File size: 1,946 Bytes
b39dfd0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | """Unit tests for high-accuracy sampling verification."""
import json
import importlib.util
from pathlib import Path
import pytest
import sys
sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
from sampler import (
verify_polylog_step_scaling,
verify_intrinsic_dimension_scaling,
verify_log_concave_gradient_sampler,
)
def test_polylog_step_scaling():
res = verify_polylog_step_scaling([1e-2, 1e-4, 1e-6])
assert res["verified"] is True
assert res["polylog_exponent_estimate"] < 3.0
assert len(res["step_data"]) == 3
def test_intrinsic_dimension_scaling():
res = verify_intrinsic_dimension_scaling(d_star=5, full_d=500, delta=1e-3)
assert res["verified"] is True
assert pytest.approx(res["theoretical_speedup"]) == 100.0
def test_log_concave_gradient_sampler():
res = verify_log_concave_gradient_sampler(dimension=3, target_accuracy=1e-2)
assert res["verified"] is True
assert res["empirical_mean_error"] < 0.3
assert res["empirical_cov_error"] < 0.4
def test_evidence_bundle():
bundle_path = Path(__file__).parent.parent / "evidence" / "bundle.json"
if bundle_path.exists():
data = json.loads(bundle_path.read_text())
assert data["paper_id"] == "71132"
assert len(data["claims"]) == 3
def test_evidence_generation_is_stable(tmp_path, monkeypatch):
generator_path = Path(__file__).parent.parent / "generate_evidence.py"
spec = importlib.util.spec_from_file_location("high_accuracy_generate_evidence", generator_path)
module = importlib.util.module_from_spec(spec)
assert spec.loader is not None
spec.loader.exec_module(module)
monkeypatch.setattr(sys, "argv", ["generate_evidence.py", "--output-dir", str(tmp_path)])
module.main()
first = json.loads((tmp_path / "bundle.json").read_text())
module.main()
second = json.loads((tmp_path / "bundle.json").read_text())
assert second == first
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