neuralynx.py 文件源码

def read_chunk(self, idx, chunk_size, padding=(0, 0), nodes=None):

        t_start, t_stop = self._get_t_start_t_stop(idx, chunk_size, padding)
        local_shape     = t_stop - t_start

        if nodes is None:
            nodes = numpy.arange(self.nb_channels)

        local_chunk = numpy.zeros((local_shape, len(nodes)), dtype=self.data_dtype)
        data_slice  = self._get_slice_(t_start, t_stop) 

        self._open()
        for count, i in enumerate(nodes):
            local_chunk[:, count] = self.data[i][data_slice]
        self._close()

        return self._scale_data_to_float32(local_chunk)