How can I take a sample of n random points from a matrix populated?

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How can I take a sample of n random points from a matrix populated with 1's and 0's ?

a=rep(0:1,5)b=rep(0,10)c=rep(1,10)dataset=matrix(cbind(a,b,c),nrow=10,ncol=3)dataset      [,1] [,2] [,3] [1,]    0    0    1 [2,]    1    0    1 [3,]    0    0    1 [4,]    1    0    1 [5,]    0    0    1 [6,]    1    0    1 [7,]    0    0    1 [8,]    1    0    1 [9,]    0    0    1[10,]    1    0    1

I want to be sure that the positions(row,col) from were I take the N samples are random.

I know sample {base} but it doesn't seem to allow me to do that, other methods I know are spatial methods that will force me to add x,y and change it to a spatial object and again back to a normal matrix.

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关键词：Points Sample random matrix opula methods matrix points change

There is a very easy way to sample a matrix that works if you understand that R represents a matrix internally as a vector.

This means you can use sample directly on your matrix. For example, let's assume you want to sample 10 points with replacement:

n <- 10
replace=TRUE
Now just use sample on your matrix:

set.seed(1)
sample(dataset, n, replace=replace)
[1] 1 0 0 1 0 1 1 0 0 1
To demonstrate how this works, let's decompose it into two steps. Step 1 is to generate an index of sampling positions, and step 2 is to find those positions in your matrix:

set.seed(1)
mysample <- sample(length(dataset), n, replace=replace)
mysample
[1]  8 12 18 28  7 27 29 20 19  2

dataset[mysample]
[1] 1 0 0 1 0 1 1 0 0 1
And, hey presto, the results of the two methods are identical.