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sort

Return a sorted copy of an array along the given axis. 
function sort(a: ArrayLike, axis?: number): NDArray
NameTypeDefaultDescription
aArrayLike—Input array.
axisnumber-1Axis along which to sort. Default is -1 (last axis). Use null to sort the flattened array.
kindstring'quicksort'Sorting algorithm. Accepted values: 'quicksort', 'mergesort', 'heapsort', 'stable'. 'stable' and 'mergesort' both use a stable sort.
Returns: NDArray — A sorted copy of the input array. 
import * as np from 'numpy-ts';

const a = np.array([3, 1, 4, 1, 5, 9]);
const sorted = np.sort(a);
// array([1, 1, 3, 4, 5, 9])

// Sort along axis 0 (columns)
const b = np.array([[3, 1], [2, 4]]);
np.sort(b, 0);
// array([[2, 1],
//        [3, 4]])

// Sort along axis 1 (rows) -- default
np.sort(b);
// array([[1, 3],
//        [2, 4]])

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argsort

Return the indices that would sort an array along the given axis. 
function argsort(a: ArrayLike, axis?: number): NDArray
NameTypeDefaultDescription
aArrayLike—Input array.
axisnumber-1Axis along which to sort.
kindstring'quicksort'Sorting algorithm ('quicksort', 'mergesort', 'heapsort', 'stable').
Returns: NDArray — Array of indices that sort the input along the given axis. 
import * as np from 'numpy-ts';

const a = np.array([30, 10, 40, 20]);
const indices = np.argsort(a);
// array([1, 3, 0, 2])

// Verify: reconstruct sorted array using the indices
// a[indices] -> [10, 20, 30, 40]

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lexsort

Perform an indirect stable sort using a sequence of keys. The last key is the primary sort key, the second-to-last is the secondary key, and so on. 
function lexsort(keys: ArrayLike[]): NDArray
NameTypeDefaultDescription
keysArrayLike[]—Sequence of arrays to sort by. The last array is the primary sort key. All arrays must have the same length.
Returns: NDArray — Array of indices that sort the data lexicographically. 
import * as np from 'numpy-ts';

// Sort by last name (primary), then first name (secondary)
const first = [1, 2, 1, 2];   // secondary key
const last  = [10, 10, 20, 20]; // primary key

const indices = np.lexsort([first, last]);
// array([0, 1, 2, 3])
// Sorted: (10,1), (10,2), (20,1), (20,2)

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partition

Rearrange elements such that the element at the kth position is where it would be in a fully sorted array. Elements before kth are all smaller, and elements after are all larger, but neither partition is necessarily sorted internally. 
function partition(a: ArrayLike, kth: number, axis?: number): NDArray
NameTypeDefaultDescription
aArrayLike—Input array.
kthnumber | number[]—Index or indices of elements to partition around.
axisnumber-1Axis along which to partition.
Returns: NDArray — A partitioned copy of the array. 
import * as np from 'numpy-ts';

const a = np.array([3, 1, 4, 1, 5, 9, 2, 6]);
const p = np.partition(a, 3);
// The element at index 3 is the 4th smallest (2).
// Elements at indices 0-2 are <= 2, elements at indices 4-7 are >= 2.
console.log(p.item(3)); // 2

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argpartition

Return indices that would partition an array. The element at the kth index in the returned order is in its final sorted position. 
function argpartition(a: ArrayLike, kth: number, axis?: number): NDArray
NameTypeDefaultDescription
aArrayLike—Input array.
kthnumber | number[]—Index or indices to partition around.
axisnumber-1Axis along which to partition.
Returns: NDArray — Array of indices that partition the input. 
import * as np from 'numpy-ts';

const a = np.array([3, 1, 4, 1, 5]);
const indices = np.argpartition(a, 2);
// indices[2] points to the element that would be at position 2 in a sorted array

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sort_complex

Sort an array by real part first, then by imaginary part for ties. Always returns a complex-typed result. 
function sort_complex(a: ArrayLike): NDArray
NameTypeDefaultDescription
aArrayLike—Input array. If not complex, it is cast to complex first.
Returns: NDArray — Sorted complex array. 
import * as np from 'numpy-ts';

const a = np.array([3, 1, 2]);
const result = np.sort_complex(a);
// array([1+0j, 2+0j, 3+0j])

// For real inputs, behaves like sort but returns complex dtype