cunfft.py 文件源码

def run(self, data, memory=None, **kwargs):
        """
        Run the adjoint NFFT on a batch of data

        Parameters
        ----------
        data: list of tuples
            list of [(t, y, w), ...] containing
            * ``t``: observation times
            * ``y``: observations
            * ``nf``: int, size of NFFT
        memory:
        **kwargs

        Returns
        -------
        powers: list of np.ndarrays
            List of adjoint NFFTs

        """
        if not hasattr(self, 'prepared_functions') or \
            not all([func in self.prepared_functions
                     for func in self.function_names]):
            self._compile_and_prepare_functions(**kwargs)

        if memory is None:
            memory = self.allocate(data, **kwargs)

        nfft_kwargs = dict(block_size=self.block_size)
        nfft_kwargs.update(kwargs)

        results = [nfft_adjoint_async(mem, self.function_tuple,
                                      **nfft_kwargs)
                   for mem in memory]

        return results