Unimplemented Python Features

Introduction

CSXCAD and openEMS began as C++ programs driven by users via Matlab/Octave, the Python bindings came relatively late in the project’s history. As a result, not all C++ and Matlab/Octave features are currently implemented in Python.

One can classify these missing features into two categories.

The C++ API was not linked to Python.

Solving this problem is relatively easy. One can add the missing C++ API binding without reimplementating any logic.

Both developers and ordinary openEMS users have contributed high-level pre-processing and post-processing features, but only specific to Matlab/Octave. Examples include numerical fitting code and model exporting code.

This problem is more difficult to solve, as the same logic must be reimplemented in Python.

The following list is list of missing Python features for reference by developers and end users.

Known Problems

Some model importing and exporting functions are unimplemented

Type 2: Missing high-level feature.
Affected APIs: ImportPLY(), ImportSTL(), export_gerber(), export_excellon(), export_povray().
Workaround: To import an STL file, use AddPolyhedronReader(). To export models, use AppCSXCAD.

Many transmission line ports are unimplemented

Type 2: Missing high-level feature.
Affected APIs: AddCurvePort(), AddStripLinePort(), AddCPWPort(), AddCircWaveGuidePort().
Workaround:

1. Create Excitation: Create the required excitations manually via AddExcitation(), with SetWeightFunction() to set the required field pattern, derive Primitives of the required geometrical shape.

2. Create Probes: Along the transmission line, add voltage and current probes with AddProbe(), derive Primitives of the required geometrical shape, and finally calculate S-parameters from measured raw voltage and currents.

Mur ABC phase velocity parameter adjustment is unimplemented

Type 1: Missing C++ binding.
Affected APIs: SetBoundaryCond()’s optional argument MUR_PhaseVelocity is unimplemented. Mur’s ABC cannot be further optimized by tuning MUR_PhaseVelocity if the boundary doesn’t end at a vacuum.
Workaround: None.

Dispersive materials are not implemented.

Type 1+2: Missing C++ binding and high-level feature.
Affected APIs: AddDebyeMaterial(), AddDjordjevicSarkarMaterial(), AddLorentzMaterial(), CalcDebyeMaterial(), CalcDjordjevicSarkarApprox(), CalcDrudeMaterial() CalcLorentzMaterial()
Workaround:
- For AddDebyeMaterial(), AddLorentzMaterial(), manually create the respective CSXCAD objects via fromType() or fromTypeName(), and manually set the model parameters via SetAttributeValue().
- For AddDjordjevicSarkarMaterial(), CalcDebyeMaterial(), CalcDjordjevicSarkarApprox(), CalcDrudeMaterial(), CalcLorentzMaterial(), no workaround is available. These Octave functions are helper functions that calculate the model’s output curves for the purpose of fitting parameters and preparing a simulation. No C++ APIs exist because they’re not actually used in the simulation.

Delay fidelity post-processing for UWB systems is unimplemented

Type 2: Missing high-level feature.
Affected API: DelayFidelity()
Workaround: None.
Comment: This is a specialized post-processing function involved in the design of ultra-wideband radios and radars. In these applications it is important to know the delay and fidelity of RF pulses. The delay is the retardation of the signal from the source to the phase center of the antenna. It is composed out of linear delay, dispersion and minimum-phase delay. Dispersion due to waveguides or frequency-dependent permittivity and minimum-phase delay due to resonances will degrade the fidelity which is the normalized similarity between excitation and radiated signal.

CTB and scikit-rf Post-Processing

You may encounter Circuit Toolbox (CTB) in openEMS simulations, which is Matlab/Octave exclusive. However, this is not a “missing feature”.

CTB is developed by openEMS’s author Thorsten Liebig and is used with openEMS in some examples, but it’s an independent library outside openEMS’s codebase. It contains network parameter calculation functions to help analyzing simulation outputs, but they’re themselves not part of the simulator.

To analyze RF circuits in Python, use other Python RF engineering libraries, such as scikit-rf. This is a 3rd-party project not associated with openEMS (although the author of this page happens to be a contributor of both).

Consersely, scikit-rf contains many sophisticated calibration, de-embedding and signal transform algorithms which represented multiple years of work. If you encounter openEMS examples with scikit-rf, Matlab/Octave alternatives would be even less straightforward to find.

Note

Development idea: To lower the language barrier, as developers, perhaps we can provide some standalone, single-purpose Octave and Python tools callable from the command-line tools, such as a Lorentz material fitter in Octave, or a SOLT calibration tool in Python? This enables users to perform a task without using the language.