Quickly allocate some groups into partitions with other groups of similar size

grouping.r

# Generate sample distributions
n = 1e2
t = 3e6
min_r = t/1000
max_r = t/50

c = 0
r = vector(mode="numeric")

for(x in 1:n){
  k = floor(runif(1, min =  pmin(min_r, t-c), max = pmin(max_r, t-c)))
  k = ifelse(is.nan(k), min_r, k)
  r[x] = k
  c = c + k
}

sum(r)

# identify partitions
p = 10
b = floor((max(r) - min(r)) / (p-1))
partition_alloc = (r - min(r)) %/% b
partition_alloc