feat(profiler/behave_shell): emit cognitive.planning_depth
Distribution of inter-command IATs bucketed against IKI_THINK_MAX_S (deep) and INTER_CMD_INSTANT_MAX (reactive); fall-through is shallow. v0.1 thresholds; D.8 re-tunes.
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tests/profiler/behave_shell/test_cognitive_planning_depth.py
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61
tests/profiler/behave_shell/test_cognitive_planning_depth.py
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"""Step D.3: ``cognitive.planning_depth``."""
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from __future__ import annotations
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from decnet.profiler.behave_shell import extract_session
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from decnet.profiler.behave_shell._parse import AsciinemaEvent
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def _of(observations: list, primitive: str):
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obs = [o for o in observations if o.primitive == primitive]
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assert len(obs) == 1, f"expected exactly one {primitive}, got {len(obs)}"
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return obs[0]
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def _commands_at(starts: list[float]) -> list[AsciinemaEvent]:
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events: list[AsciinemaEvent] = []
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for s in starts:
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events.append((s, "i", "x\r"))
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return events
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def test_no_inter_cmd_iats_no_emission() -> None:
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out = list(extract_session(_commands_at([0.0]), sid="pd-empty"))
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assert [o for o in out if o.primitive == "cognitive.planning_depth"] == []
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def test_long_pauses_emit_deep() -> None:
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"""Most pauses > 1.5s → deep."""
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out = list(extract_session(
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_commands_at([0.0, 3.0, 6.0, 9.0, 12.0, 15.0, 18.0, 21.0]),
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sid="pd-deep",
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))
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obs = _of(out, "cognitive.planning_depth")
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assert obs.value == "deep"
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def test_sub_instant_pauses_emit_reactive() -> None:
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"""Most pauses ≤ INTER_CMD_INSTANT_MAX (0.30s) → reactive."""
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out = list(extract_session(
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_commands_at([i * 0.10 for i in range(8)]),
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sid="pd-react",
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))
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obs = _of(out, "cognitive.planning_depth")
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assert obs.value == "reactive"
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def test_typing_speed_pauses_emit_shallow() -> None:
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"""Pauses around 1s — neither deep nor reactive → shallow."""
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out = list(extract_session(
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_commands_at([i * 1.0 for i in range(8)]),
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sid="pd-shallow",
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))
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obs = _of(out, "cognitive.planning_depth")
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assert obs.value == "shallow"
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def test_low_sample_count_reduces_confidence() -> None:
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short = list(extract_session(_commands_at([0.0, 1.0, 2.0]), sid="pd-short"))
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full = list(extract_session(_commands_at([i * 1.0 for i in range(8)]), sid="pd-full"))
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s = _of(short, "cognitive.planning_depth")
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f = _of(full, "cognitive.planning_depth")
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assert s.confidence < f.confidence
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