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