下面的代码显然是错误的。有什么问题吗?
i <- 0.1
i <- i + 0.05
i
## [1] 0.15
if(i==0.15) cat("i equals 0.15") else cat("i does not equal 0.15")
## i does not equal 0.15
下面的代码显然是错误的。有什么问题吗?
i <- 0.1
i <- i + 0.05
i
## [1] 0.15
if(i==0.15) cat("i equals 0.15") else cat("i does not equal 0.15")
## i does not equal 0.15
当前回答
Dplyr::near()是一个用于测试两个浮点数向量是否相等的选项。下面是文档中的例子:
sqrt(2) ^ 2 == 2
#> [1] FALSE
library(dplyr)
near(sqrt(2) ^ 2, 2)
#> [1] TRUE
该函数有一个内置的公差参数:tol = . machine $double.eps^0.5,可以调整。默认参数与all.equal()的默认参数相同。
其他回答
Dplyr::near()是一个用于测试两个浮点数向量是否相等的选项。下面是文档中的例子:
sqrt(2) ^ 2 == 2
#> [1] FALSE
library(dplyr)
near(sqrt(2) ^ 2, 2)
#> [1] TRUE
该函数有一个内置的公差参数:tol = . machine $double.eps^0.5,可以调整。默认参数与all.equal()的默认参数相同。
双精度算术中的广义比较("<=",">=","="):
比较a <= b:
IsSmallerOrEqual <- function(a,b) {
# Control the existence of "Mean relative difference..." in all.equal;
# if exists, it results in character, not logical:
if ( class(all.equal(a, b)) == "logical" && (a<b | all.equal(a, b))) { return(TRUE)
} else if (a < b) { return(TRUE)
} else { return(FALSE) }
}
IsSmallerOrEqual(abs(-2-(-2.2)), 0.2) # TRUE
IsSmallerOrEqual(abs(-2-(-2.2)), 0.3) # TRUE
IsSmallerOrEqual(abs(-2-(-2.2)), 0.1) # FALSE
IsSmallerOrEqual(3,3); IsSmallerOrEqual(3,4); IsSmallerOrEqual(4,3)
# TRUE; TRUE; FALSE
比较>= b:
IsBiggerOrEqual <- function(a,b) {
# Control the existence of "Mean relative difference..." in all.equal;
# if exists, it results in character, not logical:
if ( class(all.equal(a, b)) == "logical" && (a>b | all.equal(a, b))) { return(TRUE)
} else if (a > b) { return(TRUE)
} else { return(FALSE) }
}
IsBiggerOrEqual(3,3); IsBiggerOrEqual(4,3); IsBiggerOrEqual(3,4)
# TRUE; TRUE; FALSE
比较a = b:
IsEqual <- function(a,b) {
# Control the existence of "Mean relative difference..." in all.equal;
# if exists, it results in character, not logical:
if ( class(all.equal(a, b)) == "logical" ) { return(TRUE)
} else { return(FALSE) }
}
IsEqual(0.1+0.05,0.15) # TRUE
这有点粗俗,但很快:
if(round(i, 10)==0.15) cat("i equals 0.15") else cat("i does not equal 0.15")
加上Brian的评论(这就是原因),你可以通过使用all来克服这个问题。平等:
# i <- 0.1
# i <- i + 0.05
# i
#if(all.equal(i, .15)) cat("i equals 0.15\n") else cat("i does not equal 0.15\n")
#i equals 0.15
根据Joshua的警告,这里是更新的代码(谢谢Joshua):
i <- 0.1
i <- i + 0.05
i
if(isTRUE(all.equal(i, .15))) { #code was getting sloppy &went to multiple lines
cat("i equals 0.15\n")
} else {
cat("i does not equal 0.15\n")
}
#i equals 0.15
我也遇到过类似的问题。我使用了以下解决方案。
@我发现这个工作围绕解决不平等的切割间隔。@我 通过将选项设置为2位,did使用了r中的舍入函数 没有解决问题。
options(digits = 2)
cbind(
seq( from = 1, to = 9, by = 1 ),
cut( seq( from = 1, to = 9, by = 1), c( 0, 3, 6, 9 ) ),
seq( from = 0.1, to = 0.9, by = 0.1 ),
cut( seq( from = 0.1, to = 0.9, by = 0.1), c( 0, 0.3, 0.6, 0.9 )),
seq( from = 0.01, to = 0.09, by = 0.01 ),
cut( seq( from = 0.01, to = 0.09, by = 0.01), c( 0, 0.03, 0.06, 0.09 ))
)
基于选项(数字= 2)的不平等切割间隔输出:
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 1 0.1 1 0.01 1
[2,] 2 1 0.2 1 0.02 1
[3,] 3 1 0.3 2 0.03 1
[4,] 4 2 0.4 2 0.04 2
[5,] 5 2 0.5 2 0.05 2
[6,] 6 2 0.6 2 0.06 3
[7,] 7 3 0.7 3 0.07 3
[8,] 8 3 0.8 3 0.08 3
[9,] 9 3 0.9 3 0.09 3
options(digits = 200)
cbind(
seq( from = 1, to = 9, by = 1 ),
cut( round(seq( from = 1, to = 9, by = 1), 2), c( 0, 3, 6, 9 ) ),
seq( from = 0.1, to = 0.9, by = 0.1 ),
cut( round(seq( from = 0.1, to = 0.9, by = 0.1), 2), c( 0, 0.3, 0.6, 0.9 )),
seq( from = 0.01, to = 0.09, by = 0.01 ),
cut( round(seq( from = 0.01, to = 0.09, by = 0.01), 2), c( 0, 0.03, 0.06, 0.09 ))
)
基于圆函数的等切间隔输出:
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 1 0.1 1 0.01 1
[2,] 2 1 0.2 1 0.02 1
[3,] 3 1 0.3 1 0.03 1
[4,] 4 2 0.4 2 0.04 2
[5,] 5 2 0.5 2 0.05 2
[6,] 6 2 0.6 2 0.06 2
[7,] 7 3 0.7 3 0.07 3
[8,] 8 3 0.8 3 0.08 3
[9,] 9 3 0.9 3 0.09 3