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Python Matplotlib.patches.ConnectionPatch用法及代碼示例

Matplotlib是Python中令人驚歎的可視化庫,用於數組的二維圖。 Matplotlib是一個基於NumPy數組的多平台數據可視化庫,旨在與更廣泛的SciPy堆棧配合使用。

matplottlib.patches.ConnectionPatch

這個matplottlib.patches.ConnectionPatch 的子類matplotlib.patches.FancyArrowPatch類,用於在兩點之間建立連接線。

用法: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)

參數:

  • xyA:它是x-y圖上也稱為點A的連接線的起點。
  • xyB:它是x-y圖上連接線的起點,也稱為點B。
  • coordsA:A點的坐標。
  • coordsB:B點的坐標。
  • axesA:它是x-y圖上連接軸的起點。
  • axesB:它是x-y圖上連接軸的終點。
  • arrowstyle:用於設置連接箭頭的樣式。其默認類型為“-”。
  • arrow_transmuter:用於忽略連接線。
  • connectionstyle:它描述了posA和posB的連接方式。它可以是ConnectionStyle類的實例,也可以是connectionstyle名稱的字符串,它具有可選的逗號分隔屬性。
  • connector:通常忽略它,並決定忽略哪個連接器。
  • patchA:用於在A點添加補丁。
  • patchB:用於在B點添加補丁
  • shrinkA:用於在A點收縮連接器。
  • shrinkB:用於在B點收縮連接器。
  • mutation_scale:箭頭樣式的屬性(例如head_length)的縮放比例值。
  • mutation_aspect:變異前,矩形的高度將被該值擠壓,變異框將被其倒數拉伸。
  • clip_on:設置藝術家是否使用剪輯。
  • dpi_cor:dpi_cor當前用於linewidth-related事物和收縮因子。突變規模受此影響。

以下是有效的Kwargs key 列表;



鑰匙 描述
arrowstyle 箭頭樣式
connectionstyle 連接方式
relpos 默認值為(0.5,0.5)
patchA 默認為文本的邊框
patchB 默認為無
shrinkA 默認為2分
shrinkB 默認為2分
mutation_scale 默認為文本大小(以磅為單位)
mutation_aspect 默認值為1。
任何鑰匙 matplotlib.patches.PathPatch

xyA和xyB的坐標由字符串coordsA和coordsB表示。

屬性 描述
“圖點” 從圖的左下角指向的點
“數字像素” 圖左下角的像素
“數字分數” 0,0在圖的左下角,1,1在右上角
“軸點” 從軸的左下角開始的點
“軸像素” 軸左下角的像素
“軸分數” 0,0是軸的左下角,1,1是右上角
‘data’ 使用要注釋的對象的坐標係(默認)
“偏移點” 與xy值的偏移量(以磅為單位)
‘polar’ 您甚至可以在笛卡爾圖中為注釋指定theta,r。請注意,如果使用極軸,則無需為坐標係指定極坐標,因為這是原始的“data”坐標係。

範例1:

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()

輸出:

範例2:

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()

輸出:




相關用法


注:本文由純淨天空篩選整理自RajuKumar19大神的英文原創作品 Matplotlib.patches.ConnectionPatch class in Python。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。