"""Behavior contracts for the terminal Star Map renderer.

Asserts invariants of the timeline layout, the ported age gradient + palette, and
the constellation scrubber — never a cell snapshot, which would be a
change-detector against layout tuning.
"""

from __future__ import annotations

from agent import learning_graph_render as render

LEAD_IN = render.LEAD_IN


def _payload(skills: int = 8, memories: int = 3, *, base_ts: int = 1_700_000_000):
    nodes = []
    for i in range(skills):
        nodes.append(
            {
                "id": f"skill{i}",
                "label": f"skill{i}",
                "kind": "skill",
                "timestamp": base_ts + i * 86400 * 20,
                "category": "devops" if i % 2 else "research",
                "useCount": i,
            }
        )
    for j in range(memories):
        nodes.append(
            {
                "id": f"memory:memory:{j}",
                "label": f"mem {j}",
                "kind": "memory",
                "timestamp": base_ts + (skills + j) * 86400 * 20,
                "category": "memory",
            }
        )
    edges = [{"source": "skill0", "target": "skill1"}] if skills > 1 else []
    return {
        "nodes": nodes,
        "edges": edges,
        "clusters": [{"category": "devops", "count": skills}, {"category": "memory", "count": memories}],
        "stats": {
            "learned_skills": skills,
            "memory_nodes": memories,
            "related_edges": len(edges),
            "memory_skill_edges": 0,
        },
    }


def _flatten(grid):
    return "".join(run[0] for row in grid for run in row)


def _styles(grid):
    return {run[1] for row in grid for run in row}


def test_recency_is_timed_and_bounded():
    rec = render.compute_recency(_payload()["nodes"])
    assert rec["timed"] is True
    for ratio in rec["rec"].values():
        assert LEAD_IN - 1e-9 <= ratio <= 1 + 1e-9
    assert abs(min(rec["rec"].values()) - LEAD_IN) < 1e-9
    assert abs(max(rec["rec"].values()) - 1.0) < 1e-9


def test_recency_ink_follows_age_gradient():
    # Old quiet → recent bright (constants.ts AGE_GRADIENT), monotonic in between.
    assert abs(render.recency_ink(0.0) - render.AGE_OLD_INK) < 1e-6
    assert abs(render.recency_ink(1.0) - render.AGE_NEW_INK) < 1e-6
    samples = [render.recency_ink(x / 10) for x in range(11)]
    assert samples == sorted(samples)




def test_grid_runs_are_text_style_alpha():
    # Runs are [text, style, alpha] with an optional 4th hex override for
    # category-colored bars.
    frame = render.render_graph(_payload(), cols=60, rows=20)
    for row in frame["grid"]:
        for run in row:
            assert 3 <= len(run) <= 4
            assert isinstance(run[0], str) and isinstance(run[1], str)
            assert isinstance(run[2], (int, float)) and 0.0 <= run[2] <= 1.0
            assert run[0] != ""
            if len(run) == 4:
                assert run[3] is None or isinstance(run[3], str)


def test_bars_render_skills_and_memories():
    frame = render.render_graph(_payload(skills=10, memories=4), cols=72, rows=18, reveal=1.0)
    flat = _flatten(frame["grid"])
    # Skills draw as comet trails (━), memories anchor on diamonds (◆).
    assert "━" in flat
    assert render.MEMORY_GLYPH in flat
    styles = _styles(frame["grid"])
    assert render.STYLE_SKILL in styles
    assert render.STYLE_MEMORY in styles














def test_frames_play_through_grows_visibility():
    payload = _payload(skills=10, memories=4)
    out = render.render_frames(payload, cols=50, rows=16, frames=12)
    assert out["count"] == len(payload["nodes"])
    assert len(out["frames"]) == 12
    assert out["frames"][0]["visible"] <= out["frames"][-1]["visible"]
    assert out["frames"][-1]["visible"] == len(payload["nodes"])
    assert "axis" in out
    for fr in out["frames"]:
        assert fr["grid"]