ZMT zurich med tech

Thank you. Uploaded.

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)

sending you an email via support

[image: 1736961843959-327c9ace-0099-4e59-b102-4a34c31e609c-sim4life_fxfwepw8sg.gif] to extract the inner normal vector to the cortical surface mask the field (set NaN outside GM) using the Mask Filter available under "Field Data Tools" in the top ribbion. add the Grey Matter Surface in the post-pro interpolate the (masked) field to the grey matter surface using the "Interpolator" which is active when the masked field and surface is selected. get the normal component via the NormalFieldEvaluator under the "Field Data Tools"

Okay, I will take those considerations into account. Thanks for the fast reply!

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?

@bryn Is the 6.8 displayed on the color bar the actual maximum field strength value? I exported the values and found that the maximum is around 5.9 instead. [image: 1735124755536-42fb974e-d830-42c2-8373-84c85ee63339-image.png]

@bryn @gc00 @halder Thank you so much, You've been very helpful !

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()

@ofli Can the conductivity map after head segmentation be exported?

I want to see the impact of different grid sizes on the simulation, so I cloned a pair of simulations and modified the maximum step size of the grid. However, I found that if I create a new pair of simulations using the same settings, the grid sizes, simulation durations, and results of the new simulations and the cloned simulations are all different. Why does this happen?