matplotlib

Question

我通常使用方法 'bar'.

中的参数 'label' 按以下方式为条形图制作标签

axes[0].bar(x, y, bar_width, label='abc')
axes[0].legend()

现在我想绘制小提琴图并为每个集合制作标签，如下所示，但它不起作用，因为 'violinplot' 没有参数 'label'.

axes[0].violinplot(data1, label='abc1')
axes[1].violinplot(data2, label='abc2')

谁能帮我为每个系列制作一个标签？

Answer 1

编辑：抱歉，我现在看到您想添加图例，而不是轴标签...

您可以手动设置刻度位置，然后覆盖它们的标签：

import numpy as np
import matplotlib.pyplot as pl

pos   = [1, 2, 4, 5, 7, 8]
label = ['abc','def','ghi','jkl','mno','pqr']
data  = [np.random.normal(size=100) for i in pos]

pl.figure()
ax = pl.subplot(111)
pl.violinplot(data, pos, vert=False)
ax.set_yticks(pos)
ax.set_yticklabels(label)

Answer 2

正如评论中提到的，matplotlib 中的某些绘图不支持图例。文档仍然提供了一种为它们添加自定义图例的简单方法：http://matplotlib.org/users/legend_guide.html#proxy-legend-handles

主要思想：添加'fake'个对象，可以不在图中显示，然后用它来形成图例方法的句柄列表。

    import random
    import numpy as np
    import matplotlib.pyplot as pl
    import matplotlib.patches as mpatches
    from itertools import repeat

    red_patch = mpatches.Patch(color='red')
    # 'fake' invisible object

    pos   = [1, 2, 4, 5, 7, 8]
    label = ['plot 1','plot2','ghi','jkl','mno','pqr']
    data  = [np.random.normal(size=100) for i in pos]

    fake_handles = repeat(red_patch, len(pos))

    pl.figure()
    ax = pl.subplot(111)
    pl.violinplot(data, pos, vert=False)
    ax.legend(fake_handles, label)
    pl.show()

Answer 3

这是我对多个小提琴图的解决方案。请注意，它从给定的小提琴图的第一个阴影区域获取补丁颜色——如果有多种颜色，这可以更改为执行其他操作，或者您可以使用 [=11= 获取垂直条的颜色].

import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import numpy as np

labels = []
def add_label(violin, label):
    color = violin["bodies"][0].get_facecolor().flatten()
    labels.append((mpatches.Patch(color=color), label))


positions = np.arange(3,13,3)
data = np.random.randn(1000, len(positions))
add_label(plt.violinplot(data, positions), "Flat")    

positions = np.arange(1, 10, 2)
data = np.random.randn(1000, len(positions)) + positions
add_label(plt.violinplot(data, positions), "Linear")

positions = np.arange(2, 11, 1)
data = np.random.randn(1000, len(positions)) + positions ** 2 / 4
add_label(plt.violinplot(data, positions), "Quadratic")

plt.legend(*zip(*labels), loc=2)

Answer 4

有一个比@Ian Hincks 代码更简单的解决方案，无需使用 mpatches

import matplotlib.pyplot as plt
import numpy as np

positions = np.arange(3,13,3)
data = np.random.randn(1000, len(positions))
vp1 = plt.violinplot(data, positions) 

positions = np.arange(1, 10, 2)
data = np.random.randn(1000, len(positions)) + positions
vp2 = plt.violinplot(data, positions)

positions = np.arange(2, 11, 1)
data = np.random.randn(1000, len(positions)) + positions ** 2 / 4
vp3 = plt.violinplot(data, positions)

plt.legend([vp1['bodies'][0],vp2['bodies'][0], vp3['bodies'][0]], ['flat', 'linear', 'quadratic'], loc=2)[enter image description here][1]

要使用线条而不是正文，请将 vp1['bodies'][0] 替换为 vp1['cbars']

演示：violin plot with labels

Answer 5

更简洁明了的解决方案可以是：

plt.style.use('seaborn')
import matplotlib.pyplot as plt
labels = ['df=9' , 'df=99', 'df=999', 'df=9999', 'N($\mu=0$, $\sigma=2)$']
colors = ['orange', 'lightblue', 'lightgreen', 'yellow', 'green']
def make_violinplot(x, labels, colors):
    parts = plt.violinplot(x, showmeans=True, showmedians=True)
    for body, color in zip(parts['bodies'],colors):
        body.set_facecolor(color)
        parts['cmeans'].set_color('red')
        parts['cmedians'].set_color('blue')
    plt.legend(label[enter image description here][1]s, loc='upper left')
    plt.xticks(np.arange(1, len(labels)+1), labels)
    plt.title("probability density plots t- vs normal distribution")
    plt.rcParams["figure.figsize"] = [8,8]
    return
make_violinplot(t_dists, labels, colors)

matplotlib - 为小提琴图制作标签

matplotlib - making labels for violin plots

python

label