Description Usage Arguments Details Examples
relate
returns a vector Y = F(X) where F maps
each element of input vector X
from its position in vector A
to its corresponding position in vector B. Can be applied as a
vectorised keyvalue dictionary with an optional default return value.
Additional options restrict mapping types so relation F must be a
function, injective, surjective, etc.
relation
returns a reusable function F that performs the same
operation as relate
. In addition to providing a reusable function,
if handle_duplicate_mappings = TRUE
, relation
checks for and
eliminates duplicate mappings that would be invalid inputs for
relate
. If report_properties = TRUE
, relation
also
prints the restrictions the mapping from A
to B
conforms to.
1 2 3 4 5 6 7 8 9 10 11  relate(X, A, B, default = NA, atomic = TRUE, named = FALSE,
allow_default = TRUE, heterogeneous_outputs = FALSE,
handle_duplicate_mappings = FALSE, report_properties = FALSE,
relation_type = "func", restrictions = list(),
map_error_response = "warn")
relation(A, B, default = NA, atomic = TRUE, named = FALSE,
allow_default = TRUE, heterogeneous_outputs = FALSE,
handle_duplicate_mappings = FALSE, report_properties = FALSE,
relation_type = "func", restrictions = list(),
map_error_response = "warn")

X 
A vector of inputs 
A 
A vector possible inputs ordered to correspond to desired outputs
given by 
B 
A vector possible outputs ordered to correspond to each input to the
relation given by 
default 
The default value to return if F(x) is undefined. 
atomic 
If 
named 
The elements of the returned vector Y will be named by to their corresponding inputs in X. 
allow_default 
If TRUE, the provided default will be returned when
F(x) is undefined; otherwise invalid mappings will return an error
determined by the 
heterogeneous_outputs 
By default, elements y of the output
vector Y will be returned as atomic vectors. In manytomany and
onetomany relations, if the elements in the codomain are not all of the
same type, this will coerce outputs to the same type. Set

handle_duplicate_mappings 
If 
report_properties 
If 
relation_type 
Ensure that the relation is restricted to a certain type, e.g. "bijection". See Details. 
restrictions 
A named list of logicals imposing constraints on the
relation. These will only be used if relation_type is 
map_error_response 
How to deal with mapping errors caused by violated restrictions. Takes values "ignore", "warn", or "throw". 
relate
returns vector of outputs Y = F(X) where the
F is a relation defined by the collection of ordered pairs (a_i,
b_i) where a_i, b_i are the ith elements of A
and
B
respectively. If F(x) is undefined because x is not in
A or it does not map to an element of B
, relate
will
either return default
if allow_default = TRUE
. Otherwise the
function will throw an error.
The relation F can be restricted so it conforms to a particular type
specified by relation_type
. If relation_type = NULL
, the
properties are determined by restrictions specified with a named list, for
example restrictions = list(min_one_y_per_x = TRUE)
. For all
relations where min_one_y_per_x = FALSE
, only a list vector can be
returned, so an error will be thrown if atomic = TRUE
. If A
and B
do not produce a relation that conforms to the specified type
or restrictions, the value of map_error_response
will determine
whether the relate
ignores the error, reports it, or throws it. The
full list of restrictions and relation types are listed below:
Restrictions
NB: 1) The restrictions
argument is only used if
relation_type = NULL
; 2) If relation is allowed to return multiple
values, i.e. max_one_y_per_x = FALSE
, then atomic
must be set
to FALSE
, otherwise an error will be throw; 3). All unspecified
restrictions are assumed false, e.g. restrictions = list()
is
equivalent to restrictions = list("min_one_y_per_x" = FALSE,
"min_one_x_per_y" = FALSE, "max_one_y_per_x" = FALSE, "max_one_x_per_y" =
FALSE)
min_one_y_per_x
Guarantees at least one
y = F(x) in B
exists for each x in A
. Returns an
error if B is longer than A.
min_one_x_per_y
Guarantees at
least one x in A
exists for each y in B
such that
y = F(x). Returns an error if A is longer than B.
max_one_y_per_x
Guarantees no more than one y = F(x) in
B
exists for each x in A
. Returns an error if A
contains duplicate elements.
max_one_x_per_y
Guarantees no
more than one x in A
exists for each y in B
such
that y = F(x). Returns an error if B contains duplicate elements.
Relation types
relation_type =
"one_to_one"
Onetoone relations require that each element in the domain
to map to at most one element in the codomain, and each element of the
codomain to map from the only one element in the domain. There may still be
elements in A
that do not have a mapping to an element in B
,
and vice versa. This is equivalent to
restrictions =
list(
"min_one_y_per_x" = FALSE,
"min_one_x_per_y" = FALSE,
"max_one_y_per_x"
= TRUE,
"max_one_x_per_y" = TRUE
relation_type = "many_to_many"
Manytomany relations allow multiple elements in the domain to map to the same element of the codomain, and multiple elements of the codomain to map from the same element of the domain. This is equivalent to
restrictions =
list(
"min_one_y_per_x" = FALSE,
"min_one_x_per_y" = FALSE,
"max_one_y_per_x"
= FALSE,
"max_one_x_per_y" = FALSE
relation_type = "one_to_many"
Onetomany relations require each element of the domain to map to a distinct set of one or more elements in the codomain. This is equivalent to
restrictions
= list(
"min_one_y_per_x" = FALSE,
"min_one_x_per_y" = FALSE,
"max_one_y_per_x"
= FALSE,
"max_one_x_per_y" = TRUE
relation_type = "many_to_one"
Manytoone relations allows sets of one or more elements in the domain to map to the same distinct element in the codomain. This is equivalent to
restrictions = list(
"min_one_y_per_x" = FALSE,
"min_one_x_per_y"
= FALSE,
"max_one_y_per_x" = TRUE,
"max_one_x_per_y" = FALSE
relation_type = "func"
Functions map each element in the domain to exactly one element in the codomain. This is equivalent to
restrictions = list(
"min_one_y_per_x" = TRUE,
"min_one_x_per_y" =
FALSE,
"max_one_y_per_x" = TRUE,
"max_one_x_per_y" = FALSE
relation_type = "injection"
A function is injective if every element of the domain maps to a unique element of the codomain. This is equivalent to
restrictions = list(
"min_one_y_per_x" = TRUE,
"min_one_x_per_y" =
FALSE,
"max_one_y_per_x" = TRUE,
"max_one_x_per_y" = TRUE
relation_type = "surjection"
A function is surjective if every element of the codomain maps from an element of the domain. This is equivalent to
restrictions = list(
"min_one_y_per_x" = TRUE,
"min_one_x_per_y" =
TRUE,
"max_one_y_per_x" = TRUE,
"max_one_x_per_y" = FALSE
relation_type = "bijection"
A function is bijective if it is both injective and surjective, i.e. a complete onetoone mapping. This is equivalent to
restrictions = list(
"min_one_y_per_x" = TRUE,
"min_one_x_per_y" =
TRUE,
"max_one_y_per_x" = TRUE,
"max_one_x_per_y" = TRUE
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118  ## Map from one vector to another
relate(c("a", "e", "i", "o", "u"), letters, LETTERS)
# [1] "A" "E" "I" "O" "U"
## or
caps < relation(letters, LETTERS)
caps("t")
# [1] "T"
caps(c("p", "q", "r"))
# [1] "P" "Q" "R"
## Create a new column in a data frame
df < data.frame(
name = c("Alice", "Bob", "Charlotte", "Dan", "Elise", "Frank"),
position = c("right", "leanleft", "left", "left", "leanright", "no response")
)
positions < c("left", "leanleft", "independent", "leanright", "right")
colours < c("darkblue", "lightblue", "green", "lightred", "darkred")
df$colour < relate(df$position, positions, colours, default = "gray")
df
# name position colour
# 1 Alice right darkred
# 2 Bob leanleft lightblue
# 3 Charlotte left darkblue
# 4 Dan left darkblue
# 5 Elise leanright lightred
# 6 Frank no response gray
## Authors have a manytomany relation with books:
## a book can have multiple authors and authors can write multiple books
my_library < data.frame(
author = c(
"Arendt",
"AustenSmith",
"AustenSmith",
"AustenSmith",
"Banks",
"Banks",
"Camus",
"Camus",
"Arendt",
"Dryzek",
"Dunleavy"
),
work = c(
"The Human Condition",
"Social Choice and Voting Models",
"Information Aggregation, Rationality, and the Condorcet Jury Theorem",
"Positive Political Theory I",
"Information Aggregation, Rationality, and the Condorcet Jury Theorem",
"Positive Political Theory I",
"The Myth of Sisyphus",
"The Rebel",
"The Origins of Totalitarianism",
"Theories of the Democratic State",
"Theories of the Democratic State"
),
stringsAsFactors = FALSE
)
relate(
X = c("Arendt", "AustenSmith", "Banks", "Dryzek", "Dunleavy"),
A = my_library$author,
B = my_library$work,
atomic = FALSE,
named = TRUE,
relation_type = "many_to_many"
)
# $Arendt
# [1] "The Human Condition" "The Origins of Totalitarianism"
#
# $`AustenSmith`
# [1] "Social Choice and Voting Models"
# [2] "Information Aggregation, Rationality, and the Condorcet Jury Theorem"
# [3] "Positive Political Theory I"
#
# $Banks
# [1] "Information Aggregation, Rationality, and the Condorcet Jury Theorem"
# [2] "Positive Political Theory I"
#
# $Dryzek
# [1] "Theories of the Democratic State"
#
# $Dunleavy
# [1] "Theories of the Democratic State"
## Duplicate mappings will return multiple copies by default:
relate(
X = 1:3,
A = c(1, 2, 2, 3, 4, 5),
B = c('a', 'b', 'b', 'c', 'd', 'e'),
relation_type = "many_to_many",
atomic = FALSE
)
# [[1]]
# [1] "a"
#
# [[2]]
# [1] "b" "b"
#
# [[3]]
# [1] "c"
## Use handle_duplicate_mappings = TRUE to ignore these and avoid mapping errors.
nums_to_letters < relation(
A = c(1, 2, 2, 3, 4, 5),
B = c('a', 'b', 'b', 'c', 'd', 'e'),
relation_type = "bijection",
handle_duplicate_mappings = TRUE
)
nums_to_letters(X = c(1, 2, 3))
# [1] "a" "b" "c"
## Use relation with report_properties = TRUE to determine the properties of specified relation
domain < 3:3
image < domain^2
relation(domain, image, report_properties = TRUE)
# Relation properties:
# min_one_y_per_x min_one_x_per_y max_one_y_per_x max_one_x_per_y
# TRUE TRUE TRUE FALSE

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