Linear time selection algorithm for ndarrays
npm install ndarray-selectndarray-select
==============
Finds the kth element in an ndarray in linear time with high probability. This implementation is based on the quick select algorithm and mutates the array in place.
javascript
var pack = require("ndarray-pack")
var ndselect = require("ndarray-select")var points = pack([0, 0, 1, 2.5, -1])
//Find the median element in the list
var median = ndselect(points, points.shape[0]>>1)
console.log(median.get())
`#### Output
0 2.5 -1
$3
It is also possible to select vectors (using lexicographical comparisons):
javascript
var pack = require("ndarray-pack")
var ndselect = require("ndarray-select")var points = pack([
[0, 0, 1],
[100, 0, 10],
[50, 1, 10],
[0, 2.5, -1],
[-1, -1, -1]
])
//Find the median element in the list
var median = ndselect(points, points.shape[0]>>1)
console.log(median.get(0), median.get(1), median.get(2))
`#### Output
0 2.5 -1
Install
Install using npm: npm install ndarray-select
API
javascript
var ndselect = require("ndarray-select")
`####
Selects the kth item from the ndarray along the first axis of array.*
array is an ndarray
* k is the rank of the item which is being selected
* compare is an optional comparison function that gets a pair of ndarrays as input.Returns An ndarray view of
array.pick(k)Note This method modifies
. After completion, the element at position k will be in sorted order, with all elements and all elements >array.pick(k) after k in the list.####
ndselect.compile(order, useCompare, dtype)
Precompiles an optimized selection algorithm for an array with the given index order and datatype.*
is the order of the ndarray
* useCompare is a flag which if set uses a comparison function
* dtype is the datatype of the arrayReturns An optimized
ndselect` function