def __distributor_setup__(self, **kwargs):
"""
A `SparseDistributor` handles the SparseFunction decomposition based on
physical ownership, and allows to convert between global and local indices.
"""
return SparseDistributor(kwargs['npoint'], self._sparse_dim,
kwargs['grid'].distributor)
def __shape_setup__(cls, **kwargs):
grid = kwargs.get('grid')
# A Grid must have been provided
if grid is None:
raise TypeError('Need `grid` argument')
shape = kwargs.get('shape')
npoint = kwargs['npoint']
if shape is None:
glb_npoint = SparseDistributor.decompose(npoint, grid.distributor)
shape = (glb_npoint[grid.distributor.myrank], )
return shape
def __shape_setup__(cls, **kwargs):
grid = kwargs.get('grid')
# A Grid must have been provided
if grid is None:
raise TypeError('Need `grid` argument')
shape = kwargs.get('shape')
npoint = kwargs['npoint']
if shape is None:
glb_npoint = SparseDistributor.decompose(npoint, grid.distributor)
shape = (glb_npoint[grid.distributor.myrank],)
return shape