def buildAndSaveModel(start: datetime, end: datetime, patternList=[]): sw = SWImpl() from earnmi_demo.strategy_demo.kbars.analysis_KPattern_skip1_predit2 import \ Generate_Feature_KPattern_skip1_predit2 for kPattern in patternList: generateTrainData = Generate_Feature_KPattern_skip1_predit2( kPatters=[kPattern]) sw.collect(start, end, generateTrainData) featureData = generateTrainData.getPandasData() filleName = f"models/predict_sw_top_k_{kPattern}.m" print(f"k线形态[{kPattern}]的模型能力:") model = PredictModel() model.setFeature(featureData) model.printCrossScoreTest() model.saveToFile(filleName)
writer.close() print(f"write dataSize = {size}") return True def onDestroy(self): super().onDestroy() if __name__ == "__main__": sw = SWImpl() start = datetime(2014, 5, 1) end = datetime(2020, 8, 17) ##查找有意义的k线形态 findKPatternCollector = Find_KPattern_skip1_predit2() findKPatternCollector.print_on_destroy = True #sw.collect(start, end,findKPatternCollector) ##打印更详细的信息 #printMoreDetail = More_detail_KPattern_skip1_predit2(kPatters=[712]) #printMoreDetail.print_on_destroy = True #sw.collect(start, end,printMoreDetail) ##生成训练数据。 generateTrainData = Generate_Feature_KPattern_skip1_predit2(kPatters=[884]) sw.collect(start, end, generateTrainData) trainData = generateTrainData.getPandasData() generateTrainData.writeToXml() pass