Climbing Beta Optimizer

import numpy as np
from hold import Hold
from wall import Wall
from climber import Climber
from torso import Torso
from state import State
from planner import find_best_betasholds = [    Hold(0.0, 0.0, 0.0),    Hold(50, 30, 0.0),    Hold(-50, 40, 0.0),    Hold(20, 80, 0.0),    Hold(-30, 90, 0.0),    Hold(60, 120, 0.0),    Hold(-50, 130, 0.0),    Hold(0.0, 160, 0.0)]
wall = Wall(holds)climber = Climber(height=170)climber.mass = 65torso = Torso(    position=np.array([0.0, 5.0, 15.0]),    roll=0,    pitch=0,    yaw=0,    width=40,    height=60,    thickness=20)state = State(    left_hand=2,    right_hand=1,    left_foot=0,    right_foot=0,    torso=torso)roll_values = [-10, 0, 10]pitch_values = [-10, 0, 10]yaw_values = [-10, 0, 10]arm_extensions = [0.7, 0.8, 0.9, 1.0]leg_extensions = [0.7, 0.8, 0.9, 1.0]betas = find_best_betas(    state,    wall,    climber,    radius=80,    roll_values=roll_values,    pitch_values=pitch_values,    yaw_values=yaw_values,    arm_extensions=arm_extensions,    leg_extensions=leg_extensions)print(f"Found {len(betas)} betas")for i, beta in enumerate(betas, start=1):    print(f"\n===== BETA {i} =====")    print(f"Score: {beta.score}")    print(f"Left Hand : {beta.left_hand}")    print(f"Right Hand: {beta.right_hand}")    print(f"Left Foot : {beta.left_foot}")    print(f"Right Foot: {beta.right_foot}")    print(f"Roll : {beta.torso.roll}")    print(f"Pitch: {beta.torso.pitch}")    print(f"Yaw  : {beta.torso.yaw}")    print(f"Left Arm Margin : {beta.left_arm_margin:.2f}")    print(f"Right Arm Margin: {beta.right_arm_margin:.2f}")    print(f"Left Leg Margin : {beta.left_leg_margin:.2f}")    print(f"Right Leg Margin: {beta.right_leg_margin:.2f}")```