=和==有什么区别? [英] What is the difference between = and ==?

问题描述

=和==有什么区别?我发现双等号允许我的脚本运行，而一个等号产生错误消息的情况.什么时候应该使用==代替=?

What is the difference between = and ==? I have found cases where the double equal sign will allow my script to run while one equal sign produces an error message. When should I use == instead of =?

推荐答案

=的含义取决于上下文. ==始终用于测试相等性.

It depends on context as to what = means. == is always for testing equality.

=可以

在大多数情况下，

1. 可以代替赋值运算符<-.

1. in most cases used as a drop-in replacement for <-, the assignment operator.

> x = 10
> x
[1] 10

用作用于将值分配给函数调用中的参数的键-值对的分隔符.

used as the separator for key-value pairs used to assign values to arguments in function calls.

rnorm(n = 10, mean = 5, sd = 2)

由于上述2，=不能在所有情况下用作<-的替代产品.考虑

Because of 2. above, = can't be used as a drop-in replacement for <- in all situations. Consider

> rnorm(N <- 10, mean = 5, sd = 2)
 [1] 4.893132 4.572640 3.801045 3.646863 4.522483 4.881694 6.710255 6.314024
 [9] 2.268258 9.387091
> rnorm(N = 10, mean = 5, sd = 2)
Error in rnorm(N = 10, mean = 5, sd = 2) : unused argument (N = 10)
> N
[1] 10

现在，有些人会认为rnorm(N <- 10, mean = 5, sd = 2)编程不佳，但这是有效的，您需要了解=和<-之间的分配差异.

Now some would consider rnorm(N <- 10, mean = 5, sd = 2) poor programming, but it is valid and you need to be aware of the differences between = and <- for assignment.

==始终用于相等性测试:

== is always used for equality testing:

> set.seed(10)
> logi <- sample(c(TRUE, FALSE), 10, replace = TRUE)
> logi
 [1] FALSE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE
> logi == TRUE
 [1] FALSE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE FALSE  TRUE
> seq.int(1, 10) == 5L
 [1] FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE

也请小心使用==，因为它确实等于和涉及浮点运算的计算机上，您可能无法获得预期的答案.例如，来自?'==':

Do be careful with == too however, as it really means exactly equal to and on a computer where floating point operations are involved you may not get the answer you were expecting. For example, from ?'==':

> x1 <- 0.5 - 0.3
> x2 <- 0.3 - 0.1
> x1 == x2                           # FALSE on most machines
[1] FALSE
> identical(all.equal(x1, x2), TRUE) # TRUE everywhere
[1] TRUE

其中all.equal()测试是否相等，这是由于精度/浮点运算的损失而导致的一些模糊性.

where all.equal() tests for equality allowing for a little bit of fuzziness due to loss of precision/floating point operations.

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