Functional Programming Patterns

Predicate Filter

Keep Matching Values

A predicate is a function that returns TRUE or FALSE for each input value.

Program

Play the script to change the minimum value used by the predicate.

min_value
predicate_filter.R
Replay: real traced execution (multi-file project)
min_value <- 4
values <- c(1, 3, 5, 7)
keep <- function(x) x >= min_value
selected <- values[vapply(values, keep, logical(1))]
count <- length(selected)
label <- paste("count", count, sep = ":")
cat(label, "\n", sep = "")

min_value <- 2
values <- c(1, 3, 5, 7)
keep <- function(x) x >= min_value
selected <- values[vapply(values, keep, logical(1))]
count <- length(selected)
label <- paste("count", count, sep = ":")
cat(label, "\n", sep = "")

min_value <- 6
values <- c(1, 3, 5, 7)
keep <- function(x) x >= min_value
selected <- values[vapply(values, keep, logical(1))]
count <- length(selected)
label <- paste("count", count, sep = ":")
cat(label, "\n", sep = "")

  1. min_value ← 4

    1min_value <- 42values <- c(1, 3, 5, 7)
    values this step4min_value

  2. values ← 1, 3, 5, 7

    1min_value <- 42values <- c(1, 3, 5, 7)3keep <- function(x) x >= min_value
    values this step1, 3, 5, 7values

  3. keep ← x >= 4

    2values <- c(1, 3, 5, 7)3keep <- function(x) x >= min_value4selected <- values[vapply(values, keep, logical(1))]
    values this stepx >= 4keep4min_value

  4. selected ← 5, 7

    3keep <- function(x) x >= min_value4selected <- values[vapply(values, keep, logical(1))]5count <- length(selected)
    values this step5, 7selected1, 3, 5, 7valuesx >= 4keep

  5. count ← 2

    4selected <- values[vapply(values, keep, logical(1))]5count <- length(selected)6label <- paste("count", count, sep = ":")
    values this step2count5, 7selected

  6. label ← count:2

    5count <- length(selected)6label <- paste("count", count, sep = ":")7cat(label, "\n", sep = "")
    values this stepcount:2label2count

  7. cat(label, " ", sep = "")

    6label <- paste("count", count, sep = ":")7cat(label, "\n", sep = "")
    outputcount:2
    values this stepcount:2label

  1. min_value ← 2

    1min_value <- 22values <- c(1, 3, 5, 7)
    values this step2min_value

  2. values ← 1, 3, 5, 7

    1min_value <- 22values <- c(1, 3, 5, 7)3keep <- function(x) x >= min_value
    values this step1, 3, 5, 7values

  3. keep ← x >= 2

    2values <- c(1, 3, 5, 7)3keep <- function(x) x >= min_value4selected <- values[vapply(values, keep, logical(1))]
    values this stepx >= 2keep2min_value

  4. selected ← 3, 5, 7

    3keep <- function(x) x >= min_value4selected <- values[vapply(values, keep, logical(1))]5count <- length(selected)
    values this step3, 5, 7selected1, 3, 5, 7valuesx >= 2keep

  5. count ← 3

    4selected <- values[vapply(values, keep, logical(1))]5count <- length(selected)6label <- paste("count", count, sep = ":")
    values this step3count3, 5, 7selected

  6. label ← count:3

    5count <- length(selected)6label <- paste("count", count, sep = ":")7cat(label, "\n", sep = "")
    values this stepcount:3label3count

  7. cat(label, " ", sep = "")

    6label <- paste("count", count, sep = ":")7cat(label, "\n", sep = "")
    outputcount:3
    values this stepcount:3label

  1. min_value ← 6

    1min_value <- 62values <- c(1, 3, 5, 7)
    values this step6min_value

  2. values ← 1, 3, 5, 7

    1min_value <- 62values <- c(1, 3, 5, 7)3keep <- function(x) x >= min_value
    values this step1, 3, 5, 7values

  3. keep ← x >= 6

    2values <- c(1, 3, 5, 7)3keep <- function(x) x >= min_value4selected <- values[vapply(values, keep, logical(1))]
    values this stepx >= 6keep6min_value

  4. selected ← 7

    3keep <- function(x) x >= min_value4selected <- values[vapply(values, keep, logical(1))]5count <- length(selected)
    values this step7selected1, 3, 5, 7valuesx >= 6keep

  5. count ← 1

    4selected <- values[vapply(values, keep, logical(1))]5count <- length(selected)6label <- paste("count", count, sep = ":")
    values this step1count7selected

  6. label ← count:1

    5count <- length(selected)6label <- paste("count", count, sep = ":")7cat(label, "\n", sep = "")
    values this stepcount:1label1count

  7. cat(label, " ", sep = "")

    6label <- paste("count", count, sep = ":")7cat(label, "\n", sep = "")
    outputcount:1
    values this stepcount:1label
predicate The `keep` function returns one logical value for each input.
logical map `vapply(values, keep, logical(1))` evaluates the predicate across the vector.
filter Indexing with the logical result keeps only matching values.