anti
d90c8b70ce
BEHAVE-EXTRACTOR.md Phase B Step B.1.
* SessionContext gains typing_bursts: tuple[tuple[float, ...], ...]
built by _split_typing_bursts(iats) — splits at gaps > IKI_THINK_MAX_S
(1.5s) and drops bursts of fewer than 3 IATs. Mirrors prototype's
_split_into_bursts at BEHAVE/prototype_extractors/shell/extract.py:275.
* _features/motor.py:keystroke_cadence(ctx) emits one Observation
in {steady, bursty, hunt_and_peck, machine}. Median CV across
typing bursts; mean IKI < IKI_MACHINE_MAX_S paired with CV <
CV_MACHINE_MAX → machine. Confidence 0.85/0.70/0.65/0.60 per the
prototype's calibration history.
* < MIN_INPUTS_FOR_CADENCE inputs or zero typing bursts → skip
emission. v0.1 emits only the burst-CV variant; the prototype's
NAIVE session-CV variant is parked for v0.2.
* Calibration grid widened (PHASE_A_PRIMITIVES → PHASE_AB_PRIMITIVES)
to include motor.keystroke_cadence. Grid green across all five
shards.
Tests: too-few-inputs → no emit, all-think-pauses → no burst → no
emit, uniform IATs → steady, sub-5ms → machine, mixed-pace → bursty,
extreme bimodal → hunt_and_peck.
37 lines
1020 B
Python
37 lines
1020 B
Python
"""Registered feature functions.
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Each entry takes a ``SessionContext`` and yields zero or more
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``Observation`` instances. Adding a primitive = adding a function in a
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sibling module and appending it to ``FEATURES``.
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"""
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from __future__ import annotations
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from typing import Callable, Iterable
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from decnet_behave_core.spec.envelope import Observation
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from decnet.profiler.behave_shell._ctx import SessionContext
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from decnet.profiler.behave_shell._features.cognitive import (
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command_branch_diversity,
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feedback_loop_engagement,
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inter_command_consistency,
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inter_command_latency_class,
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)
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from decnet.profiler.behave_shell._features.motor import (
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input_modality,
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keystroke_cadence,
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paste_burst_rate,
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)
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FeatureFn = Callable[[SessionContext], Iterable[Observation]]
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FEATURES: tuple[FeatureFn, ...] = (
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input_modality,
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paste_burst_rate,
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keystroke_cadence,
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inter_command_latency_class,
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command_branch_diversity,
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feedback_loop_engagement,
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inter_command_consistency,
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)
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