Summaries | R Documentation |
Fast aggregation functions for booltype
vectors. namely bit
, all
, any
, anyNA
,
min
, max
, range
,
sum
and summary
.
Now all boolean summaries (except for anyNA
because the generic does not allow it) have an optional range
argument to restrict the range of evalution.
Note that the boolean summaries have meaning and return values differing from logical aggregation functions: they treat NA
as FALSE
,
min
, max
and range
give the minimum and maximum positions of TRUE
, summary
returns counts of FALSE
, TRUE
and the range
.
Note that you can force the boolean interpretation by calling the booltype method explicitely on any booltypes
input, e.g. min.booltype()
, see the examples.
## S3 method for class 'bit'
all(x, range = NULL, ...)
## S3 method for class 'bit'
any(x, range = NULL, ...)
## S3 method for class 'bit'
anyNA(x, recursive = FALSE)
## S3 method for class 'bit'
sum(x, range = NULL, ...)
## S3 method for class 'bit'
min(x, range = NULL, ...)
## S3 method for class 'bit'
max(x, range = NULL, ...)
## S3 method for class 'bit'
range(x, range = NULL, ...)
## S3 method for class 'bit'
summary(object, range = NULL, ...)
## S3 method for class 'bitwhich'
all(x, range = NULL, ...)
## S3 method for class 'bitwhich'
any(x, range = NULL, ...)
## S3 method for class 'bitwhich'
anyNA(x, recursive = FALSE)
## S3 method for class 'bitwhich'
sum(x, range = NULL, ...)
## S3 method for class 'bitwhich'
min(x, range = NULL, ...)
## S3 method for class 'bitwhich'
max(x, range = NULL, ...)
## S3 method for class 'bitwhich'
range(x, range = NULL, ...)
## S3 method for class 'bitwhich'
summary(object, range = NULL, ...)
## S3 method for class 'which'
all(x, range = NULL, ...)
## S3 method for class 'which'
any(x, range = NULL, ...)
## S3 method for class 'which'
anyNA(x, recursive = FALSE)
## S3 method for class 'which'
sum(x, range = NULL, ...)
## S3 method for class 'which'
min(x, range = NULL, ...)
## S3 method for class 'which'
max(x, range = NULL, ...)
## S3 method for class 'which'
range(x, range = NULL, ...)
## S3 method for class 'which'
summary(object, range = NULL, ...)
## S3 method for class 'booltype'
all(x, range = NULL, ...)
## S3 method for class 'booltype'
any(x, range = NULL, ...)
## S3 method for class 'booltype'
anyNA(x, ...)
## S3 method for class 'booltype'
sum(x, range = NULL, ...)
## S3 method for class 'booltype'
min(x, range = NULL, ...)
## S3 method for class 'booltype'
max(x, range = NULL, ...)
## S3 method for class 'booltype'
range(x, range = NULL, ...)
## S3 method for class 'booltype'
summary(object, range = NULL, ...)
## S3 method for class 'ri'
all(x, range = NULL, ...)
## S3 method for class 'ri'
any(x, range = NULL, ...)
## S3 method for class 'ri'
anyNA(x, recursive = FALSE)
## S3 method for class 'ri'
sum(x, ...)
## S3 method for class 'ri'
min(x, ...)
## S3 method for class 'ri'
max(x, ...)
## S3 method for class 'ri'
range(x, ...)
## S3 method for class 'ri'
summary(object, ...)
x |
an object of class bit or bitwhich |
range |
a |
... |
formally required but not used |
recursive |
formally required but not used |
object |
an object of class bit |
Summaries of bit
vectors are quite fast because we use a double loop that fixes each
word in a processor register. Furthermore we break out of looping as soon
as possible. Summaries of bitwhich
vectors are even faster, if the selection is very skewed.
as expected
Jens Oehlschlägel
length
l <- c(NA, FALSE, TRUE)
b <- as.bit(l)
all(l)
all(b)
all(b, range=c(3,3))
all.booltype(l, range=c(3,3))
min(l)
min(b)
sum(l)
sum(b)
summary(l)
summary(b)
summary.booltype(l)
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