165 lines
6.0 KiB
Python
165 lines
6.0 KiB
Python
"""Control primitives: speed modulation, Strömbom, Sequential, ActiveScan."""
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import math
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import pytest
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from herding.control.active_scan import (
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EMPTY_DEBOUNCE_STEPS, INITIAL_SCAN_STEPS, ActiveScanTeacher,
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)
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from herding.control.modulation import (
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MIN_SPEED, SLOW_NEAR_SHEEP, modulate_speed_near_sheep,
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)
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from herding.control.sequential import compute_action as sequential_action
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from herding.control.strombom import (
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DELTA_DRIVE, F_FACTOR, compute_action as strombom_action,
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)
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from herding.world.geometry import PEN_ENTRY
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# ---------------------------------------------------------------------------
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# Modulation
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# ---------------------------------------------------------------------------
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def test_modulation_empty_input_passthrough():
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assert modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), []) == (1.0, 0.0)
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assert modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), {}) == (1.0, 0.0)
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def test_modulation_far_sheep_passthrough():
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vx, vy = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), [(100.0, 0.0)])
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assert (vx, vy) == (1.0, 0.0)
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def test_modulation_close_sheep_min_speed():
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vx, vy = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0), [(0.0, 0.0)])
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assert math.isclose(vx, MIN_SPEED)
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assert vy == 0.0
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def test_modulation_preserves_direction():
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vx, vy = modulate_speed_near_sheep(0.6, 0.8, (0.0, 0.0), [(1.0, 0.0)])
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ratio = math.hypot(vx, vy)
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# Direction preserved.
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assert math.isclose(vx / ratio, 0.6, abs_tol=1e-6)
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assert math.isclose(vy / ratio, 0.8, abs_tol=1e-6)
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def test_modulation_linear_ramp_midpoint():
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vx, _ = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0),
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[(SLOW_NEAR_SHEEP / 2, 0.0)])
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expected = MIN_SPEED + (1.0 - MIN_SPEED) * 0.5
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assert math.isclose(vx, expected, abs_tol=1e-6)
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def test_modulation_accepts_dict_input():
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vx_list, _ = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0),
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[(1.0, 0.0)])
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vx_dict, _ = modulate_speed_near_sheep(1.0, 0.0, (0.0, 0.0),
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{"t0": (1.0, 0.0)})
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assert math.isclose(vx_list, vx_dict)
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# ---------------------------------------------------------------------------
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# Strömbom
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# ---------------------------------------------------------------------------
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def test_strombom_empty_input_idle():
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vx, vy, mode = strombom_action((0.0, 0.0), {}, PEN_ENTRY)
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assert (vx, vy, mode) == (0.0, 0.0, "idle")
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def test_strombom_tight_flock_drives():
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# A tight 3-sheep cluster centred at (0, 8): radius < F_FACTOR·√3.
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sheep = {"s0": (0.0, 8.0), "s1": (0.5, 8.5), "s2": (-0.5, 8.0)}
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vx, vy, mode = strombom_action((0.0, 0.0), sheep, PEN_ENTRY)
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assert mode == "drive"
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assert math.isclose(math.hypot(vx, vy), 1.0, abs_tol=1e-3)
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def test_strombom_scattered_flock_collects():
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# Sparse, max radius > F_FACTOR·√n.
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sheep = {"s0": (10.0, 10.0), "s1": (-10.0, -10.0), "s2": (0.0, 0.0)}
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_vx, _vy, mode = strombom_action((0.0, 0.0), sheep, PEN_ENTRY)
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assert mode == "collect"
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def test_strombom_ignores_already_penned_sheep():
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"""Sheep south of the gate plane are excluded from the active set."""
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sheep = {
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"s_active": (5.0, 5.0),
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"s_penned": (11.5, -20.0),
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}
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# With one active sheep, Strömbom drives (radius = 0 < threshold).
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_vx, _vy, mode = strombom_action((0.0, 0.0), sheep, PEN_ENTRY)
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assert mode == "drive"
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# ---------------------------------------------------------------------------
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# Sequential
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# ---------------------------------------------------------------------------
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def test_sequential_empty_input_idle():
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vx, vy, mode = sequential_action((0.0, 0.0), {}, PEN_ENTRY)
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assert (vx, vy, mode) == (0.0, 0.0, "idle")
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def test_sequential_targets_closest_to_pen():
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near = (10.0, -5.0) # closer to pen entry (11.5, -15)
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far = (-10.0, 10.0)
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sheep = {"near": near, "far": far}
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_vx, _vy, mode = sequential_action((0.0, 0.0), sheep, PEN_ENTRY)
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assert mode.startswith("drive:near")
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# ---------------------------------------------------------------------------
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# ActiveScan wrapper
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# ---------------------------------------------------------------------------
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def test_active_scan_initial_phase_rotates():
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teacher = ActiveScanTeacher(strombom_action)
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# First call → opening rotation regardless of input.
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vx, vy, mode = teacher((0.0, 0.0), 0.0, {"s0": (5.0, 0.0)}, PEN_ENTRY)
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assert mode == "scan_initial"
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assert math.isclose(math.hypot(vx, vy), 1.0, abs_tol=1e-6)
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def test_active_scan_hands_off_to_base_after_opener():
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teacher = ActiveScanTeacher(strombom_action, initial_scan_steps=2)
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# Burn through the opener.
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for _ in range(2):
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teacher((0.0, 0.0), 0.0, {"s0": (0.0, 8.0)}, PEN_ENTRY)
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_vx, _vy, mode = teacher((0.0, 0.0), 0.0, {"s0": (0.0, 8.0)}, PEN_ENTRY)
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# Either drive (Strömbom mode label) or collect; not scan_initial.
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assert "scan" not in mode
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def test_active_scan_holds_last_action_on_brief_empty():
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teacher = ActiveScanTeacher(strombom_action, initial_scan_steps=1)
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# Step once (opening), then once with a visible sheep — sets last_action.
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teacher((0.0, 0.0), 0.0, {}, PEN_ENTRY)
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teacher((0.0, 0.0), 0.0, {"s0": (0.0, 8.0)}, PEN_ENTRY)
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last = teacher.last_action
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# Now a single empty frame → hold.
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vx, vy, mode = teacher((0.0, 0.0), 0.0, {}, PEN_ENTRY)
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assert mode == "hold"
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assert (vx, vy) == last
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def test_active_scan_explores_after_sustained_empty():
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teacher = ActiveScanTeacher(strombom_action, initial_scan_steps=1)
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teacher((0.0, 0.0), 0.0, {}, PEN_ENTRY) # opener
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for _ in range(EMPTY_DEBOUNCE_STEPS):
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last_vx, last_vy, mode = teacher((5.0, 5.0), 0.0, {}, PEN_ENTRY)
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assert mode in ("explore", "scan_at_centre")
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def test_active_scan_reset_clears_state():
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teacher = ActiveScanTeacher(strombom_action, initial_scan_steps=5)
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for _ in range(3):
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teacher((0.0, 0.0), 0.0, {}, PEN_ENTRY)
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assert teacher.step == 3
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teacher.reset()
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assert teacher.step == 0
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assert teacher.empty_streak == 0
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