Hi
Actually you did not. Your original question was:
> Error in if (fraction <= 1) { : missing value where TRUE/FALSE needed
> I used this:
> var <- ifelse(test$operator == 'T14', 1, 0)
> operator has several values like T1, T3, T7, T15, T31, T37
> For some values like T3, T7 it works fine but for majority of values
> it gives error.
> When I use: is.na(ts$operator), it shows all false values so no NAs.
Only now we could inspect your whole code and it was already pointed that the
error does not originate from ifelse.
With the same data and ifelse code I did not get any error.
test <- structure(list(DepthTree = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
<snip>
> str(test)
'data.frame': 146 obs. of 15 variables:
$ DepthTree : num 1 1 1 1 1 1 1 1 1 1 ...
<snip>
$ numCovered : num 0 0 0 0 0 0 0 0 0 0 ...
$ operator : Factor w/ 16 levels "T0","T1","T2",..: 4 4 7 8 8 8 11 4 10 7
...
$ methodReturn : Factor w/ 22 levels "I","V","Z","method",..: 2 2 2 2 2 2 2 4
4 2 ...
$ numTestsCover: num 16 15 15 16 15 15 15 4 4 16 ...
$ mutantAssert : num 55 55 55 55 55 55 55 13 13 55 ...
$ classAssert : num 3 3 3 3 3 3 3 3 3 3 ...
$ isKilled : Factor w/ 2 levels "yes","no": 2 2 2 2 2 2 2 2 2 2 ...
>
prot <- ifelse(test$operator == 'T13', 1, 0)
the most probable source of the error is
fc= fairness_check(explainer,
protected = prot,
privileged = privileged)
so you should check explainer and privileged
Cheers
Petr
From: javed khan <javedbtk...@gmail.com>
Sent: Wednesday, January 26, 2022 3:45 PM
To: PIKAL Petr <petr.pi...@precheza.cz>
Cc: R-help <r-help@r-project.org>
Subject: Re: [R] Error in if (fraction <= 1) { : missing value where
TRUE/FALSE needed
Hi Pikal, why would I hide something? I provided just a code where error is.
Full code is:
index= sample(1:nrow(data), 0.7*nrow(data))
train= data[index,]
test= data[-index,]
task = TaskClassif$new("data", backend = train, target = "isKilled")
learner= lrn("classif.gbm", predict_type = "prob")
model= learner$train(task )
explainer = explain_mlr3(model,
data = test[,-15],
y = as.numeric(test$isKilled)-1,
label="GBM")
prot <- ifelse(test$operator == 'T13', 1, 0)
privileged <- '1'
fc= fairness_check(explainer,
protected = prot,
privileged = privileged)
plot(fc)
And my data is the following:
str(test)
'data.frame': 146 obs. of 15 variables:
$ DepthTree : num 1 1 1 1 1 1 1 1 1 1 ...
$ NumSubclass : num 0 0 0 0 0 0 0 0 0 0 ...
$ McCabe : num 1 3 3 3 3 3 3 1 1 2 ...
$ LOC : num 3 10 10 10 10 10 10 4 4 5 ...
$ DepthNested : num 1 2 2 2 2 2 2 1 1 2 ...
$ CA : num 1 1 1 1 1 1 1 1 1 1 ...
$ CE : num 2 2 2 2 2 2 2 2 2 2 ...
$ Instability : num 0.667 0.667 0.667 0.667 0.667 0.667 0.667 0.667 0.667
0.667 ...
$ numCovered : num 0 0 0 0 0 0 0 0 0 0 ...
$ operator : Factor w/ 16 levels "T0","T1","T2",..: 4 4 7 8 8 8 11 4 10 7
...
$ methodReturn : Factor w/ 22 levels "I","V","Z","method",..: 2 2 2 2 2 2 2 4
4 2 ...
$ numTestsCover: num 16 15 15 16 15 15 15 4 4 16 ...
$ mutantAssert : num 55 55 55 55 55 55 55 13 13 55 ...
$ classAssert : num 3 3 3 3 3 3 3 3 3 3 ...
$ isKilled : Factor w/ 2 levels "yes","no": 2 2 2 2 2 2 2 2 2 2 ...
> dput(test)
structure(list(DepthTree = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 2, 2, 1, 2, 1, 1, 1), NumSubclass = c(0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2), McCabe = c(1, 3, 3,
3, 3, 3, 3, 1, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1, 1, 1, 2,
2, 2, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 5, 5, 5, 5, 5, 5, 5, 5, 2, 2, 2,
2, 5, 5, 5, 5, 5, 5, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 2, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1,
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 2, 2,
2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1), LOC = c(3,
10, 10, 10, 10, 10, 10, 4, 4, 5, 22, 22, 22, 22, 22, 22, 22,
22, 3, 3, 3, 3, 3, 8, 8, 8, 4, 23, 23, 23, 23, 23, 23, 23, 23,
23, 23, 16, 16, 16, 16, 16, 16, 8, 8, 8, 8, 8, 8, 16, 16, 16,
16, 16, 16, 20, 20, 20, 20, 20, 20, 20, 20, 7, 7, 7, 7, 18, 18,
18, 18, 18, 18, 3, 15, 15, 15, 15, 15, 15, 15, 15, 15, 6, 15,
15, 15, 15, 15, 15, 15, 15, 15, 9, 9, 9, 9, 9, 9, 4, 4, 3, 3,
3, 3, 3, 4, 4, 6, 6, 5, 5, 5, 8, 8, 8, 3, 3, 3, 3, 3, 3, 7, 3,
3, 3, 3, 15, 15, 15, 15, 15, 15, 15, 15, 3, 3, 3, 3, 4, 4, 8,
4, 4, 4, 3), DepthNested = c(1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 4,
4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 2, 2, 2, 1, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1,
3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2,
1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1,
1, 1, 1, 1, 2, 1, 1, 1, 1), CA = c(1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 1), CE = c(2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 2, 2, 2, 2, 2, 2, 0, 2, 0, 0, 2), Instability = c(0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.667, 0.667, 0.667, 0.667, 0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
0.667, 0.667, 0.667, 0.667, 0.667, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0, 0.667, 0, 0,
0.667), numCovered = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
150, 54, 54, 123, 54, 54, 123, 54, 189, 189, 189, 138, 33, 18,
27, 27, 18, 27, 15, 54, 54, 150, 150, 54, 150, 150, 54, 150,
66, 60, 12, 60, 15, 45, 72, 12, 12, 45, 255, 255, 255, 255, 129,
129, 0, 0, 6, 6, 6, 6, 303, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 15, 21, 12, 12, 12, 12, 12, 12, 12, 12,
48, 1557, 9, 12, 0, 0, 141, 0, 21, 21, 21), operator = structure(c(4L,
4L, 7L, 8L, 8L, 8L, 11L, 4L, 10L, 7L, 4L, 7L, 8L, 8L, 8L, 9L,
9L, 11L, 7L, 8L, 2L, 8L, 8L, 7L, 8L, 10L, 11L, 1L, 2L, 2L, 4L,
8L, 8L, 8L, 8L, 10L, 12L, 4L, 6L, 6L, 8L, 8L, 8L, 7L, 7L, 8L,
8L, 9L, 9L, 1L, 4L, 6L, 8L, 8L, 8L, 1L, 1L, 7L, 7L, 7L, 8L, 8L,
13L, 7L, 8L, 9L, 9L, 1L, 1L, 2L, 7L, 8L, 10L, 10L, 4L, 7L, 7L,
7L, 8L, 8L, 8L, 9L, 9L, 10L, 1L, 8L, 8L, 8L, 8L, 10L, 11L, 11L,
11L, 6L, 7L, 8L, 9L, 9L, 10L, 6L, 10L, 1L, 4L, 7L, 10L, 6L, 7L,
13L, 7L, 13L, 7L, 8L, 9L, 4L, 6L, 9L, 8L, 10L, 8L, 10L, 8L, 10L,
9L, 8L, 10L, 13L, 10L, 2L, 7L, 7L, 8L, 8L, 9L, 11L, 11L, 10L,
10L, 13L, 13L, 8L, 8L, 9L, 4L, 6L, 10L, 10L), .Label = c("T0",
"T1", "T2", "T3", "T4", "T5", "T6", "T7", "T8", "T9", "T10",
"T11", "T12", "T13", "T14", "T15"), class = "factor"), methodReturn =
structure(c(2L,
2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L,
3L, 3L, 1L, 1L, 3L, 3L, 3L, 3L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 2L, 2L, 4L, 4L, 1L, 3L, 1L, 1L,
4L), .Label = c("I", "V", "Z", "method", "D", "[D", "[[D", "J",
"[I", "C", "[J", "[C", "[S", "F", "[F", "[B", "S", "B", "[Z",
"[[S", "[[B", "[[Z"), class = "factor"), numTestsCover = c(16,
15, 15, 16, 15, 15, 15, 4, 4, 16, 16, 16, 15, 15, 15, 16, 16,
15, 3, 3, 2, 2, 2, 16, 11, 16, 4, 16, 16, 3, 16, 16, 4, 16, 16,
16, 16, 2, 3, 2, 1, 4, 1, 16, 15, 16, 15, 16, 16, 2, 2, 2, 3,
2, 2, 4, 5, 5, 4, 5, 5, 4, 5, 4, 4, 4, 4, 4, 3, 4, 4, 3, 4, 4,
5, 5, 4, 4, 5, 4, 4, 5, 4, 4, 4, 3, 4, 4, 4, 4, 3, 3, 4, 4, 4,
4, 4, 6, 6, 0, 0, 2, 2, 2, 2, 7, 17, 17, 15, 15, 15, 15, 15,
16, 16, 16, 16, 15, 16, 16, 15, 17, 17, 16, 16, 5, 4, 4, 4, 4,
4, 4, 4, 4, 4, 16, 16, 3, 4, 0, 0, 5, 0, 4, 4, 1), mutantAssert = c(55,
55, 55, 55, 55, 55, 55, 13, 13, 55, 55, 55, 55, 55, 55, 55, 55,
55, 9, 9, 9, 9, 9, 55, 41, 55, 13, 55, 55, 5, 55, 55, 13, 55,
55, 55, 55, 8, 13, 8, 4, 13, 4, 55, 55, 55, 55, 55, 55, 9, 9,
9, 9, 9, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 6, 9, 9, 6,
9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 6, 9, 9, 9, 9, 6, 6, 9,
9, 9, 9, 9, 14, 14, 0, 0, 2, 2, 2, 2, 15, 58, 58, 55, 55, 55,
55, 55, 58, 58, 58, 55, 55, 55, 55, 55, 58, 58, 58, 58, 9, 9,
6, 6, 6, 6, 6, 6, 6, 6, 55, 55, 5, 13, 0, 0, 11, 0, 9, 9, 8),
classAssert = c(3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 1, 1, 3, 0,
3, 3, 0), isKilled = structure(c(2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L,
1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 2L, 1L, 1L, 1L), .Label = c("yes", "no"), class = "factor")),
row.names = c(3L,
9L, 12L, 13L, 14L, 15L, 19L, 21L, 22L, 24L, 28L, 29L, 39L, 44L,
46L, 51L, 52L, 57L, 62L, 63L, 68L, 71L, 73L, 75L, 77L, 80L, 83L,
84L, 85L, 86L, 90L, 95L, 100L, 102L, 103L, 108L, 112L, 120L,
122L, 123L, 142L, 143L, 146L, 158L, 159L, 160L, 163L, 167L, 168L,
170L, 174L, 176L, 183L, 186L, 192L, 196L, 199L, 203L, 205L, 206L,
208L, 214L, 221L, 226L, 229L, 233L, 234L, 235L, 236L, 237L, 238L,
249L, 252L, 255L, 260L, 267L, 270L, 271L, 273L, 275L, 276L, 277L,
278L, 286L, 288L, 293L, 295L, 297L, 298L, 300L, 301L, 302L, 306L,
312L, 313L, 316L, 317L, 331L, 333L, 338L, 341L, 342L, 344L, 346L,
348L, 359L, 370L, 375L, 378L, 381L, 382L, 383L, 386L, 389L, 390L,
394L, 397L, 400L, 402L, 403L, 404L, 408L, 415L, 418L, 419L, 423L,
425L, 426L, 429L, 431L, 432L, 433L, 444L, 446L, 447L, 448L, 449L,
451L, 452L, 457L, 458L, 470L, 474L, 476L, 479L, 484L), class = "data.frame")
On Wed, Jan 26, 2022 at 3:29 PM PIKAL Petr <mailto:petr.pi...@precheza.cz>
wrote:
Hi
It seems that you are hiding what you really do.
This
> options(error = NULL)
works fine without any error. So please If you want some reasonable answer
post question with data and code which is causing the error.
My wild guess is that you have some objects in your environment and you do
not know that they are used in you commands. Try to start fresh R session
and try to inspect your environment with
ls()
Cheers
Petr
> -----Original Message-----
> From: R-help <mailto:r-help-boun...@r-project.org> On Behalf Of javed khan
> Sent: Wednesday, January 26, 2022 3:05 PM
> To: Ivan Krylov <mailto:krylov.r...@gmail.com>
> Cc: R-help <mailto:r-help@r-project.org>
> Subject: Re: [R] Error in if (fraction <= 1) { : missing value where
TRUE/FALSE
> needed
>
> Ivan, thanks
>
> When I use options(error = NULL)
>
> it says: Error during wrapup: missing value where TRUE/FALSE needed
> Error: no more error handlers available (recursive errors?); invoking
'abort'
> restart
>
> With traceback(), I get
>
> 4: readable_number(max_value - min_value, FALSE)
> 3: get_nice_ticks(lower_bound, upper_bound)
>
> On Wed, Jan 26, 2022 at 2:53 PM Ivan Krylov <mailto:krylov.r...@gmail.com>
> wrote:
>
> > On Wed, 26 Jan 2022 14:47:16 +0100
> > javed khan <mailto:javedbtk...@gmail.com> wrote:
> >
> > > Error in if (fraction <= 1) { : missing value where TRUE/FALSE
> > > needed
> >
> > > var <- ifelse(test$operator == 'T14', 1, 0)
> >
> > The error must be in a place different from your test$operator
> > comparison. Have you tried traceback() to get the call stack leading
> > to the error? Or options(error = recover) to land in a debugger
> > session the moment an uncaught error happens? (Use options(error =
> > NULL) to go back to the default behaviour.)
> >
> > Unrelated: var <- test$operator == 'T14' will also give you an
> > equivalent logical vector with a bit less work.
> >
> > --
> > Best regards,
> > Ivan
> >
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
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