gb_sets(3)

NAME
gb_sets - General Balanced Trees

DESCRIPTION

An implementation of ordered sets using Prof. Arne Andersson's General Balanced Trees. This can be much more efficient than using ordered lists, for larger sets, but depends on the application.

This module considers two elements as different if and only if they do not compare equal ( == ).

COMPLEXITY NOTE

The complexity on set operations is bounded by either O(|S|) or O(|T| * log(|S|)), where S is the largest given set, depending on which is fastest for any particular function call. For operating on sets of almost equal size, this implementation is about 3 times slower than using ordered-list sets directly. For sets of very different sizes, however, this solution can be arbitrarily much faster; in practical cases, often between 10 and 100 times. This implementation is particularly suited for accumulating elements a few at a time, building up a large set (more than 100-200 elements), and repeatedly testing for membership in the current set.

As with normal tree structures, lookup (membership testing), insertion and deletion have logarithmic complexity.

COMPATIBILITY

All of the following functions in this module also exist and do the same thing in the sets and ordsets modules. That is, by only changing the module name for each call, you can try out different set representations.

    *   add_element/2

    *   del_element/2

    *   filter/2

    *   fold/3

    *   from_list/1

    *   intersection/1

    *   intersection/2

    *   is_element/2

    *   is_set/1

    *   is_subset/2

    *   new/0

    *   size/1

    *   subtract/2

    *   to_list/1

    *   union/1

    *   union/2

DATA TYPES

gb_set() = a GB set

EXPORTS

add(Element, Set1) -> Set2
add_element(Element, Set1) -> Set2

    Types
        Element = term()
        Set1 = Set2 = gb_set()

    Returns a new gb_set formed from Set1 with Element inserted. If Element is already an element in Set1 , nothing is changed.

balance(Set1) -> Set2

    Types
        Set1 = Set2 = gb_set()

    Rebalances the tree representation of Set1 . Note that this is rarely necessary, but may be motivated when a large number of elements have been deleted from the tree without further insertions. Rebalancing could then be forced in order to minimise lookup times, since deletion only does not rebalance the tree.

delete(Element, Set1) -> Set2

    Types
        Element = term()
        Set1 = Set2 = gb_set()

    Returns a new gb_set formed from Set1 with Element removed. Assumes that Element is present in Set1 .

delete_any(Element, Set1) -> Set2
del_element(Element, Set1) -> Set2

    Types
        Element = term()
        Set1 = Set2 = gb_set()

    Returns a new gb_set formed from Set1 with Element removed. If Element is not an element in Set1 , nothing is changed.

difference(Set1, Set2) -> Set3
subtract(Set1, Set2) -> Set3

    Types
        Set1 = Set2 = Set3 = gb_set()

    Returns only the elements of Set1 which are not also elements of Set2 .

empty() -> Set
new() -> Set

    Types
        Set = gb_set()

    Returns a new empty gb_set.

filter(Pred, Set1) -> Set2

    Types
        Pred = fun (E) -> bool()
        E = term()
        Set1 = Set2 = gb_set()

    Filters elements in Set1 using predicate function Pred .

fold(Function, Acc0, Set) -> Acc1

    Types
        Function = fun (E, AccIn) -> AccOut
        Acc0 = Acc1 = AccIn = AccOut = term()
        E = term()
        Set = gb_set()

    Folds Function over every element in Set returning the final value of the accumulator.

from_list(List) -> Set

    Types
        List = [term()]
        Set = gb_set()

    Returns a gb_set of the elements in List , where List may be unordered and contain duplicates.

from_ordset(List) -> Set

    Types
        List = [term()]
        Set = gb_set()

    Turns an ordered-set list List into a gb_set. The list must not contain duplicates.

insert(Element, Set1) -> Set2

    Types
        Element = term()
        Set1 = Set2 = gb_set()

    Returns a new gb_set formed from Set1 with Element inserted. Assumes that Element is not present in Set1 .

intersection(Set1, Set2) -> Set3

    Types
        Set1 = Set2 = Set3 = gb_set()

    Returns the intersection of Set1 and Set2 .

intersection(SetList) -> Set

    Types
        SetList = [gb_set()]
        Set = gb_set()

    Returns the intersection of the non-empty list of gb_sets.

is_disjoint(Set1, Set2) -> bool()

    Types
        Set1 = Set2 = gb_set()

    Returns true if Set1 and Set2 are disjoint (have no elements in common), and false otherwise.

is_empty(Set) -> bool()

    Types
        Set = gb_set()

    Returns true if Set is an empty set, and false otherwise.

is_member(Element, Set) -> bool()
is_element(Element, Set) -> bool()

    Types
        Element = term()
        Set = gb_set()

    Returns true if Element is an element of Set , otherwise false .

is_set(Term) -> bool()

    Types
        Term = term()

    Returns true if Set appears to be a gb_set, otherwise false .

is_subset(Set1, Set2) -> bool()

    Types
        Set1 = Set2 = gb_set()

    Returns true when every element of Set1 is also a member of Set2 , otherwise false .

iterator(Set) -> Iter

    Types
        Set = gb_set()
        Iter = term()

    Returns an iterator that can be used for traversing the entries of Set ; see next/1 . The implementation of this is very efficient; traversing the whole set using next/1 is only slightly slower than getting the list of all elements using to_list/1 and traversing that. The main advantage of the iterator approach is that it does not require the complete list of all elements to be built in memory at one time.

largest(Set) -> term()

    Types
        Set = gb_set()

    Returns the largest element in Set . Assumes that Set is nonempty.

next(Iter1) -> {Element, Iter2} | none

    Types
        Iter1 = Iter2 = Element = term()

    Returns {Element, Iter2} where Element is the smallest element referred to by the iterator Iter1 , and Iter2 is the new iterator to be used for traversing the remaining elements, or the atom none if no elements remain.

singleton(Element) -> gb_set()

    Types
        Element = term()

    Returns a gb_set containing only the element Element .

size(Set) -> int()

    Types
        Set = gb_set()

    Returns the number of elements in Set .

smallest(Set) -> term()

    Types
        Set = gb_set()

    Returns the smallest element in Set . Assumes that Set is nonempty.

take_largest(Set1) -> {Element, Set2}

    Types
        Set1 = Set2 = gb_set()
        Element = term()

    Returns {Element, Set2} , where Element is the largest element in Set1 , and Set2 is this set with Element deleted. Assumes that Set1 is nonempty.

take_smallest(Set1) -> {Element, Set2}

    Types
        Set1 = Set2 = gb_set()
        Element = term()

    Returns {Element, Set2} , where Element is the smallest element in Set1 , and Set2 is this set with Element deleted. Assumes that Set1 is nonempty.

to_list(Set) -> List

    Types
        Set = gb_set()
        List = [term()]

    Returns the elements of Set as a list.

union(Set1, Set2) -> Set3

    Types
        Set1 = Set2 = Set3 = gb_set()

    Returns the merged (union) gb_set of Set1 and Set2 .

union(SetList) -> Set

    Types
        SetList = [gb_set()]
        Set = gb_set()

    Returns the merged (union) gb_set of the list of gb_sets.

SEE ALSO

gb_trees(3) , ordsets(3) , sets(3)