我正在使用 R 的 psych 库，并在 R 中绘制相关对。
我想保存此函数生成的绘图并将其导出到 Word 文档中，例如使用 ReporteRs，但我不能这样做。这个问题已经在here讨论过。
当我深入研究为什么我无法导出它时，我意识到用 R 写这个：
plot <- pairs.panel(...)
在打印情节时给了我：NULL
因此，无论pairs.panels 生成的对象是什么，它都可以存储在变量中或重新用于导出到报告中。
作为一种解决方法，我使用 png() 将绘图存储在图像中，然后导入图像并将其插入到报告中...效率低且速度慢，因此任何解决方法都会有所帮助 谢谢，
【问题讨论】：
如果您查看psych 的代码库，特别是pairs.panels，您会发现它使用基本图形 来完成工作，并在那里绘制所有元素。不依赖于ggplot2。基础文件于 2007 年形成。
如果您承诺使用此软件包，我认为您将不得不继续使用 png() 之类的方式保存图像。从理论上讲，可以分叉并尝试移植.....
不确定您要做什么，但如果您要进行成对比较，另一种选择是利用其他libraries。
例如：
ggcorplot 早在 2011 年由 Dalhousie 大学的 Mike Lawrence 撰写（但比 pairs.panels.R 更新了 4 年）使用 ggplot2。
library(ggplot2)
#define a helper function (borrowed from the "ez" package)
ezLev=function(x,new_order){
for(i in rev(new_order)){
x=relevel(x,ref=i)
}
return(x)
}
ggcorplot = function(data,var_text_size,cor_text_limits){
# normalize data
for(i in 1:length(data)){
data[,i]=(data[,i]-mean(data[,i]))/sd(data[,i])
}
# obtain new data frame
z=data.frame()
i = 1
j = i
while(i<=length(data)){
if(j>length(data)){
i=i+1
j=i
}else{
x = data[,i]
y = data[,j]
temp=as.data.frame(cbind(x,y))
temp=cbind(temp,names(data)[i],names(data)[j])
z=rbind(z,temp)
j=j+1
}
}
names(z)=c('x','y','x_lab','y_lab')
z$x_lab = ezLev(factor(z$x_lab),names(data))
z$y_lab = ezLev(factor(z$y_lab),names(data))
z=z[z$x_lab!=z$y_lab,]
#obtain correlation values
z_cor = data.frame()
i = 1
j = i
while(i<=length(data)){
if(j>length(data)){
i=i+1
j=i
}else{
x = data[,i]
y = data[,j]
x_mid = min(x)+diff(range(x))/2
y_mid = min(y)+diff(range(y))/2
this_cor = cor(x,y)
this_cor.test = cor.test(x,y)
this_col = ifelse(this_cor.test$p.value<.05,'<.05','>.05')
this_size = (this_cor)^2
cor_text = ifelse(
this_cor>0
,substr(format(c(this_cor,.123456789),digits=2)[1],2,4)
,paste('-',substr(format(c(this_cor,.123456789),digits=2)[1],3,5),sep='')
)
b=as.data.frame(cor_text)
b=cbind(b,x_mid,y_mid,this_col,this_size,names(data)[j],names(data)[i])
z_cor=rbind(z_cor,b)
j=j+1
}
}
names(z_cor)=c('cor','x_mid','y_mid','p','rsq','x_lab','y_lab')
z_cor$x_lab = ezLev(factor(z_cor$x_lab),names(data))
z_cor$y_lab = ezLev(factor(z_cor$y_lab),names(data))
diag = z_cor[z_cor$x_lab==z_cor$y_lab,]
z_cor=z_cor[z_cor$x_lab!=z_cor$y_lab,]
#start creating layers
points_layer = layer(
geom = 'point'
, data = z
, mapping = aes(
x = x
, y = y
)
)
lm_line_layer = layer(
geom = 'line'
, geom_params = list(colour = 'red')
, stat = 'smooth'
, stat_params = list(method = 'lm')
, data = z
, mapping = aes(
x = x
, y = y
)
)
lm_ribbon_layer = layer(
geom = 'ribbon'
, geom_params = list(fill = 'green', alpha = .5)
, stat = 'smooth'
, stat_params = list(method = 'lm')
, data = z
, mapping = aes(
x = x
, y = y
)
)
cor_text = layer(
geom = 'text'
, data = z_cor
, mapping = aes(
x=y_mid
, y=x_mid
, label=cor
, size = rsq
, colour = p
)
)
var_text = layer(
geom = 'text'
, geom_params = list(size=var_text_size)
, data = diag
, mapping = aes(
x=y_mid
, y=x_mid
, label=x_lab
)
)
f = facet_grid(y_lab~x_lab,scales='free')
o = opts(
panel.grid.minor = theme_blank()
,panel.grid.major = theme_blank()
,axis.ticks = theme_blank()
,axis.text.y = theme_blank()
,axis.text.x = theme_blank()
,axis.title.y = theme_blank()
,axis.title.x = theme_blank()
,legend.position='none'
)
size_scale = scale_size(limits = c(0,1),to=cor_text_limits)
return(
ggplot()+
points_layer+
lm_ribbon_layer+
lm_line_layer+
var_text+
cor_text+
f+
o+
size_scale
)
}
#set up some fake data
library(MASS)
N=100
#first pair of variables
variance1=1
variance2=2
mean1=10
mean2=20
rho = .8
Sigma=matrix(c(variance1,sqrt(variance1*variance2)*rho,sqrt(variance1*variance2)*rho,variance2),2,2)
pair1=mvrnorm(N,c(mean1,mean2),Sigma,empirical=T)
#second pair of variables
variance1=10
variance2=20
mean1=100
mean2=200
rho = -.4
Sigma=matrix(c(variance1,sqrt(variance1*variance2)*rho,sqrt(variance1*variance2)*rho,variance2),2,2)
pair2=mvrnorm(N,c(mean1,mean2),Sigma,empirical=T)
my_data=data.frame(cbind(pair1,pair2))
ggcorplot(
data = my_data
, var_text_size = 30
, cor_text_limits = c(2,30)
)
示例用法和输出：
ggcorplot(
data = iris[1:4],
var_text_size = 5,
cor_text_limits = c(5,10))
产量
【讨论】：
从 2021 年开始，pairs.panels 可以与 png 一起使用。请参阅http://personality-project.org/r/psych/HowTo/factor.pdf 的第 11 页。语法是
png(filename = <panels_fn.png>, width = 480, height = 480, units = "px", pointsize = 12,
bg = "white", res = NA, family = "", restoreConsole = TRUE,
type = c("windows", "cairo", "cairo-png"), antialias = "d")
pairs.panels(df[, relevant_cols], lm = FALSE, main = my_plot_title )
dev.off()
您可以更改 png 参数以适合。有趣的是，如果我写，它确实不起作用
p <- pairs.panels(df[, relevant_cols], lm = FALSE, main = my_plot_title )
png(filename = <panels_fn.png>, width = 480, height = 480, units = "px", pointsize = 12,
bg = "white", res = NA, family = "", restoreConsole = TRUE,
type = c("windows", "cairo", "cairo-png"), antialias = "d")
print(p)
dev.off()
【讨论】：