# numpy.linalg.LinAlgError: Matrix is not positive definite

- **ID:** `python/scipy-linalg-singular`
- **Domain:** python
- **Category:** runtime_error
- **Verification:** ai_generated
- **Fix Rate:** 80%

## Root Cause

Cholesky decomposition (np.linalg.cholesky / scipy.linalg.cholesky) requires a symmetric positive-definite matrix. Numerical noise, non-symmetric input, or a truly indefinite matrix breaks this.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| 3.x | active | — | — |

## Workarounds

1. **** (90% success)
   ```
   A = (A + A.T) / 2; A += 1e-8 * np.eye(A.shape[0]); L = np.linalg.cholesky(A)
   ```
2. **** (85% success)
   ```
   Use scipy.linalg.ldl(A) or np.linalg.eigh(A) for indefinite matrices
   ```

## Dead Ends

- **** — Regularization too small for ill-conditioned matrices (70% fail)
- **** — Triangular part isn't symmetric (90% fail)