hawkes.py 文件源码

def predict_one(self,_id,duration,pred_year):
        try:
            patent = self.params['patent'][str(_id)]
        except KeyError,e:
            return None
        w1 = self.params['w1']
        alpha = patent['alpha']
        w2 = self.params['w2']
        fea = numpy.mat(patent['fea'])
        ti = patent['cite']
        beta = numpy.mat(self.params['beta'])

        cut_point = pred_year - int(float((patent['year'])))
        tr = numpy.mat([x for x in ti if x <= cut_point])
        pred = self.predict_year_by_year(tr,cut_point,duration,
            beta*numpy.mat(fea).T,w1,alpha,w2)

        _dict = {}
        for i in range(len(pred)):
            year = pred_year + i + 1
            _dict[year] = pred[i]
        _list = sorted(_dict.items(),key=lambda x:x[0])
        return _list