collapse (version 2.1.5)

fmin-fmax: Fast (Grouped) Maxima and Minima for Matrix-Like Objects

Description

fmax and fmin are generic functions that compute the (column-wise) maximum and minimum value of all values in x, (optionally) grouped by g. The TRA argument can further be used to transform x using its (grouped) maximum or minimum value.

Usage

fmax(x, ...)
fmin(x, ...)
# S3 method for default
fmax(x, g = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = TRUE, ...)
# S3 method for default
fmin(x, g = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = TRUE, ...)
# S3 method for matrix
fmax(x, g = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = TRUE, drop = TRUE, ...)
# S3 method for matrix
fmin(x, g = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = TRUE, drop = TRUE, ...)
# S3 method for data.frame
fmax(x, g = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = TRUE, drop = TRUE, ...)
# S3 method for data.frame
fmin(x, g = NULL, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = TRUE, drop = TRUE, ...)
# S3 method for grouped_df
fmax(x, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = FALSE, keep.group_vars = TRUE, ...)
# S3 method for grouped_df
fmin(x, TRA = NULL, na.rm = .op[["na.rm"]],
     use.g.names = FALSE, keep.group_vars = TRUE, ...)

Value

fmax returns the maximum value of x, grouped by g, or (if TRA is used) x transformed by its (grouped) maximum value. Analogous, fmin returns the minimum value ...

Details

Missing-value removal as controlled by the na.rm argument is done at no extra cost since in C++ any logical comparison involving NA or NaN evaluates to FALSE. Large performance gains can nevertheless be achieved in the presence of missing values if na.rm = FALSE, since then the corresponding computation is terminated once a NA is encountered and NA is returned (unlike max and min which just run through without any checks).

For further computational details see fsum.

See Also

Fast Statistical Functions, Collapse Overview

Examples

## default vector method
mpg <- mtcars$mpg
fmax(mpg)                         # Maximum value
fmin(mpg)                         # Minimum value (all examples below use fmax but apply to fmin)
fmax(mpg, TRA = "%")              # Simple transformation: Take percentage of maximum value
fmax(mpg, mtcars$cyl)             # Grouped maximum value
fmax(mpg, mtcars[c(2,8:9)])       # More groups..
g <- GRP(mtcars, ~ cyl + vs + am) # Precomputing groups gives more speed !
fmax(mpg, g)
fmax(mpg, g, TRA = "%")           # Groupwise percentage of maximum value
fmax(mpg, g, TRA = "replace")     # Groupwise replace by maximum value

## data.frame method
fmax(mtcars)
head(fmax(mtcars, TRA = "%"))
fmax(mtcars, g)
fmax(mtcars, g, use.g.names = FALSE) # No row-names generated

## matrix method
m <- qM(mtcars)
fmax(m)
head(fmax(m, TRA = "%"))
fmax(m, g) # etc..

## method for grouped data frames - created with dplyr::group_by or fgroup_by
mtcars |> fgroup_by(cyl,vs,am) |> fmax()
mtcars |> fgroup_by(cyl,vs,am) |> fmax("%")
mtcars |> fgroup_by(cyl,vs,am) |> fselect(mpg) |> fmax()