Question

我有这样的循环，尝试使用虚拟变量来实现解决方案here

aaa <- DFM %*% t(DFM)   #DFM is Quanteda dfm-sparse-matrix
for(i in 1:nrow(aaa)) aaa[i,] <- aaa[i,][order(aaa[i,], decreasing = TRUE)]

但现在

for(i in 1:nrow(mmm)) mmm[i,] <- aaa[i,][order(aaa[i,], decreasing = TRUE)]

其中mmm尚不存在，目标是与mmm <- t(apply(a, 1, sort, decreasing = TRUE))做同样的事情。但是现在在for循环之前我需要初始化mmm否则Error: object 'mmm' not found。 aaa和mmm的类型为dgCMatrix，由两个Quanteda DFM matrices的矩阵乘法给出。

结构

aaaFunc由矩阵乘法DFM %*% t(DFM)给出，其中DFM是Quanteda稀疏dfm矩阵。结构是

> str(aaaFunc)
Formal class 'dgCMatrix' [package "Matrix"] with 6 slots
  ..@ i       : int [1:39052309] 0 2 1 0 2 2616 2880 3 4 5 ...
  ..@ p       : int [1:38162] 0 2 3 7 8 10 13 15 16 96 ...
  ..@ Dim     : int [1:2] 38161 38161
  ..@ Dimnames:List of 2
  .. ..$ : chr [1:38161] "90120000" "90120000" "90120000" "86140000" ...
  .. ..$ : chr [1:38161] "90120000" "90120000" "90120000" "86140000" ...
  ..@ x       : num [1:39052309] 1 1 1 1 2 1 1 1 2 1 ...
  ..@ factors : list()

DFM上的

错误，其中提到here方法，关于复制R对象而没有其内容但其结构/等的一般问题。

A。错误aaaFunc.mt[]<- NA

> aaaFunc.mt <- aaaFunc[0,]; aaaFunc.mt[] <- NA; aaaFunc.mt[1,]
Error in intI(i, n = x@Dim[1], dn[[1]], give.dn = FALSE) : index larger than maximal 0

B。错误mySparseMatrix.mt[nrow(mySparseMatrix),]<-

> aaaFunc.mt <- aaaFunc[0,]; aaaFunc.mt[nrow(aaaFunc),] <- NA
Error in intI(i, n = di[margin], dn = dn[[margin]], give.dn = FALSE) : 
  index larger than maximal 0

C。错误replace(...,NA)

Browse[2]> mmmFunc <- replace(aaaFunc,NA);
Error in replace(aaaFunc, NA) : 
  argument "values" is missing, with no default
Browse[2]> mmmFunc <- replace(aaaFunc,,NA);
Error in `[<-`(`*tmp*`, list, value = NA) : 
  argument "list" is missing, with no default
Browse[2]> mmmFunc <- replace(aaaFunc,c(),NA);
Error in .local(x, i, j, ..., value) : 
  not-yet-implemented 'Matrix[<-' method

如何初始化由两个Quanteda DFM矩阵的矩阵乘法给出的空dgCMatrix？

Answer 1

以下内容将初始化空稀疏矩阵或重置现有稀疏矩阵，同时保留两个维度dimnames

library(Matrix)

i <- c(1,3:8)
j <- c(2,9,6:10)
x <- 7 * (1:7)
A <- sparseMatrix(i, j, x = x)
rownames(A) <- letters[seq_len(nrow(A))]

A2 <- sparseMatrix(i = integer(0), j = integer(0), dim = A@Dim, dimnames = A@Dimnames)

A@i <- integer(0)
A@p[] <- 0L
A@x <- numeric(0)

setequal(A, A2)
[1] TRUE

R：初始化由两个Quanteda DFM稀疏矩阵的矩阵乘法给出的空dgCMatrix？

1 个答案: