This chapter describes the functions that deal with combinatorics. We
mainly concentrate on two areas. One is about **selections**, that is the
ways one can select elements from a set. The other is about
**partitions**, that is the ways one can partition a set into the union of
pairwise disjoint subsets.

First this package contains various functions that are related to the number of selections from a set (see Factorial, Binomial) or to the number of partitions of a set (see Bell, Stirling1, Stirling2). Those numbers satisfy literally thousands of identities, which we do no mention in this document, for a thorough treatment see GKP90.

Then this package contains functions to compute the selections from a set (see Combinations), ordered selections, i.e., selections where the order in which you select the elements is important (see Arrangements), selections with repetitions, i.e., you are allowed to select the same element more than once (see UnorderedTuples) and ordered selections with repetitions (see Tuples).

As special cases of ordered combinations there are functions to compute all permutations (see PermutationsList), all fixpointfree permutations (see Derangements) of a list.

This package also contains functions to compute partitions of a set (see PartitionsSet), partitions of an integer into the sum of positive integers (see Partitions, RestrictedPartitions) and ordered partitions of an integer into the sum of positive integers (see OrderedPartitions).

Moreover, it provides three functions to compute Fibonacci numbers (see Fibonacci), Lucas sequences (see Lucas), or Bernoulli numbers (see Bernoulli).

Finally, there is a function to compute the number of permutations that fit a given 1-0 matrix (see Permanent).

All these functions are in the file `"LIBNAME/combinat.g"`

.

- Factorial
- Binomial
- Bell
- Stirling1
- Stirling2
- Combinations
- Arrangements
- UnorderedTuples
- Tuples
- PermutationsList
- Derangements
- PartitionsSet
- Partitions
- OrderedPartitions
- RestrictedPartitions
- SignPartition
- AssociatedPartition
- BetaSet
- Dominates
- PowerPartition
- PartitionTuples
- Fibonacci
- Lucas
- Bernoulli
- Permanent

`Factorial( `

`n` )

`Factorial`

returns the **factorial** *n!* of the positive integer `n`,
which is defined as the product *1 * 2 * 3 * .. * n*.

*n!* is the number of permutations of a set of *n* elements. *1/n!* is
the coefficient of *x ^{n}* in the formal series

gap> List( [0..10], Factorial ); [ 1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880, 3628800 ] gap> Factorial( 30 ); 265252859812191058636308480000000

`PermutationsList`

(see PermutationsList) computes the set of all
permutations of a list.

`Binomial( `

`n`, `k` )

`Binomial`

returns the **binomial coefficient** *n \choose k* of integers
`n` and `k`, which is defined as *n! / (k! (n-k)!)* (see Factorial).
We define *0 \choose 0 = 1*, *n \choose k = 0* if *k<0* or *n<k*,
and *n \choose k = (-1) ^{k} -n+k-1 \choose k* if

*n \choose k* is the number of combinations with *k* elements, i.e.,
the number of subsets with *k* elements, of a set with *n* elements.
*n \choose k* is the coefficient of the term *x ^{k}* of the polynomial

gap> List( [0..4], k->Binomial( 4, k ) ); [ 1, 4, 6, 4, 1 ] # Knuth calls this the trademark of Binomial gap> List( [0..6], n->List( [0..6], k->Binomial( n, k ) ) );; gap> PrintArray( last ); [ [ 1, 0, 0, 0, 0, 0, 0 ], # the lower triangle is [ 1, 1, 0, 0, 0, 0, 0 ], # called Pascal's triangle [ 1, 2, 1, 0, 0, 0, 0 ], [ 1, 3, 3, 1, 0, 0, 0 ], [ 1, 4, 6, 4, 1, 0, 0 ], [ 1, 5, 10, 10, 5, 1, 0 ], [ 1, 6, 15, 20, 15, 6, 1 ] ] gap> Binomial( 50, 10 ); 10272278170

`NrCombinations`

(see Combinations) is the generalization of `Binomial`

for multisets. `Combinations`

(see Combinations) computes the set of
all combinations of a multiset.

`Bell( `

`n` )

`Bell`

returns the **Bell number** *B(n)*. The Bell numbers are defined by
*B(0)=1* and the recurrence *B(n+1) = ∑ _{k=0}^{n}{n \choose kB(k)}*.

*B(n)* is the number of ways to partition a set of `n` elements into
pairwise disjoint nonempty subsets (see PartitionsSet). This implies
of course that *B(n) = ∑ _{k=0}^{n}S_{2}(n,k)* (see Stirling2).

gap> List( [0..6], n -> Bell( n ) ); [ 1, 1, 2, 5, 15, 52, 203 ] gap> Bell( 14 ); 190899322

`Stirling1( `

`n`, `k` )

`Stirling1`

returns the **Stirling number of the first kind** *S _{1}(n,k)* of
the integers

*S _{1}(n,k)* is the number of permutations of

gap> List( [0..4], k->Stirling1( 4, k ) ); [ 0, 6, 11, 6, 1 ] # Knuth calls this the trademark ofSgap> List( [0..6], n->List( [0..6], k->Stirling1( n, k ) ) );; gap> PrintArray( last ); [ [ 1, 0, 0, 0, 0, 0, 0 ], # Note the similarity [ 0, 1, 0, 0, 0, 0, 0 ], # with Pascal's [ 0, 1, 1, 0, 0, 0, 0 ], # triangle for the [ 0, 2, 3, 1, 0, 0, 0 ], # Binomial numbers [ 0, 6, 11, 6, 1, 0, 0 ], [ 0, 24, 50, 35, 10, 1, 0 ], [ 0, 120, 274, 225, 85, 15, 1 ] ] gap> Stirling1(50,10); 101623020926367490059043797119309944043405505380503665627365376_{1}

`Stirling2( `

`n`, `k` )

`Stirling2`

returns the **Stirling number of the second kind** *S _{2}(n,k)*
of the integers

*S _{2}(n,k)* is the number of ways to partition a set of

gap> List( [0..4], k->Stirling2( 4, k ) ); [ 0, 1, 7, 6, 1 ] # Knuth calls this the trademark ofSgap> List( [0..6], n->List( [0..6], k->Stirling2( n, k ) ) );; gap> PrintArray( last ); [ [ 1, 0, 0, 0, 0, 0, 0 ], # Note the similarity with [ 0, 1, 0, 0, 0, 0, 0 ], # Pascal's triangle for [ 0, 1, 1, 0, 0, 0, 0 ], # the Binomial numbers [ 0, 1, 3, 1, 0, 0, 0 ], [ 0, 1, 7, 6, 1, 0, 0 ], [ 0, 1, 15, 25, 10, 1, 0 ], [ 0, 1, 31, 90, 65, 15, 1 ] ] gap> Stirling2( 50, 10 ); 26154716515862881292012777396577993781727011_{2}

`Combinations( `

`mset` )

`Combinations( `

`mset`, `k` )

`NrCombinations( `

`mset` )

`NrCombinations( `

`mset`, `k` )

In the first form `Combinations`

returns the set of all combinations of
the multiset `mset`. In the second form `Combinations`

returns the set
of all combinations of the multiset `mset` with `k` elements.

In the first form `NrCombinations`

returns the number of combinations of
the multiset `mset`. In the second form `NrCombinations`

returns the
number of combinations of the multiset `mset` with `k` elements.

A **combination** of `mset` is an unordered selection without repetitions
and is represented by a sorted sublist of `mset`. If `mset` is a proper
set, there are *|mset| \choose k* (see Binomial) combinations
with `k` elements, and the set of all combinations is just the **powerset**
of `mset`, which contains all **subsets** of `mset` and has cardinality
*2 ^{|mset|}*.

gap> Combinations( [1,2,2,3] ); [ [ ], [ 1 ], [ 1, 2 ], [ 1, 2, 2 ], [ 1, 2, 2, 3 ], [ 1, 2, 3 ], [ 1, 3 ], [ 2 ], [ 2, 2 ], [ 2, 2, 3 ], [ 2, 3 ], [ 3 ] ] gap> NrCombinations( [1..52], 5 ); 2598960 # number of different hands in a game of poker

The function `Arrangements`

(see Arrangements) computes ordered
selections without repetitions, `UnorderedTuples`

(see UnorderedTuples)
computes unordered selections with repetitions and `Tuples`

(see
Tuples) computes ordered selections with repetitions.

`Arrangements( `

`mset` )

`Arrangements( `

`mset`, `k` )

`NrArrangements( `

`mset` )

`NrArrangements( `

`mset`, `k` )

In the first form `Arrangements`

returns the set of arrangements of the
multiset `mset`. In the second form `Arrangements`

returns the set of
all arrangements with `k` elements of the multiset `mset`.

In the first form `NrArrangements`

returns the number of arrangements of
the multiset `mset`. In the second form `NrArrangements`

returns the
number of arrangements with `k` elements of the multiset `mset`.

An **arrangement** of `mset` is an ordered selection without repetitions
and is represented by a list that contains only elements from `mset`, but
maybe in a different order. If `mset` is a proper set there are
*|mset|! / (|mset|-k)!* (see Factorial) arrangements with `k`
elements.

As an example of arrangements of a multiset, think of the game Scrabble.
Suppose you have the six characters of the word `settle`

and you have to
make a four letter word. Then the possibilities are given by

gap> Arrangements( ["s","e","t","t","l","e"], 4 ); [ [ "e", "e", "l", "s" ], [ "e", "e", "l", "t" ], [ "e", "e", "s", "l" ], [ "e", "e", "s", "t" ], # 96 more possibilities [ "t", "t", "s", "e" ], [ "t", "t", "s", "l" ] ]

Can you find the five proper English words, where `lets`

does not count?
Note that the fact that the list returned by `Arrangements`

is a proper
set means in this example that the possibilities are listed in the same
order as they appear in the dictionary.

gap> NrArrangements( ["s","e","t","t","l","e"] ); 523

The function `Combinations`

(see Combinations) computes unordered
selections without repetitions, `UnorderedTuples`

(see UnorderedTuples)
computes unordered selections with repetitions and `Tuples`

(see
Tuples) computes ordered selections with repetitions.

`UnorderedTuples( `

`set`, `k` )

`NrUnorderedTuples( `

`set`, `k` )

`UnorderedTuples`

returns the set of all unordered tuples of length `k`
of the set `set`.

`NrUnorderedTuples`

returns the number of unordered tuples of length `k`
of the set `set`.

An **unordered tuple** of length `k` of `set` is a unordered selection with
repetitions of `set` and is represented by a sorted list of length `k`
containing elements from `set`. There are *|set|+k-1 \choose k*
(see Binomial) such unordered tuples.

Note that the fact that `UnOrderedTuples`

returns a set implies that the
last index runs fastest. That means the first tuple contains the
smallest element from `set` `k` times, the second tuple contains the
smallest element of `set` at all positions except at the last positions,
where it contains the second smallest element from `set` and so on.

As an example for unordered tuples think of a poker-like game played with 5 dice. Then each possible hand corresponds to an unordered five-tuple from the set [1..6]

gap> NrUnorderedTuples( [1..6], 5 ); 252 gap> UnorderedTuples( [1..6], 5 ); [ [ 1, 1, 1, 1, 1 ], [ 1, 1, 1, 1, 2 ], [ 1, 1, 1, 1, 3 ], [ 1, 1, 1, 1, 4 ], [ 1, 1, 1, 1, 5 ], [ 1, 1, 1, 1, 6 ], # 99 more tuples [ 1, 3, 4, 5, 6 ], [ 1, 3, 4, 6, 6 ], [ 1, 3, 5, 5, 5 ], # 99 more tuples [ 3, 3, 4, 4, 5 ], [ 3, 3, 4, 4, 6 ], [ 3, 3, 4, 5, 5 ], # 39 more tuples [ 5, 5, 6, 6, 6 ], [ 5, 6, 6, 6, 6 ], [ 6, 6, 6, 6, 6 ] ]

The function `Combinations`

(see Combinations) computes unordered
selections without repetitions, `Arrangements`

(see Arrangements)
computes ordered selections without repetitions and `Tuples`

(see
Tuples) computes ordered selections with repetitions.

`Tuples( `

`set`, `k` )

`NrTuples( `

`set`, `k` )

`Tuples`

returns the set of all ordered tuples of length `k` of the set
`set`.

`NrTuples`

returns the number of all ordered tuples of length `k` of the
set `set`.

An **ordered tuple** of length `k` of `set` is an ordered selection with
repetition and is represented by a list of length `k` containing elements
of `set`. There are *|set| ^{k}* such ordered tuples.

Note that the fact that `Tuples`

returns a set implies that the last
index runs fastest. That means the first tuple contains the smallest
element from `set` `k` times, the second tuple contains the smallest
element of `set` at all positions except at the last positions, where it
contains the second smallest element from `set` and so on.

gap> Tuples( [1,2,3], 2 ); [ [ 1, 1 ], [ 1, 2 ], [ 1, 3 ], [ 2, 1 ], [ 2, 2 ], [ 2, 3 ], [ 3, 1 ], [ 3, 2 ], [ 3, 3 ] ] gap> NrTuples( [1..10], 5 ); 100000

`Tuples(`

can also be viewed as the `set`,`k`)`k`-fold cartesian product
of `set` (see Cartesian).

The function `Combinations`

(see Combinations) computes unordered
selections without repetitions, `Arrangements`

(see Arrangements)
computes ordered selections without repetitions, and finally the function
`UnorderedTuples`

(see UnorderedTuples) computes unordered selections
with repetitions.

`PermutationsList( `

`mset` )

`NrPermutationsList( `

`mset` )

`PermutationsList`

returns the set of permutations of the multiset
`mset`.

`NrPermutationsList`

returns the number of permutations of the multiset
`mset`.

A **permutation** is represented by a list that contains exactly the same
elements as `mset`, but possibly in different order. If `mset` is a
proper set there are *|mset| !* (see Factorial) such permutations.
Otherwise if the first elements appears *k _{1}* times, the second element
appears

gap> PermutationsList( [1,2,3] ); [ [ 1, 2, 3 ], [ 1, 3, 2 ], [ 2, 1, 3 ], [ 2, 3, 1 ], [ 3, 1, 2 ], [ 3, 2, 1 ] ] gap> PermutationsList( [1,1,2,2] ); [ [ 1, 1, 2, 2 ], [ 1, 2, 1, 2 ], [ 1, 2, 2, 1 ], [ 2, 1, 1, 2 ], [ 2, 1, 2, 1 ], [ 2, 2, 1, 1 ] ] gap> NrPermutationsList( [1,2,2,3,3,3,4,4,4,4] ); 12600

The function `Arrangements`

(see Arrangements) is the generalization of
`PermutationsList`

that allows you to specify the size of the
permutations. `Derangements`

(see Derangements) computes permutations
that have no fixpoints.

`Derangements( `

`list` )

`NrDerangements( `

`list` )

`Derangements`

returns the set of all derangements of the list `list`.

`NrDerangements`

returns the number of derangements of the list `list`.

A **derangement** is a fixpointfree permutation of `list` and is
represented by a list that contains exactly the same elements as `list`,
but in such an order that the derangement has at no position the same
element as `list`. If the list `list` contains no element twice there
are exactly *|list|! (1/2! - 1/3! + 1/4! - .. (-1) ^{n}/n!)*
derangements.

Note that the ratio `NrPermutationsList([1..n])/NrDerangements([1..n])`

,
which is *n! / (n! (1/2! - 1/3! + 1/4! - .. (-1) ^{n}/n!))* is an
approximation for the base of the natural logarithm

As an example of derangements suppose that you have to send four different letters to four different people. Then a derangement corresponds to a way to send those letters such that no letter reaches the intended person.

gap> Derangements( [1,2,3,4] ); [ [ 2, 1, 4, 3 ], [ 2, 3, 4, 1 ], [ 2, 4, 1, 3 ], [ 3, 1, 4, 2 ], [ 3, 4, 1, 2 ], [ 3, 4, 2, 1 ], [ 4, 1, 2, 3 ], [ 4, 3, 1, 2 ], [ 4, 3, 2, 1 ] ] gap> NrDerangements( [1..10] ); 1334961 gap> Int( 10^7*NrPermutationsList([1..10])/last ); 27182816 gap> Derangements( [1,1,2,2,3,3] ); [ [ 2, 2, 3, 3, 1, 1 ], [ 2, 3, 1, 3, 1, 2 ], [ 2, 3, 1, 3, 2, 1 ], [ 2, 3, 3, 1, 1, 2 ], [ 2, 3, 3, 1, 2, 1 ], [ 3, 2, 1, 3, 1, 2 ], [ 3, 2, 1, 3, 2, 1 ], [ 3, 2, 3, 1, 1, 2 ], [ 3, 2, 3, 1, 2, 1 ], [ 3, 3, 1, 1, 2, 2 ] ] gap> NrDerangements( [1,2,2,3,3,3,4,4,4,4] ); 338

The function `PermutationsList`

(see PermutationsList) computes all
permutations of a list.

`PartitionsSet( `

`set` )

`PartitionsSet( `

`set`, `k` )

`NrPartitionsSet( `

`set` )

`NrPartitionsSet( `

`set`, `k` )

In the first form `PartitionsSet`

returns the set of all unordered
partitions of the set `set`. In the second form `PartitionsSet`

returns
the set of all unordered partitions of the set `set` into `k` pairwise
disjoint nonempty sets.

In the first form `NrPartitionsSet`

returns the number of unordered
partitions of the set `set`. In the second form `NrPartitionsSet`

returns the number of unordered partitions of the set `set` into `k`
pairwise disjoint nonempty sets.

An **unordered partition** of `set` is a set of pairwise disjoint nonempty
sets with union `set` and is represented by a sorted list of such sets.
There are *B( |set| )* (see Bell) partitions of the set `set` and
*S _{2}( |set|, k )* (see Stirling2) partitions with

gap> PartitionsSet( [1,2,3] ); [ [ [ 1 ], [ 2 ], [ 3 ] ], [ [ 1 ], [ 2, 3 ] ], [ [ 1, 2 ], [ 3 ] ], [ [ 1, 2, 3 ] ], [ [ 1, 3 ], [ 2 ] ] ] gap> PartitionsSet( [1,2,3,4], 2 ); [ [ [ 1 ], [ 2, 3, 4 ] ], [ [ 1, 2 ], [ 3, 4 ] ], [ [ 1, 2, 3 ], [ 4 ] ], [ [ 1, 2, 4 ], [ 3 ] ], [ [ 1, 3 ], [ 2, 4 ] ], [ [ 1, 3, 4 ], [ 2 ] ], [ [ 1, 4 ], [ 2, 3 ] ] ] gap> NrPartitionsSet( [1..6] ); 203 gap> NrPartitionsSet( [1..10], 3 ); 9330

Note that `PartitionsSet`

does currently not support multisets and that
there is currently no ordered counterpart.

`Partitions( `

`n` )

`Partitions( `

`n`, `k` )

`NrPartitions( `

`n` )

`NrPartitions( `

`n`, `k` )

In the first form `Partitions`

returns the set of all (unordered)
partitions of the positive integer `n`. In the second form `Partitions`

returns the set of all (unordered) partitions of the positive integer `n`
into sums with `k` summands.

In the first form `NrPartitions`

returns the number of (unordered)
partitions of the positive integer `n`. In the second form
`NrPartitions`

returns the number of (unordered) partitions of the
positive integer `n` into sums with `k` summands.

An **unordered partition** is an unordered sum *n = p _{1}+p_{2} +..+ p_{k}* of
positive integers and is represented by the list

It is possible to associate with every partition of the integer `n` a
conjugacy class of permutations in the symmetric group on `n` points and
vice versa. Therefore *p(n) := NrPartitions(n)* is the number of
conjugacy classes of the symmetric group on `n` points.

Ramanujan found the identities *p(5i+4) = 0* mod 5, *p(7i+5) = 0* mod 7
and *p(11i+6) = 0* mod 11 and many other fascinating things about the
number of partitions.

Do not call `Partitions`

with an `n` much larger than 40, in which case
there are 37338 partitions, since the list will simply become too large.

gap> Partitions( 7 ); [ [ 1, 1, 1, 1, 1, 1, 1 ], [ 2, 1, 1, 1, 1, 1 ], [ 2, 2, 1, 1, 1 ], [ 2, 2, 2, 1 ], [ 3, 1, 1, 1, 1 ], [ 3, 2, 1, 1 ], [ 3, 2, 2 ], [ 3, 3, 1 ], [ 4, 1, 1, 1 ], [ 4, 2, 1 ], [ 4, 3 ], [ 5, 1, 1 ], [ 5, 2 ], [ 6, 1 ], [ 7 ] ] gap> Partitions( 8, 3 ); [ [ 3, 3, 2 ], [ 4, 2, 2 ], [ 4, 3, 1 ], [ 5, 2, 1 ], [ 6, 1, 1 ] ] gap> NrPartitions( 7 ); 15 gap> NrPartitions( 100 ); 190569292

The function `OrderedPartitions`

(see OrderedPartitions) is the ordered
counterpart of `Partitions`

.

`OrderedPartitions( `

`n` )

`OrderedPartitions( `

`n`, `k` )

`NrOrderedPartitions( `

`n` )

`NrOrderedPartitions( `

`n`, `k` )

In the first form `OrderedPartitions`

returns the set of all ordered
partitions of the positive integer `n`. In the second form
`OrderedPartitions`

returns the set of all ordered partitions of the
positive integer `n` into sums with `k` summands.

In the first form `NrOrderedPartitions`

returns the number of ordered
partitions of the positive integer `n`. In the second form
`NrOrderedPartitions`

returns the number of ordered partitions of the
positive integer `n` into sums with `k` summands.

An **ordered partition** is an ordered sum *n = p _{1} + p_{2} + .. + p_{k}* of
positive integers and is represented by the list

Do not call `OrderedPartitions`

with an `n` larger than 15, the list
will simply become too large.

gap> OrderedPartitions( 5 ); [ [ 1, 1, 1, 1, 1 ], [ 1, 1, 1, 2 ], [ 1, 1, 2, 1 ], [ 1, 1, 3 ], [ 1, 2, 1, 1 ], [ 1, 2, 2 ], [ 1, 3, 1 ], [ 1, 4 ], [ 2, 1, 1, 1 ], [ 2, 1, 2 ], [ 2, 2, 1 ], [ 2, 3 ], [ 3, 1, 1 ], [ 3, 2 ], [ 4, 1 ], [ 5 ] ] gap> OrderedPartitions( 6, 3 ); [ [ 1, 1, 4 ], [ 1, 2, 3 ], [ 1, 3, 2 ], [ 1, 4, 1 ], [ 2, 1, 3 ], [ 2, 2, 2 ], [ 2, 3, 1 ], [ 3, 1, 2 ], [ 3, 2, 1 ], [ 4, 1, 1 ] ] gap> NrOrderedPartitions(20); 524288

The function `Partitions`

(see Partitions) is the unordered counterpart
of `OrderedPartitions`

.

`RestrictedPartitions( `

`n`, `set` )

`RestrictedPartitions( `

`n`, `set`, `k` )

`NrRestrictedPartitions( `

`n`, `set` )

`NrRestrictedPartitions( `

`n`, `set`, `k` )

In the first form `RestrictedPartitions`

returns the set of all
restricted partitions of the positive integer `n` with the summands of
the partition coming from the set `set`. In the second form
`RestrictedPartitions`

returns the set of all partitions of the positive
integer `n` into sums with `k` summands with the summands of the
partition coming from the set `set`.

In the first form `NrRestrictedPartitions`

returns the number of
restricted partitions of the positive integer `n` with the summands
coming from the set `set`. In the second form `NrRestrictedPartitions`

returns the number of restricted partitions of the positive integer `n`
into sums with `k` summands with the summands of the partition coming
from the set `set`.

A **restricted partition** is like an ordinary partition (see Partitions)
an unordered sum *n = p _{1}+p_{2} +..+ p_{k}* of positive integers and is
represented by the list

`[1..n]`

.

gap> RestrictedPartitions( 8, [1,3,5,7] ); [ [ 1, 1, 1, 1, 1, 1, 1, 1 ], [ 3, 1, 1, 1, 1, 1 ], [ 3, 3, 1, 1 ], [ 5, 1, 1, 1 ], [ 5, 3 ], [ 7, 1 ] ] gap> NrRestrictedPartitions( 50, [1,5,10,25,50] ); 50

The last example tells us that there are 50 ways to return 50 cent change using 1, 5, 10 cent coins, quarters and halfdollars.

`SignPartition( `

`pi` )

returns the sign of a permutation with cycle structure `pi`.

gap> SignPartition([6,5,4,3,2,1]); -1

This function actually describes a homomorphism of the symmetric group
*S _{n}* into the cyclic group of order 2, whose kernel is exactly the
alternating group

`AssociatedPartition( `

`pi` )

returns the associated partition of the partition `pi`.

gap> AssociatedPartition([4,2,1]); [ 3, 2, 1, 1 ] gap> AssociatedPartition([6]); [ 1, 1, 1, 1, 1, 1 ]

The **associated partition** of a partition `pi` is defined to be the
partition belonging to the transposed of the Young diagram of `pi`.

`BetaSet( `

`p` )

Here `p` is a partition (a non-increasing list of positive integers).
`BetaSet`

returns the corresponding nomalized Beta set.

gap> BetaSet([3,3,1]); [ 1, 4, 5 ]

A beta-set is a set of positive integers, up to the **shift** equivalence
relation. This equivalence relation is the transitive closure of the
elementary equivalence of *[s _{1},...,s_{n}]* and

`Dominates(`

` μ`,

The dominance ordering is an important partial order in representation
theory. `Dominates(`

returns ` μ`,

`true`

if either
`false`

otherwise.

gap> Dominates([5,4],[4,4,1]); true

`PowerPartition( `

`pi`, `k` )

returns the partition corresponding to the `k`-th power of a permutation
with cycle structure `pi`.

gap> PowerPartition([6,5,4,3,2,1], 3); [ 5, 4, 2, 2, 2, 2, 1, 1, 1, 1 ]

Each part *l* of `pi` is replaced by *d = *gcd*(l, k)* parts *l/d*. So if
`pi` is a partition of *n* then *<pi> ^{k}* also is a partition of

`PowerPartition`

describes the powermap of symmetric groups.
`PartitionTuples( `

`n`, `r` )

`NrPartitionTuples( `

`n`, `r` )

`PartitionTuples( `

returns the list of all `n`, `r` )`r`--tuples of
partitions that together partition `n`. `NrPartitionTuples`

just returns
their number.

gap> PartitionTuples(3, 2); [ [ [ 1, 1, 1 ], [ ] ], [ [ 1, 1 ], [ 1 ] ], [ [ 1 ], [ 1, 1 ] ], [ [ ], [ 1, 1, 1 ] ], [ [ 2, 1 ], [ ] ], [ [ 1 ], [ 2 ] ], [ [ 2 ], [ 1 ] ], [ [ ], [ 2, 1 ] ], [ [ 3 ], [ ] ], [ [ ], [ 3 ] ] ] gap> NrPartitionTuples(3,2); 10

`r`--tuples of partitions describe the classes and the characters of
wreath products of groups with `r` conjugacy classes with the symmetric
group *S _{n}*.

`Fibonacci( `

`n` )

`Fibonacci`

returns the `n`th number of the **Fibonacci sequence**. The
Fibonacci sequence *F _{n}* is defined by the initial conditions

Using generating functions one can prove that *F _{n} = φ^{n} - 1/φ^{n}*,
where

`Fibonnaci(``k`)

is the special case `Lucas(1,-1,``k`)[1]

(see Lucas).

gap> Fibonacci( 10 ); 55 gap> Fibonacci( 35 ); 9227465 gap> Fibonacci( -10 ); -55

`Lucas( `

`P`, `Q`, `k` )

`Lucas`

returns the `k`-th values of the **Lucas sequence** with parameters
`P` and `Q`, which must be integers, as a list of three integers.

Let *α, β* be the two roots of *x ^{2} - P x + Q* then we define

The following recurrence relations are easily derived from the definition

*U _{0} = 0, U_{1} = 1, U_{k} = P U_{k-1} - Q U_{k-2}* and

Those relations are actually used to define

`Lucas`

if
Also the more complex relations used in `Lucas`

can be easily derived

*U _{2k} = U_{k} V_{k}, U_{2k+1} = (P U_{2k} + V_{2k}) / 2* and

`Fibonnaci(`

(see Fibonacci) is simply `k`)`Lucas(1,-1,`

. In an
abuse of notation, the sequence `k`)[1]`Lucas(1,-1,`

is sometimes called
the Lucas sequence.
`k`)[2]

gap> List( [0..10], i->Lucas(1,-2,i)[1] ); [ 0, 1, 1, 3, 5, 11, 21, 43, 85, 171, 341 ] #2gap> List( [0..10], i->Lucas(1,-2,i)[2] ); [ 2, 1, 5, 7, 17, 31, 65, 127, 257, 511, 1025 ] #^{k}- (-1)^{k})/32gap> List( [0..10], i->Lucas(1,-1,i)[1] ); [ 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55 ] # Fibonacci sequence gap> List( [0..10], i->Lucas(2,1,i)[1] ); [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ] # the roots are equal^{k}+ (-1)^{k}

`Bernoulli( `

`n` )

`Bernoulli`

returns the `n`-th **Bernoulli number** *B _{n}*, which is defined
by

*B _{n}/n!* is the coefficient of

gap> Bernoulli( 4 ); -1/30 gap> Bernoulli( 10 ); 5/66 gap> Bernoulli( 12 ); -691/2730 # there is no simple pattern in Bernoulli numbers gap> Bernoulli( 50 ); 495057205241079648212477525/66 # and they grow fairly fast

`Permanent( `

`mat` )

`Permanent`

returns the **permanent** of the matrix `mat`. The permanent
is defined by *∑ _{p ∈ Symm(n)}{∏_{i=1}^{n}mat[i][i^{p}]}*.

Note the similarity of the definition of the permanent to the definition of the determinant. In fact the only difference is the missing sign of the permutation. However the permanent is quite unlike the determinant, for example it is not multilinear or alternating. It has however important combinatorical properties.

```
gap> Permanent( [[0,1,1,1],
> [1,0,1,1],
> [1,1,0,1],
> [1,1,1,0]] );
9 # inefficient way to compute
````NrDerangements([1..4])`

gap> Permanent( [[1,1,0,1,0,0,0],
> [0,1,1,0,1,0,0],
> [0,0,1,1,0,1,0],
> [0,0,0,1,1,0,1],
> [1,0,0,0,1,1,0],
> [0,1,0,0,0,1,1],
> [1,0,1,0,0,0,1]] );
24 # 24 permutations fit the projective plane of order 2

gap3-jm

11 Mar 2019