The problem has been resolved! Thank you for your assistance!

BTW. this is a temporary fix, which breaks inline plotting with matplotlib. We have fixed it in the release branch. A slightly improved workaround may be to temporarily unset the MPLBACKEND environment variable before the call to HeadModelGeneration, e.g. something like this import os original_backend = os.environ.pop("MPLBACKEND", None) labelfield = HeadModelGeneration( images=image_list, add_dura=True, close_skin=True, close_csf=True, close_skull=True, version=ImageML.eHeadModel.head16, ) if original_backend is not None: os.environ["MPLBACKEND"] = original_backend

thanks for this feedback. we will try to add more examples that demonstrate how to use/modify anatomical models, triangle meshes, etc.

I tried to reproduce this doing the following. I create three entities a cylinder copy it and convert the copy to a triangle mesh generate an unstructured tetrahedral mesh Then I drag these entities to the Analysis (ModelToGridFilter in Python API). I tried to use the surface viewer, but since they have no fields, nothing is displayed (this changed since 7.0 or before - it used to display a white surface). To generate a field I used the Calculator, and added expressions like coordsY*jHat, i.e. (0, coordsY, 0) where coordsY is the y-coordinate from the points in the geometry. Create a vector viewer for each (from the left: Solid Body, TriangleMesh, UnstructuredMesh). The third one samples vector values using Line/Plane/Box sources. [image: 1749109986009-d5bc2f0e-af54-4fca-8265-1431e94207ca-image.png] To get the vectors on the surface of the UnstructuredMesh, I had to first extract the surface, via Field Data Tools -> Surface Filter [image: 1749110185730-938040d9-2fcf-4cad-a42e-7c2f0d4592ec-image.png] The generated Python ("To Python' in context menu) script for item 5 was: # This script was auto-generated by Sim4Life version 8.2.0.16890 import numpy import s4l_v1.analysis as analysis import s4l_v1.document as document import s4l_v1.model as model import s4l_v1.units as units from s4l_v1 import ReleaseVersion from s4l_v1 import Unit try: # Define the version to use for default values ReleaseVersion.set_active(ReleaseVersion.version8_2) # Creating the analysis pipeline # Adding a new ModelToGridFilter inputs = [] model_to_grid_filter = analysis.core.ModelToGridFilter(inputs=inputs) model_to_grid_filter.Name = "Cylinder 3" model_to_grid_filter.Entity = model.AllEntities()["Cylinder 3"] model_to_grid_filter.UpdateAttributes() document.AllAlgorithms.Add(model_to_grid_filter) # Adding a new FieldCalculator inputs = [model_to_grid_filter.Outputs["Unstructured Grid"]] field_calculator = analysis.field.FieldCalculator(inputs=inputs) field_calculator.Expression = u"coordsZ*kHat" field_calculator.UpdateAttributes() document.AllAlgorithms.Add(field_calculator) # Adding a new FieldSurfaceFilter inputs = [field_calculator.Outputs["Result(x,y,z)"]] field_surface_filter = analysis.field.FieldSurfaceFilter(inputs=inputs) field_surface_filter.UpdateAttributes() document.AllAlgorithms.Add(field_surface_filter) # Adding a new VectorFieldViewer inputs = [field_surface_filter.Outputs["Result(x,y,z)"]] vector_field_viewer = analysis.viewers.VectorFieldViewer(inputs=inputs) vector_field_viewer.Data.Phase = u"0°" vector_field_viewer.Vector.Plane.PlaneCenter = numpy.array([0.05300000309944153, -0.03099999949336052, 0.012000000104308128]) vector_field_viewer.UpdateAttributes() document.AllAlgorithms.Add(vector_field_viewer) except Exception as exc: import traceback traceback.print_exc() # Reset active version to default ReleaseVersion.reset() raise(exc)

This is in an older version of sim4life 8.0, maybe the problem has already been fixed. Otherwise I think this was a multiport simulation but I forget now... Maybe that could be a strange bug where it works for multi but not single or vise versa.

So my problem was solved for the simple phantom a sphere. It can be voxeled. I am having a discussion with chatgpt about how to load Duke into the simulation section because currently it wont be voxeled. Is there a simple few lines of code that loads Duke and all the default tissue electrical properties or is it necessary to assign each tissue type in a loop or via thousands lines of code (as I have seen elsewhere)....

@Sylvain I exported the electric field results from an AC simulation and found that the last six columns of the data are imaginary numbers. Are these the electric field values in three different directions? Why aren't they time-varying? Did I only export the peak values?

Hi, You would get that error if there was no simulation named "0_17_35_29" in the currently opened document. Maybe you should check what simulations you have in your project and if you do have a simulation with that name? One way to list all simulation names via python is to run something like: for s in document.AllSimulations: print(s.Name)

@halder When I performed TI simulation using the spherical model, I found that if I changed the current direction of one pair of electrodes, the maximum value of the TI Max (x, y, z) slice remained unchanged. Changing the current of one pair of electrodes should have shifted from the original same-direction superposition to a reverse weakening, so why does it remain unchanged? Is it because Max Modulation only uses EM for calculations?

Hi, you can try something like the following to extract the reflection coefficient. You can always try to build extraction manually once and select "To python" by right-clicking on the end of the tree (i.e. the component you extract from your pipeline) import numpy import s4l_v1.analysis as analysis import s4l_v1.document as document import s4l_v1.model as model import s4l_v1.units as units from s4l_v1 import ReleaseVersion from s4l_v1 import Unit sim_name = "MRI Volume Coil Cleg = 29.5 pF" ###### define the sim name in this case this is a multiport FDTD simulation Adding a new EmMultiPortSimulationExtractor simulation = document.AllSimulations[sim_name] em_multi_port_simulation_extractor = simulation.Results() this is extracting a port inputs = [em_multi_port_simulation_extractor.Outputs["MRI Volume Coil Cleg = 29.5 pF - Endring source 1 (Birdcage 1)"]] em_port_simulation_extractor = analysis.extractors.EmPortSimulationExtractor(inputs=inputs) em_port_simulation_extractor.Name = "MRI Volume Coil Cleg = 29.5 pF - Endring source 1 (Birdcage 1)" em_port_simulation_extractor.UpdateAttributes() document.AllAlgorithms.Add(em_port_simulation_extractor) em_sensor_extractor = em_port_simulation_extractor["Endring source 1 (Birdcage 1)"] document.AllAlgorithms.Add(em_sensor_extractor) ref_coef_data = em_sensor_extractor.Outputs["Reflection Coefficient(f)"] ref_coef_data.Update() freqlist = ref_coef_data.Data.Axis ref_coef = refCoeff.Data.GetComponent(0) ref_coef_magnitude = np.sqrt(np.real(ref_coef)**2 + np.imag(ref_coef)**2) import matplotlib.pyplot as plt plt.plot(freqlist,ref_coef_magnitude)

As far as I'm aware it is not possible to suppress those messages. Maybe try writing your customized messages into a log file instead?

Hi! In all the tutorial python scripts this is shown. Within the python scripter you can click on the folder icon and choose "Open Example Script". There you will find lots of python scripts, that show how this is done. Here a small excerpt from the script "tutorial_emlf_parallel_plate.py": sim = CreateSimulation() s4l_v1.document.AllSimulations.Add(sim) sim.UpdateGrid() sim.CreateVoxels(path) sim.RunSimulation(wait=True) I suggest always creating a simulation, and an analysis function, that is then called in the RunTutorial function. It's best to then also create a main: def RunTutorial( path ): import s4l_v1.document s4l_v1.document.New() CreateModel() sim = CreateSimulation() s4l_v1.document.AllSimulations.Add(sim) sim.UpdateGrid() sim.CreateVoxels(path) sim.RunSimulation(wait=True) AnalyzeSimulation(sim) def main(data_path=None, project_dir=None): """ data_path = path to a folder that contains data for this simulation (e.g. model files) project_dir = path to a folder where this project and its results will be saved """ import sys import os print("Python ", sys.version) print("Running in ", os.getcwd(), "@", os.environ['COMPUTERNAME']) if project_dir is None: project_dir = os.path.expanduser(os.path.join('~', 'Documents', 's4l_python_tutorials') ) if not os.path.exists(project_dir): os.makedirs(project_dir) fname = os.path.splitext(os.path.basename(_CFILE))[0] + '.smash' project_path = os.path.join(project_dir, fname) RunTutorial( project_path ) if __name__ == '__main__': main()

Thank you, I could obtain the same also using this: analysis.exporters.MatlabExporter.ExportTo(matlab_exporter,matlab_exporter.FileName) Do you think it is a good solution as well?

You can open a smash file using import s4l_v1 as s4l s4l.document.Open(smash_file_path) You can save it using s4l.document.Save(smash_file_path) You can find a simulation using (assuming you have unique simulation names sim = [sim for sim in s4l.document.AllSimulations if sim.Name == "the name of your simulation"][0] If you want to load different models (from .sab file or .smash), but don't need to load e.g. simulations (in .smash file), you can import the file entities = s4l.model.Import(file_path) if you need to reset the document or model because you are accumulating too many entities and memory use is getting too high, you can use e.g. # reset the model sl4.model.Clear() # or keep entities, but discard model history import XCoreModeling as xcm xcm.GetActiveModel().ClearHistory() # or reset entire document (reset model, simulations, analysis) s4l.document.New()