我汇总了韦恩图(Venn Diagram)所有绘制方法，推荐收藏~~

DataCharm

发布于 2021-12-09 06:56:18

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今天这篇推文小编就汇总一下有关Venn Diagram(韦恩图) 的绘制方法，主要内容包括：

Venn Diagram(韦恩图)的简介
Venn Diagram(韦恩图)的R绘制方法
Venn Diagram(韦恩图)的Python绘制方法

Venn Diagram(韦恩图)的简介

Venn Diagram(韦恩图)，或叫Venn图、文氏图、温氏图，是在所谓的集合论（或者类的理论）数学分支中表示集合或者类的一种草图，主要用于显示元素集合重叠区域的图示，如下图所示：

Venn Diagram Example

那么，我们如何使用R或者Python实现Venn Diagram(韦恩图)的高效绘制呢？首先小编介绍R绘制的方法。

Venn Diagram(韦恩图)的R绘制方法

R-ggvenn包绘制

使用R绘制Venn Diagram图，首先想到的肯定是ggplot2,而ggvenn包作为ggplot2的拓展包且有geom_*(),这里就最先介绍。ggvenn包主要使用ggvenn()函数和geom_venn()绘图函数(ggplot2图层语法类似)绘制。官网：https://github.com/yanlinlin82/ggvenn

我们首先介绍下其主要的参数设置：

1. For filling:

fill_color(填充颜色)：默认是 c("blue", "yellow", "green", "red")
fill_alpha(透明度)：默认是0.5

2. For stroke:

stroke_color(线条颜色)：默认是"black"
stroke_alpha(线条透明度)：默认是1
stroke_size(线条宽度)：默认是1
stroke_linetype：默认是"solid"

3. For set name:

set_name_color(文本名颜色)：默认是"black"
set_name_size(文本名大小)：默认是6

4. For text:

text_color(文本颜色)：默认是"black"
text_size(文本大小)：默认是4.

以上各参数为ggvenn()和geom_venn()绘图函数的共同参数，其他额外参数小伙伴们可自行查阅哈~

接下来，我们结合实例进行解释说明哈~

「样例一」:ggvenn()函数绘制

# 样例数据
a <- list(`Set 1` = c(1, 3, 5, 7, 9),
          `Set 2` = c(1, 5, 9, 13),
          `Set 3` = c(1, 2, 8, 9),
          `Set 4` = c(6, 7, 10, 12))
#可视化绘制
opar <- par(family = "Roboto Condensed")
ggvenn(a,fill_color=mypal,fill_alpha = .7,stroke_linetype = "longdash",set_name_size = 8,
      text_size=5)

Example Of ggvenn()

「样例二」:geom_venn()函数绘制

# 生成样例数据
d <- tibble(value   = c(1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13),
            `Set 1` = c(T, F, T, T, F, T, F, T, F,  F,  F),
            `Set 2` = c(T, F, F, T, F, F, F, T, F,  F,  T),
            `Set 3` = c(T, T, F, F, F, F, T, T, F,  F,  F),
            `Set 4` = c(F, F, F, F, T, T, F, F, T,  T,  F))
# 可视化绘制
ggvenn_4 <- ggplot(d, aes(A = `Set 1`, B = `Set 2`, C = `Set 3`, D = `Set 4`)) +
  geom_venn(fill_color=mypal,fill_alpha = .7,stroke_linetype = "longdash",set_name_size = 8,
            text_size=5) + 
  theme_void()+
  coord_fixed() +
  labs(title = "Example of ggvenn:: geom_venn function",
       subtitle = "processed charts with geom_venn()",
       caption = "Visualization by DataCharm") +
  theme(plot.title = element_text(hjust = 0.5,vjust = .5,color = "black",face = 'bold',
                                  size = 20, margin = margin(t = 1, b = 12)),
        plot.subtitle = element_text(hjust = 0,vjust = .5,size=15),
       plot.caption = element_text(face = 'bold',size = 12))

Example Of geom_venn()

这里分别使用了ggvenn() 和 geom_venn() 函数绘制了韦恩图，更多细节，感兴趣的小伙伴可参考官网进行理解哈~

R-ggVennDiagram包绘制

R-ggVennDiagram包和ggvenn包一样也是ggplot2的拓展包，其可以支持2~7维的韦恩图绘制，这里小编直接通过使用ggVennDiagram()绘制韦恩图进行解释。

「样例」：

library(ggVennDiagram)
# 样例数据
genes <- paste("gene",1:1000,sep="")
set.seed(20210419)
x <- list(A=sample(genes,300),
          B=sample(genes,525),
          C=sample(genes,440),
          D=sample(genes,350))
# 可视化绘制
library(ggplot2)
ggVennDiagram(x, category.names = c("Stage 1","Stage 2","Stage 3", "Stage4"),
              size=1,lty="longdash",color="gray60") + 
  scale_fill_gradient(name="Count",low="#EC7D85",high = "#182F6F") +
  hrbrthemes::theme_ipsum(base_family = "sans") +
  labs(title = "Example of ggVennDiagram:: ggVennDiagram function",
       subtitle = "processed charts with ggVennDiagram()",
       caption = "Visualization by DataCharm") +
  theme(plot.title = element_text(hjust = 0.5,vjust = .5,color = "black",face = 'bold',
                                  size = 20, margin = margin(t = 1, b = 12)),
        plot.subtitle = element_text(hjust = 0,vjust = .5,size=15),
        plot.caption = element_text(face = 'bold',size = 12),
        axis.text.x = element_blank(),
        axis.text.y = element_blank(),
        axis.title.x = element_blank(),
        axis.title.y = element_blank())

Example of ggVennDiagram

Venn Diagram(韦恩图)的Python绘制方法

要想使用Python绘制韦恩图(这里主要介绍基于matplotlib的绘制方法，交互式后期统一介绍)，这里介绍一个非常便捷的方法-matplotlib-venn 绘制。安装方式如下：

「安装」：

easy_install matplotlib-venn

「官网」：https://github.com/konstantint/matplotlib-venn

「样例一」：两个集合

from matplotlib_venn import venn2, venn2_circles, venn2_unweighted
from matplotlib_venn import venn3, venn3_circles
import matplotlib.pyplot as plt

# 样例数据
Group1 = ['a','b','c','e','f','g','i','p','q']
Group2 = ['b','e','f','h','k','q','r','s','t','u','v','z']
Group3 = ['c','e','g','h','j','k','o','q','z']

#可视化绘制
plt.rcParams['font.family'] = ["Times New Roman"]
fig, ax = plt.subplots(figsize=(5,3),dpi=110)
vee2 = venn2([set(Group1), set(Group2)],set_labels=("Group1", "Group2"),
      set_colors=("#0073C2FF", "#EFC000FF"), alpha = 0.8,ax=ax)
venn2_circles([set(Group1), set(Group2)], linestyle="--", linewidth=2, color="black",ax=ax)

# 定制化设置:设置字体属性
for text in vee2.set_labels:
    text.set_fontsize(15);
for text in vee2.subset_labels:  
    text.set_fontsize(16)
    text.set_fontweight("bold")
ax.text(.8,-.1,'\nVisualization by DataCharm',transform = ax.transAxes,
        ha='center', va='center',fontsize = 8,color='black')
plt.title("Example Of venn2() and venn2_circles()",size=15,fontweight="bold",
         backgroundcolor="#868686FF",color="black",style="italic")

Example Of venn2()

「样例二」：三个集合

fig, ax = plt.subplots(figsize=(5,3),dpi=110)
vd3=venn3([set(Group1),set(Group2),set(Group3)],
          set_labels=("Group1","Group2","Group3"),
          set_colors=('#0073C2FF','#EFC000FF',"#CD534CFF"), 
          alpha = 0.8,ax=ax)
venn3_circles([set(Group1), set(Group2),set(Group3)], linestyle="--", linewidth=2, color="black",ax=ax)
# 定制化设置
for text in vd3.set_labels:
    text.set_fontsize(15);
    text.set_fontweight("bold")
for text in vd3.subset_labels:
    text.set_fontsize(15)
    text.set_fontweight("bold")
ax.text(.8,-.1,'\nVisualization by DataCharm',transform = ax.transAxes,
        ha='center', va='center',fontsize = 9,color='black')
plt.title("Example Of venn3() and venn3_circles()",fontweight="bold",fontsize=15,
          pad=30,backgroundcolor="#868686FF",color="black",style="italic")

Example Of venn3()

当然，你还可以通过如下代码定义”圈“的样式：

···
c3 = venn3_circles([set(Group1), set(Group2),set(Group3)], linestyle="--", linewidth=2, color="black",ax=ax)
···
# 对圆进行设置
c3[1].set_lw(7)
c3[1].set_ls(":")
c3[1].set_color("#7AA6DCFF")
···