Python中的 Matplotlib.patches.ConnectionPatch 类

Matplotlib是Python中用于数组二维图的惊人可视化库。 Matplotlib 是一个基于 NumPy 数组构建的多平台数据可视化库，旨在与更广泛的 SciPy 堆栈配合使用。

matplotlib.patches.ConnectionPatch

matplotlib.patches.ConnectionPatch 是 matplotlib.patches.FancyArrowPatch 类的子类，用于制作两点之间的连接线。

Syntax: class matplotlib.patches.ConnectionPatch(xyA, xyB, coordsA, coordsB=None, axesA=None, axesB=None, arrowstyle=’-‘, arrow_transmuter=None, connectionstyle=’arc3’, connector=None, patchA=None, patchB=None, shrinkA=0.0, shrinkB=0.0, mutation_scale=10.0, mutation_aspect=None, clip_on=False, dpi_cor=1.0, **kwargs)

Parameters: 

• xyA: It is the start point of connecting line on x-y plot also called Point A.
• xyB: It is the start point of connecting line on x-y plot also called Point B.
• coordsA: Coordinate of point A.
• coordsB: Coordinate of point B.
• axesA: It is the start point of connecting axes on x-y plot.
• axesB: It is the end point of connecting axes on x-y plot.
• arrowstyle: It is used for styling the connection arrow. Its default type is ‘-‘.
• arrow_transmuter: It is used to ignore a connecting line.
• connectionstyle: It describes how posA and posB are connected. It can be an instance of the class ConnectionStyle or a string by the name of connectionstyle, it has optional comma-separated attributes. 
• connector: It is generally ignored and decides which connector to ignore.
• patchA: Used to add patches at point A.
• patchB: Used to add patches at point B
• shrinkA: Used to shrink the connector at point A.
• shrinkB: Used to shrink the connector at point B.
• mutation_scale: Value with which attributes of arrowstyle (e.g., head_length) gets scaled.
• mutation_aspect: The height of the rectangle will be squeezed by this value before the mutation and the mutated box will be stretched by the inverse of it.
• clip_on: Set whether the artist uses clipping.
• dpi_cor: dpi_cor is currently used for linewidth-related things and shrink factor. Mutation scale is affected by this. 
   

以下是有效的 Kwargs 密钥列表；

Key	Description
arrowstyle	the arrow style
connectionstyle	the connection style
relpos	default is (0.5, 0.5)
patchA	default is bounding box of the text
patchB	default is None
shrinkA	default is 2 points
shrinkB	default is 2 points
mutation_scale	default is text size (in points)
mutation_aspect	default is 1.
?	any key for matplotlib.patches.PathPatch

xyA 和 xyB 的坐标由字符串coordsA 和 coordsB 表示。

Property	Description
‘figure points’	points from the lower left corner of the figure
‘figure pixels’	pixels from the lower left corner of the figure
‘figure fraction’	0, 0 is lower left of figure and 1, 1 is upper right
‘axes points’	points from lower left corner of axes
‘axes pixels’	pixels from lower left corner of axes
‘axes fraction’	0, 0 is lower left of axes and 1, 1 is upper right
‘data’	use the coordinate system of the object being annotated (default)
‘offset points’	offset (in points) from the xy value
‘polar’	you can specify theta, r for the annotation, even in cartesian plots. Note that if you are using a polar axes, you do not need to specify polar for the coordinate system since that is the native “data” coordinate system.

示例 1：

Python3

from matplotlib.patches import ConnectionPatch
import matplotlib.pyplot as plt
 
fig, (ax1, ax2) = plt.subplots(1, 2,
                               figsize =(6, 3))
 
# Draw a simple arrow between
# two points in axes coordinates
# within a single axes.
xyA = (0.2, 0.2)
xyB = (0.8, 0.8)
coordsA = "data"
coordsB = "data"
con = ConnectionPatch(xyA, xyB,
                      coordsA, coordsB,
                      arrowstyle ="-|>",
                      shrinkA = 5, shrinkB = 5,
                      mutation_scale = 20,
                      fc ="w")
 
ax1.plot([xyA[0], xyB[0]], [xyA[1],
                            xyB[1]], "o")
ax1.add_artist(con)
 
# Draw an arrow between the
# same point in data coordinates,
# but in different axes.
xy = (0.3, 0.2)
con = ConnectionPatch(
    xyA = xy, coordsA = ax2.transData,
    xyB = xy, coordsB = ax1.transData,
    arrowstyle ="->", shrinkB = 5)
 
ax2.add_artist(con)
 
# Draw a line between the different
# points, defined in different coordinate
# systems.
con = ConnectionPatch(
    # in axes coordinates
    xyA =(0.6, 1.0), coordsA = ax2.transAxes,
    # x in axes coordinates, y in data coordinates
    xyB =(0.0, 0.2), coordsB = ax2.get_yaxis_transform(),
    arrowstyle ="-")
 
ax2.add_artist(con)
 
ax1.set_xlim(0, 1)
ax1.set_ylim(0, 1)
ax2.set_xlim(0, .5)
ax2.set_ylim(0, .5)
 
plt.show()

输出：

示例 2：

Python3

import matplotlib.pyplot as plt
from matplotlib.patches import ConnectionPatch
import numpy as np
 
 
# make figure and assign axis
# objects
fig = plt.figure(figsize =(9, 5))
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
fig.subplots_adjust(wspace = 0)
 
# pie chart parameters
ratios = [.27, .56, .17]
explode = [0.1, 0, 0]
 
# rotate so that first wedge is
# split by the x-axis
angle = -180 * ratios[0]
ax1.pie(ratios, autopct ='% 1.1f %%',
        startangle = angle,
        explode = explode)
 
# bar chart parameters
 
xpos = 0
bottom = 0
ratios = [.33, .54, .07, .06]
width = .2
colors = [[.1, .3, .5],
          [.1, .3, .3],
          [.1, .3, .7],
          [.1, .3, .9]]
 
for j in range(len(ratios)):
    height = ratios[j]
    ax2.bar(xpos, height, width,
            bottom = bottom,
            color = colors[j])
     
    ypos = bottom + ax2.patches[j].get_height() / 2
    bottom += height
    ax2.text(xpos,
             ypos,
             "% d %%" % (ax2.patches[j].get_height() * 100),
             ha ='center')
 
ax2.set_title('')
ax2.legend(('50-65', 'Over 65', '35-49', 'Under 35'))
ax2.axis('off')
ax2.set_xlim(- 2.5 * width, 2.5 * width)
 
# use ConnectionPatch to draw
# lines between the two plots
# get the wedge data
theta1, theta2 = ax1.patches[0].theta1, ax1.patches[0].theta2
center, r = ax1.patches[0].center, ax1.patches[0].r
bar_height = sum([item.get_height() for item in ax2.patches])
 
# draw top connecting line
x = r * np.cos(np.pi / 180 * theta2) + center[0]
y = np.sin(np.pi / 180 * theta2) + center[1]
con = ConnectionPatch(xyA =(-width / 2, bar_height),
                      coordsA = ax2.transData,
                      xyB =(x, y),
                      coordsB = ax1.transData)
 
con.set_color([0, 0, 0])
con.set_linewidth(4)
ax2.add_artist(con)
 
# draw bottom connecting line
x = r * np.cos(np.pi / 180 * theta1) + center[0]
y = np.sin(np.pi / 180 * theta1) + center[1]
 
con = ConnectionPatch(xyA =(-width / 2, 0),
                      coordsA = ax2.transData,
                      xyB =(x, y),
                      coordsB = ax1.transData)
 
con.set_color([0, 0, 0])
ax2.add_artist(con)
con.set_linewidth(4)
 
plt.show()

输出：