setops-methods | R Documentation |
Performs set operations on IntegerRanges and IntegerRangesList objects.
## Vector-wise set operations
## --------------------------
## S4 method for signature 'IntegerRanges,IntegerRanges'
union(x, y)
## S4 method for signature 'Pairs,missing'
union(x, y, ...)
## S4 method for signature 'IntegerRanges,IntegerRanges'
intersect(x, y)
## S4 method for signature 'Pairs,missing'
intersect(x, y, ...)
## S4 method for signature 'IntegerRanges,IntegerRanges'
setdiff(x, y)
## S4 method for signature 'Pairs,missing'
setdiff(x, y, ...)
## Element-wise (aka "parallel") set operations
## --------------------------------------------
## S4 method for signature 'IntegerRanges,IntegerRanges'
punion(x, y, fill.gap=FALSE)
## S4 method for signature 'Pairs,missing'
punion(x, y, ...)
## S4 method for signature 'IntegerRanges,IntegerRanges'
pintersect(x, y, resolve.empty=c("none", "max.start", "start.x"))
## S4 method for signature 'Pairs,missing'
pintersect(x, y, ...)
## S4 method for signature 'IntegerRanges,IntegerRanges'
psetdiff(x, y)
## S4 method for signature 'Pairs,missing'
psetdiff(x, y, ...)
## S4 method for signature 'IntegerRanges,IntegerRanges'
pgap(x, y)
x , y |
Objects representing ranges. |
fill.gap |
Logical indicating whether or not to force a union by using the rule
|
resolve.empty |
One of |
... |
The methods for Pairs objects pass any extra argument
to the internal call to |
The union
, intersect
and setdiff
methods
for IntegerRanges objects return a "normal" IntegerRanges
object representing the union, intersection and (asymmetric!)
difference of the sets of integers represented by x
and
y
.
punion
, pintersect
, psetdiff
and pgap
are generic functions that compute the element-wise (aka "parallel")
union, intersection, (asymmetric!) difference and gap between
each element in x
and its corresponding element in y
.
Methods for IntegerRanges objects are defined. For these methods,
x
and y
must have the same length (i.e. same number
of ranges). They return a IntegerRanges object parallel
to x
and y
i.e. where the i-th range corresponds
to the i-th range in x
and iny
) and represents
the union/intersection/difference/gap of/between the corresponding
x[i]
and y[i]
.
If x
is a Pairs
object, then y
should be missing, and the operation is performed between the members
of each pair.
By default, pintersect
will throw an error when an "ambiguous
empty range" is formed. An ambiguous empty range can occur three
different ways: 1) when corresponding non-empty ranges elements x
and y
have an empty intersection, 2) if the position of an empty
range element does not fall within the corresponding limits of a non-empty
range element, or 3) if two corresponding empty range elements do not have
the same position. For example if empty range element [22,21] is intersected
with non-empty range element [1,10], an error will be produced; but if
it is intersected with the range [22,28], it will produce [22,21].
As mentioned in the Arguments section above, this behavior can be
changed using the resolve.empty
argument.
On IntegerRanges objects, union
, intersect
, and
setdiff
return an IRanges instance that is guaranteed
to be normal (see isNormal
) but is NOT promoted to
NormalIRanges.
On IntegerRanges objects, punion
, pintersect
,
psetdiff
, and pgap
return an object of the same class
and length as their first argument.
H. Pagès and M. Lawrence
pintersect
is similar to narrow
, except the
end points are absolute, not relative. pintersect
is also
similar to restrict
, except ranges outside of the
restriction become empty and are not discarded.
setops-methods in the GenomicRanges package for set operations on genomic ranges.
findOverlaps-methods for finding/counting overlapping ranges.
intra-range-methods and inter-range-methods for intra range and inter range transformations.
IntegerRanges and IntegerRangesList objects. In particular, normality of an IntegerRanges object is discussed in the man page for IntegerRanges objects.
mendoapply
in the S4Vectors package.
x <- IRanges(c(1, 5, -2, 0, 14), c(10, 9, 3, 11, 17))
subject <- Rle(1:-3, 6:2)
y <- Views(subject, start=c(14, 0, -5, 6, 18), end=c(20, 2, 2, 8, 20))
## Vector-wise operations:
union(x, ranges(y))
union(ranges(y), x)
intersect(x, ranges(y))
intersect(ranges(y), x)
setdiff(x, ranges(y))
setdiff(ranges(y), x)
## Element-wise (aka "parallel") operations:
try(punion(x, ranges(y)))
punion(x[3:5], ranges(y)[3:5])
punion(x, ranges(y), fill.gap=TRUE)
try(pintersect(x, ranges(y)))
pintersect(x[3:4], ranges(y)[3:4])
pintersect(x, ranges(y), resolve.empty="max.start")
psetdiff(ranges(y), x)
try(psetdiff(x, ranges(y)))
start(x)[4] <- -99
end(y)[4] <- 99
psetdiff(x, ranges(y))
pgap(x, ranges(y))
## On IntegerRangesList objects:
irl1 <- IRangesList(a=IRanges(c(1,2),c(4,3)), b=IRanges(c(4,6),c(10,7)))
irl2 <- IRangesList(c=IRanges(c(0,2),c(4,5)), a=IRanges(c(4,5),c(6,7)))
union(irl1, irl2)
intersect(irl1, irl2)
setdiff(irl1, irl2)
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