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- import json
- import numpy as np
- from mapping1.onehot_generate import onehot_generate
- onehot_generate()
- # 从文件读取关键词与one-hot编码的字典
- with open("./mapping1/keyword_one_hot_dict.json", "r", encoding="utf-8") as json_file:
- keyword_one_hot_dict = json.load(json_file)
- # 从文件读取故障现象词的向量字典
- with open("./mapping1/phenomenon_vector_dict.json", "r", encoding="utf-8") as json_file:
- phenomenon_vector_dict = json.load(json_file)
- def mapping(sentence: str):
- # 初始化词向量
- sentence_vector = np.zeros(len(keyword_one_hot_dict[list(keyword_one_hot_dict.keys())[0]]), dtype=np.int32)
- # 遍历关键词表,逐个查找关键词是否在句子中
- for word in keyword_one_hot_dict.keys():
- if word in sentence:
- keyword_vector = np.array(keyword_one_hot_dict[word], dtype=np.int32)
- sentence_vector += keyword_vector
- # 判断是否有对应的故障现象
- matched_phenomenon = None
- for phenomenon, vector in phenomenon_vector_dict.items():
- if np.array_equal(sentence_vector, vector):
- matched_phenomenon = phenomenon
- break
- # 输出结果
- if matched_phenomenon:
- return(matched_phenomenon)
- else:
- return None
- # 输入句子
- #sentence = "液压2系统压力正常"
- #print(mapping(sentence))
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