# OpenBLAS Low-Rank Matrix Compression (SVD/PCA)

> OpenBLAS Low-Rank Matrix Compression (SVD/PCA) is a paid API for AI agents from stat.halowerk.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-29).

Factorizes a matrix into rank-k left and right singular vectors with singular values, optionally centering columns for PCA, and returns reconstruction error and spectral energy retained along with the full spectrum.

## Facts

- Endpoint: POST https://stat.halowerk.com/v1/oss-openblas-low-rank-matrix-compress?utm_source=zero.xyz
- Price: $0.002/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-29
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/openblas-low-rank-matrix-compression-svd-pca-2d8034a1
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_946C-Au28i49r3_mcmryN

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability openblas-low-rank-matrix-compression-svd-pca-2d8034a1 -d '<json body>'
```

Example prompt: Compress this 50×30 data matrix to rank 5 using low-rank SVD, and center the columns first so it's doing PCA — I want to see the reconstruction error, how much spectral energy is retained, and the full singular value spectrum so I can decide if rank 5 is good enough.

## When to prefer this

Choose this endpoint when you need truncated SVD or PCA on a matrix up to 128×128 and want reconstruction diagnostics (Frobenius error, spectral energy fraction) and the full spectrum in a single call, avoiding a second round-trip to pick a different rank. Prefer it over generic linear algebra libraries when you need a hosted, pay-per-call solution with no infrastructure overhead and OpenBLAS-backed numerical precision.

## Known failure modes

- rank k exceeds the smaller matrix dimension — returns an error
- matrix dimensions exceed 128×128 limit — returns validation error
- matrix contains values outside the allowed ±1,000,000 range — returns validation error
- matrix has inconsistent row lengths (ragged array) — returns parsing error
- payment not included or insufficient — returns 402 Payment Required

## How this service works

Factors a matrix into rank-k left and right factors with their singular values, optionally centering the columns first, and states what the compression actually cost: the Frobenius reconstruction error against the input and the fraction of spectral energy retained. The full spectrum comes back too, so a caller can pick a different k without a second call. With centering enabled this is principal component analysis, and the column means are returned as part of the model.

## Output

Returns left singular vectors (U), right singular vectors (V), and singular values for the requested rank k, plus the full singular value spectrum so the caller can re-evaluate without a second call. Also reports the Frobenius reconstruction error between the low-rank approximation and the original matrix, the fraction of total spectral energy retained, and (when center_columns is true) the column means used during centering.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "bodyType"
   ],
   "properties": {
    "type": {
     "const": "http"
    },
    "method": {
     "const": "POST"
    },
    "bodyType": {
     "const": "json"
    },
    "schemaUrl": {
     "type": "string",
     "format": "uri"
    },
    "exampleUrl": {
     "type": "string",
     "format": "uri"
    }
   },
   "additionalProperties": true
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "const": "json"
    },
    "schemaUrl": {
     "type": "string",
     "format": "uri"
    },
    "exampleUrl": {
     "type": "string",
     "format": "uri"
    }
   },
   "additionalProperties": true
  }
 },
 "additionalProperties": true
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/openblas-low-rank-matrix-compression-svd-pca-2d8034a1/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
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