Package 'permutations' reference manual

Title:	The Symmetric Group: Permutations of a Finite Set
Description:	Manipulates invertible functions from a finite set to itself. Can transform from word form to cycle form and back. To cite the package in publications please use Hankin (2020) "Introducing the permutations R package", SoftwareX, volume 11 <doi:10.1016/j.softx.2020.100453>.
Authors:	Robin K. S. Hankin [aut, cre] , Paul Egeler [ctb]
Maintainer:	Robin K. S. Hankin <[email protected]>
License:	GPL-2
Version:	1.1-5
Built:	2024-09-16 06:20:37 UTC
Source:	CRAN

The Symmetric Group: Permutations of a Finite Set

Description

Manipulates invertible functions from a finite set to itself. Can transform from word form to cycle form and back. To cite the package in publications please use Hankin (2020) "Introducing the permutations R package", SoftwareX, volume 11 <doi:10.1016/j.softx.2020.100453>.

Details

The DESCRIPTION file:

Package:	permutations
Type:	Package
Title:	The Symmetric Group: Permutations of a Finite Set
Version:	1.1-5
Imports:	magic,numbers,partitions (>= 1.9-17),freealg (>= 1.0-4)
Authors@R:	c( person(given=c("Robin", "K. S."), family="Hankin", role = c("aut","cre"), email="[email protected]", comment = c(ORCID = "0000-0001-5982-0415")), person("Paul", "Egeler", email = "[email protected]", role = c("ctb"), comment = c(ORCID = "0000-0001-6948-9498")) )
Maintainer:	Robin K. S. Hankin <[email protected]>
Depends:	R (>= 3.5.0), methods
LazyData:	TRUE
Description:	Manipulates invertible functions from a finite set to itself. Can transform from word form to cycle form and back. To cite the package in publications please use Hankin (2020) "Introducing the permutations R package", SoftwareX, volume 11 <doi:10.1016/j.softx.2020.100453>.
License:	GPL-2
Suggests:	rmarkdown,testthat,knitr,magrittr,covr
VignetteBuilder:	knitr
URL:	https://github.com/RobinHankin/permutations
BugReports:	https://github.com/RobinHankin/permutations/issues
NeedsCompilation:	no
Packaged:	2024-07-17 13:29:03 UTC; rhankin
Author:	Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>), Paul Egeler [ctb] (<https://orcid.org/0000-0001-6948-9498>)
Repository:	CRAN
Date/Publication:	2024-07-17 15:20:02 UTC

Index of help topics:

Ops.permutation         Arithmetic Ops Group Methods for permutations
allperms                All permutations with given characteristics
as.function.permutation
                        Coerce a permutation to a function
c                       Concatenation of permutations
capply                  Apply functions to elements of a cycle
cayley                  Cayley tables for permutation groups
commutator              Group-theoretic commutator: the dot object
conjugate               Are two permutations conjugate?
cyclist                 details of cyclists
derangement             Tests for a permutation being a derangement
dodecahedron            The dodecahedron group
faro                    Faro shuffles
fbin                    The fundamental bijection
fixed                   Fixed elements
get1                    Retrieve particular cycles or components of
                        cycles
id                      The identity permutation
inverse                 Inverse of a permutation
length.word             Various vector-like utilities for permutation
                        objects.
megaminx                megaminx
megaminx_plotter        Plotting routine for megaminx sequences
nullperm                Null permutations
orbit                   Orbits of integers
outer                   Outer product of vectors of permutations
perm_matrix             Permutation matrices
permorder               The order of a permutation
permutation             Functions to create and coerce word objects and
                        cycle objects
permutations-package    The Symmetric Group: Permutations of a Finite
                        Set
print.permutation       Print methods for permutation objects
rperm                   Random permutations
sgn                     Sign of a permutation
shape                   Shape of a permutation
size                    Gets or sets the size of a permutation
tidy                    Utilities to neaten permutation objects
valid                   Functions to validate permutations

Further information is available in the following vignettes:

`cyclist`	cyclist (source, pdf)
`order_of_ops`	order of operations (source, pdf)
`print`	print methods (source, pdf)
`representation`	representation theory (source, pdf)
`permutations`	a vignette for the permutations package (source, pdf)

Author(s)

Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>), Paul Egeler [ctb] (<https://orcid.org/0000-0001-6948-9498>)

Maintainer: Robin K. S. Hankin <[email protected]>

Examples

a <- rperm(10,5)
b <- rperm(10,5)

a*b

inverse(a)


a <- rperm(10,5)
b <- rperm(10,5)

a*b

inverse(a)

All permutations with given characteristics

Description

Functionality to enumerate permutations given different characteristics. In the following, n is assumed to be a non-negative integer. Permutations, in general, are coerced to cycle form.

allperms(n) returns all $n!$ permutations of $[n]$ .
allcycn() returns all $(n-1)!$ permutations of $[n]$ comprising a single cycle of length $n$ .
allcyc(s) returns all single-cycle permutations of set $s$ . If $s$ has a repeated value, an opaque error message is returned.
allpermslike(o) takes a length-one vector o of permutations and returns a vector comprising permutations with the same shape and cycle sets as it argument.
some_perms_shape(part) takes an integer partition part, as in a set of non-negative integers, and returns a vector comprising every permutation of size sum(part) with shape part that has its cycles in increasing order.
all_cyclic_shuffles(u) takes a permutation u and returns a vector comprising of all permutations with the same shape and cycle sets. It is vectorised so that argument u may be a vector of permutations.
all_perms_shape(p) takes a permutation p and returns a vector of all permutations of size sum(p) and shape p.

Usage

allperms(n)
allcycn(n)
allcyc(s)
allpermslike(o)
some_perms_shape(shape)
all_cyclic_shuffles(o)
all_perms_shape(shape)
allperms(n)
allcycn(n)
allcyc(s)
allpermslike(o)
some_perms_shape(shape)
all_cyclic_shuffles(o)
all_perms_shape(shape)

Arguments

`shape`	A set of strictly positive integers, interpreted as the shape of a partition
`s`	A set of strictly positive integers, interpreted as a set on which permutations are defined
`n`	The size of the permutation
`o`	A vector of permutations, coerced to cycle form. Function `allpermslike()` considers only the first element

Details

Function allperms() is very basic (the idiom is word(t(partitions::perms(n)))) but is here for completeness.

Note

Function allcyc() is taken directly from Er's “fine-tuned” algorithm. It should really be implemented in C as part of the partitions package but I have not yet got round to this.

Author(s)

Robin K. S. Hankin

References

M. C. Er 1989 “Efficient enumeration of cyclic permutations in situ”. International Journal of Computer Mathematics, volume 29:2-4, pp121-129.

Examples


allperms(5)

allcycn(5)

allcyc(c(5,6,8,3))

allpermslike(as.cycle("(12)(34)(5678)"))
allpermslike(rgivenshape(c(1,1,3,4)))
some_perms_shape(c(2,2,4))
all_cyclic_shuffles(cyc_len(3:5))
all_perms_shape(c(2,2,3))
allperms(5)

allcycn(5)

allcyc(c(5,6,8,3))

allpermslike(as.cycle("(12)(34)(5678)"))
allpermslike(rgivenshape(c(1,1,3,4)))
some_perms_shape(c(2,2,4))
all_cyclic_shuffles(cyc_len(3:5))
all_perms_shape(c(2,2,3))

Coerce a permutation to a function

Description

Coerce a permutation to an executable function

Usage

## S3 method for class 'permutation'
as.function(x, ...)
## S3 method for class 'permutation'
as.function(x, ...)

Arguments

`x`	permutation
`...`	further arguments (currently ignored)

Note

Multiplication of permutations loses associativity when using functional notation; see examples.

Also, note that the coerced function will not take an argument greater than the size (qv) of the permutation.

Author(s)

Robin K. S. Hankin

Examples

x <- cyc_len(3)
y <- cyc_len(5)

xfun <- as.function(x)
yfun <- as.function(y)

stopifnot(xfun(yfun(2)) == as.function(y*x)(2)) # note transposition of x & y

# written in postfix notation one has the very appealing form x(fg) = (xf)g

# it's vectorized:
as.function(rperm(10,9))(1)   
as.function(as.cycle(1:9))(sample(9))
x <- cyc_len(3)
y <- cyc_len(5)

xfun <- as.function(x)
yfun <- as.function(y)

stopifnot(xfun(yfun(2)) == as.function(y*x)(2)) # note transposition of x & y

# written in postfix notation one has the very appealing form x(fg) = (xf)g

# it's vectorized:
as.function(rperm(10,9))(1)   
as.function(as.cycle(1:9))(sample(9))

Concatenation of permutations

Description

Concatenate words or cycles together

Usage

## S3 method for class 'word'
c(...)
## S3 method for class 'cycle'
c(...)
## S3 method for class 'permutation'
rep(x, ...)
## S3 method for class 'word'
c(...)
## S3 method for class 'cycle'
c(...)
## S3 method for class 'permutation'
rep(x, ...)

Arguments

`...`	In the methods for `c()`, objects to be concatenated. Must all be of the same type: either all `word`, or all `cycle`
`x`	In the method for `rep()`, a permutation object

Note

The methods for c() do not attempt to detect which type (word or cycle) you want as conversion is expensive.

Function rep.permutation() behaves like base::rep() and takes the same arguments, eg times and each.

Author(s)

Robin K. S. Hankin

Examples

x <- as.cycle(1:5)
y <- cycle(list(list(1:4,8:9),list(1:2)))


# concatenate cycles:
c(x,y)

# concatenate words:
c(rperm(5,3),rperm(6,9))   # size adjusted to maximum size of args


# repeat words:
rep(x, times=3)



x <- as.cycle(1:5)
y <- cycle(list(list(1:4,8:9),list(1:2)))


# concatenate cycles:
c(x,y)

# concatenate words:
c(rperm(5,3),rperm(6,9))   # size adjusted to maximum size of args


# repeat words:
rep(x, times=3)

Apply functions to elements of a cycle

Description

Function capply() means “cycle apply” and is modelled on lapply(). It applies a function to every element in the cycles of its argument.

Usage

capply(X, fun, ...)capply(X, fun, ...)

Arguments

`X`	Permutation, coerced to cycle
`fun`	Function to be applied to each element of `X`
`...`	Further arguments to `fun()`

Details

This function is just a convenience wrapper really.

Value

Returns a permutation in cycle form

Note

Function allcyc() is a nice application of capply().

Author(s)

Robin K. S. Hankin

Examples



(x <- rperm())
capply(x,function(x){x+100})
capply(x,rev)

all(is.id(capply(x,rev)*x))  # should be TRUE

capply(rcyc(20,5,9),sort)

capply(rcyc(20,5,9),sample)  # still 5-cycles


capply(cyc_len(1:9),\(x)x[x>4])

capply(cyc_len(1:9),\(x)x^2)


(x <- rperm())
capply(x,function(x){x+100})
capply(x,rev)

all(is.id(capply(x,rev)*x))  # should be TRUE

capply(rcyc(20,5,9),sort)

capply(rcyc(20,5,9),sample)  # still 5-cycles


capply(cyc_len(1:9),\(x)x[x>4])

capply(cyc_len(1:9),\(x)x^2)

Cayley tables for permutation groups

Description

Produces a nice Cayley table for a subgroup of the symmetric group on $n$ elements

Usage

cayley(x)
cayley(x)

Arguments

`x`	A vector of permutations in cycle form

Details

Cayley's theorem states that every group G is isomorphic to a subgroup of the symmetric group acting on G. In this context it means that if we have a vector of permutations that comprise a group, then we can nicely represent its structure using a table.

If the set x is not closed under multiplication and inversion (that is, if x is not a group) then the function may misbehave. No argument checking is performed, and in particular there is no check that the elements of x are unique, or even that they include an identity.

Value

A square matrix giving the group operation

Author(s)

Robin K. S. Hankin

Examples


## cyclic group of order 4:
cayley(as.cycle(1:4)^(0:3))

## Klein group:
K4 <- as.cycle(c("()","(12)(34)","(13)(24)","(14)(23)"))
names(K4) <- c("00","01","10","11")
cayley(K4)


## S3, the symmetric group on 3 elements:
S3 <- as.cycle(c(
    "()",
    "(12)(35)(46)", "(13)(26)(45)",
    "(14)(25)(36)", "(156)(243)", "(165)(234)"
))
names(S3) <- c("()","(ab)","(ac)","(bc)","(abc)","(acb)")
cayley(S3)


## Now an example from the onion package, the quaternion group:
## Not run: 
 library(onion)
 a <- c(H1,-H1,Hi,-Hi,Hj,-Hj,Hk,-Hk)
 X <- word(sapply(1:8,function(k){sapply(1:8,function(l){which((a*a[k])[l]==a)})}))
 cayley(X)  # a bit verbose; rename the vector:
 names(X) <- letters[1:8]
 cayley(X)  # more compact

## End(Not run)

## cyclic group of order 4:
cayley(as.cycle(1:4)^(0:3))

## Klein group:
K4 <- as.cycle(c("()","(12)(34)","(13)(24)","(14)(23)"))
names(K4) <- c("00","01","10","11")
cayley(K4)


## S3, the symmetric group on 3 elements:
S3 <- as.cycle(c(
    "()",
    "(12)(35)(46)", "(13)(26)(45)",
    "(14)(25)(36)", "(156)(243)", "(165)(234)"
))
names(S3) <- c("()","(ab)","(ac)","(bc)","(abc)","(acb)")
cayley(S3)


## Now an example from the onion package, the quaternion group:
## Not run: 
 library(onion)
 a <- c(H1,-H1,Hi,-Hi,Hj,-Hj,Hk,-Hk)
 X <- word(sapply(1:8,function(k){sapply(1:8,function(l){which((a*a[k])[l]==a)})}))
 cayley(X)  # a bit verbose; rename the vector:
 names(X) <- letters[1:8]
 cayley(X)  # more compact

## End(Not run)

Group-theoretic commutator: the dot object

Description

In the permutations package, the dot is defined as the Group-theoretic commutator: $[x,y]=x^{-1}y^{-1}xy$ . This is a bit of an exception to the usual definition of xy-yx (along with the freegroup package). Package idiom is commutator(x,y) or .[x,y].

The Jacobi identity does not make sense in the context of the permutations package, but the Hall-Witt identity is obeyed.

The “dot” object is defined and discussed in inst/dot.Rmd, which creates file data/dot.rda.

Usage

commutator(x, y)
commutator(x, y)

Arguments

x, y

Permutation objects, coerced to word

Author(s)

Robin K. S. Hankin

Examples


.[as.cycle("123456789"),as.cycle("12")]


x <- rperm(10,7)
y <- rperm(10,8)
z <- rperm(10,9)

uu <- 
commutator(commutator(x,y),z^x) *
commutator(commutator(z,x),y^z) *
commutator(commutator(y,z),x^y) 

stopifnot(all(is.id(uu)))  # this is the  Hall-Witt identity


.[x,y]

is.id(.[.[x,y],z^x] * .[.[z,x],y^z] * .[.[y,z],x^y])
is.id(.[.[x,-y],z]^y * .[.[y,-z],x]^z * .[.[z,-x],y]^x)
.[as.cycle("123456789"),as.cycle("12")]


x <- rperm(10,7)
y <- rperm(10,8)
z <- rperm(10,9)

uu <- 
commutator(commutator(x,y),z^x) *
commutator(commutator(z,x),y^z) *
commutator(commutator(y,z),x^y) 

stopifnot(all(is.id(uu)))  # this is the  Hall-Witt identity


.[x,y]

is.id(.[.[x,y],z^x] * .[.[z,x],y^z] * .[.[y,z],x^y])
is.id(.[.[x,-y],z]^y * .[.[y,-z],x]^z * .[.[z,-x],y]^x)

Are two permutations conjugate?

Description

Returns TRUE if two permutations are conjugate and FALSE otherwise.

Usage

are_conjugate(x, y)
are_conjugate_single(a,b)
are_conjugate(x, y)
are_conjugate_single(a,b)

Arguments

x, y, a, b

Objects of class permutation, coerced to cycle form

Details

Two permutations are conjugate if and only if they have the same shape. Function are_conjugate() is vectorized and user-friendly; function are_conjugate_single() is lower-level and operates only on length-one permutations.

The reason that are_conjugate_single() is a separate function and not bundled inside are_conjugate() is that dealing with the identity permutation is a pain in the arse.

Value

Returns a vector of Booleans

Note

The functionality detects conjugateness by comparing the shapes of two permutations; permutations are coerced to cycle form because function shape() does.

The group action of conjugation, that is $x^y$ or y^-1 x y, is documented at conjugation.

 are_conjugate(x,conjugate(x^y))

is always TRUE.

Author(s)

Robin K. S. Hankin

Examples


as.cycle("(123)(45)") %~% as.cycle("(89)(712)")  # same shape
as.cycle("(123)(45)") %~% as.cycle("(89)(7124)") # different shape

are_conjugate(rperm(20,3),rperm(20,3))

rperm(20,3) %~% as.cycle(1:3)

z <- rperm(300,4)
stopifnot(all(are_conjugate(z,id)==is.id(z)))

data(megaminx)
stopifnot(all(are_conjugate(megaminx,megaminx^as.cycle(sample(129)))))
as.cycle("(123)(45)") %~% as.cycle("(89)(712)")  # same shape
as.cycle("(123)(45)") %~% as.cycle("(89)(7124)") # different shape

are_conjugate(rperm(20,3),rperm(20,3))

rperm(20,3) %~% as.cycle(1:3)

z <- rperm(300,4)
stopifnot(all(are_conjugate(z,id)==is.id(z)))

data(megaminx)
stopifnot(all(are_conjugate(megaminx,megaminx^as.cycle(sample(129)))))

details of cyclists

Description

Various functionality to deal with cyclists

Usage

vec2cyclist_single(p)
vec2cyclist_single_cpp(p)
remove_length_one(x)
cyclist2word_single(cyc,n)
nicify_cyclist(x,rm1=TRUE, smallest_first=TRUE)
vec2cyclist_single(p)
vec2cyclist_single_cpp(p)
remove_length_one(x)
cyclist2word_single(cyc,n)
nicify_cyclist(x,rm1=TRUE, smallest_first=TRUE)

Arguments

`p`	Integer vector, interpreted as a word
`x`, `cyc`	A cyclist
`n`	In function `cycle2word_single()`, the size of the permutation to induce
`rm1`, `smallest_first`	In function `nicify_cyclist()`, Boolean, governing whether or not to remove length-1 cycles, and whether or not to place the smallest element in each cycle first (non-default values are used by `standard_cyclist()`)

Details

A cyclist is an object corresponding to a permutation P. It is a list with elements that are integer vectors corresponding to the cycles of P. This object is informally known as a cyclist, but there is no S3 class corresponding to it. In general use, one should not usually deal with cyclists at all: they are internal low-level objects not intended for the user.

An object of S3 class cycle is a (possibly named) list of cyclists. NB: there is an unavoidable notational clash here. When considering a single permutation, “cycle” means group-theoretic cycle [eg $1\longrightarrow 2\longrightarrow 3\longrightarrow 1$ ]; when considering R objects, “cycle” means “an R object of class cycle whose elements are permutations written in cycle form”.

The elements of a cyclist are the disjoint group-theoretic cycles. Note the redundancies inherent: firstly, because the cycles commute, their order is immaterial (and a list is ordered); and secondly, the cycles themselves are invariant under cyclic permutation. Heigh ho.

A cyclist may be poorly formed in a number of ways: the cycles may include repeats, or contain elements which are common to more than one cycle. Such problems are detected by cyclist_valid(). Also, there are less serious problems: the cycles may include length-one cycles; the cycles may start with an element that is not the smallest. These issues are dealt with by nicify_cyclist().

Function nicify_cyclist() takes a cyclist and puts it in a nice form but does not alter the permutation. It takes a cyclist and removes length-one cycles; then orders each cycle so that the smallest element appears first (that is, it changes (523) to (235)). It then orders the cycles by the smallest element. Function nicify_cyclist() is called automatically by cycle(). Remember that nicify_cyclist() takes a cyclist!
Function remove_length_one() takes a cyclist and removes length-one cycles from it.
Function vec2cyclist_single() takes a vector of integers, interpreted as a word, and converts it into a cyclist. Length-one cycles are discarded.
Function vec2cyclist_single_cpp() is a placeholder for a function that is not yet written.
Function cyclist2word_single() takes a cyclist and returns a vector corresponding to a single word. This function is not intended for everyday use; function cycle2word() is much more user-friendly.
Function char2cyclist_single() takes a character string like “(342)(19)” and turns it into a cyclist, in this case list(c(3,4,2),c(1,9)). This function returns a cyclist which is not necessarily canonicalized: it might have length-one cycles, and the cycles themselves might start with the wrong number or be incorrectly ordered. It attempts to deal with absence of commas in a sensible way, so “(18,19)(2,5)” is dealt with appropriately too. The function is insensitive to spaces. Also, one can give it an argument which does not correspond to a cycle object, eg char2cyclist_single("(94)(32)(19)(1)") (in which “9” is repeated). The function does not return an error, but to catch this kind of problem use char2cycle() which calls the validity checks.

The user should use char2cycle() which executes validity checks and coerces to a cycle object.

See also the “cyclist” vignette [type vignette("cyclist") at the command line] which contains more details and examples.

Author(s)

Robin K. S. Hankin

Examples

vec2cyclist_single(c(7,9,3,5,8,6,1,4,2))

char2cyclist_single("(342)(19)")

nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)))
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),rm1=TRUE)

nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=FALSE,rm1=FALSE)
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=FALSE,rm1=TRUE )
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=TRUE ,rm1=FALSE)
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=TRUE ,rm1=TRUE )
 

cyclist2word_single(list(c(1,4,3),c(7,8)))


vec2cyclist_single(c(7,9,3,5,8,6,1,4,2))

char2cyclist_single("(342)(19)")

nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)))
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),rm1=TRUE)

nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=FALSE,rm1=FALSE)
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=FALSE,rm1=TRUE )
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=TRUE ,rm1=FALSE)
nicify_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)),smallest_first=TRUE ,rm1=TRUE )
 

cyclist2word_single(list(c(1,4,3),c(7,8)))

Tests for a permutation being a derangement

Description

A derangement is a permutation which leaves no element fixed.

Usage

is.derangement(x)
is.derangement(x)

Arguments

`x`	Object to be tested

Value

A vector of Booleans corresponding to whether the permutations are derangements or not.

Note

The identity permutation is problematic because it potentially has zero size.

The identity element is not a derangement, although the (zero-size) identity cycle and permutation both return TRUE under the natural R idiom all(P != seq_len(size(P))).

Author(s)

Robin K. S. Hankin

Examples


allperms(4)
is.derangement(allperms(4))

M <- matrix(c(1,2,3,4, 2,3,4,1, 3,2,4,1),byrow=TRUE,ncol=4)
M
is.derangement(word(M))

is.derangement(rperm(16,4))

allperms(4)
is.derangement(allperms(4))

M <- matrix(c(1,2,3,4, 2,3,4,1, 3,2,4,1),byrow=TRUE,ncol=4)
M
is.derangement(word(M))

is.derangement(rperm(16,4))

The dodecahedron group

Description

Permutations comprising the dodecahedron group on either its faces or its edges; also the full dodecahedron group

Details

The package provides a number of objects for investigating dodecahedral groups:

Object dodecahedron_face is a cycle object with 60 elements corresponding to the permutations of the faces of a dodecahedron, numbered 1-12 as in the megaminx net. Object dodecahedron_edge is the corresponding object for permuting the edges of a dodecahedron. The edges are indexed by the lower of the two adjoining facets on the megaminx net.

Objects full_dodecahedron_face and full_dodecahedron_edge give the 120 elements of the full dodecahedron group, that is, the dodecahedron group including reflections. NB: these objects are not isomorphic to S5.

Note

File zzz_dodecahedron.R is not really intended to be human-readable. The source file is in inst/dodecahedron_group.py and inst/full_dodecahedron_group.py which contain documented python source code.

Examples


permprod(dodecahedron_face)

permprod(dodecahedron_face)

Faro shuffles

Description

A faro shuffle, faro(),is a permutation of a deck of $2n$ cards. The cards are split into two packs, 1:n and (n+1):2n, and interleaved: cards are taken alternately from top of each pack and placed face down on the table. A faro out-shuffle takes the first card from 1:n and a faro in-shuffle takes the first card from (n+1):(2*n).

A generalized faro shuffle, faro_gen(), splits the pack into m equal parts and applies the same permutation to each pack, and the same permutation to each set of packs, before interleaving. The interleaving itself is simply a matrix transpose; it is possible to omit this step by passing interleave=FALSE.

Usage

faro(n, out = TRUE)
faro_gen(n,m,p1=id,p2=id,interleave=TRUE)
faro(n, out = TRUE)
faro_gen(n,m,p1=id,p2=id,interleave=TRUE)

Arguments

`n`	Number of cards in each pack
`m`	Number of packs
`p1`, `p2`	Permutations for cards and packs respectively, coerced to word form
`interleave`	Boolean, with default `TRUE` meaning to actually perform the interleaving and `FALSE` meaning not to
`out`	Boolean, with default `TRUE` meaning to return an out-shuffle and `FALSE` meaning to return an in-shuffle

Value

Returns a permutation in word form

Author(s)

Robin K. S. Hankin

Examples

faro(4)
faro(4,FALSE)

faro_gen(9,3)
faro_gen(7,4,cyc_len(7),cyc_len(4))
faro_gen(7,4,cyc_len(7),cyc_len(4),interleave=FALSE)

sapply(seq_len(10),function(n){permorder(faro(n,FALSE))}) # OEIS  A002326

plot(as.vector(as.word(faro(10))),type='b')
plot(as.vector(faro_gen(8,5,p1=cyc_len(8)^2,interleave=FALSE)))

faro(4)
faro(4,FALSE)

faro_gen(9,3)
faro_gen(7,4,cyc_len(7),cyc_len(4))
faro_gen(7,4,cyc_len(7),cyc_len(4),interleave=FALSE)

sapply(seq_len(10),function(n){permorder(faro(n,FALSE))}) # OEIS  A002326

plot(as.vector(as.word(faro(10))),type='b')
plot(as.vector(faro_gen(8,5,p1=cyc_len(8)^2,interleave=FALSE)))

The fundamental bijection

Description

Stanley defines the fundamental bijection on page 30.

Given $w=(14)(2)(375)(6)$ , Stanley writes it in standard form (specifically: each cycle is written with its largest element first; cycles are written in increasing order of their largest element). Thus we obtain $(2)(41)(6)(753)$ .

Then we obtain $w^*$ from $w$ by writing it in standard form an erasing the parentheses (that is, viewing the numbers as a word); here $w^*=2416753$ .

Given this, $w$ may be recovered by inserting a left parenthesis preceding every left-to-right maximum, and right parentheses where appropriate.

Function standard() takes an object of class cycle and returns a list of cyclists. NB this does not return an object of class “cycle” because cycle() calls nicify().

Function standard_cyclist() retains length-one cycles (compare nicify_cyclist(), which does not).

Usage

standard(cyc,n=NULL)
standard_cyclist(x,n=NULL)
fbin_single(vec)
fbin(W)
fbin_inv(cyc)
standard(cyc,n=NULL)
standard_cyclist(x,n=NULL)
fbin_single(vec)
fbin(W)
fbin_inv(cyc)

Arguments

`vec`	In function `fbin_single()`, an integer vector
`W`	In functions `fbin()` and `fbin_inv()`, an object of class permutation, coerced to word and cycle form respectively
`cyc`	In functions `fbin_single()` and `standard()`, permutation object coerced to cycle form
`n`	In function `standard()` and `standard_cyclist()`, size of the partition to assume, with default `NULL` meaning to use the largest element of any cycle
`x`	In function `standard_cyclist()`, a cyclist

Details

The user-friendly functions are fbin() and fbin_inv() which perform Stanley's “fundamental bijection”. Function fbin() takes a word object and returns a cycle; function fbin_inv() takes a cycle and returns a word.

The other functions are low-level helper functions that are not really intended for the user (except possibly standard(), which puts a cycle object in standard order in list form).

Author(s)

Robin K. S. Hankin

References

R. P. Stanley 2011 Enumerative Combinatorics

Examples


# Stanley's example w:
standard(cycle(list(list(c(1,4),c(3,7,5)))))

standard_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)))


w_hat <- c(2,4,1,6,7,5,3)

fbin(w_hat)
fbin_inv(fbin(w_hat))


x <- rperm(40,9)
stopifnot(all(fbin(fbin_inv(x))==x))
stopifnot(all(fbin_inv(fbin(x))==x))

# Stanley's example w:
standard(cycle(list(list(c(1,4),c(3,7,5)))))

standard_cyclist(list(c(4, 6), c(7), c(2, 5, 1), c(8, 3)))


w_hat <- c(2,4,1,6,7,5,3)

fbin(w_hat)
fbin_inv(fbin(w_hat))


x <- rperm(40,9)
stopifnot(all(fbin(fbin_inv(x))==x))
stopifnot(all(fbin_inv(fbin(x))==x))

Fixed elements

Description

Finds which elements of a permutation object are fixed

Usage

## S3 method for class 'word'
fixed(x)
## S3 method for class 'cycle'
fixed(x)
## S3 method for class 'word'
fixed(x)
## S3 method for class 'cycle'
fixed(x)

Arguments

`x`	Object of class `word` or `cycle`

Value

Returns a Boolean vector corresponding to the fixed elements of a permutation.

Note

The function is vectorized; if given a vector of permutations, fixed() returns a Boolean vector showing which elements are fixed by all of the permutations.

This function has two methods: fixed.word() and fixed.cycle(), neither of which coerce.

Author(s)

Robin K. S. Hankin

Examples

fixed(as.cycle(1:3)+as.cycle(8:9))   # elements 4,5,6,7 are fixed
fixed(id)


data(megaminx)
fixed(megaminx)


fixed(as.cycle(1:3)+as.cycle(8:9))   # elements 4,5,6,7 are fixed
fixed(id)


data(megaminx)
fixed(megaminx)

Retrieve particular cycles or components of cycles

Description

Given an object of class cycle, function get1() returns a representative of each of the disjoint cycles in the object's elements. Function get_cyc() returns the cycle containing a specific element.

Usage

get1(x,drop=TRUE)
get_cyc(x,elt)
get1(x,drop=TRUE)
get_cyc(x,elt)

Arguments

`x`	permutation object (coerced to `cycle` class)
`drop`	In function `get1()`, argument `drop` controls the behaviour if `x` is length 1. If `drop` is `TRUE`, then a vector of representative elements is returned; if `FALSE`, then a list with one vector element is returned
`elt`	Length-one vector interpreted as a permutation object

Author(s)

Robin K. S. Hankin

Examples

data(megaminx)
get1(megaminx)
get1(megaminx[1])
get1(megaminx[1],drop=TRUE)

get_cyc(megaminx,11) 

data(megaminx)
get1(megaminx)
get1(megaminx[1])
get1(megaminx[1],drop=TRUE)

get_cyc(megaminx,11)

The identity permutation

Description

The identity permutation leaves every element fixed

Usage

is.id(x)
is.id_single_cycle(x)
## S3 method for class 'cycle'
is.id(x)
## S3 method for class 'list'
is.id(x)
## S3 method for class 'word'
is.id(x)
is.id(x)
is.id_single_cycle(x)
## S3 method for class 'cycle'
is.id(x)
## S3 method for class 'list'
is.id(x)
## S3 method for class 'word'
is.id(x)

Arguments

`x`	Object to be tested

Details

The identity permutation is problematic because it potentially has zero size.

Value

The variable id is a cycle as this is more convenient than a zero-by-one matrix.

Function is.id() returns a Boolean with TRUE if the corresponding element is the identity, and FALSE otherwise. It dispatches to either is.id.cycle() or is.id.word() as appropriate.

Function is.id.list() tests a cyclist for identityness.

Note

The identity permutations documented here are distinct from the null permutations documented at nullperm.Rd.

Author(s)

Robin K. S. Hankin

Examples

is.id(id)

as.word(id)  # weird

x <- rperm(10,4)
x[3] <- id
is.id(x*inverse(x))
is.id(id)

as.word(id)  # weird

x <- rperm(10,4)
x[3] <- id
is.id(x*inverse(x))

Inverse of a permutation

Description

Calculates the inverse of a permutation in either word or cycle form

Usage

inverse(x)
## S3 method for class 'word'
inverse(x)
## S3 method for class 'cycle'
inverse(x)
inverse_word_single(W)
inverse_cyclist_single(cyc)
inverse(x)
## S3 method for class 'word'
inverse(x)
## S3 method for class 'cycle'
inverse(x)
inverse_word_single(W)
inverse_cyclist_single(cyc)

Arguments

`x`	Object of class `permutation` to be inverted
`W`	In function `inverse_word_single()`, a vector corresponding to a permutation in word form (that is, one row of a `word` object)
`cyc`	In function `inverse_cyclist_single()`, a cyclist to be inverted

Details

The package provides methods to invert objects of class word (the R idiom is W[W] <- seq_along(W)) and also objects of class cycle (the idiom is lapply(cyc,function(o){c(o[1],rev(o[-1]))})).

The user should use inverse() directly, which dispatches to either inverse.word() or inverse.cycle() as appropriate.

Sometimes, using idiom such as x^-1 or id/x gives neater code, although these may require coercion between word form and cycle form.

Value

Function inverse() returns an object of the same class as its argument.

Note

Inversion of words is ultimately performed by function inverse_word_single():

inverse_word_single <- function(W){
    W[W] <- seq_along(W)
    return(W)
}

which can be replaced by order() although this is considerably less efficient, especially for small sizes of permutations. One of my longer-term plans is to implement this in C, although it is not clear that this will be any faster.

Author(s)

Robin K. S. Hankin

Examples

x <- rperm(10,6)
x
inverse(x)

all(is.id(x*inverse(x)))  # should be TRUE

inverse(as.cycle(matrix(1:8,9,8)))

x <- rperm(10,6)
x
inverse(x)

all(is.id(x*inverse(x)))  # should be TRUE

inverse(as.cycle(matrix(1:8,9,8)))

Various vector-like utilities for permutation objects.

Description

Various vector-like utilities for permutation objects such as length, names(), etc

Usage

## S3 method for class 'word'
length(x)
## S3 replacement method for class 'permutation'
length(x) <- value
## S3 method for class 'word'
names(x)
## S3 replacement method for class 'word'
names(x) <- value
## S3 method for class 'word'
length(x)
## S3 replacement method for class 'permutation'
length(x) <- value
## S3 method for class 'word'
names(x)
## S3 replacement method for class 'word'
names(x) <- value

Arguments

`x`	permutation object
`value`	In function `names<-.word()`, the new names

Details

These functions have methods only for word objects; cycle objects use the methods for lists. It is easy to confuse the length of a permutation with its size.

It is not possible to set the length of a permutation; this is more trouble than it is worth.

Author(s)

Robin K. S. Hankin

Examples


x <- rperm(5,9)
x
names(x) <- letters[1:5]
x

megaminx
length(megaminx)   # the megaminx group has 12 generators, one per face.
size(megaminx)     # the megaminx group is a subgroup of S_129.

names(megaminx) <- NULL   # prints more nicely.
megaminx
x <- rperm(5,9)
x
names(x) <- letters[1:5]
x

megaminx
length(megaminx)   # the megaminx group has 12 generators, one per face.
size(megaminx)     # the megaminx group is a subgroup of S_129.

names(megaminx) <- NULL   # prints more nicely.
megaminx

megaminx

Description

A set of generators for the megaminx group

Details

Each element of megaminx corresponds to a clockwise turn of 72 degrees. See the vignette for more details.

`megaminx[, 1]`	W	White
`megaminx[, 2]`	Pu	Purple
`megaminx[, 3]`	DY	Dark Yellow
`megaminx[, 4]`	DB	Dark Blue
`megaminx[, 5]`	R	Red
`megaminx[, 6]`	DG	Dark Green
`megaminx[, 7]`	LG	Light Green
`megaminx[, 8]`	O	Orange
`megaminx[, 9]`	LB	Light Blue
`megaminx[,10]`	LY	Light Yellow
`megaminx[,11]`	Pi	Pink
`megaminx[,12]`	Gy	Gray

Vector megaminx_colours shows what colour each facet has at start. Object superflip is a megaminx operation that flips each of the 30 edges.

These objects can be generated by running script inst/megaminx.R, which includes some further discussion and technical documentation and creates file megaminx.rda which resides in the data/ directory.

Author(s)

Robin K. S. Hankin

Examples


data(megaminx)
megaminx
megaminx^5  # should be the identity
inverse(megaminx)  # turn each face anticlockwise


megaminx_colours[permprod(megaminx)]  # risky but elegant...

W    # turn the White face one click clockwise (colour names as per the
     # table above)


megaminx_colours[as.word(W,129)]      # it is safer to ensure a size-129 word;
megaminx_colours[as.word(W)]          # but the shorter version will work


# Now some superflip stuff:

X <- W * Pu^(-1) * W * Pu^2 * DY^(-2) 
Y <- LG^(-1) * DB^(-1) * LB * DG      
Z <- Gy^(-2) * LB * LG^(-1) * Pi^(-1) * LY^(-1)


sjc3 <- (X^6)^Y * Z^9  # superflip (Jeremy Clark)


p1 <- (DG^2 * W^4 * DB^3 * W^3 * DB^2 * W^2 * DB^2 * R * W * R)^3
m1 <- p1^(Pi^3)

p2 <- (O^2 * LG^4 * DB^3 * LG^3 * DB^2 * LG^2 * DB^2 * DY * LG * DY)^3
m2 <- p2^(DB^2)

p3 <- (LB^2 * LY^4 * Gy * Pi^3 * LY * Gy^4)^3
m3 <- p3^LB

# m1,m2 are 32 moves, p3 is 20, total = 84

stopifnot(m1+m2+m3==sjc3)




data(megaminx)
megaminx
megaminx^5  # should be the identity
inverse(megaminx)  # turn each face anticlockwise


megaminx_colours[permprod(megaminx)]  # risky but elegant...

W    # turn the White face one click clockwise (colour names as per the
     # table above)


megaminx_colours[as.word(W,129)]      # it is safer to ensure a size-129 word;
megaminx_colours[as.word(W)]          # but the shorter version will work


# Now some superflip stuff:

X <- W * Pu^(-1) * W * Pu^2 * DY^(-2) 
Y <- LG^(-1) * DB^(-1) * LB * DG      
Z <- Gy^(-2) * LB * LG^(-1) * Pi^(-1) * LY^(-1)


sjc3 <- (X^6)^Y * Z^9  # superflip (Jeremy Clark)


p1 <- (DG^2 * W^4 * DB^3 * W^3 * DB^2 * W^2 * DB^2 * R * W * R)^3
m1 <- p1^(Pi^3)

p2 <- (O^2 * LG^4 * DB^3 * LG^3 * DB^2 * LG^2 * DB^2 * DY * LG * DY)^3
m2 <- p2^(DB^2)

p3 <- (LB^2 * LY^4 * Gy * Pi^3 * LY * Gy^4)^3
m3 <- p3^LB

# m1,m2 are 32 moves, p3 is 20, total = 84

stopifnot(m1+m2+m3==sjc3)

Plotting routine for megaminx sequences

Description

Plots a coloured diagram of a dodecahedron net representing a megaminx

Usage

megaminx_plotter(megperm=id,offset=c(0,0),M=diag(2),setup=TRUE,...)
megaminx_plotter(megperm=id,offset=c(0,0),M=diag(2),setup=TRUE,...)

Arguments

`megperm`	Permutation to be plotted
`offset`, `M`	Offset and transformation matrix, see details
`setup`	Boolean, with default `TRUE` meaning to set up the plot with a `plot()` statement, and `FALSE` meaning to plot the points on a pre-existing canvas
`...`	Further arguments passed to `polygon()`

Details

Function megaminx_plotter() plots a coloured diagram of a dodecahedron net representing a megaminx. The argument may be specified as a sequence of turns that are applied to the megaminx from START.

The function uses rather complicated internal variables pentagons, triangles, and quads whose meaning and genesis is discussed in heavily-documented file inst/guide.R.

The diagram is centered so that the common vertex of triangles 28 and 82 is at $(0,0)$ .

Author(s)

Robin K. S. Hankin

Examples

data("megaminx")

megaminx_plotter()  # START
megaminx_plotter(W) # after turning the White face one click
megaminx_plotter(superflip)

size <- 0.95
o <- 290

## Not run: 
pdf(file="fig1.pdf")
megaminx_plotter(M=size*diag(2),offset=c(-o,0),setup=TRUE)
megaminx_plotter(W,M=size*diag(2),offset=c(+o,0),setup=FALSE)
dev.off()

pdf(file="fig2.pdf")
p <- permprod(sample(megaminx,100,replace=TRUE))
megaminx_plotter(p,M=size*diag(2),offset=c(-o,0),setup=TRUE)
megaminx_plotter(superflip,M=size*diag(2),offset=c(+o,0),setup=FALSE)
dev.off()

## End(Not run)
data("megaminx")

megaminx_plotter()  # START
megaminx_plotter(W) # after turning the White face one click
megaminx_plotter(superflip)

size <- 0.95
o <- 290

## Not run: 
pdf(file="fig1.pdf")
megaminx_plotter(M=size*diag(2),offset=c(-o,0),setup=TRUE)
megaminx_plotter(W,M=size*diag(2),offset=c(+o,0),setup=FALSE)
dev.off()

pdf(file="fig2.pdf")
p <- permprod(sample(megaminx,100,replace=TRUE))
megaminx_plotter(p,M=size*diag(2),offset=c(-o,0),setup=TRUE)
megaminx_plotter(superflip,M=size*diag(2),offset=c(+o,0),setup=FALSE)
dev.off()

## End(Not run)

Null permutations

Description

Null permutations are the equivalent of NULL

Usage

nullcycle
nullword
nullcycle
nullword

Format

Object nullcycle is an empty list coerced to class cycle, specifically cycle(list())

Object nullword is a zero-row matrix, coerced to word, specifically word(matrix(integer(0),0,0))

Details

These objects are here to deal with the case where a length-zero permutation is extracted. The behaviour of these null objects is not entirely consistent.

Note

The objects documented here are distinct from the identity permutation, id, documented separately.

Examples


rperm(10,4)[0]  # null word

as.cycle(1:5)[0]  # null cycle

data(megaminx)
c(NULL,megaminx)      # probably not what the user intended...
c(nullcycle,megaminx) # more useful.
c(id,megaminx)        # also useful.

rperm(10,4)[0]  # null word

as.cycle(1:5)[0]  # null cycle

data(megaminx)
c(NULL,megaminx)      # probably not what the user intended...
c(nullcycle,megaminx) # more useful.
c(id,megaminx)        # also useful.

Arithmetic Ops Group Methods for permutations

Description

Allows arithmetic operators to be used for manipulation of permutation objects such as addition, multiplication, division, integer powers, etc.

Usage

## S3 method for class 'permutation'
Ops(e1, e2)
cycle_power(x,pow)
cycle_power_single(x,pow)
cycle_sum(e1,e2)
cycle_sum_single(c1,c2)
word_equal(e1,e2)
word_prod(e1,e2)
word_prod_single(e1,e2)
permprod(x)
vps(vec,pow)
ccps(n,pow)
helper(e1,e2)
cycle_plus_integer_elementwise(x,y)
conjugation(e1,e2)
## S3 method for class 'permutation'
Ops(e1, e2)
cycle_power(x,pow)
cycle_power_single(x,pow)
cycle_sum(e1,e2)
cycle_sum_single(c1,c2)
word_equal(e1,e2)
word_prod(e1,e2)
word_prod_single(e1,e2)
permprod(x)
vps(vec,pow)
ccps(n,pow)
helper(e1,e2)
cycle_plus_integer_elementwise(x,y)
conjugation(e1,e2)

Arguments

`x`, `e1`, `e2`	Objects of class “`permutation`”
`c1`, `c2`	Objects of class `cycle`
`pow`	Integer vector of powers
`vec`	In function `vps()`, a vector of integers corresponding to a cycle
`n`	In function `ccps()`, the integer power to which `cycle(seq_len(n))` is to be raised; may be positive or negative
`y`	In experimental function `cycle_plus_integer_elementwise()`, an integer

Details

Function Ops.permutation() passes binary arithmetic operators (“+”, “*”, “/”, “^”, and “==”) to the appropriate specialist function.

Multiplication, as in a*b, is effectively word_prod(a,b); it coerces its arguments to word form (because a*b = b[a]).

Raising permutations to integer powers, as in a^n, is cycle_power(a,n); it coerces a to cycle form and returns a cycle (even if $n=1$ ). Negative and zero values of n operate as expected. Function cycle_power() is vectorized; it calls cycle_power_single(), which is not. This calls vps() (“Vector Power Single”), which checks for simple cases such as pow=0 or the identity permutation; and function vps() calls function ccps() which performs the actual number-theoretic manipulation to raise a cycle to a power.

Group-theoretic conjugation is implemented: in package idiom, a^b gives inverse(b)*a*b. The notation is motivated by the identities x^(yz)=(x^y)^z and (xy)^z=x^z*y^z [or $x^{yz}=(x^y)^z$ and $(xy)^z=x^zy^z$ ]. Internally, conjugation() is called. The concept of conjugate permutations [that is, permutations with the same shape()] is discussed at conjugate.

The sum of two permutations a and b, as in a+b, is defined if the cycle representations of the addends are disjoint. The sum is defined as the permutation given by juxtaposing the cycles of a with those of b. Note that this operation is commutative. If a and b do not have disjoint cycle representations, an error is returned. This is useful if you want to guarantee that two permutations commute (NB: permutation a commutes with a^i for i any integer, and in particular a commutes with itself. But a+a returns an error: the operation checks for disjointness, not commutativity).

Permutation “division”, as in a/b, is a*inverse(b). Note that a/b*c is evaluated left to right so is equivalent to a*inverse(b)*c. See note.

Function helper() sorts out recycling for binary functions, the behaviour of which is inherited from cbind(), which also handles the names of the returned permutation.

Experimental functionality is provided to define the “sum” of a permutation and an integer. If $x$ is a permutation in cycle form with $x=(abc)$ , say, and $n$ an integer, then $x+n=(a+n,b+n,c+n)$ : each element of each cycle of $x$ is increased by $n$ . Note that this has associativity consequences. For example, x+(x+n) might be defined but not (x+x)+n, as the two “+” operators have different interpretations. Distributivity is similarly broken (see the examples). Package idiom includes x-n [defined as x + (-n)] and n+x but not n-x as inverses are defined multiplicatively. The implementation is vectorised.

Value

None of these functions are really intended for the end user: use the ops as shown in the examples section.

Note

The class of the returned object is the appropriate one.

Unary operators to invert a permutation are problematic in the package. I do not like using “id/x” to represent a permutation inverse: the idiom introduces an utterly redundant object (“id”), and forces the use of a binary operator where a unary operator is needed. Similar comments apply to “x^-1”, which again introduces a redundant object (-1) and uses a binary operator.

Currently, “-x” returns the multiplicative inverse of x, but this is not entirely satisfactory either, as it uses additive notation: the rest of the package uses multiplicative notation. Thus x*-x == id, which looks a little odd but OTOH noone has a problem with x^-1 for inverses.

I would like to follow APL and use “/x”, but this does not seem to be possible in R. The natural unary operator would be the exclamation mark “!x”. However, redefining the exclamation mark to give permutation inverses, while possible, is not desirable because its precedence is too low. One would like !x*y to return inverse(x)*y but instead standard precedence rules means that it returns inverse(x*y). Earlier versions of the package interpreted !x as inverse(x), but it was a disaster: to implement the commutator $[x,y]=x^{-1}y^{-1}xy$ , for example, one would like to use !x*!y*x*y, but this is interpreted as !(x*(!y*(x*y))); one has to use (!x)*(!y)*x*y. I found myself having to use heaps of brackets everywhere. This caused such severe cognitive dissonance that I removed exclamation mark for inverses from the package. I might reinstate it in the future. There does not appear to be a way to define a new unary operator due to the construction of the parser.

Author(s)

Robin K. S. Hankin

Examples



x <- rperm(10,9) # word form
y <- rperm(10,9) # word form

x*y  # products are given in word form but the print method coerces to cycle form
print_word(x*y)

x^5  # powers are given in cycle form

x^as.cycle(1:5)  # conjugation (not integer power!); coerced to word.

x*inverse(x) == id  # all TRUE


# the 'sum' of two permutations is defined if their cycles are disjoint:
as.cycle(1:4) + as.cycle(7:9)

data(megaminx)
megaminx[1] + megaminx[7:12] 

rperm() + 100

z <- cyc_len(4)
z
z+100
z + 0:5
(z + 0:5)*z

w <- cyc_len(7) + 1
(w+1)*(w-1)

x <- rperm(10,9) # word form
y <- rperm(10,9) # word form

x*y  # products are given in word form but the print method coerces to cycle form
print_word(x*y)

x^5  # powers are given in cycle form

x^as.cycle(1:5)  # conjugation (not integer power!); coerced to word.

x*inverse(x) == id  # all TRUE


# the 'sum' of two permutations is defined if their cycles are disjoint:
as.cycle(1:4) + as.cycle(7:9)

data(megaminx)
megaminx[1] + megaminx[7:12] 

rperm() + 100

z <- cyc_len(4)
z
z+100
z + 0:5
(z + 0:5)*z

w <- cyc_len(7) + 1
(w+1)*(w-1)

Orbits of integers

Description

Finds the orbit of a given integer

Usage

orbit_single(c1,n1)
orbit(cyc,n)
orbit_single(c1,n1)
orbit(cyc,n)

Arguments

`c1`, `n1`	In (low-level) function `orbit_single()`, a cyclist and an integer vector respectively
`cyc`, `n`	In (vectorized) function `orbit()`, `cyc` is coerced to a cycle, and `n` is an integer vector

Value

Given a cyclist c1 and integer n1, function orbit_single() returns the single cycle containing integer n1. This is a low-level function, not intended for the end-user.

Function orbit() is the vectorized equivalent of orbit_single(). Vectorization is inherited from cbind().

The orbit of a fixed point $p$ is $\left\lbrace p\right\rbrace$ ; the code uses an ugly hack to ensure that this is the case.

Note

Orbits are useful in a more general group theoretic context. Consider a finite group $G$ acting on a set $X$ , that is

$\alpha\colon G\times X\longrightarrow X.$

Writing $\alpha(g,x)=gx$ , we define $\alpha$ to be a group action if $ex=x$ and $g(hx)=(gh)x$ where $g,h\in G$ and $e$ is the group identity. For any $x\in X$ we define the orbit $Gx$ of $x$ to be the set of elements of $X$ to which $x$ can be moved by an element of $G$ . Symbolically:

$Gx=\left\lbrace gx\colon g\in G\right\rbrace$

Now, we abuse notation slightly. In the context of permutation groups, we consider a fixed permutation $\sigma$ . We consider the group $G=\left\langle\sigma\right\rangle$ , that is, the group generated by $\sigma$ ; the group action is that of $G$ on set $X=\left\lbrace 1,2,\ldots,n\right\rbrace$ with the obvious definition $\sigma x=\sigma(x)$ for $\sigma\in G$ and $x\in X$ . This clearly is a group action as $\operatorname{id}(x)=x$ and $\sigma(\mu x)=(\sigma\mu)x$ .

$Gx=\bigcup_{i\in\mathbb{Z}}\sigma^i(x)$

Expressing $\sigma$ in cycle form makes it easy to see that the orbit of any element $x$ of $X$ is just the other members in the cycle containing $x$ . For example, consider $\sigma=(26)(348)$ and $x=4$ . Then

$G=\left\langle(26)(348)\right\rangle = \bigcup_{i\in\mathbb{Z}}[(26)(348)]^i$

Because we are only interested in the effects on $x=4$ , we only need to consider the cycle $(348)$ : this is the only cycle that affects $x=4$ , and the $(26)$ cycle may be ignored as it does not affect element 4. So

$G4=\bigcup_{i\in\mathbb{Z}}(348)^i(4)=\left\lbrace 3,4,8\right\rbrace$

[observe the slight notational abuse above: “ $(348)$ ” means “the function $f(\cdot)$ with $f(3)=4$ , $f(4)=8$ , and $f(8)=3$ ”].

Author(s)

Robin K. S. Hankin

Examples


orbit(as.cycle("(123)"),1:5)
orbit(as.cycle(c("(12)","(123)(45)","(2345)")),1)
orbit(as.cycle(c("(12)","(123)(45)","(2345)")),1:3)

data(megaminx)
orbit(megaminx,13)

orbit(as.cycle("(123)"),1:5)
orbit(as.cycle(c("(12)","(123)(45)","(2345)")),1)
orbit(as.cycle(c("(12)","(123)(45)","(2345)")),1:3)

data(megaminx)
orbit(megaminx,13)

Outer product of vectors of permutations

Description

The outer product of two vectors of permutations is the pairwise product of each element of the first with each element of the second.

Details

It works in much the same way as base::outer(). The third argument, FUN, as in outer(X,Y,FUN="*") is regular group-theoretic multiplication but can be replaced with + if you are sure that the cycles of X and Y are distinct, see the examples. Each element of the returned matrix is a one-element list.

The print method may have room for improvement.

Author(s)

Robin K. S. Hankin

Examples


(M <- outer(rperm(),rperm()))
outer(cyc_len(4) + 0:3, cyc_len(4) + 100:101,"+")  # OK because the cycles are distinct

do.call("c",M) # c(M) gives a list and unlist(a) gives a numeric vector

(M <- outer(rperm(),rperm()))
outer(cyc_len(4) + 0:3, cyc_len(4) + 100:101,"+")  # OK because the cycles are distinct

do.call("c",M) # c(M) gives a list and unlist(a) gives a numeric vector

Permutation matrices

Description

Given a permutation, coerce to word form and return the corresponding permutation matrix

Usage

perm_matrix(p,s=size(p))
is.perm_matrix(M)
pm_to_perm(M)
perm_matrix(p,s=size(p))
is.perm_matrix(M)
pm_to_perm(M)

Arguments

`p`	Permutation, coerced to word form, of length 1
`s`	Size of permutation matrix or permutation
`M`	Permutation matrix

Details

Given a permutation p of size $s$ , function perm_matrix() returns a square matrix with $s$ rows and $s$ columns. Entries are either 0 or 1; each row and each column has exactly one entry of 1 and the rest zero.

Row and column names of the permutation matrix are integers; this makes the printed version more compact.

Function pm_to_perm() takes a permutation matrix and returns the equivalent permutation in word form.

Note

Given a word p with size s, the idiom for perm_matrix() boils down to

    M <- diag(s)
    M[p,]

This is used explicitly in the representations vignette. There is another way:

    M <- diag(s)
    M[cbind(seq_len(s),p)] <- 1
    M

which might be useful sometime.

See also the representation and order_of_ops vignettes, which discuss permutation matrices.

Author(s)

Robin K. S. Hankin

Examples


perm_matrix(rperm(1,9))


p1 <- rperm(1,40)
M1 <- perm_matrix(p1)
p2 <- rperm(1,40)
M2 <- perm_matrix(p2)

stopifnot(is.perm_matrix(M1))

stopifnot(all(solve(M1) == perm_matrix(inverse(p1))))
stopifnot(all(M1 %*% M2 == perm_matrix(p1*p2)))


stopifnot(p1 == pm_to_perm(perm_matrix(p1)))

data("megaminx")
image(perm_matrix(permprod(megaminx)),asp=1,axes=FALSE)

perm_matrix(rperm(1,9))


p1 <- rperm(1,40)
M1 <- perm_matrix(p1)
p2 <- rperm(1,40)
M2 <- perm_matrix(p2)

stopifnot(is.perm_matrix(M1))

stopifnot(all(solve(M1) == perm_matrix(inverse(p1))))
stopifnot(all(M1 %*% M2 == perm_matrix(p1*p2)))


stopifnot(p1 == pm_to_perm(perm_matrix(p1)))

data("megaminx")
image(perm_matrix(permprod(megaminx)),asp=1,axes=FALSE)

The order of a permutation

Description

Returns the order of a permutation $P$ : the smallest strictly positive integer $n$ for which $P^n$ is the identity.

Usage

permorder(x, singly = TRUE)
permorder(x, singly = TRUE)

Arguments

`x`	Permutation, coerced to `cycle` form
`singly`	Boolean, with default `TRUE` meaning to return the order of each element of the vector, and `FALSE` meaning to return the order of the vector itself (that is, the smallest strictly positive integer for which `all(x^n==id)`).

Details

Coerces its argument to cycle form.

The order of the identity permutation is 1.

Note

Uses mLCM() from the numbers package.

Author(s)

Robin K. S. Hankin

Examples

x <- rperm(5,20)
permorder(x)
permorder(x,FALSE)

stopifnot(all(is.id(x^permorder(x))))
stopifnot(is.id(x^permorder(x,FALSE)))
x <- rperm(5,20)
permorder(x)
permorder(x,FALSE)

stopifnot(all(is.id(x^permorder(x))))
stopifnot(is.id(x^permorder(x,FALSE)))

Functions to create and coerce word objects and cycle objects

Description

Functions to create permutation objects. permutation is a virtual class.

Usage

word(M)
permutation(x)
is.permutation(x)
cycle(x)
is.word(x)
is.cycle(x)
as.word(x,n=NULL)
as.cycle(x)
cycle2word(x,n=NULL)
char2cycle(char)
cyc_len(n)
shift_cycle(n)
## S3 method for class 'word'
as.matrix(x,...)
word(M)
permutation(x)
is.permutation(x)
cycle(x)
is.word(x)
is.cycle(x)
as.word(x,n=NULL)
as.cycle(x)
cycle2word(x,n=NULL)
char2cycle(char)
cyc_len(n)
shift_cycle(n)
## S3 method for class 'word'
as.matrix(x,...)

Arguments

`M`	In function `word()`, a matrix with rows corresponding to permutations in word form
`x`	See details
`n`	In functions `as.word()` and `cycle2word()`, the size of the word to return; in function `cyc_len()`, the length of the cycles to return
`char`	In function `char2cycle()` a character vector which is coerced to a cycle object
`...`	Further arguments passed to `as.matrix()`

Details

Functions word() and cycle() are rather formal functions which make no attempt to coerce their arguments into sensible forms. The user should use permutation(), which detects the form of the input and dispatches to as.word() or as.cycle(), which are much more user-friendly and try quite hard to Do The Right Thing (tm).

Functions word() and cycle() are the only functions in the package which assign class word or cycle to an object.

Function word() takes a matrix and returns a word object; silently coerces to integer.

Function cycle() takes a “cyclist”, that is, a list whose elements are lists whose elements are vectors (which are disjoint cycles); and returns an object of class “cycle”. It nicifies its input with nicify_cyclist() before returning it.

A word is a matrix whose rows correspond to permutations in word format.

A cycle is a list whose elements correspond to permutations in cycle form. A cycle object comprises elements which are informally dubbed ‘cyclists’. A cyclist is a list of integer vectors corresponding to the cycles of the permutation.

Function cycle2word() converts cycle objects to word objects.

Function shift_cycle() is a convenience wrapper for as.cycle(seq_len(n)); cyc_len() is a synonym.

It is a very common error (at least, it is for me) to use cycle() when you meant as.cycle().

The print method is sensitive to the value of option ‘print_word_as_cycle’, documented at print.Rd.

Function as.matrix.word() coerces a vector of permutations in word form to a matrix, each row of which is a word. To get a permutation matrix (that is, a square matrix of ones and zeros with exactly one entry of 1 in each row and each column), use perm_matrix().

In function as.word(), argument n cannot act to reduce the size of the word, only increase it. If you want to reduce the size, use trim() or tidy(). This function does not call word() except directly (e.g. it does not call size<-.word(), as this would give a recursion).

Value

Returns a cycle object or a word object

Author(s)

Robin K. S. Hankin

Examples


word(matrix(1:8,7,8)) # default print method coerces to cycle form

cycle(list(list(c(1,8,2),c(3,6)),list(1:2, 4:8)))

char2cycle(c("(1,4)(6,7)","(3,4,2)(8,19)", "(56)","(12345)(78)","(78)"))

jj <- c(4,2,3,1)

as.word(jj)
as.cycle(jj)

as.cycle(1:2)*as.cycle(1:8) == as.cycle(1:8)*as.cycle(1:2)  # FALSE!

x <- rperm(10,7)
y <- rperm(10,7)
as.cycle(commutator(x,y))

cyc_len(1:9)


word(matrix(1:8,7,8)) # default print method coerces to cycle form

cycle(list(list(c(1,8,2),c(3,6)),list(1:2, 4:8)))

char2cycle(c("(1,4)(6,7)","(3,4,2)(8,19)", "(56)","(12345)(78)","(78)"))

jj <- c(4,2,3,1)

as.word(jj)
as.cycle(jj)

as.cycle(1:2)*as.cycle(1:8) == as.cycle(1:8)*as.cycle(1:2)  # FALSE!

x <- rperm(10,7)
y <- rperm(10,7)
as.cycle(commutator(x,y))

cyc_len(1:9)

Print methods for permutation objects

Description

Print methods for permutation objects with matrix-like printing for words and bracket notation for cycle objects.

Usage

## S3 method for class 'cycle'
print(x, give_string=FALSE, ...)
## S3 method for class 'word'
print(x, h = getOption("print_word_as_cycle"), ...)
as.character_cyclist(y,comma=TRUE)
## S3 method for class 'cycle'
print(x, give_string=FALSE, ...)
## S3 method for class 'word'
print(x, h = getOption("print_word_as_cycle"), ...)
as.character_cyclist(y,comma=TRUE)

Arguments

`x`	Object of class `permutation` with `word` objects dispatched to `print.word()` and `cycle` objects dispatched to `print.cycle()`
`h`	Boolean, with default `TRUE` meaning to coerce words to cycle form before printing. See details
`...`	Further arguments (currently ignored)
`y`, `comma`	In `as.character.cyclist()`, argument `y` is a list of cycles (a cyclist); and `comma` is Boolean, specifying whether to include a comma in the output
`give_string`	In function

Details

Printing of word objects is controlled by options("print_word_as_cycle"). The default behaviour is to coerce a word to cycle form and print that, with a notice that the object itself was coerced from word.

If options("print_word_as_cycle") is FALSE, then objects of class word are printed as a matrix with rows being the permutations and fixed points indicated with a dot.

Function as.character_cyclist() is an internal function used by print.cycle(), and is not really designed for the end-user. It takes a cyclist and returns a character string.

Function print_word() and print_cycle() are provided for power users. These functions print their argument directly as word or cycle form; they coerce to the appropriate form. Use print_word() if you have a permutation in word form and want to inspect it as a word form but (for some reason) do not want to set options("print_word_as_cycle"). See size.Rd for a use-case.

Coercing a cycle to a character vector can be done with as.character(), which returns a character vector that is suitable for as.cycle(), so if a is a cycle all(as.cycle(as.character(a)) == a) will return TRUE. If you want to use the options of the print method, use print.cycle(...,give_string=TRUE), which respects the print options discussed below. Neither of these give useful output if their argument is in word form.

The print method includes experimental functionality to display permutations of sets other than the default of integers $1,2,\ldots, n$ . Both cycle and word print methods are sensitive to option perm_set: the default value of NULL means to use integers. The symbols may be the elements of any character vector; use idiom such as

options("perm_set" = letters)

to override the default. But beware! If the permutation includes numbers greater than the length of perm_set, then NA will be printed. It is possible to use vectors with elements of more than one character (e.g. state.abb).

In the printing of cycle objects, commas are controlled with option "comma". The default NULL means including commas in the representation if the size of the permutation exceeds 9. This works well for integers but is less suitable when using letters or state abbreviations. Force the use of commas by setting the option to TRUE or FALSE, e.g.

options("comma" = TRUE)

The print method does not change the internal representation of word or cycle objects, it only affects how they are printed.

The print method is sensitive to experimental option print_in_length_order (via function as.character_cyclist()). If TRUE, permutations cycle form will be printed but with the cycles in increasing length order. Set it with

options("print_in_length_order" = TRUE)

There is a package vignette (type vignette("print") at the command line) which gives more details and long-form documentation.

Value

Returns its argument invisibly, after printing it (except for print.cycle(x,give_string=TRUE), in which case a character vector is returned).

Author(s)

Robin K. S. Hankin

Examples


# generate a permutation in *word* form:
x <- rperm(4,9)

# default behaviour is to print in cycle form irregardless:
x

# change default using options():
options(print_word_as_cycle=FALSE)

# objects in word form now printed using matrix notation:
x

# printing of cycle form objects not altered:
as.cycle(x)

# restore default:
options(print_word_as_cycle=TRUE)

as.character_cyclist(list(1:4,10:11,20:33))  # x a cyclist;
as.character_cyclist(list(c(1,5,4),c(2,2)))  # does not check for consistency
as.character_cyclist(list(c(1,5,4),c(2,9)),comma=FALSE)

options("perm_set" = letters)
rperm(r=9)
options("perm_set" = NULL)  # restore default
# generate a permutation in *word* form:
x <- rperm(4,9)

# default behaviour is to print in cycle form irregardless:
x

# change default using options():
options(print_word_as_cycle=FALSE)

# objects in word form now printed using matrix notation:
x

# printing of cycle form objects not altered:
as.cycle(x)

# restore default:
options(print_word_as_cycle=TRUE)

as.character_cyclist(list(1:4,10:11,20:33))  # x a cyclist;
as.character_cyclist(list(c(1,5,4),c(2,2)))  # does not check for consistency
as.character_cyclist(list(c(1,5,4),c(2,9)),comma=FALSE)

options("perm_set" = letters)
rperm(r=9)
options("perm_set" = NULL)  # restore default

Random permutations

Description

Function rperm() creates a word object of random permutations. Function rcyc() creates random permutations comprising a single (group-theoretic) cycle of a specified length. Functions r1cyc() and rgs1() are low-level helper functions.

Usage

rperm(n=10,r=7,moved=NA)
rcyc(n,len,r=len)
r1cyc(len,vec)
rgs1(s)
rgivenshape(n,s,size=sum(s))
rperm(n=10,r=7,moved=NA)
rcyc(n,len,r=len)
r1cyc(len,vec)
rgs1(s)
rgivenshape(n,s,size=sum(s))

Arguments

`n`	Number of permutations to create
`r`	Size of permutations
`len`	Length of cycles in `rcyc()` and `r1cyc()`
`moved`	In function `rperm()`, integer specifying how many elements can move (that is, how many elements do not map to themselves), with default `NA` meaning to choose a permutation at random. This is useful if you want a permutation that has a compact cycle representation
`vec`	Vector of integers to generate a cycle from
`s`, `size`	Shape and size of permutations to create

Value

Returns an object of class word

Note

Argument moved specifies a maximum number of elements that do not map to themselves; the actual number of non-fixed elements might be lower (as some elements might map to themselves). You can control the number of non-fixed elements precisely with argument len of function rcyc(), although this will give only permutations with a single (group-theoretic) cycle.

Argument s of function rgivensize() can include 1s (ones). Although length-one cycles are dropped from the resulting permutation, it is sometimes useful to include them to increase the size of the result, see examples.

In function rgivenshape(), if primary argument n is a vector of length greater than 1, it is interpreted as the shape of the permutation, and a single random permutation is returned.

Author(s)

Robin K. S. Hankin

Examples

rperm()
as.cycle(rperm(30,9))
rperm(10,9,2)

rcyc(20,5)
rcyc(20,5,9)

rgivenshape(10,c(2,3))   # size 5
rgivenshape(10,c(2,3,1,1)) # size 7

rgivenshape(1:9)

allpermslike(rgivenshape(c(1,1,3,4)))

rperm()
as.cycle(rperm(30,9))
rperm(10,9,2)

rcyc(20,5)
rcyc(20,5,9)

rgivenshape(10,c(2,3))   # size 5
rgivenshape(10,c(2,3,1,1)) # size 7

rgivenshape(1:9)

allpermslike(rgivenshape(c(1,1,3,4)))

Sign of a permutation

Description

Returns the sign of a permutation

Usage

sgn(x)
is.even(x)
is.odd(x)
sgn(x)
is.even(x)
is.odd(x)

Arguments

`x`	permutation object

Details

The sign of a permutation is $\pm 1$ depending on whether it is even or odd. A permutation is even if it can be written as a product of an even number of transpositions, and odd if it can be written as an odd number of transpositions. The map $\operatorname{sgn}\colon S_n\longrightarrow\left\lbrace +1,-1\right\rbrace$ is a homomorphism; see examples.

Note

Internally, function sgn() coerces to cycle form.

The sign of the null permutation is NULL.

Author(s)

Robin K. S. Hankin

Examples


sgn(id)  # always problematic

sgn(rperm(10,5))

x <- rperm(40,6)
y <- rperm(40,6)


stopifnot(all(sgn(x*y) == sgn(x)*sgn(y)))   # sgn() is a homomorphism


z <- as.cycle(rperm(20,9,5))
z[is.even(z)]
z[is.odd(z)]

sgn(id)  # always problematic

sgn(rperm(10,5))

x <- rperm(40,6)
y <- rperm(40,6)


stopifnot(all(sgn(x*y) == sgn(x)*sgn(y)))   # sgn() is a homomorphism


z <- as.cycle(rperm(20,9,5))
z[is.even(z)]
z[is.odd(z)]

Shape of a permutation

Description

Returns the shape of a permutation. If given a word, it coerces to cycle form.

Usage

shape(x, drop = TRUE,id1 = TRUE,decreasing = FALSE)
shape_cyclist(cyc,id1=TRUE)
padshape(x, drop = TRUE, n=NULL)
shapepart(x)
shapepart_cyclist(cyc,n=NULL)
shape(x, drop = TRUE,id1 = TRUE,decreasing = FALSE)
shape_cyclist(cyc,id1=TRUE)
padshape(x, drop = TRUE, n=NULL)
shapepart(x)
shapepart_cyclist(cyc,n=NULL)

Arguments

`x`	Object of class `cycle` (if not, coerced)
`cyc`	A cyclist
`n`	Integer governing the size of the partition assumed, with default `NULL` meaning to use the largest element
`drop`	Boolean, with default `TRUE` meaning to unlist if possible
`id1`	Boolean, with default `TRUE` in function `shape_cyclist()` meaning that the shape of the identity is “1” and `FALSE` meaning that the shape is `NULL`
`decreasing`	In function `shape()`, Boolean with default `FALSE` meaning to return the cycle lengths in the order given by `nicify_cyclist()` and `TRUE` meaning to sort in decreasing order

Value

Function shape() returns a list with elements representing the lengths of the component cycles.

Function shapepart() returns an object of class partition showing the permutation as a set partition of disjoint cycles.

Function padshape() returns a list of shapes but padded with ones so the total is the size of the permutation.

shapepart_cyclist() and shapepart_cyclist() are low-level helper functions.

Note

What I call “shape”, others call the “cycle type”, so you will sometimes see “cycle type determines conjugacy class” as a theorem.

Author(s)

Robin K. S. Hankin

Examples


jj <- as.cycle(c("123","","(12)(34)","12345"))
jj
shape(jj)

shape(rperm(10,9)) # coerced to cycle

a <- rperm()
identical(shape(a,dec=TRUE),shape(a^cyc_len(2),dec=TRUE))


data(megaminx)
shape(megaminx)

jj <- megaminx*megaminx[1]
identical(shape(jj),shape(tidy(jj)))  #tidy() does not change shape


allperms(3)
shapepart(allperms(3))
shapepart(rperm(10,5))

shape_cyclist(list(1:4,8:9))
shapepart_cyclist(list(1:4,8:9))

jj <- as.cycle(c("123","","(12)(34)","12345"))
jj
shape(jj)

shape(rperm(10,9)) # coerced to cycle

a <- rperm()
identical(shape(a,dec=TRUE),shape(a^cyc_len(2),dec=TRUE))


data(megaminx)
shape(megaminx)

jj <- megaminx*megaminx[1]
identical(shape(jj),shape(tidy(jj)))  #tidy() does not change shape


allperms(3)
shapepart(allperms(3))
shapepart(rperm(10,5))

shape_cyclist(list(1:4,8:9))
shapepart_cyclist(list(1:4,8:9))

Gets or sets the size of a permutation

Description

The ‘size’ of a permutation is the cardinality of the set for which it is a bijection.

Usage

size(x)
addcols(M,n)
## S3 method for class 'word'
size(x)
## S3 method for class 'cycle'
size(x)
## S3 replacement method for class 'word'
size(x) <- value
## S3 replacement method for class 'cycle'
size(x) <- value
size(x)
addcols(M,n)
## S3 method for class 'word'
size(x)
## S3 method for class 'cycle'
size(x)
## S3 replacement method for class 'word'
size(x) <- value
## S3 replacement method for class 'cycle'
size(x) <- value

Arguments

`x`	A permutation object
`M`	A matrix that may be coerced to a word
`n`, `value`	the size to set to, an integer

Details

For a word object, the size is equal to the number of columns. For a cycle object, it is equal to the largest element of any cycle.

Function addcols() is a low-level function that operates on, and returns, a matrix. It just adds columns to the right of M, with values equal to their column numbers, thus corresponding to fixed elements. The resulting matrix has n columns. This function cannot remove columns, so if n<ncol(M) an error is returned.

Setting functions cannot decrease the size of a permutation; use trim() for this.

It is meaningless to change the size of a cycle object. Trying to do so will result in an error. But you can coerce cycle objects to word form, and change the size of that.

Function size<-.word() [as in size(x) <- 9] trims its argument down with trim() and then adds fixed elements if necessary. Compare addcols(), which works only on permutations in word form.

Author(s)

Robin K. S. Hankin

Examples


size(as.cycle(c("(17)","(123)(45)")))  # should be 7

x <- as.word(as.cycle("123"))
print_word(x)
size(x) <- 9
print_word(x)


size(as.cycle(1:5) + as.cycle(100:101))

size(id)
size(as.cycle(c("(17)","(123)(45)")))  # should be 7

x <- as.word(as.cycle("123"))
print_word(x)
size(x) <- 9
print_word(x)


size(as.cycle(1:5) + as.cycle(100:101))

size(id)

Utilities to neaten permutation objects

Description

Various utilities to neaten word objects by removing fixed elements

Usage

tidy(x)
trim(x)
tidy(x)
trim(x)

Arguments

`x`	Object of class `word`, or in the case of `tidy()`, coerced to class `word`

Details

Function trim() takes a word and, starting from the right, strips off columns corresponding to fixed elements until it finds a non-fixed element. This makes no sense for cycle objects; if x is of class cycle, an error is returned.

Function tidy() is more aggressive. This firstly removes all fixed elements, then renames the non-fixed ones to match the new column numbers. The map is an isomorphism (sic) with respect to composition.

Value

Returns an object of class word

Note

Results in empty (that is, zero-column) words if a vector of identity permutations is given

Author(s)

Robin K. S. Hankin

Examples

as.cycle(5:3)+as.cycle(7:9)
tidy(as.cycle(5:3)+as.cycle(7:9))

as.cycle(tidy(c(as.cycle(1:2),as.cycle(6:7))))


nicify_cyclist(list(c(4,6), c(7), c(2,5,1), c(8,3)))

data(megaminx)
tidy(megaminx)  # has 120 columns, not 129
stopifnot(all(unique(sort(unlist(as.cycle(tidy(megaminx)),recursive=TRUE)))==1:120))

jj <- megaminx*megaminx[1]
stopifnot(identical(shape(jj),shape(tidy(jj))))  #tidy() does not change shape

as.cycle(5:3)+as.cycle(7:9)
tidy(as.cycle(5:3)+as.cycle(7:9))

as.cycle(tidy(c(as.cycle(1:2),as.cycle(6:7))))


nicify_cyclist(list(c(4,6), c(7), c(2,5,1), c(8,3)))

data(megaminx)
tidy(megaminx)  # has 120 columns, not 129
stopifnot(all(unique(sort(unlist(as.cycle(tidy(megaminx)),recursive=TRUE)))==1:120))

jj <- megaminx*megaminx[1]
stopifnot(identical(shape(jj),shape(tidy(jj))))  #tidy() does not change shape

Functions to validate permutations

Description

Functions to validate permutation objects: if valid, return TRUE and if not valid, generate a warning() and return FALSE.

Function singleword.valid() takes an integer vector, interpreted as a word, and checks that it is a permutation of seq_len(max(x)).

Function cycle.valid() takes a cyclist and checks for disjoint cycles of strictly positive integers with no repeats.

Usage

singleword_valid(w)
cyclist_valid(x)
singleword_valid(w)
cyclist_valid(x)

Arguments

`x`	In function `cycle_valid()`, a cyclist
`w`	In function `singleword_valid()`, an integer vector

Value

Returns either TRUE, or stops with an informative error message

Author(s)

Robin K. S. Hankin

Examples


singleword_valid(sample(1:9))      # TRUE
singleword_valid(c(3L,4L,2L,1L))   # TRUE
singleword_valid(c(3,4,2,1))       # FALSE (not integer)
singleword_valid(c(3L,3L,2L,1L))   # FALSE (3 repeated)

cyclist_valid(list(c(1,8,2),c(3,6))) # TRUE
cyclist_valid(list(c(1,8,2),c(3,6))) # FALSE ('8' is repeated)
cyclist_valid(list(c(1,8,1),c(3,6))) # FALSE ('1' is repeated)
cyclist_valid(list(c(0,8,2),c(3,6))) # FALSE (zero element)

singleword_valid(sample(1:9))      # TRUE
singleword_valid(c(3L,4L,2L,1L))   # TRUE
singleword_valid(c(3,4,2,1))       # FALSE (not integer)
singleword_valid(c(3L,3L,2L,1L))   # FALSE (3 repeated)

cyclist_valid(list(c(1,8,2),c(3,6))) # TRUE
cyclist_valid(list(c(1,8,2),c(3,6))) # FALSE ('8' is repeated)
cyclist_valid(list(c(1,8,1),c(3,6))) # FALSE ('1' is repeated)
cyclist_valid(list(c(0,8,2),c(3,6))) # FALSE (zero element)

Package 'permutations'

Help Index

The Symmetric Group: Permutations of a Finite Set

Description

Details

Author(s)

Examples

All permutations with given characteristics

Description

Usage

Arguments

Details

Note

Author(s)

References

See Also

Examples

Coerce a permutation to a function

Description

Usage

Arguments

Note

Author(s)

Examples

Concatenation of permutations

Description

Usage

Arguments

Note

Author(s)

See Also

Examples

Apply functions to elements of a cycle

Description

Usage

Arguments

Details

Value

Note

Author(s)

See Also

Examples

Cayley tables for permutation groups

Description

Usage

Arguments

Details

Value

Author(s)

Examples

Group-theoretic commutator: the dot object

Description

Usage

Arguments

Author(s)

Examples

Are two permutations conjugate?

Description

Usage

Arguments

Details

Value

Note

Author(s)

See Also

Examples

details of cyclists

Description

Usage

Arguments

Details

Author(s)

See Also

Examples

Tests for a permutation being a derangement

Description

Usage

Arguments

Value

Note