Spec

Code-Snippets

curl "https://api.oanor.com/matrix-api/v1/meta" \
  -H "x-oanor-key: oanor_test_..."

await fetch("https://api.oanor.com/matrix-api/v1/meta", {
  headers: { "x-oanor-key": "oanor_test_..." }
});

$ch = curl_init("https://api.oanor.com/matrix-api/v1/meta");
curl_setopt($ch, CURLOPT_HTTPHEADER, ["x-oanor-key: oanor_test_..."]);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
$out = curl_exec($ch);

import requests
requests.get(
    "https://api.oanor.com/matrix-api/v1/meta",
    headers={"x-oanor-key": "oanor_test_..."}
)

Beispiel-Response

Echte Antwort dieses Endpoints, erfasst beim letzten Health-Check.

{
    "data": {
        "name": "Matrix API",
        "notes": "Matrices up to 60x60. Singular matrices return invertible=false / no unique solution rather than erroring. Nothing is stored.",
        "version": "v1",
        "endpoints": [
            {
                "path": "/v1/multiply",
                "params": {
                    "a": "matrix [[…]]",
                    "b": "matrix [[…]]"
                },
                "returns": "the matrix product and its dimensions"
            },
            {
                "path": "/v1/analyze",
                "params": {
                    "matrix": "matrix [[…]]"
                },
                "returns": "transpose, rank, and (square) determinant, trace, symmetry, inverse"
            },
            {
                "path": "/v1/solve",
                "params": {
                    "a": "square coefficient matrix [[…]]",
                    "b": "right-hand side vector […]"
                },
                "returns": "the solution vector x of Ax=b"
            },
            {
                "path": "/v1/meta",
                "params": [],
                "returns": "this document"
            }
        ],
        "description": "Linear algebra as an API: multiply matrices, analyse a matrix, and solve linear systems — all computed locally and exactly. The multiply endpoint returns the product A×B (checking that the inner dimensions match). The analyze endpoint takes any matrix and returns its transpose and rank, and for square matrices also the determinant, trace, whether it is symmetric and invertible, and the inverse when it exists — using LU decomposition with partial pivoting and Gauss-Jordan elimination for numerical stability. The solve endpoint solves a system Ax = b for a square coefficient matrix by Gaussian elimination with partial pivoting, reporting cleanly when the matrix is singular and has no unique solution. Matrices are passed as JSON arrays of rows, e.g. [[1,2],[3,4]]. Everything is deterministic and instant. Ideal for data science and machine-learning prep, computer graphics and transforms, engineering and physics, computer-vision calibration, and teaching linear algebra. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 4 endpoints. This is matrix and linear-algebra maths; for 3D rotations use a quaternion API, for vectors use a vector API, and for statistics use a stats API."
    },
    "meta": {
        "timestamp": "2026-06-03T17:42:15.736Z",
        "request_id": "d2c991cc-c22d-40c4-9b06-e1dd21ba55cf"
    },
    "status": "ok",
    "message": "Meta",
    "success": true
}