Reset cumsum as it reaches certain value

Question

I want to reset cumsum over a vector as it reaches certain value.

Eg for the following vector:

v <- c(3, 5, 2, 5, 3, 4, 5, 3, 1, 4)

expected output is:

c(0, 0, 10, 0, 0, 22, 0, 30, 0, 0)

With reset <- 10 I can reduce the task to flagging the first values after the full integer:

res <- cumsum(v)
resd <- res/reset
resd
# [1] 0.3 0.8 1.0 1.5 1.8 2.2 2.7 3.0 3.1 3.5

Expected output is this:

c(F, F, T, F, F, T, F, T, F, F) # or 
c(0, 0, 1.0, 0, 0, 2.2, 0, 3.0, 0, 0)

I need a fast way to calculate one of those.

Answer 1

my (improved) solution:

v <- c(3, 5, 2, 5, 3, 4, 5, 3, 1, 4)
res <- cumsum(v)
reset <- 10
resd <- res/reset
res[diff(c(0, floor(resd))) == 0] <- 0
print(res) #gives 0  0 10  0  0 22  0 30  0  0

---

edit: now the first element in v can be larger than 10.

Answer 2

Another possible approach:

v <- c(3, 5, 2, 5, 3, 4, 5, 3, 1, 4)
reset <- 10
s <- cumsum(v)
idx <- as.integer(s / reset)
logic <- idx >= 1 & !duplicated(idx)

> logic
[1] FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE

# corresponding one-liner
logic <- with(list(idx=as.integer(cumsum(v) / reset)),idx >= 1 & !duplicated(idx))

---

Just for fun I've also created a Rcpp version of the function :

library(Rcpp)
library(inline)

cumsumResetRcpp <- cxxfunction(signature(values='numeric',reset='integer'),
'
  Rcpp::IntegerVector r(reset);
  int resetVal = r[0];
  Rcpp::NumericVector v(values);
  int n = v.size();
  Rcpp::NumericVector result(n);
  double cumsum = 0;
  for(int i = 0; i < n; i++){
    int prevCumSumFloor = (int)(cumsum / resetVal);
    cumsum += v[i];
    int currCumSumFloor = (int)(cumsum / resetVal);
    if(currCumSumFloor > prevCumSumFloor)
      result[i] = cumsum;
  }
  return( result ) ;
', plugin="Rcpp", verbose=FALSE,includes='')

Comparison with my previous version :

library(microbenchmark)

baseRVersion <- function(v,reset){
   a <- cumsum(v)
   a[!with(list(idx=as.integer(a / reset)),idx >= 1 & !duplicated(idx))] <- 0
   a
}

RcppVersion <- function(v,reset){
  cumsumResetRcpp(v,reset)
}

set.seed(1234)
v <- sample(5,1e6,replace=TRUE)

microbenchmark(baseRVersion(v,10), RcppVersion(v,10),times=20)


# Result :
   Unit: milliseconds
                expr      min       lq     mean    median       uq      max neval
 baseRVersion(v, 10) 69.78914 74.34717 91.67828 102.95764 103.6911 105.4055    20
  RcppVersion(v, 10) 17.28785 17.58432 18.89449  19.25759  19.8595  20.5627    20

Answer 3

This sets all cumsums less than 10 or ones where the modulo division by 10 value is duplicated to zero:

a <- cumsum(v)
 a %/% 10
 [1] 0 0 1 1 1 2 2 3 3 3

a[ duplicated(a %/% 10) | a<10 ] <- 0
a
 [1]  0  0 10  0  0 22  0 30  0  0

Answer 4

Because I can never resist...

qaswed <-function(v) {
res <- cumsum(v)
reset <- 10
resd <- res/reset
res[diff(c(0, floor(resd))) == 0] <- 0
}

digemall <-function(v){
reset <- 10
 with(list(idx=as.integer(cumsum(v) / reset)),idx >= 1 & !duplicated(idx))
 }

 colonel <-function(v){
 ifelse(c(0, diff(cumsum(v) %/% 10)), cumsum(v), 0)
 }

 userx <- function(v){
 a <- cumsum(v)
c(a[1] >= 10, a[-1] %/% 10 > a[-length(a)] %/% 10)
}

set.seed(5)
v <- sample(5,1e6,replace=TRUE)

microbenchmark(qaswed(v),digemall(v),colonel(v),userx(v),times=10)



 Unit: milliseconds
        expr       min        lq      mean    median        uq       max neval
   qaswed(v)  45.97558  50.29943  86.54772  85.52356  88.60232 200.89699    10
 digemall(v)  54.12038  58.85200  67.15433  60.51172  64.40194  99.32623    10
  colonel(v) 200.80942 233.56203 254.33662 252.65635 275.16588 306.76971    10
    userx(v)  53.87098  56.55786  71.38571  57.98169  92.94224  96.69956    10

Answer 5

v <- c(3, 5, 2, 5, 3, 4, 5, 3, 1, 4)
a <- cumsum(v)
c(a[1] >= 10, a[-1] %/% 10 > a[-length(a)] %/% 10)

Output:

[1] FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE