anti
f948e10830
Composite over three [0, 1]-clipped sub-signals (chunking variance, error rate from D.0's Command.errored, pace variability), mean-aggregated and bucketed against COGNITIVE_LOAD_LOW_MAX / COGNITIVE_LOAD_MEDIUM_MAX. Components missing data drop out of the mean rather than zeroing it. v0.1 thresholds; D.8 re-tunes once D.2-D.7 are stable. Confidence held at 0.60 (composite over soft sub-signals) and halved below the 5-command sample-size floor.
51 lines
1.3 KiB
Python
51 lines
1.3 KiB
Python
"""Registered feature functions.
|
|
|
|
Each entry takes a ``SessionContext`` and yields zero or more
|
|
``Observation`` instances. Adding a primitive = adding a function in a
|
|
sibling module and appending it to ``FEATURES``.
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
from typing import Callable, Iterable
|
|
|
|
from decnet_behave_core.spec.envelope import Observation
|
|
|
|
from decnet.profiler.behave_shell._ctx import SessionContext
|
|
from decnet.profiler.behave_shell._features.cognitive import (
|
|
cognitive_load,
|
|
command_branch_diversity,
|
|
feedback_loop_engagement,
|
|
inter_command_consistency,
|
|
inter_command_latency_class,
|
|
)
|
|
from decnet.profiler.behave_shell._features.motor import (
|
|
command_chunking,
|
|
error_correction,
|
|
input_modality,
|
|
keystroke_cadence,
|
|
motor_stability,
|
|
paste_burst_rate,
|
|
pipe_chaining_depth,
|
|
shortcut_usage,
|
|
tab_completion,
|
|
)
|
|
|
|
FeatureFn = Callable[[SessionContext], Iterable[Observation]]
|
|
|
|
FEATURES: tuple[FeatureFn, ...] = (
|
|
input_modality,
|
|
paste_burst_rate,
|
|
keystroke_cadence,
|
|
motor_stability,
|
|
error_correction,
|
|
command_chunking,
|
|
tab_completion,
|
|
shortcut_usage,
|
|
pipe_chaining_depth,
|
|
inter_command_latency_class,
|
|
command_branch_diversity,
|
|
feedback_loop_engagement,
|
|
inter_command_consistency,
|
|
cognitive_load,
|
|
)
|