local heap = require'heap'
Priority queues implemented as binary heaps. A binary heap is a binary tree that maintains the lowest (or highest) value at the root. The tree is laid as an implicit data structure over an array. Pushing and popping values from the heap is O(log n). Removal is O(n) by default unless a key is reserved on the elements (assuming they’re indexable) to store the element index which makes removal O(log n) too.
API
heap.heap(...) > push, pop 
create a heap API from a stack API 
heap.cdataheap(h) > h 
create a fixedcapacity cdatabased heap 
heap.valueheap([h]) > h 
create a heap for Lua values 
h:push(val) > i 
push a value 
h:pop([i][, dst]) > val 
pop value (root value at default index 1) 
h:replace(i, val) 
replace value at index 
h:peek([i][, dst]) > val 
get value without popping it 
h:find(v) > i 
find value and return its index 
h:remove(v) > truefalse 
find value and remove it 
h:length() > n 
number of elements in heap 
API Notes:
 values that compare equally are popped in random order.
heap.heap(push, pop, swap, len, cmp) > push, pop, rebalance
Create a heap API:
push(v) > i drop a value into the heap and return its index
pop(i) remove the value at index i (root is at index 1)
rebalance(i) rebalance the heap after the value at i has been changed
from a stack API:
push(v) add a value to the top of the stack
pop() remove the value at the top of the stack
swap(i, j) swap two values (indices start at 1)
len() > n number of elements in stack
cmp(i, j) > bool compare elements
The heap can be a minheap or maxheap depending on the comparison function. If cmp(i, j) returns a[i] < a[j] then it’s a minheap. Stack indices are assumed to be consecutive.
heap.cdataheap(h) > h
Create a cdata heap over table h
which must contain:
ctype
: element type (required).
min_capacity
: heap starting capacity (optional, defaults to 0).
cmp
: a comparison function (optional).
index_key
: enables O(1) h:find(v)
and thus O(log n) h:remove(v)
at the price of setting e[index_key]
on all elements of the heap, otherwise h:find(v)
is O(n) and h:remove(v)
is O(n).
dynarray
: alternative glue.dynarray
implementation (optional).
Note: cdata
heaps are 1indexed just like value heaps.
Example:
local h = heap.cdataheap{
ctype = [[
struct {
int priority;
int order;
}
]],
cmp = function(a, b)
if a.priority == b.priority then
return a.order > b.order
end
return a.priority < b.priority
end}
h:push{priority = 20, order = 1}
h:push{priority = 10, order = 2}
h:push{priority = 10, order = 3}
h:push{priority = 20, order = 4}
assert(h:pop().order == 3)
assert(h:pop().order == 2)
assert(h:pop().order == 4)
assert(h:pop().order == 1)
Note: the order
field in this example is used to stabilize the order in which elements with the same priority are popped.
heap.valueheap([h]) > h
Create a value heap from table h
, which can contain:
cmp
: a comparison function (optional).
index_key
: enables O(1) h:find(v)
and thus O(log n) h:remove(v)
at the price of setting e[index_key]
on all elements of the heap, otherwise h:find(v)
is O(n) and h:remove(v)
is O(n).
 a preallocated heap in the array part of the table (optional).
Note: trying to push nil
into a value heap raises an error.
Example:
local h = heap.valueheap{cmp = function(a, b)
return a.priority < b.priority
end}
h:push{priority = 20, etc = 'bar'}
h:push{priority = 10, etc = 'foo'}
assert(h:pop().priority == 10)
assert(h:pop().priority == 20)
TODO
 heapifying the initial array
 merge(h), meld(h)
Last updated:
2 years ago

Edit on GitHub