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Rename multi-segment functions to two-concept names; polish docstrings

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Naming pass: rename functions whose third+ segment is redundant or
implementation-detail, sticking to the codebase's preferred
``noun_verb`` / ``verb_noun`` two-concept idiom. Renames are atomic
across definitions, callers, and tests.

  is_penned_position        →  is_penned
  modulate_speed_near_sheep →  modulate_speed
  mecanum_kinematics_step   →  mecanum_step
  policy_forward_mean       →  forward_mean

Two-concept patterns like ``velocity_to_wheels`` / ``detections_from_scan``
/ ``make_strombom_predictor`` are left alone — they're idiomatic
converters / factories that read as a single concept, and the longer
form aids grep-ability.

Docstring polish:
* ``herding/config.py`` header drops the "previously lived as a
  module-level literal" historical framing — we ship as a single
  thing, so the refactor anecdote no longer earns its keep. The
  usage examples now mention both ``HERDING_WEBOTS`` and
  ``HERDING_MEC_WEBOTS`` presets.

126 pytest cases still pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Johnny Fernandes
2026-05-17 01:58:15 +00:00
parent 10c01a938e
commit 7ab69ab0f3
14 changed files with 75 additions and 77 deletions
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tests/test_control.py
+9 -9
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@@ -8,7 +8,7 @@ from herding.control.active_scan import (
EMPTY_DEBOUNCE_STEPS, INITIAL_SCAN_STEPS, ActiveScanTeacher,
)
from herding.control.modulation import (
MIN_SPEED, SLOW_NEAR_SHEEP, modulate_speed_near_sheep,
MIN_SPEED, SLOW_NEAR_SHEEP, modulate_speed,
)
from herding.control.sequential import compute_action as sequential_action
from herding.control.strombom import (
@@ -23,23 +23,23 @@ from herding.world.geometry import PEN_ENTRY
# ---------------------------------------------------------------------------
def test_modulation_empty_input_passthrough():
assert modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), []) == (1.0, 0.0)
assert modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), {}) == (1.0, 0.0)
assert modulate_speed(1.0, 0.0, (0.0, 0.0), []) == (1.0, 0.0)
assert modulate_speed(1.0, 0.0, (0.0, 0.0), {}) == (1.0, 0.0)
def test_modulation_far_sheep_passthrough():
vx, vy = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), [(100.0, 0.0)])
vx, vy = modulate_speed(1.0, 0.0, (0.0, 0.0), [(100.0, 0.0)])
assert (vx, vy) == (1.0, 0.0)
def test_modulation_close_sheep_min_speed():
vx, vy = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), [(0.0, 0.0)])
vx, vy = modulate_speed(1.0, 0.0, (0.0, 0.0), [(0.0, 0.0)])
assert math.isclose(vx, MIN_SPEED)
assert vy == 0.0
def test_modulation_preserves_direction():
vx, vy = modulate_speed_near_sheep(0.6, 0.8, (0.0, 0.0), [(1.0, 0.0)])
vx, vy = modulate_speed(0.6, 0.8, (0.0, 0.0), [(1.0, 0.0)])
ratio = math.hypot(vx, vy)
# Direction preserved.
assert math.isclose(vx / ratio, 0.6, abs_tol=1e-6)
@@ -47,16 +47,16 @@ def test_modulation_preserves_direction():
def test_modulation_linear_ramp_midpoint():
vx, _ = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0),
vx, _ = modulate_speed(1.0, 0.0, (0.0, 0.0),
[(SLOW_NEAR_SHEEP / 2, 0.0)])
expected = MIN_SPEED + (1.0 - MIN_SPEED) * 0.5
assert math.isclose(vx, expected, abs_tol=1e-6)
def test_modulation_accepts_dict_input():
vx_list, _ = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0),
vx_list, _ = modulate_speed(1.0, 0.0, (0.0, 0.0),
[(1.0, 0.0)])
vx_dict, _ = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0),
vx_dict, _ = modulate_speed(1.0, 0.0, (0.0, 0.0),
{"t0": (1.0, 0.0)})
assert math.isclose(vx_list, vx_dict)