Is there any difference between testing isTRUE(all.equal(x, y)) and identical(x, y)?
测试isTRUE（all.equal（x，y））和相同（x，y）之间有什么区别吗？
The help page says:
帮助页面说：
Don't use 'all.equal' directly in 'if' expressions-either use 'isTRUE(all.equal(....))' or 'identical' if appropriate.
不要在'if'表达式中直接使用'all.equal' - 如果合适，使用'isTRUE（all.equal（....））'或'same'。
but that "if appropriate" leaves me in doubt. How do I decide which of the two is appropriate?
但“如果合适的话”让我怀疑。我如何确定哪两个合适？
3 个解决方案
#1
21
all.equal tests for near equality, while identical is more exact (e.g. it has no tolerance for differences, and it compares storage type). From ?identical:
all.equal测试接近相等，而相同则更精确（例如，它不具有差异容差，并且它比较存储类型）。来自？相同：
The function ‘all.equal’ is also sometimes used to test equality this way, but was intended for something different: it allows for small differences in numeric results.
函数'all.equal'有时也用于以这种方式测试相等性，但是用于不同的东西：它允许数值结果的微小差异。
And one reason you would wrap all.equal in isTRUE is because all.equal will report differences rather than simply return FALSE.
你在isTRUE中包装all.equal的一个原因是因为all.equal将报告差异而不是简单地返回FALSE。
#2
12
identical is fussier. For example:
相同是更麻烦。例如：
> identical(as.double(8), as.integer(8))
[1] FALSE
> all.equal(as.double(8), as.integer(8))
[1] TRUE
> as.double(8) == as.integer(8)
[1] TRUE
#3
9
In addition to differences in numerical tolerance and comparison of storage mode, unlike all.equal(), identical also tests equality of associated environments. Regular objects in R don't normally have associated environments -- they are most commonly associated with function and formula (and terms) objects. But to illustrate, I'll give two trivial objects different (newly created) environments:
除了数值容差的差异和存储模式的比较之外，与all.equal（）不同，相同的也测试相关环境的相等性。 R中的常规对象通常不具有关联环境 - 它们通常与函数和公式（和术语）对象相关联。但为了说明，我将给出两个不同的（新创建的）环境：
x <- 2; environment(x) <- new.env()
y <- 2; environment(y) <- new.env()
all.equal(x,y) ## TRUE
identical(x,y) ## FALSE
There is an ignore.environment argument:
有一个ignore.environment参数：
ignore.environment: logical indicating if their environments should be ignored when comparing closures.
ignore.environment：指示在比较闭包时是否应忽略其环境的逻辑。
but since it is only applied when comparing closures (i.e. functions), it doesn't make a difference in this case - nor will it make a difference when comparing formulae or terms objects.
但由于它仅在比较闭包（即函数）时应用，因此在这种情况下不会产生差异 - 在比较公式或术语对象时也不会产生差异。
#1
21
all.equal tests for near equality, while identical is more exact (e.g. it has no tolerance for differences, and it compares storage type). From ?identical:
all.equal测试接近相等，而相同则更精确（例如，它不具有差异容差，并且它比较存储类型）。来自？相同：
The function ‘all.equal’ is also sometimes used to test equality this way, but was intended for something different: it allows for small differences in numeric results.
函数'all.equal'有时也用于以这种方式测试相等性，但是用于不同的东西：它允许数值结果的微小差异。
And one reason you would wrap all.equal in isTRUE is because all.equal will report differences rather than simply return FALSE.
你在isTRUE中包装all.equal的一个原因是因为all.equal将报告差异而不是简单地返回FALSE。
#2
12
identical is fussier. For example:
相同是更麻烦。例如：
> identical(as.double(8), as.integer(8))
[1] FALSE
> all.equal(as.double(8), as.integer(8))
[1] TRUE
> as.double(8) == as.integer(8)
[1] TRUE
#3
9
In addition to differences in numerical tolerance and comparison of storage mode, unlike all.equal(), identical also tests equality of associated environments. Regular objects in R don't normally have associated environments -- they are most commonly associated with function and formula (and terms) objects. But to illustrate, I'll give two trivial objects different (newly created) environments:
除了数值容差的差异和存储模式的比较之外，与all.equal（）不同，相同的也测试相关环境的相等性。 R中的常规对象通常不具有关联环境 - 它们通常与函数和公式（和术语）对象相关联。但为了说明，我将给出两个不同的（新创建的）环境：
x <- 2; environment(x) <- new.env()
y <- 2; environment(y) <- new.env()
all.equal(x,y) ## TRUE
identical(x,y) ## FALSE
There is an ignore.environment argument:
有一个ignore.environment参数：
ignore.environment: logical indicating if their environments should be ignored when comparing closures.
ignore.environment：指示在比较闭包时是否应忽略其环境的逻辑。
but since it is only applied when comparing closures (i.e. functions), it doesn't make a difference in this case - nor will it make a difference when comparing formulae or terms objects.
但由于它仅在比较闭包（即函数）时应用，因此在这种情况下不会产生差异 - 在比较公式或术语对象时也不会产生差异。