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https://github.com/MCCTeam/Minecraft-Console-Client
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418f17b4a1
Theory simulator: - Add 2D side-wall jump physics with yaw sweep for worst-case margin - Generate sidewall theory cases (flat/ascend/descend, wall_offset 0/1) - Add momentum-capabilities.json with band compression and max_reach - Extend models, capabilities, canonical, and renderers for sidewall Full-coverage parkour test suite (tools/test-parkour.py): - Derive test matrix from momentum-capabilities.json - Build linear/neo/ceiling courses via RCON with 7-block clear margin - Use /goto for pathfinding, parse A* and PathMgr log output - Stop-at-first-failure per (family, subfamily, dy, ceil, wo) group - Hierarchical --filter (e.g. linear/flat, ceiling/headhitter/ceil2.5) - Exclude sidewall from default matrix (identical max_reach to linear) Pathing execution fixes: - Align parkour contracts and timing budgets with live test results - Fix jump-entry yaw snapping for grounded handoffs - Template helper and sprint jump template refinements Made-with: Cursor
186 lines
7.5 KiB
Python
186 lines
7.5 KiB
Python
from tools.pathing_theory.models import TheoryCase
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from tools.pathing_theory.primitives import (
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PLAYER_WIDTH,
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TARGET_BLOCK_WIDTH,
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can_reach_gap,
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can_reach_gap_with_side_wall,
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get_apex,
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get_landing,
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)
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MAX_MOMENTUM_TICKS = 12
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def _float_token(value: float) -> str:
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return f"{value:.1f}".replace("-", "m").replace(".", "p")
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def build_theory_cases() -> list[TheoryCase]:
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cases: list[TheoryCase] = []
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for sprint, movement_mode in [
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(False, "walk"),
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(True, "sprint"),
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]:
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for momentum_ticks in range(0, MAX_MOMENTUM_TICKS + 1):
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apex_y, _ = get_apex(sprint=sprint, momentum_ticks=momentum_ticks)
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for gap in range(0, 8):
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for delta_y in [0.0, 1.0, -1.0, -2.0]:
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ok, landing_x, needed_x = can_reach_gap(
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gap_blocks=gap,
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dy=delta_y,
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sprint=sprint,
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momentum_ticks=momentum_ticks,
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)
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subfamily = (
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"flat"
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if delta_y == 0.0
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else "ascend"
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if delta_y > 0.0
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else "descend"
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)
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cases.append(
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TheoryCase(
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case_id=(
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f"linear-{subfamily}-{movement_mode}-mm{momentum_ticks}"
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f"-gap{gap}-dy{_float_token(delta_y)}"
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),
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family="linear",
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subfamily=subfamily,
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movement_mode=movement_mode,
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momentum_ticks=momentum_ticks,
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gap_blocks=gap,
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delta_y=delta_y,
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ceiling_height=None,
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wall_width=None,
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wall_offset=None,
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expected_reachable=ok,
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landing_x=landing_x,
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apex_y=apex_y,
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margin=None if landing_x is None else landing_x - needed_x,
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)
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)
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for sprint, movement_mode in [
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(False, "walk"),
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(True, "sprint"),
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]:
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for momentum_ticks in range(0, MAX_MOMENTUM_TICKS + 1):
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apex_y, _ = get_apex(sprint=sprint, momentum_ticks=momentum_ticks)
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landing = get_landing(
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sprint=sprint,
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target_y=0.0,
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landing_x_start=0.0,
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momentum_ticks=momentum_ticks,
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)
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for wall_width in [1, 2, 3, 4]:
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landing_x = None if landing is None else landing[0]
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needed_x = wall_width + PLAYER_WIDTH
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margin = None if landing_x is None else landing_x - needed_x
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cases.append(
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TheoryCase(
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case_id=f"neo-neo-{movement_mode}-mm{momentum_ticks}-wall{wall_width}",
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family="neo",
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subfamily="neo",
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movement_mode=movement_mode,
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momentum_ticks=momentum_ticks,
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gap_blocks=None,
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delta_y=0.0,
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ceiling_height=None,
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wall_width=wall_width,
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wall_offset=None,
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expected_reachable=margin is not None and margin >= 0.0,
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landing_x=landing_x,
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apex_y=apex_y,
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margin=margin,
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)
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)
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for momentum_ticks in range(0, MAX_MOMENTUM_TICKS + 1):
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for ceiling_height in [4.0, 3.0, 2.5, 2.0, 1.8125]:
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apex_y, _ = get_apex(
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sprint=True,
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momentum_ticks=momentum_ticks,
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ceiling_y=ceiling_height,
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)
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for gap in [1, 2, 3, 4]:
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landing = get_landing(
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sprint=True,
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target_y=0.0,
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landing_x_start=0.5 + gap,
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momentum_ticks=momentum_ticks,
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ceiling_y=ceiling_height,
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landing_width=TARGET_BLOCK_WIDTH,
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)
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landing_x = None if landing is None else landing[0]
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needed_x = 0.5 + gap - (PLAYER_WIDTH / 2.0)
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margin = None if landing_x is None else landing_x - needed_x
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cases.append(
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TheoryCase(
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case_id=(
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f"ceiling-headhitter-sprint-mm{momentum_ticks}-gap{gap}"
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f"-ceil{str(ceiling_height).replace('.', 'p')}"
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),
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family="ceiling",
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subfamily="headhitter",
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movement_mode="sprint",
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momentum_ticks=momentum_ticks,
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gap_blocks=gap,
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delta_y=0.0,
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ceiling_height=ceiling_height,
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wall_width=None,
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wall_offset=None,
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expected_reachable=margin is not None and margin >= 0.0,
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landing_x=landing_x,
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apex_y=apex_y,
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margin=margin,
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)
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)
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# --- Side-wall jump family ---
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for sprint, movement_mode in [
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(False, "walk"),
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(True, "sprint"),
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]:
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for momentum_ticks in range(0, MAX_MOMENTUM_TICKS + 1):
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apex_y, _ = get_apex(sprint=sprint, momentum_ticks=momentum_ticks)
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for wall_offset in [0, 1]:
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for gap in range(0, 8):
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for delta_y in [0.0, 1.0, -1.0, -2.0]:
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ok, landing_x, needed_x = can_reach_gap_with_side_wall(
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gap_blocks=gap,
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dy=delta_y,
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wall_offset=wall_offset,
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sprint=sprint,
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momentum_ticks=momentum_ticks,
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)
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subfamily = (
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"flat"
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if delta_y == 0.0
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else "ascend"
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if delta_y > 0.0
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else "descend"
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)
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cases.append(
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TheoryCase(
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case_id=(
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f"sidewall-{subfamily}-{movement_mode}-mm{momentum_ticks}"
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f"-gap{gap}-dy{_float_token(delta_y)}-wo{wall_offset}"
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),
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family="sidewall",
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subfamily=subfamily,
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movement_mode=movement_mode,
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momentum_ticks=momentum_ticks,
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gap_blocks=gap,
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delta_y=delta_y,
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ceiling_height=None,
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wall_width=None,
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wall_offset=wall_offset,
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expected_reachable=ok,
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landing_x=landing_x,
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apex_y=apex_y,
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margin=None if landing_x is None else landing_x - needed_x,
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)
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)
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return cases
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