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
