Question

The question hast 2 parts.

1. Which is the data structure in R that allows to store the paired data:

   0:0  
   0.5:10  
   1:20  
   

   (Python dictionary {[0]:0, [0.5]:10, [1]:20})

   and how to initiate it with one liner? i.e. to couple seq(0,1,by=0.5)
   with seq(0,10,by=5) in this data structure

2. Assume I added 0.25 to the list, then I want the weighted average of the neighbor nodes to appear (automatically) in the data set, i.e. the element 0.25:5 and the paired set would be

   0:0
   0.25:5  
   0.5:10  
   1:20  
   

   If I add the element 0.3, then it must be paired with 5+(10-5)*(0.3-0.25)/(0.5-0.25)=6 and element 0.3:6 to be added.

How I can create the class with S4 or Reference Class class model where I could put this functionality?

Answer 1

A two-column data.frame seems appropriate:

xy <- data.frame(x = seq(0, 1, by = 0.5), y = seq(0, 20, by = 10))
xy
#     x  y
# 1 0.0  0
# 2 0.5 10
# 3 1.0 20

Then, what you are trying to do is a linear-interpolation, which you can achieve using the approx function. For example:

approx(xy$x, xy$y, xout = 0.3)
# $x
# [1] 0.3
# 
# $y
# [1] 6

If you want to add that result to the data.frame, you can do something like:

xy <- as.data.frame(approx(xy$x, xy$y, xout = sort(c(xy$x, 0.3))))
xy
#     x  y
# 1 0.0  0
# 2 0.3  6
# 3 0.5 10
# 4 1.0 20

which is a bit expensive, especially if you plan to add points one at a time. You could instead add all your points at once since the result is independent of the order in which you add them:

add.points <- c(0.25, 0.3)
xy <- as.data.frame(approx(xy$x, xy$y, xout = sort(c(xy$x, add.points))))
xy
#      x  y
# 1 0.00  0
# 2 0.25  5
# 3 0.30  6
# 4 0.50 10
# 5 1.00 20