| """Recommended performance-sensitive interface: already-existing real ndarrays. |
| |
| This is an integration example, not a benchmark or a production certificate. |
| """ |
| from pathlib import Path |
| import sys |
| sys.path.insert(0, str(Path(__file__).resolve().parents[1])) |
| import numpy as np |
| from qzguard import PreparedBank |
|
|
| x = np.linspace(-1.0, 1.0, 4096, dtype=np.float64) |
| values = np.column_stack((x, x + 0.25, x - 0.5, 2*x)) |
| bank = PreparedBank(values - 0.01, values + 0.01, backend='filtered') |
| threshold = np.array([-0.2, 0.05, -0.7, -0.4], dtype=np.float64) |
| for step in range(3): |
| lower = np.ones(len(x), dtype=np.float64) |
| upper = lower * (1.1 + step * 0.05) |
| result = bank.evaluate(lower, upper, threshold, relation='>=') |
| assert result.all_guaranteed |
| print({'step': step, 'backend': result.backend, |
| 'guaranteed': result.guaranteed, 'modes': result.modes}) |
|
|
