extends SceneTree

## Regression for authored directional locomotion.
##
## The old test expected one forward run to be procedurally yawed or reversed.
## The runtime now blends separate forward/back/left/right source cycles. This
## gate verifies that physical direction enters that authored BlendSpace, stride
## speed stays calibrated, and the feet actually move in every cardinal case.

## The real controller ground speed, not a convenient library-preview speed.
## This is the failure mode the test exists to catch: the old lateral cycle was
## technically "matched" at 5 m/s but exploded to 6.1x playback in gameplay.
const SPEED := 11.0
const SETTLE_FRAMES := 18
const SAMPLE_FRAMES := 24
const CASES := [
	["forward", 0.0, 1.0, "Sprint"],
	["backward", 0.0, -1.0, "RunBackward"],
	["left", -1.0, 0.0, "RunLeft"],
	["right", 1.0, 0.0, "RunRight"],
	["forward-right", 1.0, 1.0, ""],
	["back-left", -1.0, -1.0, ""],
]

var _failures := 0


func _initialize() -> void:
	call_deferred("_run")


func _run() -> void:
	await process_frame
	var args := OS.get_cmdline_user_args()
	var path: String = args[0] if not args.is_empty() \
		else "res://assets/characters/skins/taila.glb"

	var scene := Node3D.new()
	root.add_child(scene)
	current_scene = scene
	var model := SkinnedPlayerModel.new()
	model.model_path = path
	scene.add_child(model)

	for _frame in 60:
		await process_frame
	if not model.loaded or model.skeleton == null:
		_expect(false, "the authored character loads")
		_done()
		return

	var foot := model._role_bone("foot.L", ["foot.L", "LeftFoot", "Left ankle"])
	_expect(foot >= 0, "a foot bone resolves")

	for test_case in CASES:
		var direction := Vector2(float(test_case[1]), float(test_case[2])).normalized()
		for _frame in SETTLE_FRAMES:
			model.set_locomotion(direction.x, direction.y, 0.0)
			model.update_state("ground", SPEED, false)
			await process_frame

		var blend := model.locomotion_blend_debug()
		_expect(blend.length() > 0.01 and blend.normalized().dot(direction) > 0.999,
			"%s drives the authored BlendSpace in the physical direction"
				% String(test_case[0]))
		_expect(absf(model.locomotion_effective_speed_debug() - SPEED) < 0.02,
			"%s authored stride matches %.1f m/s"
				% [String(test_case[0]), SPEED])
		var expected_clip := String(test_case[3])
		if not expected_clip.is_empty():
			_expect(model.current_clip_debug() == expected_clip,
				"%s selects %s" % [String(test_case[0]), expected_clip])

		if foot >= 0:
			var start := model.skeleton.get_bone_pose_rotation(foot)
			var greatest := 0.0
			for _frame in SAMPLE_FRAMES:
				model.set_locomotion(direction.x, direction.y, 0.0)
				model.update_state("ground", SPEED, false)
				await process_frame
				greatest = maxf(greatest, start.angle_to(
					model.skeleton.get_bone_pose_rotation(foot)))
			_expect(greatest > 0.03,
				"%s uses a moving authored foot cycle (%.3f rad)"
					% [String(test_case[0]), greatest])

	model.queue_free()
	_done()


func _expect(ok: bool, description: String) -> void:
	if ok:
		print("  OK: ", description)
	else:
		printerr("  FAIL: ", description)
		_failures += 1


func _done() -> void:
	print("\n=== AUTHORED DIRECTION SUMMARY ===")
	print("Failures: %d" % _failures)
	quit(1 if _failures > 0 else 0)