Documentation Index
Fetch the complete documentation index at: https://numpyts.dev/llms.txt
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sort
Return a sorted copy of an array along the given axis.
function sort(a: ArrayLike, axis?: number): NDArray
| Name | Type | Default | Description |
|---|
a | ArrayLike | — | Input array. |
axis | number | -1 | Axis along which to sort. Default is -1 (last axis). Use null to sort the flattened array. |
kind | string | '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]])
argsort
Return the indices that would sort an array along the given axis.
function argsort(a: ArrayLike, axis?: number): NDArray
| Name | Type | Default | Description |
|---|
a | ArrayLike | — | Input array. |
axis | number | -1 | Axis along which to sort. |
kind | string | '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]
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
| Name | Type | Default | Description |
|---|
keys | ArrayLike[] | — | 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)
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
| Name | Type | Default | Description |
|---|
a | ArrayLike | — | Input array. |
kth | number | number[] | — | Index or indices of elements to partition around. |
axis | number | -1 | Axis 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
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
| Name | Type | Default | Description |
|---|
a | ArrayLike | — | Input array. |
kth | number | number[] | — | Index or indices to partition around. |
axis | number | -1 | Axis 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
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
| Name | Type | Default | Description |
|---|
a | ArrayLike | — | 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