Extending / converting a sparse matrix into a larger sparse matrix

问题

I am aware that the title of this question is confusing, if not wrong. Sorry for this, let me explain what I try to do:

# I have a population of individuals:
population <- c("Adam", "Bob", "Chris", "Doug", "Emily", "Frank", "George","Harry", "Isaac", "Jim", "Kyle", "Louis")
population_size <- length(population) # this is 12

# I then draw a sample from this population
mysample_size <- 5
mysample <- sample(population,mysample_size, replace=FALSE)

# I then simulate a network among the people in the sample
frn <- matrix(rbinom(mysample_size*mysample_size, 1, 0.4),nrow=n)
x[x<=0] <- 0
x[x>0] <- 1
rownames(frn) <- mysample 
colnames(frn) <- mysample

*I would now like to transfer the values from frn into a matrix that includes all members from the original population, i.e. a 12 by 12 matrix. The values in that matrix would only come from the frn 5*5 matrix.

I do not know how to generate the matrix at the bottom from the matrix at the top.

I have thought of different ways (e.g. using iGraph and advancing via edgelists) or running loops, but did not really get a single alternative to run. Maybe important to know as background: My actual matrices are much larger than this and I need to run this operation many times, thus an efficient solution would be great. Thanks a lot for your help.

回答1:

Neatest solution: ind = match(mysample,population) gives you the index numbers of the rows and columns corresponding to the sample, so update the population network matrix popn by doing popn[ind,ind] = frn. Done.

回答2:

# create an empty matrix with NAs. You may have the full matrix already.
full_matrix <- matrix(rep(NA, population_size*population_size), nrow=population_size)
rownames(full_matrix) <- colnames(full_matrix) <- population
frn <- matrix(rbinom(mysample_size*mysample_size, 1, 0.4), nrow = mysample_size)
rownames(frn) <- colnames(frn) <- mysample
# Find the locations where they match
tmp <- match(rownames(frn), rownames(full_matrix))
tmp2 <- match(colnames(frn), colnames(full_matrix))

# do a merge
full_matrix[tmp,tmp2] <- frn

回答3:

You could use... a sparse matrix.

library(Matrix)
# Make sure the columns match
population <- c( mysample, setdiff(population, mysample) )
ij <- which( frn != 0, arr.ind=TRUE )
m <- sparseMatrix( 
  i = ij[,1], j=ij[,2], 
  x = 1,  # or frn[ij]
  dim = length(population)*c(1,1), 
  dimnames = list(population, population) 
)
m

来源：https://stackoverflow.com/questions/10943338/extending-converting-a-sparse-matrix-into-a-larger-sparse-matrix

标签

social-networking

sparse-matrix