from __future__ import annotations


def test_node_preservation(bundle, weighted_graph):
    assert set(weighted_graph.nodes) == set(bundle.graph.nodes)


def test_edge_preservation(bundle, weighted_graph):
    assert weighted_graph.number_of_edges() == bundle.graph.number_of_edges()


def test_weight_range(weighted_graph):
    weights = [d["w"] for _, _, d in weighted_graph.edges(data=True)]
    assert weights, "가중치가 부여된 엣지가 없습니다"
    assert all(0.0 < w <= 1.0 for w in weights)


def test_large_consumer_edges_suppressed(bundle, weighted_graph, baseline, cfg):
    from blocksys.graph import build_weighted_graph

    large_nodes = [n for n, d in weighted_graph.nodes(data=True) if d.get("is_large_consumer")]
    if not large_nodes:
        return  # Net3 기본 설정(5 L/s)에는 대수용가가 없을 수 있음

    plain = build_weighted_graph(bundle.graph, baseline, cfg)
    # 대수용가 인접 엣지는 제약 반영 전보다 가중치가 낮아야 한다(isolate 기본 정책)
    for n in large_nodes:
        for u, v, d in weighted_graph.edges(n, data=True):
            assert d["w"] <= plain[u][v]["w"]


def test_reproducibility(bundle, baseline, cfg):
    from blocksys.graph import apply_hard_constraints, build_weighted_graph

    g1 = apply_hard_constraints(build_weighted_graph(bundle.graph, baseline, cfg), cfg)
    g2 = apply_hard_constraints(build_weighted_graph(bundle.graph, baseline, cfg), cfg)

    for u, v, d in g1.edges(data=True):
        assert g2[u][v]["w"] == d["w"]