Filter objects by class

Based on https://stackoverflow.com/a/5158978/1380598.

classFilter(x, include, exclude, envir)

# S4 method for character,character,character,environment
classFilter(x, include, exclude, envir)

# S4 method for character,character,character,missing
classFilter(x, include, exclude)

# S4 method for character,character,missing,environment
classFilter(x, include, envir)

# S4 method for character,character,missing,missing
classFilter(x, include)

Arguments

x

Character vector of object names to filter, possibly from ls.

include

Class(es) to include, as a character vector.

exclude

Optional class(es) to exclude, as a character vector.

envir

The environment ins which to search for objects. Default is the calling environment.

Value

Vector of object names matching the class filter.

Note

inherits() is used internally to check the object class, which can, in some cases, return results inconsistent with is. See https://stackoverflow.com/a/27923346/1380598. These (known) cases are checked manually and corrected.

Author

Alex Chubaty

Examples

if (FALSE) {
  ## from global environment
  a <- list(1:10)     # class `list`
  b <- letters        # class `character`
  d <- stats::runif(10)      # class `numeric`
  f <- sample(1L:10L) # class `numeric`, `integer`
  g <- lm( jitter(d) ~ d ) # class `lm`
  h <- glm( jitter(d) ~ d ) # class `lm`, `glm`
  classFilter(ls(), include=c("character", "list"))
  classFilter(ls(), include = "numeric")
  classFilter(ls(), include = "numeric", exclude = "integer")
  classFilter(ls(), include = "lm")
  classFilter(ls(), include = "lm", exclude = "glm")
  rm(a, b, d, f, g, h)
}

## from local (e.g., function) environment
local({
  e <- environment()
  a <- list(1:10)     # class `list`
  b <- letters        # class `character`
  d <- stats::runif(10)      # class `numeric`
  f <- sample(1L:10L) # class `numeric`, `integer`
  g <- lm( jitter(d) ~ d ) # class `lm`
  h <- glm( jitter(d) ~ d ) # class `lm`, `glm`
  classFilter(ls(), include=c("character", "list"), envir = e)
  classFilter(ls(), include = "numeric", envir = e)
  classFilter(ls(), include = "numeric", exclude = "integer", envir = e)
  classFilter(ls(), include = "lm", envir = e)
  classFilter(ls(), include = "lm", exclude = "glm", envir = e)
  rm(a, b, d, e, f, g, h)
})

## from another environment
e = new.env(parent = emptyenv())
e$a <- list(1:10)     # class `list`
e$b <- letters        # class `character`
e$d <- stats::runif(10)      # class `numeric`
e$f <- sample(1L:10L) # class `numeric`, `integer`
e$g <- lm( jitter(e$d) ~ e$d ) # class `lm`
e$h <- glm( jitter(e$d) ~ e$d ) # class `lm`, `glm`
classFilter(ls(e), include=c("character", "list"), envir = e)
#> [1] "a" "b"
classFilter(ls(e), include = "numeric", envir = e)
#> [1] "d" "f"
classFilter(ls(e), include = "numeric", exclude = "integer", envir = e)
#> [1] "d"
classFilter(ls(e), include = "lm", envir = e)
#> [1] "g" "h"
classFilter(ls(e), include = "lm", exclude = "glm", envir = e)
#> [1] "g"
rm(a, b, d, f, g, h, envir = e)
rm(e)