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

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>

herding/config.py

@@ -1,32 +1,30 @@
 """Central configuration dataclasses for the herding simulation.
 
-Every tunable constant that previously lived as a module-level literal in
-perception/lidar_sim.py, perception/lidar_perception.py,
-perception/sheep_tracker.py, world/geometry.py, or training/herding_env.py
-is now represented here as a field with its original default value.
+Every tunable parameter lives here as a frozen dataclass field — LiDAR
+spec, cluster detection thresholds, tracker gates, robot kinematics,
+and domain-randomisation knobs — composed into :class:`HerdingConfig`.
 
-Usage — use the module defaults unchanged::
+Usage — accept the defaults::
 
-    env = HerdingEnv()          # same behaviour as before
+    env = HerdingEnv()
 
-Override a subset of parameters::
+Override a subset::
 
-    from herding.config import HerdingConfig, TrackerConfig
     cfg = HerdingConfig(tracker=TrackerConfig(forget_steps=60))
     env = HerdingEnv(herding_cfg=cfg)
 
-Use a named preset for Webots-matched training::
+Use a named preset::
 
-    from herding.config import HERDING_WEBOTS
-    env = HerdingEnv(herding_cfg=HERDING_WEBOTS)
+    env = HerdingEnv(herding_cfg=HERDING_WEBOTS)        # 140° FOV
+    env = HerdingEnv(herding_cfg=HERDING_MEC_WEBOTS)    # + mecanum slip
 
 Design notes
 ------------
-* All dataclasses are frozen — instances are immutable after construction.
-* This module must not import from other ``herding.*`` packages to avoid
-  import cycles.  Field-geometry constants (pen coordinates, field size)
-  stay in ``herding.world.geometry`` because they depend on the world
-  variant selected at runtime via ``HERDING_WORLD``.
+* All dataclasses are frozen so instances are immutable after construction.
+* This module must not import from other ``herding.*`` packages —
+  field-geometry constants live in ``herding.world.geometry`` because
+  they depend on the world variant selected at runtime via
+  ``HERDING_WORLD``, which would create an import cycle here.
 """
 
 from __future__ import annotations
@@ -257,7 +255,7 @@ class RobotConfig:
 
     ``1.0`` (default) = perfect mecanum kinematics. ``0.4`` matches the
     Webots roller-hinge mecanum proto calibration (62% slip on strafe,
-    11% on forward). Used by ``mecanum_kinematics_step`` only — has no
+    11% on forward). Used by ``mecanum_step`` only — has no
     effect on differential drive.
     """
 
@@ -266,7 +264,7 @@ class RobotConfig:
 
     ``0.0`` (default) = no bleed. ``-0.28`` matches the Webots proto's
     consistent backward push under strafe commands. Used by
-    ``mecanum_kinematics_step`` only.
+    ``mecanum_step`` only.
     """
 
     def __post_init__(self) -> None: