R：比较读取 table 中的值并更新另一个矩阵

Question

我目前在使用 R 比较特定矩阵中的每一列时遇到问题。我试图一次比较整个列的每一列，并通过 table 命令生成真假输出，然后将可以找到的真数转换为数值并将这些值输入它们关联矩阵中的各个位置。

For example, I have data in this type of format:
//Example state matrix - I am attempting to compare c1 with c2, then c1 with c3, then c1 with c4 and so on and so forth 
    c1  c2  c3  c4
r1  2   6   3   2
r2  1   1   6   5
r3  3   1   3   6

And I am trying to instead put it into this format
//Example incidence matrix - Which is how many times c1 equaled c2 in the above matrix 
    c1  c2  c3  c4
c1  3   1   1   1
c2  1   3   0   0
c3  1   0   3   0
c4  1   0   0   3

这是我到目前为止想出的代码，但是，我一直收到这个特定的错误 --

警告信息： In IncidenceMat[rat][r] = IncidenceMat[rat][r] + as.numeric(instances) ：要替换的项目数不是替换长度的倍数

rawData = read.table("5-14-2014streamW636PPstate.txt")
colnames = names(rawData) #the column names in R 
df <- data.frame(rawData)
rats = ncol(rawData) 
instances = nrow(rawData)

IncidenceMat = matrix(rep(0, rats), nrow = rats, ncol = rats) 

for(rat in rats)
   for(r in rats)
      if(rat == r){rawData[instance][rat] == rawData[instance][r] something like this would work in C++ if I attempted, 
        IncidenceMat[rat][r] = IncidenceMat[rat][r] + as.numeric(instances)
  } else{ 
    count = df[colnames[rat]] == df[colnames[r]]
    c = table(count)
    TotTrue = as.numeric(c[2][1])
    IncidenceMat[rat][r] = IncidenceMat[rat][r] + TotTrue #count would go here #this should work like a charm as well 
  }

如有任何帮助，我们将不胜感激；我也看过其中一些资源，但是，我仍然感到困惑

I tried this and this 以及我最近关闭的其他一些资源。

Answer 1

这个怎么样（注意关联矩阵是对称的）？

df
   c1 c2 c3 c4
r1  2  6  3  2
r2  1  1  6  5
r3  3  1  3  6

incidence <- matrix(rep(0, ncol(df)*ncol(df)), nrow=ncol(df))
diag(incidence) <- nrow(df)
for (i in 1:(ncol(df)-1)) {
   for (j in (i+1):ncol(df)) {
     incidence[i,j] = incidence[j,i] = sum(df[,i] == df[,j])
   }
}

incidence
     [,1] [,2] [,3] [,4]
[1,]    3    1    1    1
[2,]    1    3    0    0
[3,]    1    0    3    0
[4,]    1    0    0    3

R：比较读取 table 中的值并更新另一个矩阵

R: Compare values in a read table and update another matrix

r

matrix

analysis

这是我到目前为止想出的代码，但是，我一直收到这个特定的错误 --