CircuitModel View reference

The model view reference describes the different objects related to circuit modeling.

For a tutorial on defining compact models and circuits, please check the circuit modeling tutorial.

Instances of CircuitModelView

class ipkiss3.all.ModelInstance

Instances to other models.

reference: CompactModelView, required
name: ( String that contains only alphanumeric characters from the ASCII set or contains _$<>. ASCII set is extended on PY3. ), optional, *None allowed*

Unique name of the instance within the scope of the View/Cell

owner: ( _View ), optional, *None allowed*

link to the owner of the instance.In most cases this is automatically added by the _generate_instances method

Defining and testing models and model view


The CircuitModelView calculates a CompactModel with a circuit solver


Base class to define a compact model, which approximates the behavior of a device using an S-matrix or a set of differential equations.


A hierarchical model is a model of a circuit, that describes the circuit in terms of model instances, nets (to connect the instances), and terms.


Component that can be placed in a circuit (attached to an existing port) to 'measure' the light.


Component that can be placed in a circuit (attached to an existing port) to send a signal into the chip.


A 3D matrix.


Numerical S-matrix model consisting of a univariate B-spline representations over wavelength.


Test a compact model by running a wavelength sweep.


Map the terms of a model to different names

Spectrum analysis

High-level interface:

SpectrumAnalyzer and Spectrum give a convenient interface to analyze a group of spectra for different channels of a device or an individual spectrum, respectively.


Tool to analyze the transmission spectra of an S-matrix.


Object representing a transmission spectrum.

Low-level functions

If SpectrumAnalyzer or Spectrum don’t satisfy your needs you can also use the lower-level analysis functions:

spectrum_peaks(smatrix1dsweep[, port_pairs, ...])

Extract information about the peaks in the given S-parameter spectra


Return the power for each sample in the given spectrum: abs(y)**2


Return the power in dB for each sample in the given spectrum: 20 * log10(abs(y))

find_peaks(x, y[, method, threshold, ...])

Find peaks in data varying in one parameter.

find_peaks_spline(x, y[, threshold, smoothing])

Find peaks in data varying in one parameter by means of a spline fit.

find_peaks_cwt(x, y[, threshold])

Find peaks in data varying in one parameter by means of a wavelet convolution