parameters: (volume, kernel, mode)
return_statement: return np_conv_ok and (volume.size >= kernel.size or mode != 'same')
docstring: See if numpy supports convolution of `volume` and `kernel` (i.e. both are
      1D ndarrays and of the appropriate shape).  Numpy's 'same' mode uses the
      size of the larger input, while Scipy's uses the size of the first input.
docstring_summary: See if numpy supports convolution of `volume` and `kernel` (i.e. both are
      1D ndarrays and of the appropriate shape).  Numpy's 'same' mode uses the
      size of the larger input, while Scipy's uses the size of the first input.
docstring_tokens: See if numpy supports convolution of volume and kernel ( i . e . both are 1D ndarrays and of the appropriate shape ) . Numpy s same mode uses the size of the larger input while Scipy s uses the size of the first input .
function: def _np_conv_ok(volume, kernel, mode):
      """
      See if numpy supports convolution of `volume` and `kernel` (i.e. both are
      1D ndarrays and of the appropriate shape).  Numpy's 'same' mode uses the
      size of the larger input, while Scipy's uses the size of the first input.
      """
      np_conv_ok = volume.ndim == kernel.ndim == 1
      return np_conv_ok and (volume.size >= kernel.size or mode != 'same')
function_tokens: def _np_conv_ok ( volume , kernel , mode ) : np_conv_ok = volume . ndim == kernel . ndim == 1 return np_conv_ok and ( volume . size >= kernel . size or mode != 'same' )