92 lines
2.9 KiB
Python
92 lines
2.9 KiB
Python
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from EXP.exp_tools import collect_action_nodes,get_start,BTTest,goal_transfer_str,collect_cond_nodes,BTTest_Merge,BTTest_Merge_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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seed = 1
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random.seed(seed)
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multiple_num=1
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action_list = collect_action_nodes_multiple_num(random,multiple_num)
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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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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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goal_states = []
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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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all_result=[]
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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 = [medium_data_set]
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parm_difficule_ls = ['Medium']
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goal_set_ls=[]
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for index,dataset in enumerate(dataset_ls):
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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(goal_transfer_ls_set(y))
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goal_set_ls.append(y)
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goal_states = goal_set_ls
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merge_result=[]
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max_merge_times=16
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for merge_time in range(max_merge_times):
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if merge_time%5==0:
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print("========== merge_time=",merge_time,"================")
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param_ls=[parm_difficule_ls[0],merge_time]
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baseline_result = \
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BTTest_Merge_easy_medium_hard(bt_algo_opt=True, goal_states=goal_states,action_list=action_list,\
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start_robowaiter=start_robowaiter,merge_time=merge_time)
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tmp=[]
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tmp.extend(param_ls)
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tmp.extend(baseline_result)
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merge_result.append(tmp)
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import pandas as pd
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df = pd.DataFrame(merge_result, columns=[
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'difficult',
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'merge_time',
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'tree_size_avg', 'tree_size_std',
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'ticks_avg', 'ticks_std',
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'cond_ticks_avg', 'cond_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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import time
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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 = 'merged_result_'+parm_difficule_ls[0]+'_stats_'+str(max_merge_times)+"_states="+str(state_num)+"_acts="+str(len(action_list))+"_"+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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