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all.equal Test if Two Objects are (Nearly) Equal

Description

all.equal(x, y) is a utility to compare R objects x and y testing ‘near equality’. If they are different, comparison is still made to some extent, and a report of the differences is returned. Do not use all.equal directly in if expressions—either use isTRUE(all.equal(....)) or identical if appropriate.

Usage

all.equal(target, current, ...)

## S3 method for class 'numeric'
all.equal(target, current,
          tolerance = sqrt(.Machine$double.eps), scale = NULL,
          countEQ = FALSE,
          formatFUN = function(err, what) format(err),
          ..., check.attributes = TRUE)

## S3 method for class 'list'
all.equal(target, current, ...,
          check.attributes = TRUE, use.names = TRUE)

## S3 method for class 'environment'
all.equal(target, current, all.names = TRUE,
          evaluate = TRUE, ...)

## S3 method for class 'function'
all.equal(target, current, check.environment=TRUE, ...)

## S3 method for class 'POSIXt'
all.equal(target, current, ..., tolerance = 1e-3, scale,
          check.tzone = TRUE)


attr.all.equal(target, current, ...,
               check.attributes = TRUE, check.names = TRUE)

Arguments

Details

all.equal is a generic function, dispatching methods on the target argument. To see the available methods, use methods("all.equal"), but note that the default method also does some dispatching, e.g. using the raw method for logical targets.

Remember that arguments which follow ... must be specified by (unabbreviated) name. It is inadvisable to pass unnamed arguments in ... as these will match different arguments in different methods.

Numerical comparisons for scale = NULL (the default) are typically on relative difference scale unless the target values are close to zero: First, the mean absolute difference of the two numerical vectors is computed. If this is smaller than tolerance or not finite, absolute differences are used, otherwise relative differences scaled by the mean absolute target value. Note that these comparisons are computed only for those vector elements where target is not NA and differs from current. If countEQ is true, the equal and NA cases are counted in determining “sample” size.

If scale is numeric (and positive), absolute comparisons are made after scaling (dividing) by scale.

For complex target, the modulus (Mod) of the difference is used: all.equal.numeric is called so arguments tolerance and scale are available.

The list method compares components of target and current recursively, passing all other arguments, as long as both are “list-like”, i.e., fulfill either is.vector or is.list.

The environment method works via the list method, and is also used for reference classes (unless a specific all.equal method is defined).

The method for date-time objects uses all.equal.numeric to compare times (in "POSIXct" representation) with a default tolerance of 0.001 seconds, ignoring scale. A time zone mismatch between target and current is reported unless check.tzone = FALSE.

attr.all.equal is used for comparing attributes, returning NULL or a character vector.

Value

Either TRUE (NULL for attr.all.equal) or a vector of mode "character" describing the differences between target and current.

References

Chambers, J. M. (1998) Programming with Data. A Guide to the S Language. Springer (for =).

See Also

identical, isTRUE, ==, and all for exact equality testing.

Examples

all.equal(pi, 355/113)
# not precise enough (default tol) > relative error

d45 <- pi*(1/4 + 1:10)
stopifnot(
all.equal(tan(d45), rep(1, 10)))          # TRUE, but
all      (tan(d45) == rep(1, 10))         # FALSE, since not exactly
all.equal(tan(d45), rep(1, 10), tolerance = 0)  # to see difference

## advanced: equality of environments
ae <- all.equal(as.environment("package:stats"),
                asNamespace("stats"))
stopifnot(is.character(ae), length(ae) > 10,
          ## were incorrectly "considered equal" in R <= 3.1.1
          all.equal(asNamespace("stats"), asNamespace("stats")))

## A situation where  'countEQ = TRUE' makes sense:
x1 <- x2 <- (1:100)/10;  x2[2] <- 1.1*x1[2]
## 99 out of 100 pairs (x1[i], x2[i]) are equal:
plot(x1,x2, main = "all.equal.numeric() -- not counting equal parts")
all.equal(x1,x2) ## "Mean relative difference: 0.1"
mtext(paste("all.equal(x1,x2) :", all.equal(x1,x2)), line= -2)
##' extract the 'Mean relative difference' as number:
all.eqNum <- function(...) as.numeric(sub(".*:", '', all.equal(...)))
set.seed(17)
## When x2 is jittered, typically all pairs (x1[i],x2[i]) do differ:
summary(r <- replicate(100, all.eqNum(x1, x2*(1+rnorm(x1)*1e-7))))
mtext(paste("mean(all.equal(x1, x2*(1 + eps_k))) {100 x} Mean rel.diff.=",
            signif(mean(r), 3)), line = -4, adj=0)
## With argument  countEQ=TRUE, get "the same" (w/o need for jittering):
mtext(paste("all.equal(x1,x2, countEQ=TRUE) :",
          signif(all.eqNum(x1,x2, countEQ=TRUE), 3)), line= -6, col=2)

## comparison of date-time objects
now <- Sys.time()
stopifnot(
all.equal(now, now + 1e-4)  # TRUE (default tolerance = 0.001 seconds)
)
all.equal(now, now + 0.2)
all.equal(now, as.POSIXlt(now, "UTC"))
stopifnot(
all.equal(now, as.POSIXlt(now, "UTC"), check.tzone = FALSE)  # TRUE
)