如何在matplotlib中移动刻度线的标签? [英] How to move a tick's label in matplotlib?

问题描述

我想沿x轴水平移动刻度线的标签，而不移动相应的刻度线.

I would like to move some ticks' labels horizontally along the x-axis, without moving the corresponding ticks.

更具体地说，当使用plt.setp旋转标签时，标签文本的中心与刻度线保持对齐.我想将这些标签向右移动，以使标签的近端对齐，而不是如下图所示.

More specifically, when rotating labels with plt.setp, the centers of the labels' text stay aligned with the ticks. I would like to shift those labels to the right, so that the near ends of the labels get aligned instead as suggested on the image below.

我知道这篇文章和

I am aware of this post and this one, however the answers are interesting kludges rather than strict answers to the question.

我的代码:

import matplotlib.pyplot as plt
import numpy as np
import datetime

# my fake data
dates = np.array([datetime.datetime(2000,1,1) + datetime.timedelta(days=i) for i in range(365*5)])
data = np.sin(np.arange(365*5)/365.0*2*np.pi - 0.25*np.pi) + np.random.rand(365*5) /3

# creates fig with 2 subplots
fig = plt.figure(figsize=(10.0, 6.0))
ax = plt.subplot2grid((2,1), (0, 0))
ax2 = plt.subplot2grid((2,1), (1, 0))
## plot dates
ax2.plot_date( dates, data )

# rotates labels 
plt.setp( ax2.xaxis.get_majorticklabels(), rotation=-45 ) 

# try to shift labels to the right
ax2.xaxis.get_majorticklabels()[2].set_y(-.1)
ax2.xaxis.get_majorticklabels()[2].set_x(10**99)

plt.show()

奇怪的是，set_y的行为符合预期，但是即使我将x设置为幻想，标签也不会移动一个iota. (使用plot_date可能会引起更多的混乱，但实际上plot也会发生同样的情况.)

Strangely enough, set_y behaves as expected, but even if I set x to a fantasillion, the labels would not move by one iota. (The use of plot_date may introduce additional confusion, but the same actually happens with plot.)

推荐答案

首先，让我们使用mcve来显示问题.

First of all, let's use a mcve to show the problem.

import numpy as np
import datetime
import matplotlib.pyplot as plt
plt.rcParams["date.autoformatter.month"] = "%b %Y"

# my fake data
dates = np.array([datetime.datetime(2000,1,1) + datetime.timedelta(days=i) for i in range(365)])
data = np.sin(np.arange(365)/365.0*2*np.pi - 0.25*np.pi) + np.random.rand(365) /3

# creates fig with 2 subplots
fig, ax = plt.subplots(figsize=(6,2))
## plot dates
ax.plot_date( dates, data )

# rotates labels 
plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45 ) 

plt.tight_layout()
plt.show()

现在，正如其他答复所指出的那样，您可以使用文本的水平对齐方式.

Now as other anwers pointed out already, you may use horizontal alignment of the text.

# rotates labels and aligns them horizontally to left 
plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45, ha="left" )

您可以使用rotation_mode参数让旋转在文本的左上角发生，在这种情况下，结果会更好一些.

You may use the rotation_mode argument to let the rotation happen about the top left point of the text, giving a slightly nicer result in this case.

# rotates labels and aligns them horizontally to left 
plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45, ha="left", rotation_mode="anchor") 

如果这些选项的粒度不够细，即您想更准确地放置标签，例如将其向一侧移动一些点，您可以使用变换.以下将使用matplotlib.transforms.ScaledTranslation在水平方向上将标签偏移5个点.

In case those options are not fine grained enough, i.e. you want to position the labels more accurately, e.g. shifting it to the side by some points, you may use a transform. The following would offset the label by 5 points in horizontal direction, using a matplotlib.transforms.ScaledTranslation.

import matplotlib.transforms

plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45) 

# Create offset transform by 5 points in x direction
dx = 5/72.; dy = 0/72. 
offset = matplotlib.transforms.ScaledTranslation(dx, dy, fig.dpi_scale_trans)

# apply offset transform to all x ticklabels.
for label in ax.xaxis.get_majorticklabels():
    label.set_transform(label.get_transform() + offset)

与例如@explorerDude提供的解决方案是，偏移量独立于图形中的数据，因此它通常适用于任何绘图，并且对于给定的字体大小，其外观将相同.

The advantage of this, compared to e.g. the solution provided by @explorerDude is that the offset is independent on the data in the graph, such that it is generally applicable to any plot and would look the same for a given fontsize.

这篇关于如何在matplotlib中移动刻度线的标签?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！