为什么我不能 plot ggplot2 中的平滑曲线

Question

Good afternoon,

Assume we have the following code where i'm trying to plot ggplot2 smoothing curve :

library(ggplot2)

library(dplyr)

melted=structure(list(Var1 = c(1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L), Var2 = structure(c(1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 
4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 
7L, 7L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 
10L, 10L, 11L, 11L, 11L, 11L, 11L), .Label = c("Sensitivity", 
"Specificity", "Pos Pred Value", "Neg Pred Value", "Precision", 
"Recall", "F1", "Prevalence", "Detection Rate", "Detection Prevalence", 
"Balanced Accuracy "), class = "factor"), value = c(0, 0.85, 
0.85, 0.86, 0.86, 0, 0.188235294117647, 0.188235294117647, 0.188235294117647, 
0.188235294117647, 0, 0.711297071129707, 0.711297071129707, 0.713692946058091, 
0.713692946058091, 0, 0.347826086956522, 0.347826086956522, 0.363636363636364, 
0.363636363636364, 0, 0.711297071129707, 0.711297071129707, 0.713692946058091, 
0.713692946058091, 0, 0.85, 0.85, 0.86, 0.86, 0, 0.774487471526196, 
0.774487471526196, 0.780045351473923, 0.780045351473923, 0, 0.701754385964912, 
0.701754385964912, 0.701754385964912, 0.701754385964912, 0, 0.596491228070175, 
0.596491228070175, 0.603508771929825, 0.603508771929825, 0, 0.83859649122807, 
0.83859649122807, 0.845614035087719, 0.845614035087719, 0, 0.519117647058823, 
0.519117647058823, 0.524117647058824, 0.524117647058824)), row.names = c(NA, 
-55L), groups = structure(list(Var2 = structure(1:11, .Label = c("Sensitivity", 
"Specificity", "Pos Pred Value", "Neg Pred Value", "Precision", 
"Recall", "F1", "Prevalence", "Detection Rate", "Detection Prevalence", 
"Balanced Accuracy "), class = "factor"), .rows = structure(list(
    1:5, 6:10, 11:15, 16:20, 21:25, 26:30, 31:35, 36:40, 41:45, 
    46:50, 51:55), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), row.names = c(NA, -11L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))


ROC<-function(melted){
  v=length(which(melted[,2]=="Sensitivity"))
  
  melted= melted %>%
    group_by(Var2) %>%
    arrange(Var1) %>%
    filter(row_number()==n())
  
  x=c(0,1-filter(melted,Var2=="Specificity")$value,1)
  y=c(0,filter(melted,Var2=="Sensitivity")$value,1)
  
  x=as.numeric(x)
  y=as.numeric(y)
  
  dput(x)
  dput(y)
  
  df<-data.frame(x=x,y=y) 
  
  
  ggplot(df, aes(x=x, y=y)) +
    geom_point() +
    geom_smooth()
  
  print(melted)
}

ROC(melted)

When i call the ROC(melted) function on the melted data, i don't get the ROC plot ( Although the R code seems to be correct ). I tried to convert x and y from lists to numeric but the pb is not solved !

However with the same steps ( using raw data and not a function call ) i got the desired plot:

library(ggplot2)

library(dplyr)

  x=c(0, 0.811764705882353, 1)
  y=c(0, 0.86, 1)
  

  
  df<-data.frame(x=x,y=y) 
  
  
  ggplot(df, aes(x=x, y=y)) +
    geom_point() +
    geom_smooth()
  
  print(melted)

Thank you for help !

Answer 1

ROC(melded) will work, when you dont use "print(melted)" at the end of your function. Instead, just let the ggplot command be the last command in the function ROC<-function(melted). Then the ggplot will be the output.

library(ggplot2)

library(dplyr)

melted=structure(list(Var1 = c(1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 
1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 
2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L), Var2 = structure(c(1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 
4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 
7L, 7L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 
10L, 10L, 11L, 11L, 11L, 11L, 11L), .Label = c("Sensitivity", 
"Specificity", "Pos Pred Value", "Neg Pred Value", "Precision", 
"Recall", "F1", "Prevalence", "Detection Rate", "Detection Prevalence", 
"Balanced Accuracy "), class = "factor"), value = c(0, 0.85, 
0.85, 0.86, 0.86, 0, 0.188235294117647, 0.188235294117647, 0.188235294117647, 
0.188235294117647, 0, 0.711297071129707, 0.711297071129707, 0.713692946058091, 
0.713692946058091, 0, 0.347826086956522, 0.347826086956522, 0.363636363636364, 
0.363636363636364, 0, 0.711297071129707, 0.711297071129707, 0.713692946058091, 
0.713692946058091, 0, 0.85, 0.85, 0.86, 0.86, 0, 0.774487471526196, 
0.774487471526196, 0.780045351473923, 0.780045351473923, 0, 0.701754385964912, 
0.701754385964912, 0.701754385964912, 0.701754385964912, 0, 0.596491228070175, 
0.596491228070175, 0.603508771929825, 0.603508771929825, 0, 0.83859649122807, 
0.83859649122807, 0.845614035087719, 0.845614035087719, 0, 0.519117647058823, 
0.519117647058823, 0.524117647058824, 0.524117647058824)), row.names = c(NA, 
-55L), groups = structure(list(Var2 = structure(1:11, .Label = c("Sensitivity", 
"Specificity", "Pos Pred Value", "Neg Pred Value", "Precision", 
"Recall", "F1", "Prevalence", "Detection Rate", "Detection Prevalence", 
"Balanced Accuracy "), class = "factor"), .rows = structure(list(
    1:5, 6:10, 11:15, 16:20, 21:25, 26:30, 31:35, 36:40, 41:45, 
    46:50, 51:55), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), row.names = c(NA, -11L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"))


ROC<-function(melted){
  v=length(which(melted[,2]=="Sensitivity"))
  
  melted= melted %>%
    group_by(Var2) %>%
    arrange(Var1) %>%
    filter(row_number()==n())
  
  x=c(0,1-filter(melted,Var2=="Specificity")$value,1)
  y=c(0,filter(melted,Var2=="Sensitivity")$value,1)
  
  x=as.numeric(x)
  y=as.numeric(y)
  
  dput(x)
  dput(y)
  
  df<-data.frame(x=x,y=y) 
  
  
  ggplot(df, aes(x=x, y=y)) +
    geom_point() +
    geom_smooth()
 }

ROC(melted)