我希望用一个公式填充矩阵,该公式需要迭代矩阵cols和行以传递给公式。
以下是问题的简化代表性示例。
id_1 <- c("mammal", "mammal", "mammal", "mammal", "fish", "fish")
id_2 <- c("cat", "cat", "dog", "dog", "shark", "shark")
id_3 <- c(1, 2, 2, 3, 3, 4)
amt <- c(10, 15, 20, 25, 30, 35)
sample_data <- data.frame(id_1, id_2, id_3, amt)
sample_data_2 <- split(sample_data, sample_data$id_1)
l <- length(sample_data_2)
mat_list <- list()
i <- 1
for (i in 1:l) {
n <- nrow(sample_data_2[[i]])
cor <- matrix(ncol = n, nrow = n)
col_2 <- head(sample_data_2[[i]][,2], n)
col_3 <- head(sample_data_2[[i]][,3], n)
cor <- diag(n) +
0.5 * (outer(col_2, col_2, "!=") & outer(col_3, col_3, "==")) +
0.25 * (outer(1:n, 1:n, "!=") & (outer(col_2, col_2, "==") + outer(col_3, col_3, "==")) != 1) +
sin(col_3-col_3) * (outer(col_2, col_2, "==") & outer(col_3, col_3, "!="))
mat_list[[i]] <- cor
}
mat_list
但即使我没有得到错误,我也不认为
sin(topn.3-topn.3)
将迭代。
我真的想要这样做......
sin(col_3[j]-col_3[k])
我尝试引入嵌套for循环,但我无法让它工作
cor <- diag(n) +
0.5 * (outer(col_2, col_2, "!=") & outer(col_3, col_3, "==")) +
0.25 * (outer(1:n, 1:n, "!=") & (outer(col_2, col_2, "==") + outer(col_3, col_3, "==")) != 1) +
for(j in 1:length(col_3)) {
for (k in 1:length(col_3)) {
sin(col_3[j]-col_3[k])
}
} * (outer(col_2, col_2, "==") & outer(col_3, col_3, "!="))
Error: dims [product 4] do not match the length of object [0]
...即使嵌套的for循环工作,我认为它会陷入数据困境。有解决方案吗?
编辑:添加了所需的输出...
mat_list
[[1]]
[,1] [,2]
[1,] 1 -0.84
[2,] 0.84 1
[[2]]
[,1] [,2] [,3] [,4]
[1,] 1.00 -0.84 0.25 0.25
[2,] 0.84 1.00 0.50 0.25
[3,] 0.25 0.50 1.00 -0.84
[4,] 0.25 0.25 0.84 1.00
答案 0 :(得分:1)
您可以使用const size_t N = m_ObjVec.size();
size_t idx = N-1;
for ( ; ; )
{
CObj& curObj = *m_ObjVec[ idx ];
size_t otherIdx = FindOther( idx, N );
if ( c_NPOS != otherIdx )
{
CObj* pOtherObj = m_ObjVec[ otherIdx ];
// insert pOther after idx
m_ObjVec.insert( m_ObjVec.begin()+idx+1, pOtherObj );
// erase pOther from vector
m_ObjVec.erase( m_ObjVec.begin()+otherIdx );
}
else
{
if ( 0 == idx-- ) break;
}
}
。这是outer(col3,col3, function(x,y) sin(x,y))
:
for
答案 1 :(得分:0)
不幸的是,我需要使用的公式使用max(),当我介绍时,我得到一个错误。
这有效
cor <- diag(n) +
0.5 * (outer(col_2, col_2, "!=") & outer(col_3, col_3, "==")) +
0.25 * (outer(1:n, 1:n, "!=") & (outer(col_2, col_2, "==") + outer(col_3, col_3, "==")) != 1) +
outer(col_3,col_3,function(x,y) (sin(x-y)/min(x,y))) * (outer(col_2, col_2, "==") & outer(col_3, col_3, "!="))
[[1]]
[,1] [,2]
[1,] 1.00000 -0.28049
[2,] 0.28049 1.00000
[[2]]
[,1] [,2] [,3] [,4]
[1,] 1.000000 -0.841471 0.250000 0.250000
[2,] 0.841471 1.000000 0.500000 0.250000
[3,] 0.250000 0.500000 1.000000 -0.841471
[4,] 0.250000 0.250000 0.841471 1.000000
但是当我尝试引入最大条件错误时会抛出错误
cor <- diag(n) +
0.5 * (outer(col_2, col_2, "!=") & outer(col_3, col_3, "==")) +
0.25 * (outer(1:n, 1:n, "!=") & (outer(col_2, col_2, "==") + outer(col_3, col_3, "==")) != 1) +
outer(col_3,col_3,function(x,y) max(sin(x-y)/min(x,y),0.5)) * (outer(col_2, col_2, "==") & outer(col_3, col_3, "!="))
Error in outer(col_3, col_3, function(x, y) max(sin(x - y)/min(x, y), :
dims [product 4] do not match the length of object [1]
编辑:我想出了如何使它工作,我使用了pmax。
cor <- diag(n) +
0.5 * (outer(col_2, col_2, "!=") & outer(col_3, col_3, "==")) +
0.25 * (outer(1:n, 1:n, "!=") & (outer(col_2, col_2, "==") + outer(col_3, col_3, "==")) != 1) +
outer(col_3,col_3,function(x,y) pmax(sin(x-y)/min(x,y),0.5)) * (outer(col_2, col_2, "==") & outer(col_3, col_3, "!="))
[[1]]
[,1] [,2]
[1,] 1.0 0.5
[2,] 0.5 1.0
[[2]]
[,1] [,2] [,3] [,4]
[1,] 1.000000 0.50 0.250000 0.25
[2,] 0.841471 1.00 0.500000 0.25
[3,] 0.250000 0.50 1.000000 0.50
[4,] 0.250000 0.25 0.841471 1.00