我汇总了韦恩图(Venn Diagram)所有绘制方法,推荐收藏~~

我汇总了韦恩图(Venn Diagram)所有绘制方法,推荐收藏~~

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0.52. For stroke:

stroke_color(线条颜色):默认是"black"stroke_alpha(线条透明度):默认是1stroke_size(线条宽度):默认是1stroke_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64. 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

代码语言:javascript代码运行次数:0运行复制# 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

代码语言:javascript代码运行次数:0运行复制# 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」:

代码语言:javascript代码运行次数:0运行复制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」:

代码语言:javascript代码运行次数:0运行复制easy_install matplotlib-venn

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

「样例一」:两个集合

代码语言:javascript代码运行次数:0运行复制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

代码语言:javascript代码运行次数:0运行复制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:

代码语言:javascript代码运行次数:0运行复制···

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")

···

Example02 Of venn3()

以上小编只是介绍最基础和常用的可视化绘制方法,更多细节大家可参照官网进行探索哈~

总结今天这篇推文,小编较为系统的介绍了使用R和Python进行Venn Diagram(韦恩图)的绘制且简单介绍了Venn Diagram(韦恩图)的用途,希望大家可以有所收获哈~~

再小的技能,也应该被认真对待。

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