Material anisotropy along a curve?

Hello,
For an electro ohmic quasistatic simulation, there is a check mark to specify a material setting as anisotropic, which will enable fields to enter conductivity on and off the diagonal of xx/yy/zz. As far as I understand it, this works well for a geometry with a fixed orientation/axis, but is there a way to specify the anisotropy with respect to a spline used to create the geometry (such as for muscles or nerves)? One might imagine this as using a local coordinate system rather than the global coordinate system.
Thank you for the help 
For this you would need to use the homogeneous anisotropic conductivity. The easiest way to use that feature I think, may be to create the field distribution in Python as a FloatFieldData on a RectilinearGrid and add this to the Analysis tree via the "TrivialProducer". You can then select the anisotropic conductivity from the Analysis pipeline.
Anisotropic conductivity distributions along a spline are sometimes computed by solving a Poisson equation in a tube, with Dirichlet boundary conditions at the top and bottom. This gives a main direction for the anisotropic tensor along the spline. You can create a tube from a spline using the "Thicken Wire" tool (or in Python: XCoreModeling.ThickenWire).
Since this seems to be an important question, maybe somebody who has a working script to assign homogeneous anisotropic conductivities can share it here as a reference.

Something to get started to create an anisotropic conductivity tensor for S4L from solving a Poisson equation with boundary conditions (running an EM simulation and using its potential). Once the field is created in the analysis tab it can be used as a part of a new EM simulation for any material selected to have inhomogeneous and anisotropic properties.
import numpy as np import s4l_v1.document as document import s4l_v1.model as model import s4l_v1.simulation.emlf as emlf from s4l_v1 import ReleaseVersion, Unit from s4l_v1.model import Vec3, Translation, Rotation import s4l_v1.units as units import s4l_v1.analysis as analysis import XCoreModeling def CreateMockAnisotropicConductivity(sim): # Transversal and longitudinal sigmas sigma1 = 3.0 sigma2 = 1.0 # here conductivity has 6 component (anisotropic tensor) results = sim.Results() p = results["Overall Field"].Outputs["EM Potential(x,y,z,f0)"] p.Update() e = results["Overall Field"].Outputs["EM E(x,y,z,f0)"] e.Update() e_field = e.Data.Field(0) nc = e.Data.Grid.NumberOfCells print "E Field shape", e_field.shape print "Number of Cells", nc # E Field shape (nc, 3)  Cell centered # Calculate sigma on cell centers print "Calculate anisotropic sigma values" sigma_wm = np.zeros([nc,6]) # 6 unique values # tensor component indexing for solver iu3 = (np.array([0, 1, 2, 0, 1, 0], dtype=np.int64), np.array([0, 1, 2, 1, 2, 2], dtype=np.int64)) for idx, val in enumerate(e_field): tmp = np.zeros([3,3], dtype=np.complex) tmp[0] = val if (not np.isnan(val).any() and np.inner(val, val) != 0): P = np.dot(tmp.T, tmp) / np.inner(val,val) else: P = np.full((3, 3), 0, dtype=np.complex) sigma_tensor = sigma1*P + sigma2*( np.identity(P.shape[0])  P ) sigma_wm[idx] = sigma_tensor[iu3].real sigma_swapped = sigma_wm[:,[0,1,2,3,5,4]] # Fix bug where yz and xz were swapped tensor_conductivity = analysis.core.DoubleFieldData() tensor_conductivity.NumberOfSnapshots = 1 tensor_conductivity.NumberOfComponents = 6 tensor_conductivity.Grid = e.Data.Grid.Clone() tensor_conductivity.ValueLocation = analysis.core.eValueLocation.kCellCenter tensor_conductivity.SetField(0, sigma_swapped) #sigma_wm) # Fix bug where yz and xz were swapped tensor_conductivity.Quantity.Name = 'Anisotropic Conductivity From E Field' tensor_conductivity.Quantity.Unit = analysis.core.Unit('S/m') producer_t = analysis.core.TrivialProducer() producer_t.SetDataObject(tensor_conductivity) producer_t.Name = 'Anisotropic Conductivity' document.AllAlgorithms.Add(producer_t)