Package 'bazar' reference manual

Title:	Miscellaneous Basic Functions
Description:	A collection of miscellaneous functions for copying objects to the clipboard ('Copy'); manipulating strings ('concat', 'mgsub', 'trim', 'verlan'); loading or showing packages ('library_with_dep', 'require_with_dep', 'sessionPackages'); creating or testing for named lists ('nlist', 'as_nlist', 'is_nlist'), formulas ('is_formula'), empty objects ('as_empty', 'is_empty'), whole numbers ('as_wholenumber', 'is_wholenumber'); testing for equality ('almost_equal', 'almost_zero') and computing uniqueness ('almost_unique'); getting modified versions of usual functions ('rle2', 'sumNA'); making a pause or a stop ('pause', 'stopif'); converting into a function ('as_fun'); providing a C like ternary operator ('condition %?% true %:% false'); finding packages and functions ('get_all_pkgs', 'get_all_funs'); and others ('erase', '%nin%', 'unwhich', 'top', 'bot', 'normalize').
Authors:	Paul Poncet [aut, cre]
Maintainer:	Paul Poncet <[email protected]>
License:	GPL-3
Version:	1.1.0
Built:	2024-10-31 16:33:00 UTC
Source:	https://github.com/paulponcet/bazar

If-Then-Else ternary operator

Description

This is a C like ternary operator, the syntax being condition %?% true %:% false.

Usage

condition %?% true

lhs %:% false
condition %?% true

lhs %:% false

Arguments

`condition`	logical. A vector.
`true`, `false`	Values to use for `TRUE` and `FALSE` values of `condition`. They must be either the same length as `condition`, or length `1`.
`lhs`	Left-hand side of `%:%`, which should come from the result of a `%?%` call.

Value

If length(x) > 1, then ifelse is used.

Author(s)

Richie Cotton, see https://stackoverflow.com/a/8791496/3902976; Paul Poncet for the small modifications introduced.

Examples

(capitalize <- sample(c(TRUE, FALSE), 1))
capitalize %?% LETTERS[1:3] %:% letters[1:2]

# Does not work
## Not run: 
capitalize %?% 1*1:3 %:% 1:2

## End(Not run)

# Does work
capitalize %?% {1*1:3} %:% 1:2

# Does work too
capitalize %?% (1*1:3) %:% 1:2

# Vectorized version also works
c(capitalize,!capitalize) %?% "A" %:% c("b","c")

# Chaining operators is permitted 
FALSE %?% "a" %:% 
  (FALSE %?% "b") %:% 
  (capitalize %?% "C") %:% "c" 

(capitalize <- sample(c(TRUE, FALSE), 1))
capitalize %?% LETTERS[1:3] %:% letters[1:2]

# Does not work
## Not run: 
capitalize %?% 1*1:3 %:% 1:2

## End(Not run)

# Does work
capitalize %?% {1*1:3} %:% 1:2

# Does work too
capitalize %?% (1*1:3) %:% 1:2

# Vectorized version also works
c(capitalize,!capitalize) %?% "A" %:% c("b","c")

# Chaining operators is permitted 
FALSE %?% "a" %:% 
  (FALSE %?% "b") %:% 
  (capitalize %?% "C") %:% "c"

Value matching

Description

The function %nin% is the negation of the function %in%.

Usage

x %nin% table
x %nin% table

Arguments

`x`	vector or NULL: the values to be matched.
`table`	vector or NULL: the values to be matched against.

Value

A logical vector, indicating if a non-match was located for each element of x: thus the values are TRUE or FALSE and never NA.

Examples

1:10 %nin% c(1,3,5,9)

1:10 %nin% c(1,3,5,9)

Test (almost) equality of numeric values

Description

The function almost_equal tests if two numeric vectors have equal values up to a tolerance.

Usage

almost_equal(x, y, tolerance = sqrt(.Machine$double.eps))

almost.equal(x, y, tolerance = sqrt(.Machine$double.eps))
almost_equal(x, y, tolerance = sqrt(.Machine$double.eps))

almost.equal(x, y, tolerance = sqrt(.Machine$double.eps))

Arguments

`x`	numeric vector.
`y`	numeric vector of the same length as `x`.
`tolerance`	numeric. Differences smaller than tolerance are considered as equal. The default value is close to `1.5e-8`.

Value

A logical vector of the same length as x and y.

Author(s)

Tommy on StackOverflow, see http://stackoverflow.com/a/7667703.

Examples

almost_equal(x = 1:3, 
             y = 1:3 + c(10^(-6), 10^(-7), 10^(-8)))

almost_equal(x = 1:3, 
             y = 1:3 + c(10^(-6), 10^(-7), 10^(-8)))

Almost unique elements

Description

The function almost_unique extracts elements of a vector x that are unique up to a tolerance factor.

Usage

almost_unique(x, ...)

almost.unique(x, ...)

## Default S3 method:
almost_unique(x, tolerance = sqrt(.Machine$double.eps),
  ...)
almost_unique(x, ...)

almost.unique(x, ...)

## Default S3 method:
almost_unique(x, tolerance = sqrt(.Machine$double.eps),
  ...)

Arguments

`x`	numeric. The vector of numeric values at stake.
`...`	Additional arguments to be passed to the function `duplicated`, which is used internally by `almost_unique`.
`tolerance`	numeric. Relative differences smaller than tolerance are considered as equal. The default value is close to `1.5e-8`.

Value

A vector of the same type as x.

Examples

almost_unique(c(1, 1.01), tol = 0.1)
almost_unique(c(1, 1.01), tol = 0.01)

almost_unique(c(1, 2, 3), tol = 10)
almost_unique(c(1, 2, 3), tol = 5)
almost_unique(c(1, 2, 3), tol = 1)

almost_unique(c(1, 1.01), tol = 0.1)
almost_unique(c(1, 1.01), tol = 0.01)

almost_unique(c(1, 2, 3), tol = 10)
almost_unique(c(1, 2, 3), tol = 5)
almost_unique(c(1, 2, 3), tol = 1)

Test if values of a vector are almost zero

Description

The function almost_zero tests if values of the numeric vector x are equal to zero up to a tolerance.

Usage

almost_zero(x, tolerance = sqrt(.Machine$double.eps))

almost.zero(x, tolerance = sqrt(.Machine$double.eps))
almost_zero(x, tolerance = sqrt(.Machine$double.eps))

almost.zero(x, tolerance = sqrt(.Machine$double.eps))

Arguments

`x`	numeric. The vector of numeric values at stake.
`tolerance`	numeric. Differences smaller than tolerance are considered as equal. The default value is close to `1.5e-8`.

Value

A logical vector of the same length as x.

Examples

almost_zero(c(0, 10^(-7), 10^(-8)))

almost_zero(c(0, 10^(-7), 10^(-8)))

Convert to an empty object

Description

Convert x to an empty object.

Usage

as_empty(x, ...)

as.empty(x, ...)

## Default S3 method:
as_empty(x, ...)

## S3 method for class 'data.frame'
as_empty(x, ...)
as_empty(x, ...)

as.empty(x, ...)

## Default S3 method:
as_empty(x, ...)

## S3 method for class 'data.frame'
as_empty(x, ...)

Arguments

`x`	An object.
`...`	Additional parameterS.

Value

An empty object

Examples

x <- c("a", "b", "c")
as_empty(x)
class(as_empty(x)) # still a character

x <- factor(LETTERS)
as_empty(x)        # levels are kept
class(as_empty(x)) # still a factor

x <- data.frame(x = 1:3, y = 2:4)
as_empty(x)

x <- c("a", "b", "c")
as_empty(x)
class(as_empty(x)) # still a character

x <- factor(LETTERS)
as_empty(x)        # levels are kept
class(as_empty(x)) # still a factor

x <- data.frame(x = 1:3, y = 2:4)
as_empty(x)

Convert object to function

Description

as_fun is a generic function that does the same as as.function from package base, with the additional feature that as_fun.character converts a string into the function it names.

Usage

as_fun(x, ...)

as.fun(x, ...)

## Default S3 method:
as_fun(x, envir = parent.frame(), ...)

## S3 method for class 'character'
as_fun(x, ...)

## S3 method for class 'formula'
as_fun(x, ...)

## S3 method for class 'name'
as_fun(x, ...)

## S3 method for class 'call'
as_fun(x, ...)

## S3 method for class 'numeric'
as_fun(x, ...)

## S3 method for class 'logical'
as_fun(x, ...)

## S3 method for class 'factor'
as_fun(x, ...)

## S3 method for class 'complex'
as_fun(x, ...)

## S3 method for class 'data.frame'
as_fun(x, ...)

## S3 method for class 'lm'
as_fun(x, ...)

## S3 method for class 'rpart'
as_fun(x, ...)
as_fun(x, ...)

as.fun(x, ...)

## Default S3 method:
as_fun(x, envir = parent.frame(), ...)

## S3 method for class 'character'
as_fun(x, ...)

## S3 method for class 'formula'
as_fun(x, ...)

## S3 method for class 'name'
as_fun(x, ...)

## S3 method for class 'call'
as_fun(x, ...)

## S3 method for class 'numeric'
as_fun(x, ...)

## S3 method for class 'logical'
as_fun(x, ...)

## S3 method for class 'factor'
as_fun(x, ...)

## S3 method for class 'complex'
as_fun(x, ...)

## S3 method for class 'data.frame'
as_fun(x, ...)

## S3 method for class 'lm'
as_fun(x, ...)

## S3 method for class 'rpart'
as_fun(x, ...)

Arguments

`x`	The object to convert.
`...`	Additional arguments (currently not used).
`envir`	Environment in which the function should be defined.

Value

The desired function.

Author(s)

as_fun.character is adapted from MrFlick, see https://stackoverflow.com/a/38984214 on StackOverflow.

Examples

as_fun(mean)
as_fun("mean")
as_fun("edit")
as_fun("stats::predict")

## Uses 'rlang::as_function()' for formulas under the hood: 
f <- as_fun(~ . + 1)
f(10) # 11

## the constant function '1'
f <- as_fun(1)
f(2)   # 1
f("a") # 1

## the constant function 'FALSE'
f <- as_fun(FALSE)
f(2)   # FALSE
f("a") # FALSE

f <- as_fun(data.frame(x = 1:2, y = 2:3))
f("x") # 'x' column
f("y") # 'y' column

as_fun(mean)
as_fun("mean")
as_fun("edit")
as_fun("stats::predict")

## Uses 'rlang::as_function()' for formulas under the hood: 
f <- as_fun(~ . + 1)
f(10) # 11

## the constant function '1'
f <- as_fun(1)
f(2)   # 1
f("a") # 1

## the constant function 'FALSE'
f <- as_fun(FALSE)
f(2)   # FALSE
f("a") # FALSE

f <- as_fun(data.frame(x = 1:2, y = 2:3))
f("x") # 'x' column
f("y") # 'y' column

Transform values to NA

Description

These methods transform values to NA for different classes of objects.

Usage

as_na(x, ...)

as.na(x, ...)

## Default S3 method:
as_na(x, ...)

## S3 method for class 'data.frame'
as_na(x, ...)

## S3 method for class 'list'
as_na(x, ...)
as_na(x, ...)

as.na(x, ...)

## Default S3 method:
as_na(x, ...)

## S3 method for class 'data.frame'
as_na(x, ...)

## S3 method for class 'list'
as_na(x, ...)

Arguments

`x`	The object at stake.
`...`	Additional arguments (unused).

Value

An object of the same class as x; the attributes of x are passed unchanged to the result.

Examples

x <- c("a", "b", "c")
as_na(x)
class(as_na(x)) # still a character

x <- factor(LETTERS)
as_na(x)        # levels are kept
class(as_na(x)) # still a factor

x <- data.frame(x = 1:3, y = 2:4)
as_na(x)
dim(as_na(x))

x <- matrix(1:6, 2, 3)
attr(x, "today") <- Sys.Date()
as_na(x)        # attributes are kept

x <- c("a", "b", "c")
as_na(x)
class(as_na(x)) # still a character

x <- factor(LETTERS)
as_na(x)        # levels are kept
class(as_na(x)) # still a factor

x <- data.frame(x = 1:3, y = 2:4)
as_na(x)
dim(as_na(x))

x <- matrix(1:6, 2, 3)
attr(x, "today") <- Sys.Date()
as_na(x)        # attributes are kept

bazar: miscellaneous basic functions

Description

bazar provides a collection of miscellaneous functions for

copying objects to the clipboard (Copy);
manipulating strings (concat, mgsub, trim, verlan);
loading or showing packages (library_with_dep, require_with_dep, sessionPackages);
creating or testing for named lists (nlist, as_nlist, is_nlist), formulas (is_formula), empty objects (as_empty, is_empty), whole numbers (as_wholenumber, is_wholenumber);
testing for equality (almost_equal, almost_zero);
getting modified versions of usual functions (rle2, sumNA);
making a pause or a stop (pause, stopif);
and others (erase, %in%, unwhich).

String concatenation

Description

The function concat concatenates character vectors all together.

concat0(.) is a wrapper for concat(., sep = ""). concat_(.) is a wrapper for concat(., sep = "_").

Usage

concat(..., sep = " ", na.rm = TRUE)

concat0(..., na.rm = TRUE)

concat_(..., na.rm = TRUE)
concat(..., sep = " ", na.rm = TRUE)

concat0(..., na.rm = TRUE)

concat_(..., na.rm = TRUE)

Arguments

`...`	One or more objects, to be converted to character vectors and concatenated.
`sep`	character. The character to use to separate the result.
`na.rm`	logical. If `TRUE` (the default), missing values are removed before concatenation.

Value

Always a character value (vector of length 1).

Examples

v <- c("Florence", "Julie", "Angela")
concat0(v)
concat_(v)
concat(v, sep = "^^")
concat0(c("a", "b"), c(1, NA, 3), NA)
concat(c(NA, NA))
concat(c(NA, NA), na.rm = FALSE) # usually not desirable

v <- c("Florence", "Julie", "Angela")
concat0(v)
concat_(v)
concat(v, sep = "^^")
concat0(c("a", "b"), c(1, NA, 3), NA)
concat(c(NA, NA))
concat(c(NA, NA), na.rm = FALSE) # usually not desirable

Copy data to the clipboard

Description

The function Copy can typically be used to copy data from a data frame, in order to paste it somewhere else (in Excel for instance).

Usage

Copy(x, size = 128L, quote = TRUE, sep = "\t", na = "",
  dec = ".", ...)
Copy(x, size = 128L, quote = TRUE, sep = "\t", na = "",
  dec = ".", ...)

Arguments

`x`	An object.
`size`	integer. Number of kilobytes. Increase this value if the object `x` is too big.
`quote`	See the eponymous argument in `write.table`.
`sep`	character. The field separator string.
`na`	character. The string to use for missing values.
`dec`	character. The string to use for decimal points in numeric or complex columns.
`...`	Additional arguments to be passed to `write.table`.

Delete objects

Description

The function erase deletes all objects that live in the calling environment.

Usage

erase(ask = TRUE)
erase(ask = TRUE)

Arguments

ask

logical. If TRUE (the default), a confirmation is interactively asked to the user.

Warning

use this function with care!

Functions exported by a package

Description

get_all_funs provides all the functions exported by a given installed package.

Usage

get_all_funs(pkg)
get_all_funs(pkg)

Arguments

pkg

character. The package of interest. (Must be installed already.)

Value

A character vector, the functions exported.

Examples

get_all_funs("stats")

get_all_funs("stats")

Packages exporting a function

Description

get_all_pkgs provides all packages (belonging to a given list of packages) exported by a given function.

Usage

get_all_pkgs(fun, packages = NULL)
get_all_pkgs(fun, packages = NULL)

Arguments

`fun`	function or character. The function of interest.
`packages`	The packages to look into. If `NULL`, the list of currently attached packages is explored.

Value

A character vector, the packages.

Examples

## Not run: 
get_all_pkgs("as.fun")
get_all_pkgs(as.fun)
get_all_pkgs("stats::median")

## End(Not run)

## Not run: 
get_all_pkgs("as.fun")
get_all_pkgs(as.fun)
get_all_pkgs("stats::median")

## End(Not run)

Get formula variables

Description

The function get_vars extracts variable names from a formula.

Usage

get_vars(formula, data = NULL, intersection = TRUE)
get_vars(formula, data = NULL, intersection = TRUE)

Arguments

`formula`	a formula.
`data`	data.frame or matrix. If not `NULL`, formulas with a dot `.` are permitted.
`intersection`	logical. If `TRUE` and `data` is not `NULL`, the intersection between variables found in the formula and `data` column names is returned.

Value

a character vector, the variables found.

Examples

get_vars(y ~ x1 + x2 - x1)
get_vars(y ~ . - x1, data = data.frame(y = 1, x1 = 2, x2 = 3))
get_vars(y + z ~ x1 + x2 - x1 | x3)
get_vars(y ~ x1 + I(log(x2)))
get_vars(y ~ x1*x2)
get_vars(y ~ x1:x2)
get_vars(~ x1 + x2)

get_vars(y ~ x1 + x2 - x1)
get_vars(y ~ . - x1, data = data.frame(y = 1, x1 = 2, x2 = 3))
get_vars(y + z ~ x1 + x2 - x1 | x3)
get_vars(y ~ x1 + I(log(x2)))
get_vars(y ~ x1*x2)
get_vars(y ~ x1:x2)
get_vars(~ x1 + x2)

Test emptyness

Description

These methods test if an object x is empty.

Usage

is_empty(x)

is.empty(x)

## Default S3 method:
is_empty(x)

## S3 method for class 'data.frame'
is_empty(x)
is_empty(x)

is.empty(x)

## Default S3 method:
is_empty(x)

## S3 method for class 'data.frame'
is_empty(x)

Arguments

`x`	An object to be tested.

Value

TRUE if x is empty, FALSE otherwise.

Examples

is_empty(4)
is_empty(c())
is_empty(new.env())
is_empty(character(0))
is_empty(list())
is_empty(integer(0))
is_empty(data.frame())

is_empty(4)
is_empty(c())
is_empty(new.env())
is_empty(character(0))
is_empty(list())
is_empty(integer(0))
is_empty(data.frame())

Test if an object is a formula

Description

The function is_formula tests if the object x is a formula.

Usage

is_formula(x)

is.formula(x)
is_formula(x)

is.formula(x)

Arguments

`x`	An object.

Value

A logical, TRUE if x is a formula.

Examples

is_formula("this is a formula")
is_formula(f <- formula("y ~ x"))
is_formula(update(f, ~ . -1))

is_formula("this is a formula")
is_formula(f <- formula("y ~ x"))
is_formula(update(f, ~ . -1))

Test if the values of a vector are whole numbers

Description

The function is_wholenumber tests if values of the numeric vector x are all whole numbers (up to a tolerance).

The function as_wholenumber is a synonym for as.integer.

Usage

is_wholenumber(x, tolerance = sqrt(.Machine$double.eps))

is.wholenumber(x, tolerance = sqrt(.Machine$double.eps))

as_wholenumber(x, ...)

as.wholenumber(x, ...)
is_wholenumber(x, tolerance = sqrt(.Machine$double.eps))

is.wholenumber(x, tolerance = sqrt(.Machine$double.eps))

as_wholenumber(x, ...)

as.wholenumber(x, ...)

Arguments

`x`	a vector to be tested.
`tolerance`	numeric. Differences smaller than tolerance are considered as equal. The default value is close to `1.5e-8`.
`...`	Additional arguments passed to or from other methods.

Value

A logical, TRUE if all values of x are (finite) whole numbers. If x contains NA or NaN, then NA is returned.

Examples

x = c(1L, 10L)
is.integer(x)
is_wholenumber(x)

x = c(1, 10)
is.integer(x)
is_wholenumber(x) # here is the difference with 'is.integer'

is_wholenumber(1+10^(-7))
is_wholenumber(1+10^(-8))

x = c(1L, 10L)
is.integer(x)
is_wholenumber(x)

x = c(1, 10)
is.integer(x)
is_wholenumber(x) # here is the difference with 'is.integer'

is_wholenumber(1+10^(-7))
is_wholenumber(1+10^(-8))

Loading/Attaching and listing of packages with dependencies

Description

library_with_dep and require_with_dep behave respectively like library and require, but also load and attach dependent packages (typically packages listed in the Imports field of the DESCRIPTION file).

Usage

library_with_dep(package, help, pos = 2, lib.loc = NULL,
  character.only = FALSE, logical.return = FALSE,
  warn.conflicts = TRUE, quietly = FALSE,
  verbose = getOption("verbose"), which = "Imports",
  recursive = FALSE, reverse = FALSE)

require_with_dep(package, lib.loc = NULL, quietly = FALSE,
  warn.conflicts = TRUE, character.only = FALSE, which = "Imports",
  recursive = FALSE, reverse = FALSE, verbose = getOption("verbose"))
library_with_dep(package, help, pos = 2, lib.loc = NULL,
  character.only = FALSE, logical.return = FALSE,
  warn.conflicts = TRUE, quietly = FALSE,
  verbose = getOption("verbose"), which = "Imports",
  recursive = FALSE, reverse = FALSE)

require_with_dep(package, lib.loc = NULL, quietly = FALSE,
  warn.conflicts = TRUE, character.only = FALSE, which = "Imports",
  recursive = FALSE, reverse = FALSE, verbose = getOption("verbose"))

Arguments

`package`	the name of a package, given as a name or literal character string, or a character string, depending on whether character.only is `FALSE` (default) or `TRUE`.
`help`	the name of a package, given as a name or literal character string, or a character string, depending on whether character.only is `FALSE` (default) or `TRUE`.
`pos`	the position on the search list at which to attach the loaded namespace. Can also be the name of a position on the current search list as given by `search`().
`lib.loc`	character. A vector describing the location of R library trees to search through, or `NULL`. The default value of `NULL` corresponds to all libraries currently known to `.libPaths`(). Non-existent library trees are silently ignored.
`character.only`	logical. Indicates whether `package` or `help` can be assumed to be character strings.
`logical.return`	logical. If it is `TRUE`, then `FALSE` or `TRUE` is returned to indicate success.
`warn.conflicts`	logical. If `TRUE`, warnings are printed about conflicts from attaching the new package. A conflict is a function masking a function, or a non-function masking a non-function.
`quietly`	logical. If `TRUE`, no message confirming package attaching is printed, and most often, no errors/warnings are printed if package attaching fails.
`verbose`	logical. If `TRUE`, additional diagnostics are printed.
`which`	character. A vector listing the types of dependencies, a subset of `c("Depends", "Imports", "LinkingTo", "Suggests", "Enhances")`. Character string `"all"` is shorthand for that vector, character string `"most"` for the same vector without `"Enhances"`.
`recursive`	logical. Should (reverse) dependencies of (reverse) dependencies (and so on) be included?
`reverse`	logical. If `FALSE` (default), regular dependencies are calculated, otherwise reverse dependencies.

Multiple gsub

Description

The function mgsub is a ‘multiple’ version of gsub.

Usage

mgsub(pattern, replacement, x, ...)
mgsub(pattern, replacement, x, ...)

Arguments

`pattern`	character vector containing regular expressions to be matched in the given character vector.
`replacement`	a replacement vector of the same length as `pattern` for matched pattern. Coerced to character if possible.
`x`	vector or NULL: the values to be matched against.
`...`	additional parameters to be passed to `gsub`.

Value

A character vector of the same length as x.

Author(s)

Theodore Lytras on StackOverflow, see http://stackoverflow.com/a/15254254/3902976

Examples

mgsub(c("aa", "AA"), c("bb", "BB"), c("XXaaccAACC", "YYaaccAACC", "ZZaaccAACC"))

mgsub(c("aa", "AA"), c("bb", "BB"), c("XXaaccAACC", "YYaaccAACC", "ZZaaccAACC"))

Named lists

Description

Functions to construct, coerce and check for named lists.

Usage

nlist(...)

as_nlist(x, ...)

is_nlist(x)

as.nlist(x, ...)

is.nlist(x)
nlist(...)

as_nlist(x, ...)

is_nlist(x)

as.nlist(x, ...)

is.nlist(x)

Arguments

`...`	Named objects.
`x`	Object to be coerced or tested.

Value

A named list.

Examples

x <- nlist(x = 2, y = c("a", "b"))
is_nlist(x)

x <- nlist(x = 2, y = c("a", "b"))
is_nlist(x)

Normalize a numeric vector

Description

This function divides x by the result of fun(x).

Usage

normalize(x, fun = "max", na.rm = TRUE, ...)
normalize(x, fun = "max", na.rm = TRUE, ...)

Arguments

`x`	numeric. A vector.
`fun`	character or function. Should own an `na.rm` argument. `fun(x)` should return either one unique value, or a numeric vector of the same length as `x`.
`na.rm`	Should missing values be removed in the calculation of `fun(x)`?
`...`	Additional arguments to be passed to `fun`.

Value

A numeric vector of the same length as x.

Examples

x <- rnorm(10)
normalize(x)

x <- rnorm(10)
normalize(x)

Have a rest, make a pause

Description

The pause function stops momentarily the execution of a program. Pressing <Enter> continues the execution; typing 'stop' (without quotation marks) ends the program.

Usage

pause(duration = Inf)
pause(duration = Inf)

Arguments

duration

numeric or infinite. If duration is infinite (the default), then a pause is made until the user presses <Enter> or types 'stop'. Else if x = duration is a number, then a pause is made during x seconds.

Run length encoding (modified version)

Description

Compute the lengths and values of runs of almost_equal values in a vector.

Usage

rle2(x, tolerance = sqrt(.Machine$double.eps))
rle2(x, tolerance = sqrt(.Machine$double.eps))

Arguments

`x`	numeric vector.
`tolerance`	numeric. Differences smaller than tolerance are considered as equal. The default value is close to `1.5e-8`.

Value

An object of class "rle" which is a list with components:

lengths: an integer vector containing the length of each run.
values: a vector of the same length as lengths with the corresponding values.

Moving windows with custom function

Description

Windowed / rolling operations on a vector, with a custom function fun provided as input.

Usage

rollfun(x, k, fun = "mean", ..., .idx = NULL)

make_idx(k, n)
rollfun(x, k, fun = "mean", ..., .idx = NULL)

make_idx(k, n)

Arguments

`x`	A vector.
`k`	integer. Width of moving window; must be an integer between one and `length(x)`.
`fun`	character or function. The function to be applied on moving subvectors of `x`.
`...`	Additional arguments to be passed to `fun`.
`.idx`	integer. A vector of indices that can be precalculated with the function `make_idx`.
`n`	integer. Length of the input vector `x`.

Examples

set.seed(1)
x <- sample(1:10)
rollfun(x, k = 3)
rollfun(x, k = 3, fun = max)

set.seed(1)
x <- sample(1:10)
rollfun(x, k = 3)
rollfun(x, k = 3, fun = max)

Shows packages attached to the current R session

Description

The function sessionPackages prints the list of packages attached to the current R session.

Usage

sessionPackages(package = NULL)
sessionPackages(package = NULL)

Arguments

package

a character vector naming installed packages, or NULL (the default) meaning all attached packages.

Details

This function reuses part of the code from sessionInfo.

Value

A list with the following components:

basePkgs: a character vector of base packages which are attached.
otherPkgs (not always present): a character vector of other attached packages.

Examples

sessionPackages()

sessionPackages()

Ensure that R expressions are false

Description

If any of the expressions in ... are not all FALSE, stop is called, producing an error message indicating the first of the elements of ... which were not false.

Usage

stopif(...)
stopif(...)

Arguments

...

Any number of (logical) R expressions, which should evaluate to TRUE.

Value

(NULL if all statements in ... are FALSE.)

Examples

## Not run: 
stopif(is.empty(c(2,1)), 4 < 3) # all FALSE
stopif(is.empty(numeric(0)))

## End(Not run)

## Not run: 
stopif(is.empty(c(2,1)), 4 < 3) # all FALSE
stopif(is.empty(numeric(0)))

## End(Not run)

Modified sum of vector elements

Description

The function sumNA returns the sum of all the values in its arguments. Contrarily to sum, it returns NA instead of 0 when the input contains only missing values and missing values are removed.

Usage

sumNA(..., na.rm = FALSE)
sumNA(..., na.rm = FALSE)

Arguments

`...`	numeric or complex or logical vectors.
`na.rm`	logical. Should missing values (including `NaN`) be removed?

Value

The sum. Returns NA if x contains only missing values and na.rm = TRUE.

Examples

x <- c(NA, NA)
sum(x)
sumNA(x)
sum(x, na.rm = TRUE)
sumNA(x, na.rm = TRUE) # here is the difference with 'sum()'

sum(c())
sumNA(c())

x <- c(NA, NA)
sum(x)
sumNA(x)
sum(x, na.rm = TRUE)
sumNA(x, na.rm = TRUE) # here is the difference with 'sum()'

sum(c())
sumNA(c())

Top or bottom element of an object

Description

top(x) is an alias for head(x, 1L). bot(x) is an alias for tail(x, 1L).

Usage

top(x)

bot(x)
top(x)

bot(x)

Arguments

`x`	an object.

Value

An object (usually) like x but generally smaller.

Removes extra whitespaces from a string

Description

The function trim removes unnecessary whitespaces from a character vector.

Usage

trim(x)
trim(x)

Arguments

`x`	character. The character vector at stake.

Value

A character vector of the same length as x.

Examples

trim(c(" a b", "Hello  World "))

trim(c(" a b", "Hello  World "))

Quasi-inverse of the 'which' function

Description

The unwhich function is a kind of inverse of the which function.

Usage

unwhich(w, n)
unwhich(w, n)

Arguments

`w`	A vector of integers; morally the result of a call to `which`.
`n`	integer. The length of the result; morally the length of the `x` argument of a call to `which`.

Value

A logical vector of length n.

Examples

x1 <- c(TRUE, FALSE, TRUE, TRUE)
x2 <- unwhich(which(x1), length(x1))
identical(x1, x2) # TRUE

w1 <- c(2, 4, 5, 1, 1)
w2 <- which(unwhich(w1, 10))
identical(sort(unique(as.integer(w1))), w2) # TRUE

x1 <- c(TRUE, FALSE, TRUE, TRUE)
x2 <- unwhich(which(x1), length(x1))
identical(x1, x2) # TRUE

w1 <- c(2, 4, 5, 1, 1)
w2 <- which(unwhich(w1, 10))
identical(sort(unique(as.integer(w1))), w2) # TRUE

Back slang

Description

The verlan function reverses the order of the characters in a string.

Usage

verlan(x)
verlan(x)

Arguments

`x`	character. A vector of strings.

Value

A character vector of the same length as x.

Examples

verlan("baba") ## "abab"
verlan(c("radar", "paul")) ## c("radar", "luap")

verlan("baba") ## "abab"
verlan(c("radar", "paul")) ## c("radar", "luap")

Package 'bazar'

Help Index

If-Then-Else ternary operator

Description

Usage

Arguments

Value

Author(s)

Examples

Value matching

Description

Usage

Arguments

Value

See Also

Examples

Test (almost) equality of numeric values

Description

Usage

Arguments

Value

Author(s)

Examples

Almost unique elements

Description

Usage

Arguments

Value

See Also

Examples

Test if values of a vector are almost zero

Description

Usage

Arguments

Value

See Also

Examples

Convert to an empty object

Description

Usage

Arguments

Value

See Also

Examples

Convert object to function

Description

Usage

Arguments

Value

Author(s)

See Also

Examples

Transform values to NA

Description

Usage

Arguments

Value

Examples

bazar: miscellaneous basic functions

Description

String concatenation

Description

Usage

Arguments

Value

See Also

Examples

Copy data to the clipboard

Description

Usage

Arguments

Delete objects

Description

Usage

Arguments

Warning

Functions exported by a package

Description

Usage

Arguments