| double {base} | R Documentation |
Double-Precision Vectors
Description
Create, coerce to or test for a double-precision vector.
Usage
double(length = 0)
as.double(x, ...)
is.double(x)
single(length = 0)
as.single(x, ...)
Arguments
length |
a non-negative integer specifying the desired length. Double values will be coerced to integer: supplying an argument of length other than one is an error. |
x |
object to be coerced or tested. |
... |
further arguments passed to or from other methods. |
Details
double creates a double-precision vector of the specified
length. The elements of the vector are all equal to 0.
It is identical to numeric.
as.double is a generic function. It is identical to
as.numeric. Methods should return an object of base type
"double".
is.double is a test of double type.
R has no single precision data type. All real numbers are
stored in double precision format. The functions as.single
and single are identical to as.double and double
except they set the attribute Csingle that is used in the
.C and .Fortran interface, and they are
intended only to be used in that context.
Value
double creates a double-precision vector of the specified
length. The elements of the vector are all equal to 0.
as.double attempts to coerce its argument to be of double type:
like as.vector it strips attributes including names.
(To ensure that an object is of double type without stripping
attributes, use storage.mode.) Character strings
containing optional whitespace followed by either a decimal
representation or a hexadecimal representation (starting with
0x or 0X) can be converted, as can special values such
as "NA", "NaN", "Inf" and "infinity",
irrespective of case.
as.double for factors yields the codes underlying the factor
levels, not the numeric representation of the labels, see also
factor.
is.double returns TRUE or FALSE depending on
whether its argument is of double type or not.
Double-precision values
All R platforms are required to work with values conforming to the
IEC 60559 (also known as IEEE 754) standard. This basically works
with a precision of 53 bits, and represents to that precision a range
of absolute values from about 2 \times 10^{-308} to
2 \times 10^{308}. It also has special values
NaN (many of them), plus and minus infinity and plus and
minus zero (although R acts as if these are the same). There are
also denormal(ized) (or subnormal) numbers with values
below the range given above but represented to less precision.
See .Machine for precise information on these limits.
Note that ultimately how double precision numbers are handled is down
to the CPU/FPU and compiler.
In IEEE 754-2008/IEC60559:2011 this is called ‘binary64’ format.
Note on names
It is a historical anomaly that R has two names for its
floating-point vectors, double and numeric
(and formerly had real).
double is the name of the type.
numeric is the name of the mode and also of the implicit
class. As an S4 formal class, use "numeric".
The potential confusion is that R has used mode
"numeric" to mean ‘double or integer’, which conflicts
with the S4 usage. Thus is.numeric tests the mode, not the
class, but as.numeric (which is identical to as.double)
coerces to the class.
References
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
https://en.wikipedia.org/wiki/IEEE_754-1985, https://en.wikipedia.org/wiki/IEEE_754-2008, https://en.wikipedia.org/wiki/IEEE_754-2019, https://en.wikipedia.org/wiki/Double_precision, https://en.wikipedia.org/wiki/Denormal_number.
See Also
integer, numeric, storage.mode.
Examples
is.double(1)
all(double(3) == 0)