105 lines
3.4 KiB
Python
105 lines
3.4 KiB
Python
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from EXP.exp_tools import collect_action_nodes,get_start,BTTest,goal_transfer_str,collect_cond_nodes,BTTest_easy_medium_hard,collect_action_nodes_multiple_num
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import copy
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import random
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import re
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from dataset.data_process_check import format_check,word_correct,goal_transfer_ls_set
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import time
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import numpy as np
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seed = 1
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random.seed(seed)
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multiple_num= 5
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iters_times= 10
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# iter_action_ls=[]
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iter_action_ls = collect_action_nodes(random,multiple_num,iters_times)
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# for act in action_list:
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# print(act.name,act.cost)
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start_robowaiter = get_start()
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# 计算state总数
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state_num, vaild_state_num= collect_cond_nodes()
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easy_data_set_file = "../dataset/easy_instr_goal.txt"
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medium_data_set_file = "../dataset/medium_instr_goal.txt"
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hard_data_set_file = "../dataset/hard_instr_goal.txt"
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with open(easy_data_set_file, 'r', encoding="utf-8") as f:
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easy_data_set = f.read().strip()
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with open(medium_data_set_file, 'r', encoding="utf-8") as f:
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medium_data_set = f.read().strip()
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with open(hard_data_set_file, 'r', encoding="utf-8") as f:
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hard_data_set = f.read().strip()
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dataset_ls = [easy_data_set,medium_data_set,hard_data_set]
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parm_difficule_ls = ['Easy','Medium','Hard']
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# dataset_ls = [hard_data_set]
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# parm_difficule_ls = ['Hard']
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all_result=[]
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for index, dataset in enumerate(dataset_ls):
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print(f"\n----------- {parm_difficule_ls[index]} ----------\n")
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sections = re.split(r'\n\s*\n', dataset)
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outputs_list = [[] for _ in range(len(sections))]
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goal_set_ls = []
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for i, s in enumerate(sections):
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x, y = s.strip().splitlines()
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x = x.strip()
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y = y.strip().replace("Goal: ", "")
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goal_set_ls.append(y)
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goal_states = goal_set_ls
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b_condticks_ls=[]
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obtea_condticks_ls=[]
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b_cost_ls=[]
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obtea_cost_ls=[]
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for iter in range(iters_times):
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action_list = iter_action_ls[iter]
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print("meta states num: ",state_num)
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print("states num: ",vaild_state_num)
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print("act num: ",len(action_list))
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obt_result = BTTest_easy_medium_hard(bt_algo_opt=True, goal_states=goal_states,action_list=action_list,start_robowaiter=start_robowaiter)
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# print("\n")
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# 对比
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baseline_result = BTTest_easy_medium_hard(bt_algo_opt=False, goal_states=goal_states,action_list=action_list,start_robowaiter=start_robowaiter)
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obtea_condticks_ls.append(obt_result[4])
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b_condticks_ls.append(baseline_result[4])
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obtea_cost_ls.append(obt_result[5])
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b_cost_ls.append(baseline_result[5])
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param_ls=[parm_difficule_ls[index]]
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a_result=[]
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a_result.extend(param_ls)
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a_result.extend([round(np.mean(b_condticks_ls), 1),round(np.mean(obtea_condticks_ls), 1),round(np.mean(b_cost_ls), 1),round(np.mean(obtea_cost_ls), 1)])
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all_result.append(a_result)
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print(all_result)
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# import pandas as pd
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# df = pd.DataFrame(all_result, columns=[
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# 'difficult',
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# 'btalgorithm',
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# 'tree_size_avg', 'tree_size_std',
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# 'ticks_avg', 'ticks_std',
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# 'cost_avg', 'cost_std',
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# 'plan_time_avg', 'plan_time_std', 'plan_time_total'])
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#
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# time_str = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime()).replace("-","").replace(":","")
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# csv_file_path = 'cage_bt_result_='+time_str+'.csv'
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# df.to_csv(csv_file_path, index=True)
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# print("CSV文件已生成:", csv_file_path)
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