These functions work exactly the same as purrr::map2() and its variants, but allow you to map in parallel. Note that "parallel" as described in purrr is just saying that you are working with multiple inputs, and parallel in this case means that you can work on multiple inputs and process them all in parallel as well.

future_map2(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_chr(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_dbl(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_int(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_lgl(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_raw(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_dfr(
  .x,
  .y,
  .f,
  ...,
  .id = NULL,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_map2_dfc(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_chr(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_dbl(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_int(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_lgl(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_raw(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_dfr(
  .l,
  .f,
  ...,
  .id = NULL,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pmap_dfc(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_walk2(
  .x,
  .y,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_pwalk(
  .l,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

Arguments

.x

Vectors of the same length. A vector of length 1 will be recycled.

.y

Vectors of the same length. A vector of length 1 will be recycled.

.f

A function, formula, or vector (not necessarily atomic).

If a function, it is used as is.

If a formula, e.g. ~ .x + 2, it is converted to a function. There are three ways to refer to the arguments:

  • For a single argument function, use .

  • For a two argument function, use .x and .y

  • For more arguments, use ..1, ..2, ..3 etc

This syntax allows you to create very compact anonymous functions.

If character vector, numeric vector, or list, it is converted to an extractor function. Character vectors index by name and numeric vectors index by position; use a list to index by position and name at different levels. If a component is not present, the value of .default will be returned.

...

Additional arguments passed on to the mapped function.

.options

The future specific options to use with the workers. This must be the result from a call to furrr_options().

.env_globals

The environment to look for globals required by .x and .... Globals required by .f are looked up in the function environment of .f.

.progress

A single logical. Should a progress bar be displayed? Only works with multisession, multicore, and multiprocess futures. Note that if a multicore/multisession future falls back to sequential, then a progress bar will not be displayed.

Warning: The .progress argument will be deprecated and removed in a future version of furrr in favor of using the more robust progressr package.

.id

Either a string or NULL. If a string, the output will contain a variable with that name, storing either the name (if .x is named) or the index (if .x is unnamed) of the input. If NULL, the default, no variable will be created.

Only applies to _dfr variant.

.l

A list of vectors, such as a data frame. The length of .l determines the number of arguments that .f will be called with. List names will be used if present.

Value

An atomic vector, list, or data frame, depending on the suffix. Atomic vectors and lists will be named if .x or the first element of .l is named.

If all input is length 0, the output will be length 0. If any input is length 1, it will be recycled to the length of the longest.

Examples

plan(multisession, workers = 2) x <- list(1, 10, 100) y <- list(1, 2, 3) z <- list(5, 50, 500) future_map2(x, y, ~ .x + .y)
#> [[1]] #> [1] 2 #> #> [[2]] #> [1] 12 #> #> [[3]] #> [1] 103 #>
# Split into pieces, fit model to each piece, then predict by_cyl <- split(mtcars, mtcars$cyl) mods <- future_map(by_cyl, ~ lm(mpg ~ wt, data = .)) future_map2(mods, by_cyl, predict)
#> $`4` #> Datsun 710 Merc 240D Merc 230 Fiat 128 Honda Civic #> 26.47010 21.55719 21.78307 27.14774 30.45125 #> Toyota Corolla Toyota Corona Fiat X1-9 Porsche 914-2 Lotus Europa #> 29.20890 25.65128 28.64420 27.48656 31.02725 #> Volvo 142E #> 23.87247 #> #> $`6` #> Mazda RX4 Mazda RX4 Wag Hornet 4 Drive Valiant Merc 280 #> 21.12497 20.41604 19.47080 18.78968 18.84528 #> Merc 280C Ferrari Dino #> 18.84528 20.70795 #> #> $`8` #> Hornet Sportabout Duster 360 Merc 450SE Merc 450SL #> 16.32604 16.04103 14.94481 15.69024 #> Merc 450SLC Cadillac Fleetwood Lincoln Continental Chrysler Imperial #> 15.58061 12.35773 11.97625 12.14945 #> Dodge Challenger AMC Javelin Camaro Z28 Pontiac Firebird #> 16.15065 16.33700 15.44907 15.43811 #> Ford Pantera L Maserati Bora #> 16.91800 16.04103 #>
future_pmap(list(x, y, z), sum)
#> [[1]] #> [1] 7 #> #> [[2]] #> [1] 62 #> #> [[3]] #> [1] 603 #>
# Matching arguments by position future_pmap(list(x, y, z), function(a, b ,c) a / (b + c))
#> [[1]] #> [1] 0.1666667 #> #> [[2]] #> [1] 0.1923077 #> #> [[3]] #> [1] 0.1988072 #>
# Vectorizing a function over multiple arguments df <- data.frame( x = c("apple", "banana", "cherry"), pattern = c("p", "n", "h"), replacement = c("x", "f", "q"), stringsAsFactors = FALSE ) future_pmap(df, gsub)
#> [[1]] #> [1] "axxle" #> #> [[2]] #> [1] "bafafa" #> #> [[3]] #> [1] "cqerry" #>
future_pmap_chr(df, gsub)
#> [1] "axxle" "bafafa" "cqerry"
# \dontshow{ # Close open connections for R CMD Check if (!inherits(plan(), "sequential")) plan(sequential) # }