accumulate
Accumulate recursive folds across a list
accumulate
applies a function recursively over a list from the left, while
accumulate_right
applies the function from the right. Unlike reduce
both functions keep the intermediate results.
Usage
accumulate(.x, .f, ..., .init)accumulate_right(.x, .f, ..., .init)
Arguments
- .x
A list or atomic vector.
- .f
For
reduce()
, a 2-argument function. The function will be passed the accumulated value as the first argument and the "next" value as the second argument.For
reduce2()
, a 3-argument function. The function will be passed the accumulated value as the first argument, the next value of.x
as the second argument, and the next value of.y
as the third argument.- ...
Additional arguments passed on to
.f
.- .init
If supplied, will be used as the first value to start the accumulation, rather than using
x[[1]]
. This is useful if you want to ensure thatreduce
returns a correct value when.x
is empty. If missing, andx
is empty, will throw an error.
Examples
# NOT RUN {
1:3 %>% accumulate(`+`)
1:10 %>% accumulate_right(`*`)
# From Haskell's scanl documentation
1:10 %>% accumulate(max, .init = 5)
# Understanding the arguments .x and .y when .f
# is a lambda function
# .x is the accumulating value
1:10 %>% accumulate(~ .x)
# .y is element in the list
1:10 %>% accumulate(~ .y)
# Simulating stochastic processes with drift
# }
# NOT RUN {
library(dplyr)
library(ggplot2)
rerun(5, rnorm(100)) %>%
set_names(paste0("sim", 1:5)) %>%
map(~ accumulate(., ~ .05 + .x + .y)) %>%
map_dfr(~ data_frame(value = .x, step = 1:100), .id = "simulation") %>%
ggplot(aes(x = step, y = value)) +
geom_line(aes(color = simulation)) +
ggtitle("Simulations of a random walk with drift")
# }