Matplotlib 重叠注释 [英] Matplotlib overlapping annotations

问题描述

我想用一些文本注释图形中的条形，但如果条形靠得很近并且具有相当的高度，则注释高于 ea.其他因此难以阅读(注释的坐标取自条形位置和高度).

I want to annotate the bars in a graph with some text but if the bars are close together and have comparable height, the annotations are above ea. other and thus hard to read (the coordinates for the annotations were taken from the bar position and height).

如果发生碰撞，有没有办法移动其中一个?

Is there a way to shift one of them if there is a collision?

条形图有时非常细且非常靠近，因此仅垂直对齐并不能解决问题...

The bars are very thin and very close sometimes so just aligning vertically doesn't solve the problem...

一张图片可能会澄清一些事情:

A picture might clarify things:

推荐答案

我编写了一个快速解决方案，它根据所有其他注释的默认边界框检查每个注释位置.如果发生碰撞，它会将其位置更改为下一个可用的无碰撞位置.它还带有漂亮的箭头.

I've written a quick solution, which checks each annotation position against default bounding boxes for all the other annotations. If there is a collision it changes its position to the next available collision free place. It also puts in nice arrows.

对于一个相当极端的例子，它会产生这个(没有一个数字重叠):

For a fairly extreme example, it will produce this (none of the numbers overlap):

而不是这个:

代码如下:

import numpy as np
import matplotlib.pyplot as plt
from numpy.random import *

def get_text_positions(x_data, y_data, txt_width, txt_height):
    a = zip(y_data, x_data)
    text_positions = y_data.copy()
    for index, (y, x) in enumerate(a):
        local_text_positions = [i for i in a if i[0] > (y - txt_height) 
                            and (abs(i[1] - x) < txt_width * 2) and i != (y,x)]
        if local_text_positions:
            sorted_ltp = sorted(local_text_positions)
            if abs(sorted_ltp[0][0] - y) < txt_height: #True == collision
                differ = np.diff(sorted_ltp, axis=0)
                a[index] = (sorted_ltp[-1][0] + txt_height, a[index][1])
                text_positions[index] = sorted_ltp[-1][0] + txt_height
                for k, (j, m) in enumerate(differ):
                    #j is the vertical distance between words
                    if j > txt_height * 2: #if True then room to fit a word in
                        a[index] = (sorted_ltp[k][0] + txt_height, a[index][1])
                        text_positions[index] = sorted_ltp[k][0] + txt_height
                        break
    return text_positions

def text_plotter(x_data, y_data, text_positions, axis,txt_width,txt_height):
    for x,y,t in zip(x_data, y_data, text_positions):
        axis.text(x - txt_width, 1.01*t, '%d'%int(y),rotation=0, color='blue')
        if y != t:
            axis.arrow(x, t,0,y-t, color='red',alpha=0.3, width=txt_width*0.1, 
                       head_width=txt_width, head_length=txt_height*0.5, 
                       zorder=0,length_includes_head=True)

这是产生这些图的代码，显示了用法:

Here is the code producing these plots, showing the usage:

#random test data:
x_data = random_sample(100)
y_data = random_integers(10,50,(100))

#GOOD PLOT:
fig2 = plt.figure()
ax2 = fig2.add_subplot(111)
ax2.bar(x_data, y_data,width=0.00001)
#set the bbox for the text. Increase txt_width for wider text.
txt_height = 0.04*(plt.ylim()[1] - plt.ylim()[0])
txt_width = 0.02*(plt.xlim()[1] - plt.xlim()[0])
#Get the corrected text positions, then write the text.
text_positions = get_text_positions(x_data, y_data, txt_width, txt_height)
text_plotter(x_data, y_data, text_positions, ax2, txt_width, txt_height)

plt.ylim(0,max(text_positions)+2*txt_height)
plt.xlim(-0.1,1.1)

#BAD PLOT:
fig = plt.figure()
ax = fig.add_subplot(111)
ax.bar(x_data, y_data, width=0.0001)
#write the text:
for x,y in zip(x_data, y_data):
    ax.text(x - txt_width, 1.01*y, '%d'%int(y),rotation=0)
plt.ylim(0,max(text_positions)+2*txt_height)
plt.xlim(-0.1,1.1)

plt.show()

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