pyembedding.py 文件源码

def construct_embedding_matrix(self):
        min_delay = numpy.min(self.delays)
        max_delay = numpy.max(self.delays)

        t_list = []
        embedding_list = []
        for i in range(self.x.shape[0]):
            if (i - max_delay < 0) or (i - min_delay) >= self.x.shape[0]:
                continue
            delay_vector = numpy.array([self.x[i - delay] for delay in self.delays])
            if numpy.any(numpy.logical_or(numpy.isnan(delay_vector), numpy.isinf(delay_vector))):
                continue
            t_list.append(i)
            embedding_list.append(delay_vector)

        if len(embedding_list) == 0:
            self.t = numpy.array(t_list, dtype=float)
            self.embedding_mat = numpy.zeros((0, len(self.delays)), dtype=float)
        else:
            self.t = numpy.array(t_list)
            self.embedding_mat = numpy.array(embedding_list)
            assert self.embedding_mat.shape[1] == len(self.delays)