def interpolate_data(self, propname, mode='mean'):
r"""
Determines a pore (or throat) property as the average of it's
neighboring throats (or pores)
Parameters
----------
propname: str
The dictionary key to the values to be interpolated.
mode : str
The method used for interpolation. Options are 'mean' (default),
'min', and 'max'.
Returns
-------
vals : ndarray
An array containing interpolated pore (or throat) data
Examples
--------
>>> import openpnm as op
>>> pn = op.network.Cubic(shape=[3, 1, 1])
>>> pn['pore.value'] = [1, 2, 3]
>>> pn.interpolate_data('pore.value')
array([1.5, 2.5])
"""
from openpnm.models.misc import from_neighbor_throats, from_neighbor_pores
if propname.startswith('throat'):
values = from_neighbor_throats(target=self,
prop=propname,
mode=mode)
elif propname.startswith('pore'):
values = from_neighbor_pores(target=self, prop=propname, mode=mode)
if hasattr(self[propname], 'units'):
values *= self[propname].units
return values
def from_neighbor_pores(target, pore_prop='pore.seed', mode='min'):
return _misc.from_neighbor_pores(target=target,
pore_prop=pore_prop,
mode=mode)
def from_neighbor_pores(target, prop='pore.diameter', mode='min'):
return _misc.from_neighbor_pores(target=target, prop=prop, mode=mode)
def from_neighbor_pores(target, pore_prop='pore.seed', mode='min'):
return _misc.from_neighbor_pores(target=target, pore_prop=pore_prop,
mode=mode)