This document discusses the R debugger. It provides examples of using the browser(), debug(), and debugonce() functions to debug R code. The browser allows stepping through code line-by-line and examining variable values. debug() and debugonce() activate debugging for a function. Other debugging topics covered include traceback(), browserText(), and examining the coefficients of linear models.

1. R
Tokyo.R #16 (2011/08/27)
@a_bicky

2. • Takeshi Arabiki 1
‣ Twitter: @a_bicky
‣ : id:a_bicky
•
R
•
http://d.hatena.ne.jp/a_bicky/

3. Osaka.R #4
http://www.slideshare.net/abicky/twitterr http://www.slideshare.net/abicky/introduction-to-hadoop-mapreduce

4. • R debugger
•
•
•
• ksvm
•
•

5. debug
: http://ja.wikipedia.org/wiki/
http://getfirebug.com/whatisfirebug
R

6. R debugger

7. R debugger
‣ R debugger
‣
‣
‣
‣
‣
‣

8. R debugger
Perl
R debugger gdb
debugger
where bt T
n n n
debugonce(func※); c s s
browserSetDebug(); c fin r
c c c
Q q q
※func
<RET> debug n browser c n n
options(browserNLdisabled = TRUE) <RET>

9. browser
f <- function(x) {
y <- x * 2
browser() #
z <- y^2
return(z)
}

10. browser
f <- function(x) { > f(10)
y <- x * 2 Called from: f(10)
Browse[1]>
z <- y^2
return(z)
}

11. browser
f <- function(x) { > f(10)
y <- x * 2 Called from: f(10)
Browse[1]> ls()
z <- y^2 [1] "x" "y"
return(z) Browse[1]>
}

12. browser
f <- function(x) { > f(10)
y <- x * 2 Called from: f(10)
Browse[1]> ls()
z <- y^2 [1] "x" "y"
return(z) Browse[1]> n #
} debug: z <- y^2
Browse[2]>

13. browser
f <- function(x) { > f(10)
y <- x * 2 Called from: f(10)
Browse[1]> ls()
z <- y^2 [1] "x" "y"
return(z) Browse[1]> n #
} debug: z <- y^2
Browse[2]> z
Error: object 'z' not found
Browse[2]>
z

14. browser
f <- function(x) { > f(10)
y <- x * 2 Called from: f(10)
Browse[1]> ls()
z <- y^2 [1] "x" "y"
return(z) Browse[1]> n #
} debug: z <- y^2
Browse[2]> z
Error: object 'z' not found
Browse[2]> n
debug: return(z)
Browse[2]> z
[1] 400
Browse[2]>
z y^2

15. browser
f <- function(x) { > f(10)
y <- x * 2 Called from: f(10)
Browse[1]> ls()
z <- y^2 [1] "x" "y"
return(z) Browse[1]> n #
} debug: z <- y^2
Browse[2]> z
Error: object 'z' not found
Browse[2]> n
debug: return(z)
Browse[2]> z
[1] 400
Browse[2]> z <- 1 # z
Browse[2]> n
[1] 1
>
f(10) z

16. debug
f <- function(x) { > debug(f)
y <- x * 2 > f(10)
z <- y^2 debugging in: f(10)
return(z) debug: {
} y <- x * 2
z <- y^2
return(z)
}
Browse[2]> n
debug: y <- x * 2
browser Browse[2]> n
debug: z <- y^2
Browse[2]> n
debug: return(z)
Browse[2]> n
exiting from: f(10)
[1] 400
>

17. debugonce
> debug(f) > debugonce(f)
> f(10) > f(10)
debugging in: f(10) debugging in: f(10)
debug: { debug: {
y <- x * 2 y <- x * 2
z <- y^2 z <- y^2
return(z) return(z)
} }
Browse[2]> Q # Browse[2]> Q #
> isdebugged(f) > isdebugged(f)
[1] TRUE [1] FALSE
> f(10) > f(10)
debugging in: f(10) [1] 400
... >
※ undebug(f)

18. traceback
f <- function(x) { > f(1:5)
x <- as.character(x) Error in sum(x) : invalid
return(g(x)) 'type' (character) of argument
} > traceback()
3: h(x) h
g <- function(x) { 2: g(x)
if (length(x) > 1) { 1: f(1:10)
return(h(x)) > debug(h)
} else { > f(1:10)
return(x) debugging in: h(x)
} debug: {
} return(sum(x))
}
h <- function(x) { Browse[2]> x
return(sum(x)) [1] "1" "2" "3" "4" "5"
} Browse[2]> sum(x)
Error in sum(x) : invalid
'type' (character) of argument

19. browser
f <- function(x) { > f(5) # y = 10
y <- x * 2 [1] 100
browser(expr = y > 10) > f(10) # y = 20
z <- y^2 Called from: f(10)
return(z) Browse[1]>
}
f <- function(x) {
y <- x * 2
if (y > 10) {
browser()
}
z <- y^2
return(z)
}

20. browserText
f <- function(x) { > f(10)
browser("1st bt") Called from: f(10)
Browse[1]> where #
# < >
where 1: f(10)
browser("2nd bt")
}
Browse[1]> browserText()
[1] "1st bt"
Browse[1]> c
Called from: f(10)
Browse[1]> where #
where 1: f(10)
Browse[1]> browserText()
[1] "2nd bt"

22. ‣
‣
‣

23. head
> head(iris) # 6
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
4 4.6 3.1 1.5 0.2 setosa
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa
> head(iris, 3) # 3
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 4.7 3.2 1.3 0.2 setosa
>
※ tail

24. summary
> summary(m <- lm(weight ~ group, PlantGrowth))
Call:
lm(formula = weight ~ group, data = PlantGrowth)
Residuals:
Min 1Q Median 3Q Max
-1.0710 -0.4180 -0.0060 0.2627 1.3690
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.0320 0.1971 25.527 <2e-16 ***
grouptrt1 -0.3710 0.2788 -1.331 0.1944
grouptrt2 0.4940 0.2788 1.772 0.0877 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.6234 on 27 degrees of freedom
Multiple R-squared: 0.2641, Adjusted R-squared: 0.2096
F-statistic: 4.846 on 2 and 27 DF, p-value: 0.01591

25. str
> m # print.lm(m)
Call:
lm(formula = weight ~ group, data = PlantGrowth)
Coefficients:
(Intercept) grouptrt1 grouptrt2
5.032 -0.371 0.494
> str(m)
List of 13
$ coefficients : Named num [1:3] 5.032 -0.371 0.494
..- attr(*, "names")= chr [1:3] "(Intercept)" "grouptrt1"
"grouptrt2"
> m$coefficients #
(Intercept) grouptrt1 grouptrt2
5.032 -0.371 0.494

26. class
> class(m)
[1] "lm"
data.frame matrix
character factor
> (x <- c(b = "this is b", a = "this is a"))
b a
"this is b" "this is a"
> (index <- factor(c("a", "b")))
[1] a b
Levels: a b
> x[index] #
b a
"this is b" "this is a"
> x[as.character(index)] #
a b
"this is a" "this is b"

28. coef
> m$coefficients
(Intercept) grouptrt1 grouptrt2
5.032 -0.371 0.494
> coef(m)
(Intercept) grouptrt1 grouptrt2
5.032 -0.371 0.494

29. showMethods
> coef
standardGeneric for "coef" defined from package "stats"
function (object, ...)
standardGeneric("coef")
<environment: 0x100f8d4a0>
Methods may be defined for arguments: object
Use showMethods("coef") for currently available ones.
> showMethods("coef") # coef
Function: coef (package stats)
object="ANY"
object="gausspr"
object="kfa"
object="kqr" lm
object="ksvm"
object="lm"
selectMethod
(inherited from: object="ANY")
object="lssvm"
object="rvm"

30. selectMethod, methods
> selectMethod("coef", signature = "lm") # signature
Method Definition (Class "derivedDefaultMethod"):
function (object, ...)
UseMethod("coef")
<environment: namespace:stats>
Signatures:
object
target "ANY"
defined "ANY"
> methods(coef) # UseMethod methods
[1] coef.aov* coef.Arima* coef.default* coef.listof*
coef.nls*
Non-visible functions are asterisked
> coef.default # coef.lm coef.default
Error: object 'coef.default' not found

31. selectMethod, methods
> selectMethod("coef", signature = "lm") # signature
Method Definition (Class "derivedDefaultMethod"):
function (object, ...)
UseMethod("coef")
<environment: namespace:stats>
Signatures:
object
target "ANY"
defined "ANY"
> methods(coef) # UseMethod methods
[1] coef.aov* coef.Arima* coef.default* coef.listof*
coef.nls*
*
Non-visible functions are asterisked
> coef.default # coef.lm coef.default
Error: object 'coef.default' not found

32. package:::func
> stats:::coef.default # Non-visible pkg:::func
function (object, ...)
object$coefficients
<environment: namespace:stats>
> evalq(coef.default, environment(lm)) #
function (object, ...)
object$coefficients
<environment: namespace:stats>
> debug(stats:::coef.default)
> coef(m)
debugging in: coef.default(m)
debug: object$coefficients
Browse[2]>

34. ‣ trace
‣ recover
‣ options(error = recover)
‣ options(error = dump.frames)

35. trace
trace
trace(what, tracer, exit, at, print, signature,
where = topenv(parent.frame()), edit = FALSE)
what:
tracer:
exit:
at:
print:
signature:
where:
edit:

36. trace
trace 3 5
f <- function(x) { > trace(f, browser, at = c(3, 5))
cat("1st linen") > f()
if (TRUE) { 1st line
cat("1st 2nd linen") Tracing f() step 3
cat("2nd 2nd linen") Called from: eval(expr, envir,
} enclos)
Browse[1]> c
cat("3rd line 1st 2nd line
") 2nd 2nd line
cat("4th linen") 3rd line
} Tracing f() step 5
Called from: eval(expr, envir,
enclos)
Browse[1]> c
4th line

37. trace
trace 3 5
f <- function(x) { > trace(f, browser, at = c(3, 5))
cat("1st linen") > f()
if (TRUE) { 1st line
cat("1st 2nd linen") Tracing f() step 3
cat("2nd 2nd linen") Called from: eval(expr, envir,
} enclos)
Browse[1]> c
cat("3rd line 1st 2nd line
") 2nd 2nd line
cat("4th linen") 3rd line
} Tracing f() step 5
Called from: eval(expr, envir,
enclos)
Browse[1]> c
4th line

38. trace
trace f
f <- function(x) { # 1 > untrace(f) # trace
cat("1st linen") # 2 > as.list(body(f))
if (TRUE) { # 3 [[1]]
cat("1st 2nd linen") `{`
cat("2nd 2nd linen")
} # 1 1 [[2]]
# cat("1st linen")
cat("3rd line
[[3]]
") # 1 # 4
if (TRUE) {
cat("4th linen") # 5 cat("1st 2nd linen")
}
cat("2nd 2nd linen")
}
[[4]]
cat("3rd linen")
[[5]]
cat("4th linen")

39. trace
trace trace
f <- function(x) { > trace(f, browser, at = c(3, 5))
cat("1st linen") [1] "f"
if (TRUE) { > body(f)
cat("1st 2nd linen") {
cat("2nd 2nd linen") cat("1st linen")
} {
.doTrace(browser(), "step 3")
cat("3rd line if (TRUE) {
") cat("1st 2nd linen")
cat("4th linen") cat("2nd 2nd linen")
} }
}
cat("3rd linen")
{
.doTrace(browser(), "step 5")
cat("4th linen")
}
}

40. trace
trace trace
f <- function(x) { > trace(f, browser, at = c(3, 5))
cat("1st linen") [1] "f"
if (TRUE) { > body(f)
cat("1st 2nd linen") {
cat("2nd 2nd linen") cat("1st linen")
} { .doTrace
.doTrace(browser(), "step 3")
cat("3rd line if (TRUE) {
") cat("1st 2nd linen")
cat("4th linen") cat("2nd 2nd linen")
} }
}
cat("3rd linen")
{
.doTrace(browser(), "step 5")
cat("4th linen")
}
}

41. trace
trace trace
f <- function(x) { > f()
cat("1st linen") 1st line
if (TRUE) { Tracing f() step 3
cat("1st 2nd linen") Called from: eval(expr, envir,
cat("2nd 2nd linen") enclos)
} Browse[1]> Q
> # .doTrace
cat("3rd line > tracingState(FALSE)
") [1] TRUE
cat("4th linen") > f()
} 1st line
1st 2nd line
2nd 2nd line
3rd line
4th line
> # .doTrace
> tracingState(TRUE)
[1] FALSE

42. trace
trace
f <- function(x) { > trace(f, edit = TRUE) # f
cat("1st linen") Waiting for Emacs...
if (TRUE) { [1] "f"
cat("1st 2nd linen") > body(f)
cat("2nd 2nd linen") {
} cat("1st linen")
cat("3rd linen")
cat("3rd line browser()
") cat("4th linen")
cat("4th linen") }
} > f()
1st line
3rd line
Called from: f()
f <- function(x) { Browse[1]>
cat("1st linen")
cat("3rd linen") ※ .doTrace
browser()
cat("4th linen") tracingState
}

43. recover
recover
f <- function(x) { > f(1)
x <- g(x)
return(x) Enter a frame number, or 0 to exit
}
1: f(1)
g <- function(x) { 2: g(x)
y <- x + 1 3: h(y)
y <- h(y)
return(y) Selection: 1 # f(1)
} Called from: top level
Browse[1]> x
h <- function(y) { [1] 1
z <- y + 1
recover()
return(z)
}

44. recover
recover
f <- function(x) { Browse[1]> c
x <- g(x)
return(x) Enter a frame number, or 0 to exit
}
1: f(1)
g <- function(x) { 2: g(x)
y <- x + 1 3: h(y)
y <- h(y)
return(y) Selection: 2 # g(x)
} Called from: f(1)
Browse[1]> y
h <- function(y) { [1] 2
z <- y + 1
recover()
return(z)
}

45. recover
recover
f <- function(x) { Browse[1]> c
x <- g(x)
return(x) Enter a frame number, or 0 to exit
}
1: f(1)
g <- function(x) { 2: g(x)
y <- x + 1 3: h(y)
y <- h(y)
return(y) Selection: 3 # h(y)
} Called from: g(x)
Browse[1]> z
h <- function(y) { [1] 3
z <- y + 1
recover()
return(z)
}

46. options(error = recover)
recover recover
f <- function(x) { > options(error = recover)
x <- g(x) > f(1)
return(x) Error in print(x) : object 'x' not
} found
g <- function(x) { Enter a frame number, or 0 to exit
y <- x + 1
y <- h(y) 1: f(1)
return(y) 2: g(x)
} 3: h(y)
4: print(x)
h <- function(y) {
z <- y + 1 Selection: 3 # h(y)
print(x) # Error! Called from: h(y)
return(z) Browse[1]> x
} Error during wrapup: object 'x'
not found
Browse[1]> ls()
[1] "y" "z"

47. options(error = dump.frames)
dump.frames
dump.frames recover
f <- function(x) { > options(error = dump.frames)
x <- g(x) > f(1)
return(x) Error in print(x) : object 'x' not
} found
> ls()
g <- function(x) { [1] "f" "g" "h" "last.dump"
y <- x + 1 > debugger(last.dump)
y <- h(y) Message: Error in print(x) :
return(y) object 'x' not found
} Available environments had calls:
1: f(1)
h <- function(y) { 2: g(x)
z <- y + 1 3: h(y)
print(x) # Error! 4: print(x)
return(z)
} Enter an environment number, or 0
to exit Selection:

48. ksvm

49. ksvm
> library(kernlab)
> ksvm(Species ~ .,
+ iris,
+ class.weights = c(versicolor = 1, setosa = 10),
+ prob.model = TRUE)
Using automatic sigma estimation (sigest) for RBF or laplace
kernel
Error in lev(ret)[yd[cind]] :
only 0's may be mixed with negative subscripts

50. ksvm
> options(error = recover) # recover
> ksvm(Species ~ .,
+ iris,
+ class.weights = c(versicolor = 1, setosa = 10),
+ prob.model = TRUE)
Using automatic sigma estimation (sigest) for RBF or laplace kernel
Error in lev(ret)[yd[cind]] :
only 0's may be mixed with negative subscripts
Enter a frame number, or 0 to exit
1: ksvm(Species ~ ., iris, class.weights = c(versicolor = 1, setosa
= 10), pro
< >
9: .local(x, ...)
10: as.factor(lev(ret)[yd[cind]])
11: is.factor(x)
12: inherits(x, "factor")
Selection: 10

51. ksvm
Called from: top level
Browse[1]> ls()
[1] "x"
Browse[1]> x
Error during wrapup: promise already under evaluation: recursive
default argument reference or earlier problems?

52. ksvm
Called from: top level
Browse[1]> ls()
[1] "x"
Browse[1]> x
Error during wrapup: promise already under evaluation: recursive
default argument reference or earlier problems?

53. ksvm
> options(error = NULL)
> ksvm(Species ~ .,
+ iris,
+ class.weights = c(versicolor = 1, setosa = 10),
+ prob.model = TRUE)
Using automatic sigma estimation (sigest) for RBF or laplace kernel
Error in lev(ret)[yd[cind]] :
only 0's may be mixed with negative subscripts
> ksvm #
standardGeneric for "ksvm" defined from package "kernlab"
function (x, ...)
standardGeneric("ksvm")
<environment: 0x103623e08>
Methods may be defined for arguments: x
Use showMethods("ksvm") for currently available ones.
S4

54. ksvm
> showMethods("ksvm")
Function: ksvm (package kernlab)
x="formula"
x="kernelMatrix"
x="list"
x="matrix"
x="vector"
> selectMethod(ksvm, "formula")
Method Definition:
function (x, ...)
{
.local <- function (x, data = NULL, ..., subset, na.action =
na.omit,
scaled = TRUE)
< >
ret <- ksvm(x, y, scaled = scaled, ...)
< >
signature matrix ksvm

55. ksvm
> selectMethod(ksvm, "matrix")
Method Definition:
function (x, ...)
{
.local <- function (x, y = NULL, scaled = TRUE, type = NULL,
kernel = "rbfdot", kpar = "automatic", C = 1, nu = 0.2,
< >
, drop = FALSE][cind, ], as.factor(lev(ret)
[yd[cind]]),
< >

56. ksvm
> trace(ksvm, signature = “matrix”, edit = TRUE)
browser
browser()
if (is.null(class.weights))
cret <- ksvm(x[c(indexes[[i]], indexes
[[j]]),
, drop = FALSE][cind, ], yd[cind],
type = type(ret), kernel = kernel,
kpar = NULL, C = C, nu = nu, tol = tol,
scaled = FALSE, cross = 0, fit = FALSE,
cache = cache, prob.model = FALSE)
else cret <- ksvm(x[c(indexes[[i]], indexes
[[j]]),
, drop = FALSE][cind, ], as.factor(lev(ret)
[yd[cind]]),

57. ksvm
> ksvm(Species ~ .,
+ iris,
+ class.weights = c(versicolor = 1, setosa = 10),
+ prob.model = TRUE)
Using automatic sigma estimation (sigest) for RBF or laplace kernel
Called from: .local(x, ...)
Browse[1]> yd
[1] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[22] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1
[43] -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 1 1 1 1 1 1 1 1 1
[64] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[85] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
lev(ret)[yd[cind]] yd (-1, 1)
yd lev(ret)

59. > 1:5
[1] 1 2 3 4 5
> .Last.value
[1] 1 2 3 4 5
ESS TAB .Last.value

60. f <- function(x) {
y <- x
g(y)
}
g <- function(x) {
x <- x^2
browser()
}
> f(10)
Called from: g(y) # x y
Browse[1]> x # x 2
[1] 100
Browse[1]> y # y
Error: object 'y' not found

61. Browse[1]> evalq(y, parent.frame()) # y
[1] 10
Browse[1]> evalq(ls(), parent.frame()) #
[1] "x" "y"
Browse[1]> eval.parent(quote(y)) # part1
[1] 10
Browse[1]> get("y", parent.frame()) # part2
[1] 10
Browse[1]> ls(envir = parent.frame()) #
[1] "x" "y"
evalq(expr, parent.frame())

62. apply browser
f <- function() {
a <- lapply(1:10000, function(x) {
browser() # 1 browser()
print(x)
})
}

63. apply browser
> debug(f)
> f()
debugging in: f()
debug: {
a <- lapply(1:10000, function(x) {
browser()
print(x)
})
}
Browse[2]> n
debug: a <- lapply(1:10000, function(x) {
browser()
print(x)
})
Browse[2]>
Called from: FUN(1:10000[[1L]], ...)
Browse[2]> c
[1] 1
Called from: FUN(1:10000[[2L]], ...) # browser()
Browse[2]>

64. apply browser
Browse[2]> evalq(FUN <- edit(FUN), parent.frame())
function(x) {
browser() #
print(x)
}
Browse[2]> evalq(fix(FUN), parent.frame())
Browse[2]> FUN <<- evalq(edit(FUN), parent.frame())

66. R

67. • HI!! http://kohske.wordpress.com/?s=r+debug
• An Introduction to the Interactive Debugging Tools in R http://
www.biostat.jhsph.edu/~rpeng/docs/R-debug-tools.pdf
• Debugging in R http://www.stats.uwo.ca/faculty/murdoch/
software/debuggingR/
• Summer Computing 2011 Week 3:R debugging + misc http://
www.stat.cmu.edu/~hseltman/711/Week3.pdf
• Rdebug http://www.math.ncu.edu.tw/~chenwc/R_note/
reference/debug/Rdebug.pdf