def getTypeInt(text): formatInput(text) tms.tms_segment("./twitterData/twitterTestData.txt",[1],"./twitterData/twitterTestData1.txt","^","\t",1) #类型预测 tms.tms_predict("./twitterData/twitterTestData1.txt","./twitterData/type_model/model/tms.config",result_save_path="./twitterData/tms.result") file = open("twitterData/tms.result") text = file.read() text = text.split("\n") #情感预测 tms.tms_predict("./twitterData/twitterTestData1.txt","./twitterData/emotion/model/tms.config",result_save_path="./twitterData/emotion/tms.result") file1 = open("twitterData/emotion/tms.result") text1 = file1.read() text1 = text1.split("\n") result = [] for i in range(0,len(text)): if len(text[i]) > 0: each = text[i].split("\t") point = int(float(each[0])) each1 = text1[i].split("\t") point1 = int(float(each1[0])) result.append([point,point1]) return result
def getTypeStr(text): dir = ["新闻,娱乐类","自然灾难","航空事件","食品药物安全","饮食","科教,教育","国际事件","招聘","犯罪事件","交通事故","经济金融类","环境问题","其他","煤矿事件","医疗,疾病","科技"] dir1 = ["积极","消极","中立"] formatInput(text) tms.tms_segment("./twitterData/twitterTestData.txt",[1],"./twitterData/twitterTestData1.txt","^","\t",1) #类型预测 tms.tms_predict("./twitterData/twitterTestData1.txt","./twitterData/type_model/model/tms.config",result_save_path="./twitterData/tms.result") file = open("twitterData/tms.result") text = file.read() text = text.split("\n") #情感预测 tms.tms_predict("./twitterData/twitterTestData1.txt","./twitterData/emotion/model/tms.config",result_save_path="./twitterData/emotion/tms.result") file1 = open("twitterData/emotion/tms.result") text1 = file1.read() text1 = text1.split("\n") result = [] for i in range(0,len(text)): if len(text[i]) > 0: each = text[i].split("\t") point = int(float(each[0])) each1 = text1[i].split("\t") point1 = int(float(each1[0])) result.append([dir[point].decode("utf-8"),dir1[point1].decode("utf-8")]) return result
def getEmotionType(text): formatInput(text) curpath = os.path.join(os.path.dirname(__file__), 'twitterData/').replace('\\','/') #tms.tms_segment("./EMOTION/twitterData/twitterTestData.txt",[1],"./EMOTION/twitterData/twitterTestData1.txt","^","\t",1) tms.tms_segment(curpath+"twitterTestData.txt",[1],curpath+"twitterTestData1.txt","^","\t",1) #情感预测,0积极,1消极,2中立 tms.tms_predict(curpath+"twitterTestData1.txt",curpath+"emotion/model/tms.config",result_save_path=curpath+"emotion/tms.result") file1 = open(curpath+"emotion/tms.result") text1 = file1.read() text1 = text1.split("\n") result = [] for each in text1: each = each.split('\t') result.append(each[0]) return result
def getEmotionType(text): formatInput(text) curpath = os.path.join(os.path.dirname(__file__), 'twitterData/').replace('\\', '/') #tms.tms_segment("./EMOTION/twitterData/twitterTestData.txt",[1],"./EMOTION/twitterData/twitterTestData1.txt","^","\t",1) tms.tms_segment(curpath + "twitterTestData.txt", [1], curpath + "twitterTestData1.txt", "^", "\t", 1) #情感预测,0积极,1消极,2中立 tms.tms_predict(curpath + "twitterTestData1.txt", curpath + "emotion/model/tms.config", result_save_path=curpath + "emotion/tms.result") file1 = open(curpath + "emotion/tms.result") text1 = file1.read() text1 = text1.split("\n") result = [] for each in text1: each = each.split('\t') result.append(each[0]) return result