| from __future__ import annotations |
|
|
| from collections import Counter, defaultdict |
|
|
| import numpy as np |
|
|
| from src.generate_t2_denim_capability_v4 import ( |
| FULL_3D_FAMILIES, |
| RESOLUTIONS, |
| design, |
| solve_row, |
| ) |
|
|
|
|
| def test_v4_design_counts_and_unique_ids(): |
| rows = design() |
| assert len(rows) == 1000 |
| assert len({row["case_id"] for row in rows}) == 1000 |
| assert Counter(row["cohort"] for row in rows) == { |
| "long_cycle": 300, |
| "full_3d_nonproportional": 300, |
| "structure_derived": 200, |
| "discretization_and_observation": 200, |
| } |
| assert Counter(row["path_family"] for row in rows if row["cohort"] == "full_3d_nonproportional") == { |
| family: 50 for family in FULL_3D_FAMILIES |
| } |
|
|
|
|
| def test_v4_resolution_groups_are_complete_and_isolated(): |
| rows = [row for row in design() if row["cohort"] == "discretization_and_observation"] |
| grouped = defaultdict(list) |
| for row in rows: |
| grouped[row["group_id"]].append(row) |
| assert len(grouped) == 50 |
| for values in grouped.values(): |
| assert tuple(sorted(row["points"] for row in values)) == RESOLUTIONS |
| assert len({row["split"] for row in values}) == 1 |
| assert len({row["path_seed"] for row in values}) == 1 |
| assert len({row["maximum_equivalent_strain"] for row in values}) == 1 |
|
|
|
|
| def test_v4_long_cycle_split_is_true_horizon_ood(): |
| rows = [row for row in design() if row["cohort"] == "long_cycle"] |
| assert {row["cycle_count"] for row in rows if row["split"] == "train_long_cycle"} == {10, 25} |
| assert {row["cycle_count"] for row in rows if row["split"] == "validation_long_cycle"} == {50} |
| assert {row["cycle_count"] for row in rows if row["split"] == "test_long_cycle_ood"} == {100} |
|
|
|
|
| def test_v4_material_point_smoke_without_structure_solver(): |
| rows = design() |
| selected = ( |
| next(row for row in rows if row["cohort"] == "long_cycle"), |
| next(row for row in rows if row["cohort"] == "full_3d_nonproportional"), |
| next(row for row in rows if row["cohort"] == "discretization_and_observation"), |
| ) |
| for row in selected: |
| arrays, metrics = solve_row(row, {}) |
| assert metrics["all_finite"] |
| assert metrics["minimum_peeq_increment"] >= -1.0e-12 |
| assert metrics["maximum_yield_surface_relative_residual"] < 1.0e-8 |
| assert arrays["strain"].shape == (row["points"], 6) |
| assert arrays["stress_pa"].shape == (row["points"], 6) |
| observed, _ = solve_row(selected[-1], {}) |
| assert observed["observation_mask"].dtype == np.uint8 |
| assert observed["observation_mask"][0] == 1 |
| assert observed["observation_mask"][-1] == 1 |
|
|
|
|
| def test_every_full_3d_family_is_symmetric_and_integrable(): |
| rows = [row for row in design() if row["cohort"] == "full_3d_nonproportional"] |
| for family in FULL_3D_FAMILIES: |
| row = next(value for value in rows if value["path_family"] == family) |
| arrays, metrics = solve_row(row, {}) |
| strain = arrays["strain"] |
| assert np.isfinite(strain).all() |
| assert metrics["all_finite"] |
| assert metrics["maximum_yield_surface_relative_residual"] < 1.0e-8 |
|
|
