generic_function¶
- openpnm.models.misc.simple_equations.generic_function(target, prop, func, **kwargs)[source]¶
Runs an arbitrary function on the given data
This allows users to place a customized calculation into the automatated model regeneration pipeline.
- Parameters
target (Base) – The object which this model is associated with. This controls the length of the calculated array, and also provides access to other necessary properties.
prop (str) – The dictionary key containing the array to be operated on
func (Numpy function) – A handle to the function to apply
kwargs (keyward arguments) – All arguments required by the specific Numpy function
- Returns
result – Array containing
func(target[prop], **kwargs)
.- Return type
ndarray
Examples
The following example shows how to use a Numpy function, but any function can be used, as long as it returns an array object:
>>> import openpnm as op >>> import numpy as np >>> pn = op.network.Cubic(shape=[5, 5, 5]) >>> geo = op.geometry.GenericGeometry(network=pn, pores=pn.Ps, throats=pn.Ts) >>> geo['pore.rand'] = np.random.rand(geo.Np) >>> geo.add_model(propname='pore.cos', ... model=op.models.misc.generic_function, ... func=np.cos, ... prop='pore.rand')