I have a matrix(initialized to zeros) and a set of indices. If the i'th value in indices is j, then I want to set the (j,i)th entry of the matrix to 1.
For eg:
> m = matrix(0, 10, 7)
> indices
[1] 2 9 3 4 5 1 10
And the result should be
> result
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
[1,] 0 0 0 0 0 1 0
[2,] 1 0 0 0 0 0 0
[3,] 0 0 1 0 0 0 0
[4,] 0 0 0 1 0 0 0
[5,] 0 0 0 0 1 0 0
[6,] 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0
[9,] 0 1 0 0 0 0 0
[10,] 0 0 0 0 0 0 1
I asked a somewhat related question a little while back, which used a vector instead of a matrix. Is there a similar simple solution to this problem?
## OP's example data
m = matrix(0, 10, 7)
j <- c(2, 9, 3, 4, 5, 1, 10)
## Construct a two column matrix of indices (1st column w. rows & 2nd w. columns)
ij <- cbind(j, seq_along(j))
## Use it to subassign into the matrix
m[ij] <- 1
m
# [,1] [,2] [,3] [,4] [,5] [,6] [,7]
# [1,] 0 0 0 0 0 1 0
# [2,] 1 0 0 0 0 0 0
# [3,] 0 0 1 0 0 0 0
# [4,] 0 0 0 1 0 0 0
# [5,] 0 0 0 0 1 0 0
# [6,] 0 0 0 0 0 0 0
# [7,] 0 0 0 0 0 0 0
# [8,] 0 0 0 0 0 0 0
# [9,] 0 1 0 0 0 0 0
# [10,] 0 0 0 0 0 0 1
For the record, the answer in your linked question can easily be adapted to suit this scenario too by using sapply:
indices <- c(2, 9, 3, 4, 5, 1, 10)
sapply(indices, tabulate, nbins = 10)
# [,1] [,2] [,3] [,4] [,5] [,6] [,7]
# [1,] 0 0 0 0 0 1 0
# [2,] 1 0 0 0 0 0 0
# [3,] 0 0 1 0 0 0 0
# [4,] 0 0 0 1 0 0 0
# [5,] 0 0 0 0 1 0 0
# [6,] 0 0 0 0 0 0 0
# [7,] 0 0 0 0 0 0 0
# [8,] 0 0 0 0 0 0 0
# [9,] 0 1 0 0 0 0 0
# [10,] 0 0 0 0 0 0 1
For small datasets you might not notice the performance difference, but Josh's answer, which uses matrix indexing, would definitely be much faster, even if you changed my answer here to use vapply instead of sapply.
Related
I would create in R a square matrix where the values on main diagonal and anti-diagonal is the same. It's 2. The otherwise value is 0.
I would use the function "for" but I have no idea how to apply it.
This is that i would, but the way is wrong because i must use the function "for"
a <- matrix(0 , 10,10)
diag(a) <- 2
a <- data.frame(a)
a <- as.matrix(data.frame(lapply(a , rev)))
diag(a) <- 2
colnames(a) <- NULL
a
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,] 2 0 0 0 0 0 0 0 0 2
#> [2,] 0 2 0 0 0 0 0 0 2 0
#> [3,] 0 0 2 0 0 0 0 2 0 0
#> [4,] 0 0 0 2 0 0 2 0 0 0
#> [5,] 0 0 0 0 2 2 0 0 0 0
#> [6,] 0 0 0 0 2 2 0 0 0 0
#> [7,] 0 0 0 2 0 0 2 0 0 0
#> [8,] 0 0 2 0 0 0 0 2 0 0
#> [9,] 0 2 0 0 0 0 0 0 2 0
#> [10,] 2 0 0 0 0 0 0 0 0 2
Here's possibly the quickest way to do it with a for-loop.
m <- matrix(0, 10, 10)
for(i in 0:9) m[11*i+1] <- m[10+i*9] <- 2
m
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,] 2 0 0 0 0 0 0 0 0 2
#> [2,] 0 2 0 0 0 0 0 0 2 0
#> [3,] 0 0 2 0 0 0 0 2 0 0
#> [4,] 0 0 0 2 0 0 2 0 0 0
#> [5,] 0 0 0 0 2 2 0 0 0 0
#> [6,] 0 0 0 0 2 2 0 0 0 0
#> [7,] 0 0 0 2 0 0 2 0 0 0
#> [8,] 0 0 2 0 0 0 0 2 0 0
#> [9,] 0 2 0 0 0 0 0 0 2 0
#> [10,] 2 0 0 0 0 0 0 0 0 2
This works because a matrix can be indexed with a single number representing the entries in column 1 (1:10), then column 2 (11:20) and so on. The diagonal starts at position 1 and repeats every 11 entries. The anti-diagonal starts at 10 and repeats every 9 entries.
If this is a homework assignment, your teacher will probably want you to use the [row, column] notation for subsetting and use nested for loops, so you would be safer submitting this:
m <- matrix(0, 10, 10)
for(i in 1:10) {
for(j in 1:10) {
if(i == j || i == 11 - j) {
m[i, j] <- 2
}
}
}
m
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,] 2 0 0 0 0 0 0 0 0 2
#> [2,] 0 2 0 0 0 0 0 0 2 0
#> [3,] 0 0 2 0 0 0 0 2 0 0
#> [4,] 0 0 0 2 0 0 2 0 0 0
#> [5,] 0 0 0 0 2 2 0 0 0 0
#> [6,] 0 0 0 0 2 2 0 0 0 0
#> [7,] 0 0 0 2 0 0 2 0 0 0
#> [8,] 0 0 2 0 0 0 0 2 0 0
#> [9,] 0 2 0 0 0 0 0 0 2 0
#> [10,] 2 0 0 0 0 0 0 0 0 2
Though it would be fun watching your teacher getting their head around the first version...
Created on 2022-06-08 by the reprex package (v2.0.1)
I have tried to write a function for this part of code and I can not mange because I am new to R
can someone help me?
I made a function like this :
m <- matrix(0, nrow=10, ncol=10) # Create an adjacency matrix
and I have changed the the element of it like below :
m[1,2] <- m[2,3] <- m[3,4] <-m[4,5]<-m[5,6]<-m[6,7]<-m[7,8] <-m[8,9]<-m[9,10]<-m[1,10] <- 1
but how can i do it automatically inside a function? to automatically iterate and change value?
I am not very sure about the logic for why m[1,10] is assigned one, for the others, you can do:
m <- matrix(0, nrow=10, ncol=10)
m[row(m) == col(m)-1] <- 1
m
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 1 0 0 0 0 0 0 0 0
[2,] 0 0 1 0 0 0 0 0 0 0
[3,] 0 0 0 1 0 0 0 0 0 0
[4,] 0 0 0 0 1 0 0 0 0 0
[5,] 0 0 0 0 0 1 0 0 0 0
[6,] 0 0 0 0 0 0 1 0 0 0
[7,] 0 0 0 0 0 0 0 1 0 0
[8,] 0 0 0 0 0 0 0 0 1 0
[9,] 0 0 0 0 0 0 0 0 0 1
[10,] 0 0 0 0 0 0 0 0 0 0
I am trying to use the matrix() and diag() functions to create the following pattern, but with a 100 x 100 matrix rather than 5 x 5.
5 x 5 matrix:
| 0 1 0 0 0 |
| 1 0 1 0 0 |
| 0 1 0 1 0 |
| 0 0 1 0 1 |
| 0 0 0 1 0 |
In other words, I want to have two diagonals with values of 1, one to the left of the main diagonal, and one to the right of the main diagonal.
The diag() function (actually the diag<- function) can be used for assignment:
mat <- matrix( 0, 100,100)
diag(mat) <- 1
mat[1:10,1:10]
#-----------
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 0 0 0 0 0 0 0 0 0
[2,] 0 1 0 0 0 0 0 0 0 0
[3,] 0 0 1 0 0 0 0 0 0 0
[4,] 0 0 0 1 0 0 0 0 0 0
[5,] 0 0 0 0 1 0 0 0 0 0
[6,] 0 0 0 0 0 1 0 0 0 0
[7,] 0 0 0 0 0 0 1 0 0 0
[8,] 0 0 0 0 0 0 0 1 0 0
[9,] 0 0 0 0 0 0 0 0 1 0
[10,] 0 0 0 0 0 0 0 0 0 1
You, however, want the sub-diagonal and super-diagonal to be assigned values, so use logical expressions with col and row:
mat <- matrix( 0, 100,100)
mat[row(mat)==col(mat)-1] <- 1
mat[row(mat)==col(mat)+1] <- 1
mat[1:10,1:10]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 1 0 0 0 0 0 0 0 0
[2,] 1 0 1 0 0 0 0 0 0 0
[3,] 0 1 0 1 0 0 0 0 0 0
[4,] 0 0 1 0 1 0 0 0 0 0
[5,] 0 0 0 1 0 1 0 0 0 0
[6,] 0 0 0 0 1 0 1 0 0 0
[7,] 0 0 0 0 0 1 0 1 0 0
[8,] 0 0 0 0 0 0 1 0 1 0
[9,] 0 0 0 0 0 0 0 1 0 1
[10,] 0 0 0 0 0 0 0 0 1 0
(This method does not depend on having a square matrix. I have a vague memory that there is a faster method that does not require using row and col. For very large objects each of those functions returns a matrix of the same dimensions as their arguments.)
For the main diagonal, the row and column indices are the same. For the other diagonals, there is a difference of 1 between the row index and column index. Generate those indices directly and assign values in those indices.
sz = 5
m = matrix(0, sz, sz)
inds1 = cbind(r = 1:(sz-1), c = 2:sz)
inds2 = cbind(r = 2:sz, c = 1:(sz-1))
m[inds1] = 1
m[inds2] = 1
m
# OR, to make it concise
m = matrix(0, sz, sz)
inds = rbind(cbind(1:(sz-1), 2:sz), cbind(2:sz, 1:(sz-1)))
replace(m, inds, 1)
# [,1] [,2] [,3] [,4] [,5]
#[1,] 0 1 0 0 0
#[2,] 1 0 1 0 0
#[3,] 0 1 0 1 0
#[4,] 0 0 1 0 1
#[5,] 0 0 0 1 0
We could create a function using a math trick which would work for all square matrix.
get_off_diagonal_1s <- function(n) {
#Create a matrix with all 0's
mat <- matrix(0, ncol = n, nrow = n)
#Subtract row indices by column indices
inds = row(mat) - col(mat)
#Replace values where inds is 1 or -1
mat[inds == 1 | inds == -1] = 1
mat
}
get_off_diagonal_1s(5)
# [,1] [,2] [,3] [,4] [,5]
#[1,] 0 1 0 0 0
#[2,] 1 0 1 0 0
#[3,] 0 1 0 1 0
#[4,] 0 0 1 0 1
#[5,] 0 0 0 1 0
get_off_diagonal_1s(8)
# [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
#[1,] 0 1 0 0 0 0 0 0
#[2,] 1 0 1 0 0 0 0 0
#[3,] 0 1 0 1 0 0 0 0
#[4,] 0 0 1 0 1 0 0 0
#[5,] 0 0 0 1 0 1 0 0
#[6,] 0 0 0 0 1 0 1 0
#[7,] 0 0 0 0 0 1 0 1
#[8,] 0 0 0 0 0 0 1 0
I have the following edge list with a number that associates the edge with a path number. This is given by the following matrix which I call Totallist:
`
Begin edge end edge path number
1 3 1
3 4 1
4 5 1
6 3 2
3 2 2`
I want to construct adjacency matrices for each of the paths. In this example, I want two matrices, but there could be more. I have written the following but it only finds the matrix for the first path. I am unsure how to write something that will work for any number of paths that I throw at it:
X<-as.data.frame(table(Totallist[,3]))
nlines<-nrow(X)
nlines
freq<-X[1,2]
diameterofmatrix<-max(Totallist)
X1<-get.adjacency(graph.edgelist(as.matrix(Totallist[1:X[1,2],1:2]), directed=FALSE))
X1<-rbind(X1, 0)
X1<-cbind(X1, 0)
X1
I also need the matrices to all be the same dimension so that is why I added an extra row and column. I could continue using my method but it seems quite ugly. Thank you very much for any help.
To extract the adjacency matrices into a list you can do the following (I generate some fake data):
set.seed(42)
df <- data.frame(beginEdge = sample(1:10, 10, replace = TRUE),
endEdge = sample(1:10, 10, replace=TRUE),
pathNum = rep(c(1,2), each=5))
df
beginEdge endEdge pathNum
1 10 5 1
2 10 8 1
3 3 10 1
4 9 3 1
5 7 5 1
6 6 10 2
7 8 10 2
8 2 2 2
9 7 5 2
10 8 6 2
paths <- unique(df$pathNum) # get the paths to iterate through
If we make the nodes factors, and set the levels of the factors to all the nodes in the population, then the adjacency matrices will be computed for the population in your network. I am assuming here the network is ten actors. If your observed data contains all the nodes you want to work with set the levels to unique(c(df$beginEdge,df$endEdge)), or whatever the set of nodes are that you prefer.
df$beginEdge <- factor(df$beginEdge, levels=1:10)
df$endEdge <- factor(df$endEdge, levels=1:10)
We now go across the list of paths and create matrices storing them as a list:
list.of.adj.mats <- lapply(paths, function(i){
matrix(as.numeric((
table(df$beginEdge[df$pathNum==i],
df$endEdge[df$pathNum==i])+
table(df$endEdge[df$pathNum==i],
df$beginEdge[df$pathNum==i]))>0),
nrow=length(levels(df$beginEdge)))})
list.of.adj.mats
[[1]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 0 0 0 0 0 0 0 0 0
[2,] 0 0 0 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0 0 1 1
[4,] 0 0 0 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 1 0 0 1
[6,] 0 0 0 0 0 0 0 0 0 0
[7,] 0 0 0 0 1 0 0 0 0 0
[8,] 0 0 0 0 0 0 0 0 0 1
[9,] 0 0 1 0 0 0 0 0 0 0
[10,] 0 0 1 0 1 0 0 1 0 0
[[2]]
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 0 0 0 0 0 0 0 0 0
[2,] 0 1 0 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0 0 0 0
[4,] 0 0 0 0 0 0 0 0 0 0
[5,] 0 0 0 0 0 0 1 0 0 0
[6,] 0 0 0 0 0 0 0 1 0 1
[7,] 0 0 0 0 1 0 0 0 0 0
[8,] 0 0 0 0 0 1 0 0 0 1
[9,] 0 0 0 0 0 0 0 0 0 0
[10,] 0 0 0 0 0 1 0 1 0 0
How can I randomly add a value to a matrix?
say I have:
mat <- matrix(0, 10, 10)
v = 5
how can I add randomly v to mat, 2 positions at a time? The output should look like this after a single iteration:
out
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 0 0 0 0 0 0 0 0 0 0
[2,] 5 0 0 0 0 0 0 0 0 0
[3,] 0 0 0 0 0 0 0 0 0 0
[4,] 0 0 0 0 5 0 0 0 0 0
[5,] 0 0 0 0 0 0 0 0 0 0
[6,] 0 0 0 0 0 0 0 0 0 0
[7,] 0 0 0 0 0 0 0 0 0 0
[8,] 0 0 0 0 0 0 0 0 0 0
[9,] 0 0 0 0 0 0 0 0 0 0
[10,] 0 0 0 0 0 0 0 0 0 0
After another iteration, mat should have 2 more positions filled with the value in 'v'
You could use ?sample to randomly index your matrix:
idx <- sample(length(mat), size=2)
mat[idx] <- mat[idx] + v