> ## Documentation Index
> Fetch the complete documentation index at: https://numpyts.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# API Reference Overview

> Complete API reference for numpy-ts -- 476 of 507 NumPy functions implemented in pure TypeScript.

# API Reference

numpy-ts implements **476 out of 507** NumPy functions (**93.9%** coverage) in pure TypeScript with zero dependencies. Every function is tested against NumPy for correctness.

## Coverage by category

| Category                                          | Functions | Status |
| ------------------------------------------------- | --------- | ------ |
| [NDArray Class & Methods](./ndarray/class)        | 47/47     | 100%   |
| [Array Creation](./creation/basic)                | 35/35     | 100%   |
| [Arithmetic](./math/arithmetic)                   | 29/29     | 100%   |
| [Exponential & Logarithmic](./math/exponential)   | 9/9       | 100%   |
| [Trigonometric](./math/trigonometric)             | 16/16     | 100%   |
| [Hyperbolic](./math/hyperbolic)                   | 9/9       | 100%   |
| [Rounding](./math/rounding)                       | 7/7       | 100%   |
| [Other Math](./math/other-math)                   | 15/15     | 100%   |
| [Array Manipulation](./manipulation/shape)        | 46/46     | 100%   |
| [Reductions](./reductions/basic)                  | 36/36     | 100%   |
| [Statistics](./reductions/statistics)             | 11/11     | 100%   |
| [Linear Algebra](./linalg/products)               | 38/38     | 100%   |
| [Logic & Comparison](./logic/comparison)          | 34/34     | 100%   |
| [Sorting & Searching](./sorting/sort)             | 13/13     | 100%   |
| [Set Operations](./sets/set-ops)                  | 12/12     | 100%   |
| [Bitwise](./bitwise/bitwise-ops)                  | 13/13     | 100%   |
| [Indexing](./indexing/advanced-indexing)          | 27/27     | 100%   |
| [Gradient & Differences](./gradient/gradient-ops) | 3/3       | 100%   |
| [Polynomials](./polynomials/polynomial-ops)       | 10/10     | 100%   |
| [Random](./random/overview)                       | 53/53     | 100%   |
| [FFT](./fft/transforms)                           | 18/18     | 100%   |
| [I/O](./io/npy-npz)                               | 8/8       | 100%   |
| [Utilities](./utilities/type-checking)            | 26/26     | 100%   |
| Unplanned                                         | 0/31      | --     |

## How to read this reference

Each function page follows a consistent format:

**Signature** -- The full TypeScript signature with generics and overloads where applicable.

```typescript theme={null}
function functionName(a: NDArray, axis?: number, keepdims?: boolean): NDArray | number;
```

**Parameter table** -- Every parameter listed with its type, default value, and description.

| Parameter  | Type      | Default     | Description                                                                     |
| ---------- | --------- | ----------- | ------------------------------------------------------------------------------- |
| `a`        | `NDArray` | --          | Input array.                                                                    |
| `axis`     | `number`  | `undefined` | Axis along which to operate. When `undefined`, operates on the flattened array. |
| `keepdims` | `boolean` | `false`     | If `true`, reduced axes are kept as dimensions with size 1.                     |

**Return type** -- What the function returns (scalar when reducing all axes, `NDArray` when reducing along a single axis).

**Example** -- A short, runnable code snippet demonstrating typical usage.

<Note>
  All type signatures use the `NDArray` class from the default `numpy-ts` entry point. If you use the tree-shakeable `numpy-ts/core` entry point, return types are `NDArrayCore` instead. The API is otherwise identical.
</Note>

## Intentionally unplanned features

The following NumPy features are **not implemented** by design (31 functions):

* **Datetime types** -- `datetime64` and `timedelta64` dtypes. Use native JavaScript `Date` or libraries like `date-fns` instead.
* **Fortran-order layout** -- `order='F'` parameter. All arrays use C-contiguous (row-major) layout.
* **Object dtype** -- `dtype=object`. JavaScript does not have an equivalent concept.
* **String dtypes** -- `dtype='U'` and `dtype='S'`. Use native JavaScript strings and typed arrays separately.

These exclusions keep the library focused on numeric computation where TypeScript can match or exceed NumPy's performance.

## Quick links

<CardGroup cols={2}>
  <Card title="NDArray Class" icon="cube" href="./ndarray/class">
    Properties, core methods, and the NDArray / NDArrayCore hierarchy.
  </Card>

  <Card title="NDArray Methods" icon="layer-group" href="./ndarray/methods">
    100+ chainable instance methods on NDArray (arithmetic, reductions, shape, linalg, and more).
  </Card>

  <Card title="Array Creation" icon="plus" href="./creation/basic">
    array, zeros, ones, arange, linspace, eye, and all \*\_like variants.
  </Card>

  <Card title="Linear Algebra" icon="square-root-variable" href="./linalg/products">
    linalg.inv, linalg.det, linalg.eig, linalg.svd, linalg.solve, and more.
  </Card>

  <Card title="Random" icon="dice" href="./random/overview">
    53 random number generation functions including distributions and sampling.
  </Card>

  <Card title="FFT" icon="wave-sine" href="./fft/transforms">
    Discrete Fourier transforms: fft, ifft, rfft, irfft, fft2, fftfreq, and more.
  </Card>
</CardGroup>