是否可以向量化输出 bigz 对象的函数?
Is it possible to Vectorize functions that output bigz objects?
我怀疑一定有某种方法,例如 gmp
的 factorialZ
似乎是预矢量化的:
> library(gmp)
> factorialZ(0:9)
Big Integer ('bigz') object of length 10:
[1] 1 1 2 6 24 120 720 5040 40320 362880
与采用矢量输入并给出矢量输出的基本 R 函数一起使用似乎很舒服
> cumsum(factorialZ(0:9))
Big Integer ('bigz') object of length 10:
[1] 1 2 4 10 34 154 874 5914 46234 409114
然而,可能是因为强制转换,尝试 Vectorize
输出 bigZ 对象的函数将遇到可怕的失败:
leftFactorial<-function(n)
{
sum(factorialZ(0:(n-1)))
}
> Vectorize(leftFactorial)(1:10)
[1] 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 02 00 00 00 01 00 00
[36] 00 01 00 00 00 01 00 00 00 04 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 0a 00 00 00 01 00 00 00 01 00
[71] 00 00 01 00 00 00 22 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 9a 00 00 00 01 00 00 00 01 00 00 00 01
[106] 00 00 00 6a 03 00 00 01 00 00 00 01 00 00 00 01 00 00 00 1a 17 00 00 01 00 00 00 01 00 00 00 01 00 00 00
[141] 9a b4 00 00 01 00 00 00 01 00 00 00 01 00 00 00 1a 3e 06 00
那么当我们想要Vectorize
一个输出bigZ对象的函数时我们应该怎么做呢?
dput
允许可视化 bigZ
对象的内部结构:raw
的向量
> dput(factorialZ(0:9))
structure(as.raw(c(0x0a, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00,
0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00,
0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x18, 0x00,
0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x78,
0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
0xd0, 0x02, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
0x00, 0xb0, 0x13, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00,
0x00, 0x00, 0x80, 0x9d, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
0x00, 0x00, 0x00, 0x80, 0x89, 0x05, 0x00)), class = "bigz")
将 Vectorize
与 SIMPLIFY = TRUE
结合使用可生成 raw
个对象的简化矢量。
如评论中所述,SIMPLIFY = FALSE
有效,因为它保留了原始 Big Integer
类型:
Vectorize(leftFactorial, SIMPLIFY = FALSE)(1:10)
[[1]]
Big Integer ('bigz') :
[1] 1
[[2]]
Big Integer ('bigz') :
[1] 2
[[3]]
Big Integer ('bigz') :
[1] 4
[[4]]
Big Integer ('bigz') :
[1] 10
[[5]]
Big Integer ('bigz') :
[1] 34
[[6]]
Big Integer ('bigz') :
[1] 154
[[7]]
Big Integer ('bigz') :
[1] 874
[[8]]
Big Integer ('bigz') :
[1] 5914
[[9]]
Big Integer ('bigz') :
[1] 46234
[[10]]
Big Integer ('bigz') :
[1] 409114
我怀疑一定有某种方法,例如 gmp
的 factorialZ
似乎是预矢量化的:
> library(gmp)
> factorialZ(0:9)
Big Integer ('bigz') object of length 10:
[1] 1 1 2 6 24 120 720 5040 40320 362880
与采用矢量输入并给出矢量输出的基本 R 函数一起使用似乎很舒服
> cumsum(factorialZ(0:9))
Big Integer ('bigz') object of length 10:
[1] 1 2 4 10 34 154 874 5914 46234 409114
然而,可能是因为强制转换,尝试 Vectorize
输出 bigZ 对象的函数将遇到可怕的失败:
leftFactorial<-function(n)
{
sum(factorialZ(0:(n-1)))
}
> Vectorize(leftFactorial)(1:10)
[1] 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 02 00 00 00 01 00 00
[36] 00 01 00 00 00 01 00 00 00 04 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 0a 00 00 00 01 00 00 00 01 00
[71] 00 00 01 00 00 00 22 00 00 00 01 00 00 00 01 00 00 00 01 00 00 00 9a 00 00 00 01 00 00 00 01 00 00 00 01
[106] 00 00 00 6a 03 00 00 01 00 00 00 01 00 00 00 01 00 00 00 1a 17 00 00 01 00 00 00 01 00 00 00 01 00 00 00
[141] 9a b4 00 00 01 00 00 00 01 00 00 00 01 00 00 00 1a 3e 06 00
那么当我们想要Vectorize
一个输出bigZ对象的函数时我们应该怎么做呢?
dput
允许可视化 bigZ
对象的内部结构:raw
> dput(factorialZ(0:9))
structure(as.raw(c(0x0a, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00,
0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00,
0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x18, 0x00,
0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x78,
0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
0xd0, 0x02, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00,
0x00, 0xb0, 0x13, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00,
0x00, 0x00, 0x80, 0x9d, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01,
0x00, 0x00, 0x00, 0x80, 0x89, 0x05, 0x00)), class = "bigz")
将 Vectorize
与 SIMPLIFY = TRUE
结合使用可生成 raw
个对象的简化矢量。
如评论中所述,SIMPLIFY = FALSE
有效,因为它保留了原始 Big Integer
类型:
Vectorize(leftFactorial, SIMPLIFY = FALSE)(1:10)
[[1]]
Big Integer ('bigz') :
[1] 1
[[2]]
Big Integer ('bigz') :
[1] 2
[[3]]
Big Integer ('bigz') :
[1] 4
[[4]]
Big Integer ('bigz') :
[1] 10
[[5]]
Big Integer ('bigz') :
[1] 34
[[6]]
Big Integer ('bigz') :
[1] 154
[[7]]
Big Integer ('bigz') :
[1] 874
[[8]]
Big Integer ('bigz') :
[1] 5914
[[9]]
Big Integer ('bigz') :
[1] 46234
[[10]]
Big Integer ('bigz') :
[1] 409114