我想从“n x 1”向量
创建一个“n x 8”矩阵- 问题:我为什么要这样做?
- 答案:为了矩阵乘以“8×8”马尔可夫链概率转移矩阵,并返回预测状态的“n×8”矩阵
- 解决方案:我已经在下面的尝试3中解决了这个问题 - 但是想知道是否有更好的解决方法(而不是使用两个转置功能)?
R代码
创建一个虚拟的“n x 1”向量:(这里我们使用n = 2)
> temp_vector <- c("state 4", "state 7")
> temp_vector
[1] "state 4" "state 7"
预期产出:
NA NA NA TRUE NA NA NA NA
NA NA NA NA NA NA TRUE NA
尝试1:转换为矩阵:
> temp_matrix <- matrix(temp_vector,
ncol = 8, # there are 8 states
nrow = length(temp_vector) # there are 10 rows in the vector
)
> temp_matrix
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] "state 4" "state 4" "state 4" "state 4" "state 4" "state 4" "state 4" "state 4"
[2,] "state 7" "state 7" "state 7" "state 7" "state 7" "state 7" "state 7" "state 7"
尝试失败:这不理想,我想要一个矩阵,每行一个条目,而不是八个。
尝试2:将上面的stateSpace与矩阵进行比较,得到一个由TRUE / FALSE组成的矩阵:
> stateSpace <- c("state 1", "state 2", "state 3", "state 4", "state 5", "state 6", "state 7", "state 8")
> temp_matrix == stateSpace
state 1 state 2 state 3 state 4 state 5 state 6 state 7 state 8
[1,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[2,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
尝试2失败:预期每一行都有一个TRUE,其余行为FALSE
原因:(我认为)矩阵按列进行比较。
进一步研究尝试2,元素级别元素:
> temp_matrix[1,1] == colnames(temp_matrix)[1]
state 1
FALSE
> temp_matrix[1,2] == colnames(temp_matrix)[2]
state 2
FALSE
> temp_matrix[1,3] == colnames(temp_matrix)[3]
state 3
FALSE
> temp_matrix[1,4] == colnames(temp_matrix)[4]
state 4
TRUE
进一步研究尝试2,逐行这可行:
> temp_matrix[1,] == colnames(temp_matrix)[]
state 1 state 2 state 3 state 4 state 5 state 6 state 7 state 8
FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
> temp_matrix[2,] == colnames(temp_matrix)[]
state 1 state 2 state 3 state 4 state 5 state 6 state 7 state 8
FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE
尝试3:注意到R
中列式比较的上述知识> t(stateSpace == t(temp_matrix))
state 1 state 2 state 3 state 4 state 5 state 6 state 7 state 8
[1,] TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[2,] FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE
尝试3成功:创建此stackoverflow帖子以查看是否有更好的方法来解决此问题(而不是使用两个转置函数)
其他选择:dcast,reshape,spread;可悲的是也没有工作。
我尝试了reshape():
reshape(temp_vector, direction = "wide")
> Error in data[, timevar] : incorrect number of dimensions
我试过spread():
library(tidyr)
spread(temp_vector, key = numbers, value = value)
> Error in UseMethod("spread_") :
no applicable method for 'spread_' applied to an object of class "factor"
答案 0 :(得分:0)
试试这个:
> v <- c("state 4", "state 7")
> states <- c("state 1", "state 2", "state 3", "state 4",
+ "state 5", "state 6", "state 7", "state 8")
> m <- matrix(states, byrow = TRUE, nrow = 2, ncol = 8)
> m
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] # [,8]
# [1,] "state 1" "state 2" "state 3" "state 4" "state 5" "state 6" "state 7" "state 8"
# [2,] "state 1" "state 2" "state 3" "state 4" "state 5" "state 6" "state 7" "state 8"
> v == m
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
# [1,] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
# [2,] FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE
在R中,矩阵基本上是引擎盖下的矢量。在上面创建m
时,matrix
函数会“回收”其参数spaces
,因为它需要创建一个包含16个元素的矩阵。换句话说,以下两个函数调用产生相同的结果:
> matrix(states, byrow = TRUE, nrow = 2, ncol = 8)
> matrix(rep(states, 2), byrow = TRUE, nrow = 2, ncol = 8)
类似地,当v
和m
进行相等性比较时,v
被循环8次以生成长度为16的向量。换句话说,以下两个相等比较产生相同的结果:
> v == m
> rep(v, 8) == m
您可以将上述两个比较视为两个向量之间的比较,其中矩阵m
通过堆叠列转换回向量。您可以使用as.vector
查看m
对应的向量:
> as.vector(m)
# [1] "state 1" "state 1" "state 2" "state 2" "state 3" "state 3" "state 4" "state 4" "state 5"
# [10] "state 5" "state 6" "state 6" "state 7" "state 7" "state 8" "state 8"