Question

I am trying to duplicate each column from data frame and move it to a randomly located point within 1-3 columns and do it for each column in the data frame. I want columns to move AT LEAST one space to the left or right. Of course sample(data) reorders columns randomly, but my attempts to put it in a loop are embarrassingly bad (I admit I skipped majority of linear algebra classes, damn…). Below is an example data:

dat <- read.table(textConnection(
"-515.5718  94.33423 939.6324 -502.9918 -75.14629 946.6926
-515.2283  96.10239 939.5687 -503.1425 -73.39015 946.6360
-515.0044  97.68119 939.4177 -503.4021 -71.79252 946.6909
-514.7430  99.59141 939.3976 -503.6645 -70.08514 946.6887
-514.4449 101.08511 939.2342 -503.9207 -68.48133 946.7183
-514.2769 102.29453 939.0013 -504.2665 -67.04509 946.7809
-513.9294 104.02753 938.9436 -504.4703 -65.34361 946.7899
-513.5900 105.49624 938.7684 -504.7405 -63.75965 946.7991"
),header=F,as.is=T)
sample(dat)#random columns position

Answer 1

How about this brute-force but plenty-fast solution?

It tries out different permutations of the columns until it finds one in which each column is moved at least 1, and not more than 3 columns to left or right. When it finds such a permutation, the test in the final line of the while() call evaluates to FALSE, terminating the loop and leaving the variable x containing the acceptable permutation.

n <- ncol(dat)
while({x <- sample(n)   # Proposed new column positions
       y <- seq_len(n)  # Original column positions
       max(abs(x - y)) > 3 | min(abs(x - y)) == 0
       }) NULL
dat[x]