20012010
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gb_sets
gb_sets
General Balanced Trees
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
add(Element, Set1) -> Set2
add_element(Element, Set1) -> Set2
Add a (possibly existing) element to a gb_set
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
Rebalance tree representation of a gb_set
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
Remove an element from a gb_set
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
Remove a (possibly non-existing) element from a gb_set
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
Return the difference of two gb_sets
Set1 = Set2 = Set3 = gb_set()
Returns only the elements of Set1 which are not also
elements of Set2.
empty() -> Set
new() -> Set
Return an empty gb_set
Set = gb_set()
Returns a new empty gb_set.
filter(Pred, Set1) -> Set2
Filter gb_set elements
Pred = fun (E) -> bool()
E = term()
Set1 = Set2 = gb_set()
Filters elements in Set1 using predicate function
Pred.
fold(Function, Acc0, Set) -> Acc1
Fold over gb_set elements
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
Convert a list into a gb_set
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
Make a gb_set from an ordset list
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
Add a new element to a gb_set
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
Return the intersection of two gb_sets
Set1 = Set2 = Set3 = gb_set()
Returns the intersection of Set1 and Set2.
intersection(SetList) -> Set
Return the intersection of a list of gb_sets
SetList = [gb_set()]
Set = gb_set()
Returns the intersection of the non-empty list of gb_sets.
is_disjoint(Set1, Set2) -> bool()
Check whether two gb_sets are disjoint
Set1 = Set2 = gb_set()
Returns true if Set1 and
Set2 are disjoint (have no elements in common),
and false otherwise.
is_empty(Set) -> bool()
Test for empty gb_set
Set = gb_set()
Returns true if Set is an empty set, and
false otherwise.
is_member(Element, Set) -> bool()
is_element(Element, Set) -> bool()
Test for membership of a gb_set
Element = term()
Set = gb_set()
Returns true if Element is an element of
Set, otherwise false.
is_set(Term) -> bool()
Test for a gb_set
Term = term()
Returns true if Set appears to be a gb_set,
otherwise false.
is_subset(Set1, Set2) -> bool()
Test for subset
Set1 = Set2 = gb_set()
Returns true when every element of Set1 is
also a member of Set2, otherwise false.
iterator(Set) -> Iter
Return an iterator for a gb_set
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()
Return largest element
Set = gb_set()
Returns the largest element in Set. Assumes that
Set is nonempty.
next(Iter1) -> {Element, Iter2} | none
Traverse a gb_set with an iterator
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()
Return a gb_set with one element
Element = term()
Returns a gb_set containing only the element Element.
size(Set) -> int()
Return the number of elements in a gb_set
Set = gb_set()
Returns the number of elements in Set.
smallest(Set) -> term()
Return smallest element
Set = gb_set()
Returns the smallest element in Set. Assumes that
Set is nonempty.
take_largest(Set1) -> {Element, Set2}
Extract largest element
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}
Extract smallest element
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
Convert a gb_set into a list
Set = gb_set()
List = [term()]
Returns the elements of Set as a list.
union(Set1, Set2) -> Set3
Return the union of two gb_sets
Set1 = Set2 = Set3 = gb_set()
Returns the merged (union) gb_set of Set1 and
Set2.
union(SetList) -> Set
Return the union of a list of gb_sets
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)