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https://github.com/StefanSalewski/minmaxheap

Heap with minimum and maximum access
https://github.com/StefanSalewski/minmaxheap

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Heap with minimum and maximum access

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= Heap with minimum and maximum access

(c) Stefan Salewski

:experimental:

:source-highlighter: pygments

:pygments-style: monokai

:icons: font



Nim implementation of a Minimum-Maximum Heap as described in



https://en.wikipedia.org/wiki/Min-max_heap



http://www.akira.ruc.dk/~keld/teaching/algoritmedesign_f03/Artikler/02/Atkinson86.pdf



NOTE: See also https://nim-lang.github.io/Nim/heapqueue.html



NOTE: Nim generated API documentation is available here: http://ssalewski.de/minmaxheap.html



The implementation follow very closely these papers, writing the Nim code

was straight forward. The heap is generic, this means it works for most data elements

when "<" relation is defined. Add(), popMin() and popMax() operations are O(log N), access

to min and max is O(1) according to Wikipedia. Build time of initial heap is linear O(N)

and read access to min or max element is O(1).



Use cases for such type of a heap are rare. One application is a ID-Number generator,

where IDs are generated in increasing order, but can be returned and reused. Reused is always the smallest

available ID, but at the same time we need to know which is the largest ID still in use. That can be

done with popMin() and max() operations. In the original paper external quicksort was mentioned as a use case.



Initial heap can be generated from an array or a seq. Pop() operations will fail when len()

is already zero.



The elements in heap are stored in a seq, so there is nearly no space overhead involved.



.Cost in big O notation as a function of number of elements (N)

[options="header"]

|===

| proc name | operation | costs |

|toMinMaxHeap() | creation  | O(N) |

|initMinMaxHeap() | create empty heap  | O(1) |

|min() | get minimum  | O(1) |

|max() | get maximum  | O(1) |

|clear() | reset  | O(1) |

|len() | get number of elements  | O(1) |

|add() | insert an element  | O(log(n)) |

|popMin() | delete minimum  | O(log(n)) |

|popMax() | delete maximum  | O(log(n)) |

|===



Install:



----

nimble install https://github.com/StefanSalewski/minmaxheap

----



Currently these procs are available:



[[API]]

[source,nim]

.API

----

type MinMaxHeap*[T] = distinct seq[T]



proc initMinMaxHeap*[T](): MinMaxHeap[T]



proc toMinMaxHeap*[T](h: openarray[T]): MinMaxHeap[T]



proc clear*[T](h: var MinMaxHeap[T])



proc len*[T](h: MinMaxHeap[T]): int



proc empty*[T](h: MinMaxHeap[T]): bool



proc add*[T](h: var MinMaxHeap[T]; i: T)



proc min*[T](h: var MinMaxHeap[T]): T



proc max*[T](h: var MinMaxHeap[T]): T



proc popMin*[T](h: var MinMaxHeap[T]): T



proc popMax*[T](h: var MinMaxHeap[T]): T



proc `$`*[T](h: MinMaxHeap[T]): string =

----



Here is an example how the heap can be used:



[[t.nim]]

[source,nim]

.t.nim

----

import minmaxheap



var

  # h = toMinMaxHeap[int](@[5, 3, 9, 1, 0])

  h = toMinMaxHeap([5, 3, 9, 1, 0])



echo $(h) # @[0, 5, 9, 1, 3]

echo h.min # 0

echo h.max # 9

echo h.len # 5

echo h.popMin # 0

echo h.popMax # 9

echo h.len # 3

echo h.min # 1

echo h.max # 5

h.add(8)

echo h.len # 4

echo h.popMax # 8

echo h.len # 3

h.clear

echo h.len # 0



type

  O = object

    key: float



# we need < operator defines for elements

proc `<`(a, b: O): bool =

  a.key < b.key



var

  l = initMinMaxHeap[O]()

l.add(O(key: 1.2))

l.add(O(key: 0.9))

l.add(O(key: 3.3))

echo l.popMax # (key: 3.3)

echo l.popMin # (key: 0.9)

----