binary heap (priority queue) algorithms (ported from Python's heapq module)

A binary heap implementation in CoffeeScript/JavaScript. Ported from Python's heapq module.

This module can be used in either the browser or node.js.

for browser use, you may download the script and include it in you web page.

for node.js, you may install it via npm:

npm install heap

then require it:

var Heap = require('heap');

push and pop

var heap = ;heappush3;heappush1;heappush2;heappop; // 1

custom comparison function

var heap = return afoo - bfoo;;heappushfoo: 3;heappushfoo: 1;heappushfoo: 2;heappop; // {foo: 1}

find 3 largest/smallest items in an array

var array = 1 3 4 2 5;Heapnlargestarray 3; // [5, 4, 3] Heapnsmallestarray 3; // [1, 2, 3]

This module exposes only one object, namely the Heap class.

The constructor receives a comparison function as an optional parameter. If omitted, the heap is built as a min-heap, which means that the smallest element will be popped out first.

If the comparison function is supplied, the heap will be built according to the return value of the comparison function.

- if cmp(a, b) < 0, then item a will come prior to b
- if cmp(a, b) > 0, then item b will come prior to a

So, the comparison function has the following form:

if a is prior to b return -1; if b is prior to a return 1; return 0;

To compare numbers, simply:

return a - b;

**push(item)** (alias: **insert**)

Push item onto heap.

**pop()**

Pop the smallest item off the heap and return it.

**peek()** (alias: **top** / **front**)

Return the smallest item of the heap.

**replace(item)**

Pop and return the current smallest value, and add the new item.

This is more efficient than pop() followed by push(), and can be more appropriate when using a fixed size heap. Note that the value returned may be larger than item!

**pushpop(item)**

Fast version of a push followed by a pop.

**heapify()**

Rebuild the heap. This method may come handy when the priority of the internal data is being modified.

**updateItem(item)**

Update the position of the given item in the heap. This function should be called every time the item is being modified.

**empty()**

Determine whether the heap is empty.

**size()**

Get the number of elements stored in the heap.

**toArray()**

Return the array representation of the heap. (note: the array is a shallow copy of the heap's internal nodes)

**clone()** (alias: **copy**)

Return a clone of the heap. (note: the internal data is a shallow copy of the original one)

NOTE: All the static methods are designed to be applied on arrays.

**push(array, item, [cmp])**

Push item onto array, maintaining the heap invariant.

**pop(array, [cmp])**

Pop the smallest item off the array, maintaining the heap invariant.

**replace(array, item, [cmp])**

Pop and return the current smallest value, and add the new item.

This is more efficient than heappop() followed by heappush(), and can be more appropriate when using a fixed size heap. Note that the value returned may be larger than item!

**pushpop(array, item, [cmp])**

Fast version of a heappush followed by a heappop.

**heapify(array, [cmp])**

Build the heap.

**updateItem(array, item, [cmp])**

Update the position of the given item in the heap. This function should be called every time the item is being modified.

**nlargest(array, n, [cmp])**

Find the n largest elements in a dataset.

**nsmallest(array, n, [cmp])**

Find the n smallest elements in a dataset.

Ported by Xueqiao Xu <xueqiaoxu@gmail.com>

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