()
newLabels, newHandles = [], []
for handle, label in zip(handles, labels):
  if label not in newLabels:
    newLabels.append(label)
    newHandles.append(handle)
pyplot.legend(newHandles, newLabels)

Answer 2

Numpy解决方案基于上面的will的回应.

import numpy as np
import matplotlib.pylab as plt
a = np.array([[3.57, 1.76, 7.42, 6.52],
              [1.57, 1.20, 3.02, 6.88],
              [2.23, 4.86, 5.12, 2.81],
              [4.48, 1.38, 2.14, 0.86],
              [6.68, 1.72, 8.56, 3.23]])

plt.plot(a[:,::2].T, a[:, 1::2].T, 'r', label='data_a')
handles, labels = plt.gca().get_legend_handles_labels()

假设相等标签具有相同的句柄,获得唯一标签及其各自的索引,这些索引对应于句柄索引.

labels, ids = np.unique(labels, return_index=True)
handles = [handles[i] for i in ids]
plt.legend(handles, labels, loc='best')
plt.show()

Answer 3

所以在这里使用will的建议和另一个问题,我在这里留下我的补救措施

handles, labels = plt.gca().get_legend_handles_labels()
i =1
while i<len(labels):
    if labels[i] in labels[:i]:
        del(labels[i])
        del(handles[i])
    else:
        i +=1

plt.legend(handles, labels)

而新的情节看起来像,

Answer 4

Matplotlib给你一个很好的接口线,集合LineCollection.代码很简单

import numpy
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

a = numpy.array([[ 3.57,  1.76,  7.42,  6.52],
                 [ 1.57,  1.2 ,  3.02,  6.88],
                 [ 2.23,  4.86,  5.12,  2.81],
                 [ 4.48,  1.38,  2.14,  0.86],
                 [ 6.68,  1.72,  8.56,  3.23]])

xs = a[:,::2]
ys = a[:, 1::2]
lines = LineCollection([list(zip(x,y)) for x,y in zip(xs, ys)], label='data_a')
f, ax = plt.subplots(1, 1)
ax.add_collection(lines)
ax.legend()
ax.set_xlim([xs.min(), xs.max()]) # have to set manually
ax.set_ylim([ys.min(), ys.max()])
plt.show()

这导致以下输出:

Answer 5

一个低技术的解决方案是进行两次绘图调用。一个绘制您的数据，另一个只绘制句柄：

a = np.array([[ 3.57,  1.76,  7.42,  6.52],
              [ 1.57,  1.2 ,  3.02,  6.88],
              [ 2.23,  4.86,  5.12,  2.81],
              [ 4.48,  1.38,  2.14,  0.86],
              [ 6.68,  1.72,  8.56,  3.23]])

plt.plot(a[:,::2].T, a[:, 1::2].T, 'r')
plt.plot([],[], 'r', label='data_a')

plt.legend(loc='best')

结果如下：