This chapter contains a number of functions that did not fit in anywhere else. Some of them might be useful for other people, too, so they were included here.

`OnSubgroups( `

`, `

` ) F`

For a group `G` and an automorphism `aut` of `G`,
`OnSubgroups(`

`subgroup``,`

`aut``)`

is the image of `subgroup` under `aut`

gap> G:=Group((1,2,3),(2,3)); Group([ (1,2,3), (2,3) ]) gap> alpha:=InnerAutomorphism(G,(1,2,3)); ^(1,2,3) gap> OnSubgroups(Subgroup(G,[(2,3)]),alpha); Group([ (1,3) ])

`RepsCClassesGivenOrder( `

`, `

` ) O`

`RepsCClassesGivenOrder( `

`group``, `

`order`` )`

returns all elements of
order `order` up to conjugacy. Note that the representatives are **not**
always the smallest elements of each conjugacy class.

gap> RepsCClassesGivenOrder(SymmetricGroup(5),2); [ (4,5), (2,3)(4,5) ]

`CartesianIterator( `

` ) O`

Returns an iterator for `Cartesian(`

`tuplelist``)`

`ConcatenationOfIterators( `

` ) F`

`ConcatenationOfIterators(`

`iterlist``)`

returns an iterator which runs
through all iterators in `iterlist`. Note that the returned iterator loops
over the iterators in `iterlist` **sequentially** beginning with the first
one.

gap> it:=Iterator([1,2,3]);; gap> it2:=CartesianIterator([[9,10],[11]]);; gap> cit:=ConcatenationOfIterators([it,it2]);; gap> repeat > Print(NextIterator(cit),",\c"); > until IsDoneIterator(cit); 1,2,3,[ 9, 11 ],[ 10, 11 ],

`IsListOfIntegers( `

` ) P`

`IsListOfIntegers( `

`list`` )`

returns `IsSubset(Integers, `

`list`` )`

if `list`
is a dense list and `false`

otherwise.

`List2Tuples( `

`, `

` ) O`

If `Size( `

`list`` )`

is divisible by `int`, `List2Tuples( `

`list``,`

`int``)`

returns a list `list2` of size `int` such that
`Concatenation( `

`list2`` )= `

`list`` and every element of `

`list2` has the
same size.

gap> List2Tuples([1..6],2); [ [ 1, 2, 3 ], [ 4, 5, 6 ] ]

`MatTimesTransMat( `

` ) O`

does the same as `mat``*TransposedMat( `

`mat`` )`

but uses slightly less
space and time for large matrices.

`PartitionByFunctionNF( `

`, `

` ) O`

`PartitionByFunctionNF( `

`list``, `

`f`` )`

partitions the list `list`
according to the values of the function `f` defined on `list`.
If `f` returns `fail`

for some element of `list`,
`PartitionByFunctionNF( `

`list``, `

`f`` )`

enters a break loop.
Leaving the break loop with 'return;' is safe because
`PartitionByFunctionNF`

treats `fail`

as all other results of `f`.

`PartitionByFunction( `

`, `

` ) O`

`PartitionByFunction( `

`list``, `

`f`` )`

partitions the list `list`
according to the values of the function `f` defined on `list`.
All elements, for which `f` returns `fail`

are omitted, so
`PartitionByFunction`

does not necessarily return a partition.
If `InfoLevel(InfoRDS)`

indexInfoRDS@ttInfoRDS is at least 2, the number of
elements for which `f` returns `fail`

is shown
(if `fail`

is returned at all).

gap> PartitionByFunctionNF([-1..5],x->x^2); [ [ 0 ], [ -1, 1 ], [ 2 ], [ 3 ], [ 4 ], [ 5 ] ] gap> test:=function(x) > if x>0 then return Sqrt(x); > else return fail; > fi; > end; function( x ) ... end gap> PartitionByFunction([-1..5],test); [ [ 1 ], [ 4 ], [ 5 ], [ 2 ], [ 3 ] ] gap> SetInfoLevel(InfoRDS,2); gap> PartitionByFunction([-1..5],test); #I -2- [ [ 1 ], [ 4 ], [ 5 ], [ 2 ], [ 3 ] ] gap> PartitionByFunctionNF([-1..5],test); Error, function returned <fail> called from ... brk> return; [ [ 1 ], [ 4 ], [ 5 ], [ 2 ], [ 3 ], [ -1, 0 ] ]

`IsRootOfUnity( `

` ) P`

`IsRootOfUnity`

tests if a given cyclotomic is actually a root of unity.

`CoeffList2CyclotomicList( `

`, `

` ) O`

`CoeffList2CyclogomicList( `

`list``, `

`root`` )`

takes a list of integers
`list` and a root of unity `root` and returns a list `list2`, where
`list2[i]=list[i]* root^(i-1)`.

`AbssquareInCyclotomics( `

`, `

` ) O`

For a list of integers and a root of unity,
`AbssquareInCyclotomics( `

`list``, `

`root`` )`

returns
the modulus of `Sum(CoeffList2CyclotomicList( `

`list``, `

`root`` ))`

.

`CycsGivenCoeffSum( `

`, `

` ) O`

`CycsGivenCoeffSum( `

`sum``, `

`root`` )`

returns all elements of `Z[ root ]`
such that the coefficient sum is `sum` and all coefficients are
non-negative.
The returned list has the following form:
The cyclotomic numbers are represented by coefficients.
CoeffList2CyclotomicList can be used to get the
algebraic number represented by `list`.
The list is partitioned into equivalence classes of elements having the
same modulus.
For each class the modulus is returned.
This means that `CycsGivenCoeffSum`

returns a list of pairs where the first
entry of each pair is the square of the modulus of an element of the
second entry. And the second entry is a list of coefficient lists of
cyclotomics in `Z[ root ]` having the coefficient sum

gap> CycsGivenCoeffSum(3,E(3)); [ [ 0, [ [ 1, 1, 1 ] ] ], [ 3, [ [ 0, 1, 2 ], [ 0, 2, 1 ], [ 1, 0, 2 ], [ 1, 2, 0 ], [ 2, 0, 1 ], [ 2, 1, 0 ] ] ], [ 9, [ [ 0, 0, 3 ], [ 0, 3, 0 ], [ 3, 0, 0 ] ] ] ] gap> CycsGivenCoeffSum(2,E(2)); [ [ 0, [ [ 1, 1 ] ] ], [ 4, [ [ 0, 2 ], [ 2, 0 ] ] ] ]

The following was originally posted at the GAP forum by Thomas Breuer BreuersAnswer.

Each filter in GAP is either a simple filter or a meet of filters.
For example, `IsInt`

and `IsPosRat`

are simple filters,
and `IsPosInt`

is defined as their meet `IsInt and IsPosRat`

.

Each **simple filter** is of one of the following kinds.

1. property:
Such a filter is an operation, the filter value can be computed.
The (unary) methods of this operation must return `true`

or `false`

,
and the return value is stored in the argument,
except if the argument is of a basic data type such as cyclotomic
(including rationals and integers), finite field element, permutation,
or internally represented list --the latter with a few exceptions.
Examples of properties are `IsFinite`

, `IsAbelian`

, `IsSSortedList`

.

2. attribute tester:
Such a filter is associated to an operation that has been created
via `DeclareAttribute`

,
in the sense that the value is `true`

if and only if a return value
for (a unary method of) this operation is stored in the argument.
Currently, attribute values are stored in objects in the filter
`IsAttributeStoringRep`

.
Examples of attribute testers are `HasSize`

, `HasCentre`

,
`HasDerivedSubgroup`

.

2.' property tester:
Such a filter is similar to an attribute tester,
but the associated operation is a property.
So property testers can return `true`

also if the argument is not in
the filter `IsAttributeStoringRep`

.
Examples of property testers are `HasIsFinite`

, `HasIsAbelian`

,
`HasIsSSortedList`

.

3. category or representation:
These filters are not associated to operations, their values cannot
be computed but are set upon creation of an object and should not be
changed later, such that for a filter of this kind, one can rely on
the fact that if the value is `true`

then it was `true`

already when
the object in question was created.

The distinction between representation and category is intended to
express dependency on or independence of the way how the object is
stored internally.
For example, `IsPositionalObjectRep`

, `IsComponentObjectRep`

, and
`IsInternalRep`

are filters of the representation kind;
the idea is that such filters are used in low level methods,
and that higher level methods can be implemented without referring
to these filters.

Examples of categories are `IsInt`

, `IsRat`

, `IsPerm`

, `IsFFE`

,
and filters expressing algebraic structures,
such as `IsMagma`

, `IsMagmaWithOne`

, `IsAdditiveMagma`

.
When one calls such a filter, one can be sure that no computation is
triggered.
For example, whenever a quotient of two integers is formed, the result
is clearly in the filter `IsRat`

, but the system also stores the value
of `IsInt`

, i.e., GAP does not support ``unevaluated rationals'' for
which the `IsInt`

value is computed on demand and then stored.

4. other filters:
Some filters do not belong to the above kinds,
they are not associated to operations but they are intended to be
set (or even reset) by the user or by functions also after the creation
of objects.
Examples are `IsQuickPositionList`

, `CanEasilyTestMembership`

,
`IsHandledByNiceBasis`

.

Each **meet of filters** can involve computable simple filters (properties,
attribute and property testers) and not computable simple filters
(categories, representations, other filters).
When one calls a meet of two filters then the two filters from which
the meet was formed are evaluated (if necessary).
So a meet of filters is computable only if at least one computable simple
filter is involved.

`IsComputableFilter( `

` ) F`

'IsComputableFilter(`filter`)' returns `true` if a the filter `filter`
is computable. Filters for which 'IsComputableFilter' returns `false`
may be used in 'DeclareOperation'.

gap> IsComputableFilter( IsFinite ); true gap> IsComputableFilter( HasSize ); true gap> IsComputableFilter( HasIsFinite ); true gap> IsComputableFilter( IsPositionalObjectRep ); false gap> IsComputableFilter( IsInt ); false gap> IsComputableFilter( IsQuickPositionList ); false gap> IsComputableFilter( IsInt and IsPosRat ); false gap> IsComputableFilter( IsMagma ); false

RDS manual

February 2012