如何计算矩阵A和矩阵B之间R中的欧几里德距离,如下所示:
我有两个矩阵,即矩阵A和矩阵B
矩阵A:
[,1][,2]
[1,] 1 1
[2,] 1 2
[3,] 2 1
[4,] 2 2
[5,] 10 1
[6,] 10 2
[7,] 11 1
[8,] 11 2
[9,] 5 5
[10,] 5 6 矩阵B:
[,1][,2][,3][,4][,5][,6]
[1,] 2 1 5 5 10 1
[2,] 1 1 2 1 10 1
[3,] 5 5 5 6 11 2
[4,] 2 2 5 5 10 1
[5,] 2 1 5 6 5 5
[6,] 2 2 5 5 11 1
[7,] 2 1 5 5 10 1
[8,] 1 1 5 6 11 1
[9,] 2 1 5 5 10 1
[10,] 5 6 11 1 10 2
I want the Result matrix (euclidean distance) to be as per below:
[1,] [,2] [,3]
[1,] 1.00 5.66 9.00
[2,] 1.00 1.41
[3,]
[4,]
[5,]
[7,]
[8,]
[9,]
[10]对于矩阵A中的每一行,计算到每一行矩阵B中每一列的欧氏距离。
例如,要在结果矩阵中获得以下结果的答案:
[,1]
[1,] 计算结果如下:
A(1,1) - From Matrix A
B(2,1) - From Matrix B
= sqrt((xA -xB)^2 + (yA -yB)^2)
= sqrt((1-2)^2 + (1-1)^2)
= 1.00
xA and yA from Matrix A
xB and yB from Matrix B若要在结果矩阵中获得下列答案,请执行以下操作:
[,2]
[1,] 5.66计算结果如下:
A(1,1) - From Matrix A
B(5,5) - From Matrix B
= sqrt((xA -xB)^2 + (yA -yB)^2)
= sqrt((1-5)^2 + (1-5)^2)
= 5.66若要在结果矩阵中获得下列答案,请执行以下操作:
[,3]
[1,] 9.00计算结果如下:
A(1,1) - From Matrix A
B(10,1) - From Matrix B
= sqrt((xA -xB)^2 + (yA -yB)^2)
= sqrt((1-10)^2 + (1-1)^2)
= 9.00目前,我下面的代码只有在矩阵A和B是相同尺寸的情况下才能工作:
distance <- function(MatrixA, MatrixB) {
resultMatrix <- matrix(NA, nrow=dim(MatrixA)[1], ncol=dim(MatrixB)[1])
for(i in 1:nrow(MatrixB)) {
resultMatrix[,i] <- sqrt(rowSums(t(t(MatrixA)-MatrixB[i,])^2))
}
resultMatrix
}发布于 2018-01-05 08:49:17
只需更改for循环,就可以计算结果矩阵的每一行的所有三列:
for(i in 1:nrow(matA))
{
resultMatrix[i,1] <- sqrt(rowSums((t(MatrixA[i,])-MatrixB[i,1:2])^2))
resultMatrix[i,2] <- sqrt(rowSums((t(MatrixA[i,])-MatrixB[i,3:4])^2))
resultMatrix[i,3] <- sqrt(rowSums((t(MatrixA[i,])-MatrixB[i,5:6])^2))
}对任意数量的列广义的:
for(i in 1:nrow(MatrixA))
{
for(j in 1:((dim(MatrixB)[2])/2))
{
k = (j * 2) - 1
resultMatrix[i,j] <- sqrt(rowSums((t(MatrixA[i,])-MatrixB[i,k:(k+1)])^2))
}
}https://stackoverflow.com/questions/48109002
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