anti
f2b3393669
Replaces LICENSE (GPLv3 -> AGPLv3) and prepends `SPDX-License-Identifier: AGPL-3.0-or-later` to every source file across decnet/, decnet_web/, tests/, scripts/, and tools/. Rationale: closes the GPLv3 ASP loophole so any party operating a modified DECNET as a network service must offer their modified source. Personal copyright (Samuel Paschuan) + inbound=outbound contributions make a future unilateral relicense infeasible. - LICENSE: full AGPL-3.0 text (gnu.org/licenses/agpl-3.0.txt) - COPYRIGHT: project copyright notice - tools/add_spdx_headers.py: idempotent header injector (shebang- and PEP 263-aware) Touches 1565 source files (.py, .ts, .tsx, .js, .jsx, .css, .sh). No behavior change; comments only.
90 lines
3.6 KiB
Python
90 lines
3.6 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-or-later
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"""Step D.1: ``cognitive.cognitive_load``.
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Composite of three [0, 1]-clipped sub-signals (chunking variance, error
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rate, pace variability) → bucketed against COGNITIVE_LOAD_LOW_MAX /
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COGNITIVE_LOAD_MEDIUM_MAX. Tests pin each component at its extremes and
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confirm the bucket falls where the math says.
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"""
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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 _typed(text: str, t0: float = 0.0, dt: float = 0.05) -> list[AsciinemaEvent]:
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return [(t0 + i * dt, "i", c) for i, c in enumerate(text)]
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def _metronomic_clean_session(n: int = 8) -> list[AsciinemaEvent]:
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"""``n`` commands, perfectly even pacing, zero errors, fluent typing."""
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events: list[AsciinemaEvent] = []
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for i in range(n):
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events.extend(_typed("ls\r", t0=i * 1.0, dt=0.05))
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return events
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def test_no_commands_no_emission() -> None:
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events: list[AsciinemaEvent] = [(0.0, "i", "a")]
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out = list(extract_session(events, sid="cl-empty"))
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assert [o for o in out if o.primitive == "cognitive.cognitive_load"] == []
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def test_metronomic_clean_session_emits_low() -> None:
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"""Even pacing + clean output + steady typing → low load."""
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out = list(extract_session(_metronomic_clean_session(8), sid="cl-low"))
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obs = _of(out, "cognitive.cognitive_load")
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assert obs.value == "low"
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def test_high_error_rate_drives_load_up() -> None:
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"""Every command errored — error_load = 1.0 alone forces load >= 0.33."""
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events: list[AsciinemaEvent] = []
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for i in range(8):
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events.extend(_typed("foo\r", t0=i * 1.0, dt=0.05))
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events.append((i * 1.0 + 0.5, "o", "bash: foo: command not found\n"))
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out = list(extract_session(events, sid="cl-err"))
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obs = _of(out, "cognitive.cognitive_load")
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assert obs.value in ("medium", "high")
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def test_all_three_components_high_emits_high() -> None:
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"""Saturate every component → load ≈ 1.0 → high."""
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events: list[AsciinemaEvent] = []
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# Burst-then-gap pacing maximises pace-CV; mid-command jitter
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# maximises chunking-CV; every command errors.
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starts = [0.0, 0.1, 0.2, 30.0, 30.1, 60.0, 90.0, 90.1]
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for i, s in enumerate(starts):
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# Mid-command jitter: 'a' at s, 'b' 0.01s later, 'c' 2s later, '\r' 2.05s later
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events.append((s, "i", "a"))
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events.append((s + 0.01, "i", "b"))
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events.append((s + 2.0, "i", "c"))
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events.append((s + 2.05, "i", "\r"))
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events.append((s + 2.10, "o", "bash: abc: command not found\n"))
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out = list(extract_session(events, sid="cl-high"))
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obs = _of(out, "cognitive.cognitive_load")
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assert obs.value == "high"
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def test_low_sample_count_reduces_confidence() -> None:
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short = list(extract_session(_metronomic_clean_session(3), sid="cl-short"))
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full = list(extract_session(_metronomic_clean_session(8), sid="cl-full"))
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s = _of(short, "cognitive.cognitive_load")
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f = _of(full, "cognitive.cognitive_load")
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assert s.confidence < f.confidence
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def test_pii_no_command_bodies_in_observation() -> None:
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events: list[AsciinemaEvent] = []
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for i in range(6):
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events.extend(_typed("supersecret\r", t0=i * 1.0, dt=0.05))
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out = list(extract_session(events, sid="cl-pii"))
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obs = _of(out, "cognitive.cognitive_load")
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assert "supersecret" not in obs.model_dump_json()
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