Resetting Cumsum If Value Goes to Negative in R

Conditional cumsum with reset when accumulating and substracting at once

Here is one way you might do this:

ve$DO <- Reduce(function(x,y) pmax(x + y, 0), with(ve, V2-V3*(V1 >  0)), accumulate = TRUE)

ve
   V1 V2 V3 DO
1  -2  6  0  6
2   4  0  5  1
3   3  0  8  0
4  -5  1  0  1
5  -5  0  0  1
6  -7  2  0  3
7  -8  3  0  6
8  -2  5  0 11
9  -3  7  0 18
10 -5  7  0 25
11 -7  8  0 33
12 -8  2  0 35
13 -9  0  0 35
14 -2  0  7 35
15  1  0  9 26
16  2  0 12 14
17  4  0  0 14

Equivalent using purrr/dplyr:

library(purrr)
library(dplyr)

ve %>%
  mutate(DO = accumulate(V2-V3*(V1 >  0), .f = ~pmax(.x + .y, 0)))

cumsum with a condition to restart in R

You may use cumsum to create groups as well.

library(dplyr)

df <- df %>%
  group_by(group = cumsum(dplyr::lag(port == 0, default = 0))) %>%
  mutate(cumsum_G = cumsum(G)) %>%
  ungroup

df

#  inv   ass    port     G group cumsum_G
#  <chr> <chr> <int> <int> <dbl>    <int>
#1 i     x         2     1     0        1
#2 i     x         2     0     0        1
#3 i     x         0     1     0        2
#4 i     x         3     0     1        0
#5 i     x         3     1     1        1

You may remove the group column from output using %>% select(-group).

data

df <- structure(list(inv = c("i", "i", "i", "i", "i"), ass = c("x", 
"x", "x", "x", "x"), port = c(2L, 2L, 0L, 3L, 3L), G = c(1L, 
0L, 1L, 0L, 1L)), class = "data.frame", row.names = c(NA, -5L))

How do I fix a cumulative sum in R when dealing with negative values

We can calculate the increments with diff and use pmax to set all negative increments to 0. Then we cumsum this corrected increment:

df %>%
  group_by(player) %>%
  mutate(
    increment = c(first(LifeTimeCumulative), pmax(diff(LifeTimeCumulative), 0)),
    corrected = cumsum(increment)
  ) %>%
  ungroup()
# # A tibble: 12 × 6
#    player date       LifeTimeCumulative LifeTimeCumulativeCorrect increment corrected
#    <fct>  <date>                  <dbl>                     <dbl>     <dbl>     <dbl>
#  1 A      2022-01-01                  0                         0         0         0
#  2 A      2022-01-02                  2                         2         2         2
#  3 A      2022-01-03                  0                         2         0         2
#  4 A      2022-01-04                  1                         3         1         3
#  5 B      2022-01-01                  0                         0         0         0
#  6 B      2022-01-02                  2                         2         2         2
#  7 B      2022-01-03                  2                         2         0         2
#  8 B      2022-01-04                  1                         2         0         2
#  9 C      2022-01-01                  1                         1         1         1
# 10 C      2022-01-02                  2                         2         1         2
# 11 C      2022-01-03                  2                         2         0         2
# 12 C      2022-01-04                  0                         2         0         2  

Cumulative sum with potential resets

We can use Reduce in base R

csum2 <- Reduce(function(u, v) max(u + v, v), x, accumulate = TRUE)

-checking with OP's output

identical(csum, csum2)
#[1] TRUE

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Or another option is accumulate from purrr

library(purrr)
accumulate(x, ~  max(.x + .y, .y))

dplyr / R cumulative sum with reset

I think you can use accumulate() here to help. And i've also made a wrapper function to use for different thresholds

sum_reset_at <- function(thresh) {
  function(x) {
    accumulate(x, ~if_else(.x>=thresh, .y, .x+.y))
  }  
}

tib %>% mutate(c = sum_reset_at(5)(a))
#       t     a     c
#   <dbl> <dbl> <dbl>
# 1     1     2     2
# 2     2     3     5
# 3     3     1     1
# 4     4     2     3
# 5     5     2     5
# 6     6     3     3
tib %>% mutate(c = sum_reset_at(4)(a))
#       t     a     c
#   <dbl> <dbl> <dbl>
# 1     1     2     2
# 2     2     3     5
# 3     3     1     1
# 4     4     2     3
# 5     5     2     5
# 6     6     3     3
tib %>% mutate(c = sum_reset_at(6)(a))
#       t     a     c
#   <dbl> <dbl> <dbl>
# 1     1     2     2
# 2     2     3     5
# 3     3     1     6
# 4     4     2     2
# 5     5     2     4
# 6     6     3     7

Cumsum with criteria in R

A looping (and less fast) alternative to cumsum is Reduce(`+`, x, accumulate = TRUE). However, this Reduce approach can then be modified to your resetting cumulative sum:

Reduce(function(x, y) if (x + y > 0) x + y else 0, d, accumulate = TRUE)

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