Assigning the result of corrplot to a variable

I am using the function corrplot from corrplot package to generate a plot of a correlation matrix created with cor.test (psych package). When I try to save the result into a variable, the variable is NULL.

Anyone could advice, please?

library(corrplot)
library(psych)
library(ggpubr)

data(iris)

res_pearson.c_setosa<-iris%>%
  filter(Species=="setosa")%>%
  select(Sepal.Length:Petal.Width)%>%
  corr.test(., y = NULL, use = "complete",method="pearson",adjust="bonferroni", alpha=.05,ci=TRUE,minlength=5)

corr.a<-corrplot(res_pearson.c_setosa$r[,1:3],
         type="lower", 
         order="original", 
         p.mat = res_pearson.c_setosa$p[,1:3], 
         sig.level = 0.05, 
         insig = "blank", 
         col=col4(10), 
         tl.pos = "ld",
         tl.cex = .8, 
         tl.srt=45, 
         tl.col = "black",
         cl.cex = .8)+
  my.theme #this is a theme() piece, but if I take this away, the result is a list rather than a plot

You can create your own function where you put recordPlot at the end to save the plot. After that you can save the output of the function in a variable. Here is a reproducible example:

library(corrplot)
library(psych)
library(ggpubr)
library(dplyr)

data(iris)

res_pearson.c_setosa<-iris%>%
  filter(Species=="setosa")%>%
  select(Sepal.Length:Petal.Width)%>%
  corr.test(., y = NULL, use = "complete",method="pearson",adjust="bonferroni", alpha=.05,ci=TRUE,minlength=5)

your_function <- function(ff){
corr.a<-corrplot(ff$r[,1:3],
                 type="lower", 
                 order="original", 
                 p.mat = ff$p[,1:3], 
                 sig.level = 0.05, 
                 insig = "blank", 
                 #col=col4(10), 
                 tl.pos = "ld",
                 tl.cex = .8, 
                 tl.srt=45, 
                 tl.col = "black",
                 cl.cex = .8)
  #my.theme #this is a theme() piece, but if I take this away, the result is a list rather than a plot
recordPlot() # save the latest plot
}
your_function(res_pearson.c_setosa)

p <- your_function(res_pearson.c_setosa)

p

^{Created on 2022-07-13 by the reprex package (v2.0.1)}

As you can see, the variable p outputs the plot.