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Base R Terminal error on `R: Run from Beginning to Line`
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Description
Describe the bug
Seemingly on MacOS, there are some odd terminal behaviors when NOT using radian where extra characters get added, text is garbled, or text is sent to the terminal in a way that it breaks functionality. This new stackoverflow post brought it up though I have experienced something similar when trying to use the R: Run from Beginning to Line command on longer scripts.
To Reproduce
Steps to reproduce the behavior:
- Go to settings.json and ensure the base R term is used for
r.rterm.macandr.rpath.mac. - Set
r.bracketedPastetofalse - Open R in VS Code and
R: Run from Beginning to Lineat the bottom of a "longer" script.
I have tried this when "r.bracketedPaste": false and when it is true and code fails to execute properly either way. Interestingly, when I change r.rterm.mac back to using radian R: Run from Beginning to Line works when"r.bracketedPaste": false and when it is true.
As an example here is a function that errors out when I use R: Run from Beginning to Line.
Function
roc_f <- function(mod, response) {
# generate prediction
pred <- ROCR::prediction(
glmmTMB:::predict.glmmTMB(mod, type = "response"),
mod$frame |> dplyr::pull(response)
)
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = value,
group = variable
)
) +
ggplot2::geom_line(
ggplot2::aes(linetype = variable, color = variable)
) +
ggplot2::ggtitle(
"Cutpoint"
) +
ggplot2::ylab("Sensitivity/Specificity") +
ggplot2::xlab("Cutpoint") +
gr.sg::theme_wgfd()
# auc plot ----
# get raw auc value
auc <- ROCR::performance(
pred,
measure = "auc"
) |>
getElement("y.values") |>
unlist()
# get true positive & false positive
auc_plot <- ROCR::performance(
pred,
"tpr",
"fpr"
)
# turn to df and rename cols
auc_dat <- data.frame(
x = auc_plot@x.values,
y = auc_plot@y.values
)
colnames(auc_dat) <- c(auc_plot@x.name, auc_plot@y.name)
# ggplot2 object
auc_plot <- ggplot2::ggplot(
auc_dat,
ggplot2::aes(
x = .data[[auc_plot@x.name]],
y = .data[[auc_plot@y.name]]
)
) +
ggplot2::geom_line() +
ggplot2::geom_abline(col = "red") +
ggplot2::ggtitle(
label = "ROC curve",
subtitle = paste0("AUC: ", round(auc, digits = 3))
) +
gr.sg::theme_wgfd()
# return ----
# setup list
ls <- list(
auc_val = auc,
auc_plot = auc_plot,
cut_plot = cut_plot
)
# return
return(ls)
}
This is what happens in my terminal when I try to run it - note that it repeats itself multiple times:
Terminal
# ROC function ----
roc_f <- function(mod, response) {
# generate prediction
pred <- ROCR::prediction(
glmmTMB:::predict.glmmTMB(mod, type = "response"),
mod$frame |> dplyr::pull(response)
)
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
>
# ROC function ----
roc_f <- function(mod, response) {
# generate prediction
pred <- ROCR::prediction(
glmmTMB:::predict.glmmTMB(mod, type = "response"),
mod$frame |> dplyr::pull(response)
)
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
gg> # ROC function ----
>
> roc_f <- function(mod, response) {
# generate prediction
pred <- ROCR::prediction(
glmmTMB:::predict.glmmTMB(mod, type = "response"),
mod$frame |> dplyr::pull(response)
)
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
+ # generate prediction
pred <- ROCR::prediction(
glmmTMB:::predict.glmmTMB(mod, type = "response"),
mod$frame |> dplyr::pull(response)
)
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
+ pred <- ROCR::prediction(
+ glmmTMB:::predict.glmmTMB(mod, type = "response"),
mod$frame |> dplyr::pull(response)
)
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g + mod$frame |> dplyr::pull(response)
+ )
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- +
# cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- RO+ # cut rate ----
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
+
# cut
cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
+ # cut
+ cut <- ROCR::performance(
pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) + pred,
"tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) |+ "tpr",
"tnr"
)
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues+ "tnr"
+ )
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | +
# create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | + # create df
cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true po+ cut_df <- data.frame(
x = cut@x.values |> unlist(),
y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
+ x = cut@x.values |> unlist(),
+ y = cut@y.values |> unlist(),
alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
+ alpha = cut@alpha.values |> unlist()
)
colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
+ )
+ colnames(cut_df) <- c(cut@x.name, cut@y.name, cut@alpha.name)
cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x + cut_df <- cut_df |>
data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln+ data.table::as.data.table() |>
data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x + data.table::melt.data.table(id.vars = cut@alpha.name)
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x +
cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x + cut_plot <- ggplot2::ggplot(
cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x x x t,
+ cut_df,
ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x x x t,
+ ggplot2::aes(
x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x x x t,
.data[[auc_p + x = .data[[cut@alpha.name]],
y = y = up y = y = uplot line(
ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x x x t,
.data[[auc_p + y = y = up uplot line(
Error: unexpected '=' in:
" x = .data[[cut@alpha.name]],
y = y ="
> ggplot2::aes ggplot2::aes ggplot2::aes +
ggplot2::ggtitle(
"Cutpoint"
) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x x x t,
.data[[auc_p . )
) +
ggplot2::geom_line() +
ggplot2::geom_abline(col = "red") +
ggplo ggplo ggplo ggplo ggplo Error: unexpected symbol in " ggplot2::aes ggplot2"
> ggplot2::ggtitle(
+ "Cutpoint"
+ ) +
ci plot2::xlab("Cutpoint") +
g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x x x t,
.data[[auc_p . )
) +
ggplot2::geom_line() +
ggplot2::geom_abline(col = "red") +
ggplo ggplo ggplo ggplo ggplo ggplo te0("AUC: ", round(auc, digits = 3))
) + ci pl"Cutpoint") +
Error: unexpected symbol in:
" ) +
ci plot2"
> g g g g g g g c value
auc <- ROCR::performance(
pred,
pred,
R:: "auc"
) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
erformance(
pred,
"tpr",
f a e cols
auc_dat <- data.frame(
x x x x x x x coln x x c_p x x x xggp x x x x x x t,
.data[[auc_p . )
) +
ggplot2::geom_line() +
ggplot2::geom_abline(col = "red") +
ggplo ggplo ggplo ggplo ggplo ggplo te0("AUC: ", round(auc, digits = 3))
) +
g::theme_wgfd()
# return ----
# setup list
ls <- list(
auc_val = auc, auc_val = auc, auc_val = auc, Error: unexpected symbol in " g g"
> auc <- ROCR::performance(
+ pred,
+ pred,
+ R:: "auc"
+ ) | ) | ) | ) | ) ues ) | ) | ) # get true posi e & ) | ) |
Error: unexpected ')' in:
"R:: "auc"
) | )"
> erformance(
+ pred,
+ "tpr",
+ f a e cols
Error: unexpected symbol in:
" "tpr",
f a"
> auc_dat <- data.frame(
+ x x x x x x x coln x x c_p x x x xggp x x x x x x t,
Error: unexpected symbol in:
" auc_dat <- data.frame(
x x"
> .data[[auc_p . )
Error: unexpected symbol in " .data[[auc_p ."
> ) +
Error: unexpected ')' in " )"
> ggplot2::geom_line() +
+ ggplot2::geom_abline(col = "red") +
+ ggplo ggplo ggplo ggplo ggplo ggplo te0("AUC: ", round(auc, digits = 3))
Error: unexpected symbol in:
" ggplot2::geom_abline(col = "red") +
ggplo ggplo"
> ) +
Error: unexpected ')' in " )"
> g::theme_wgfd()
Error in loadNamespace(x) : there is no package called ‘g’
>
> # return ----
>
> # setup list
> ls <- list(
+ auc_val = auc, auc_val = auc, auc_val = auc, auc_val = )
Error: object 'auc' not found
>
> # return
> return(ls)
Error: no function to return from, jumping to top level
> }
Error: unexpected '}' in "}"
Can you fix this issue by yourself? (We appreciate the help)
No
(If applicable) Please attach setting.json
// R path for Mac OS X
"r.rterm.mac": "/usr/local/bin/R",
// Use bracketed paste mode
"r.bracketedPaste": false,
// Enable R session watcher
"r.sessionWatcher": true,
// Delay in milliseconds before sending each line to rterm (only applies if r.bracketedPaste is false)
"r.rtermSendDelay": 8,
Expected behavior
For code to be send to the terminal as expected - like with radian.
Environment (please complete the following information):
- OS: MacOS
- VSCode Version: 1.87.0
- R Version: 4.3.2
- vscode-R version: v2.8.2
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing R: Run from Beginning to Line on macOS with the base R terminal, using the reported r.rterm.mac, r.rpath.mac, and r.bracketedPaste settings. Compare behavior with radian and verify that longer scripts execute without garbled, repeated, or otherwise corrupted terminal input.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- cli, developer-experience
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100