Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
matplotlib.patches.ConnectionPatch
The matplotlib.patches.ConnectionPatch a subclass of matplotlib.patches.FancyArrowPatch class and are used for making connecting lines between two points.
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.
The below are list of valid Kwargs key;
| 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 |
The coordinates of xyA and xyB are indicated by a string coordsA and coordsB.
| 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. |
Example 1:
Python3
from matplotlib.patches import ConnectionPatchimport matplotlib.pyplot as pltfig, (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() |
Output:
Example 2:
Python3
import matplotlib.pyplot as pltfrom matplotlib.patches import ConnectionPatchimport numpy as np# make figure and assign axis # objectsfig = plt.figure(figsize =(9, 5))ax1 = fig.add_subplot(121)ax2 = fig.add_subplot(122)fig.subplots_adjust(wspace = 0)# pie chart parametersratios = [.27, .56, .17]explode = [0.1, 0, 0]# rotate so that first wedge is# split by the x-axisangle = -180 * ratios[0]ax1.pie(ratios, autopct ='% 1.1f %%', startangle = angle, explode = explode)# bar chart parametersxpos = 0bottom = 0ratios = [.33, .54, .07, .06]width = .2colors = [[.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 datatheta1, theta2 = ax1.patches[0].theta1, ax1.patches[0].theta2center, r = ax1.patches[0].center, ax1.patches[0].rbar_height = sum([item.get_height() for item in ax2.patches])# draw top connecting linex = 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 linex = 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() |
Output:
