Thanks for exploring these issue. This looks very useful.
I get:
> str( first_log(NA) )
logi TRUE
> str( first_int(NA_integer_) )
int NA
> str( first_num(NA_real_) )
num NA
> str( first_char(NA_character_) )
chr "NA"
For first_log: a bool can either be true or false. In R logical vectors
are represented as arrays of ints. When we coerce to bool, we test
whether the value is not 0. This works for most cases. I guess
conversion to bool should be avoided.
We have the is_na template function that can help:
> evalCpp( 'traits::is_na<LGLSXP>( NA_LOGICAL )' )
[1] TRUE
> evalCpp( 'traits::is_na<REALSXP>( NA_REAL )' )
[1] TRUE
And from this I can see we don't have is_na<STRSXP>, will fix this.
> str( evalCpp( 'traits::get_na<REALSXP>()' ) )
num NA
> str( evalCpp( 'traits::get_na<INTSXP>()' ) )
int NA
I guess we could come up with a nicer syntax for these, maybe static
functions in Vector<> so that we could do :
IntegerVector::is_na( )
NumericVector::get_na( )
...
More below:
Le 15/11/12 23:36, Hadley Wickham a écrit :
Hi all,
I'm working on a description of how missing values work in Rcpp
(expanding on FAQ 3.4). I'd really appreciate any comments,
corrections or suggestions on the text below.
Thanks!
Hadley
# Missing values
If you're working with missing values, you need to know two things:
* what happens when you put missing values in scalars (e.g. `double`)
* how to get and set missing values in vectors (e.g. `NumericVector`)
## Scalars
The following code explores what happens when you coerce the first
element of a vector into the corresponding scalar:
cppFunction('int first_int(IntegerVector x) {
return(x[0]);
}')
cppFunction('double first_num(NumericVector x) {
return(x[0]);
}')
cppFunction('std::string first_char(CharacterVector x) {
return((std::string) x[0]);
}')
cppFunction('bool first_log(LogicalVector x) {
return(x[0]);
}')
first_log(NA)
first_int(NA_integer_)
first_num(NA_real_)
first_char(NA_character_)
So
* `NumericVector` -> `double`: NAN
* `IntegerVector` -> `int`: NAN (not sure how this works given that
integer types don't usually have a missing value)
> str( evalCpp( 'std::numeric_limits<int>::min()' ) )
int NA
This is how NA_integer_ is represented.
* `CharacterVector` -> `std::string`: the string "NA"
Ouch. We definitely need to fix this. Will do.
* `LogicalVector` -> `bool`: TRUE
If you're working with doubles, depending on your problem, you may be
able to get away with ignoring missing values and working with NaNs.
R's missing values are a special type of the IEEE 754 floating point
number NaN (not a number). That means if you coerce them to `double`
or `int` in your C++ code, they will behave like regular NaN's.
In a logical context they always evaluate to FALSE:
evalCpp("NAN == 1")
evalCpp("NAN < 1")
evalCpp("NAN > 1")
evalCpp("NAN == NAN")
But be careful when combining then with boolean values:
evalCpp("NAN && TRUE")
evalCpp("NAN || FALSE")
In numeric contexts, they propagate similarly to NA in R:
evalCpp("NAN + 1")
evalCpp("NAN - 1")
evalCpp("NAN / 1")
evalCpp("NAN * 1")
That's very useful to let people know of these issues.
## Vectors
To set a missing value in a vector, you need to use a missing value
specific to the type of vector. Unfortunately these are not named
terribly consistently:
cppFunction('
List missing_sampler() {
NumericVector num(1);
num[0] = NA_REAL;
IntegerVector intv(1);
intv[0] = NA_INTEGER;
LogicalVector lgl(1);
lgl[0] = NA_LOGICAL;
CharacterVector chr(1);
chr[0] = NA_STRING;
List out(4);
out[0] = num;
out[1] = intv;
out[2] = lgl;
out[3] = chr;
return(out);
}
')
str(missing_sampler())
To check if a value in a vector is missing, use `ISNA`:
cppFunction('
LogicalVector is_na2(NumericVector x) {
LogicalVector out(x.size());
NumericVector::iterator x_it;
LogicalVector::iterator out_it;
for (x_it = x.begin(), out_it = out.begin(); x_it != x.end();
x_it++, out_it++) {
*out_it = ISNA(*x_it);
}
return(out);
}
')
is_na2(c(NA, 5.4, 3.2, NA))
Rcpp provides a helper function called `is_na` that works similarly to
`is_na2` above, producing a logical vector that's true where the value
in the vector was missing.
As said above, I'll add
...Vector::is_na
...Vector::get_na
to have something more consistent and not as cryptic as
traits::is_na<...>( ). People should not need to know what REALSXP,
INTSXP, LGLSXP, ... mean.
--
Romain Francois
Professional R Enthusiast
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blog: http://romainfrancois.blog.free.fr
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