Public API: opics package

components types

components.componentModel(f, data_folder, …)

Defines the base component model class used to create new components for a library.

components.compoundElement(f, s[, nets])

Defines the properties of a compound element or simulated component.

components.Waveguide(f, length, data_folder, …)

Defines the properties of a waveguide component, can be used in the interconnected between components.

opics.components module

class opics.components.Waveguide(f, length, data_folder, filename, TE_loss, **kwargs)[source]

Bases: opics.components.componentModel

Defines the properties of a waveguide component, can be used in the interconnected between components.

load_sparameters(length, data_folder, filename, TE_loss)[source]

read s_parameters

class opics.components.componentModel(f, data_folder, filename, nports=0, sparam_attr='', **kwargs)[source]

Bases: object

Defines the base component model class used to create new components for a library.

get_data(ports=None, xscale='freq', yscale='log')[source]

Get the S-parameters data for specific [input,output] port combinations, to be used for plotting functionalities. (WARNING: unused, to be used in plot_sparameters)

Parameters

  • ports (list, optional) – List of lists that contains the desired S-parameters, e.g., [[1,1],[1,2],[2,1],[2,2]]. Defaults to None.

  • xscale (str, optional) – Plotting x axis label. Defaults to “freq”.

  • yscale (str, optional) – Plotting Y axis label. Defaults to “log”.

Returns

temp_data (dict) – Dictionary containing the plotting information to be used, including S-parameters data and plotting labels.

interpolate_sparameters(target_f, source_f, source_s)[source]

Cubic interpolation of the component sparameter data to match the desired simulation frequency range.

Parameters

  • target_f (numpy.ndarray) – The target frequency range onto which the s-parameters will be interpereted on.

  • source_f (numpy.ndarray) – The source frequency range that the component data has stored.

  • source_s (numpy.ndarray) – The source s-parameters that the component data has stored.

Returns

sparameters (numpy.ndarray) – Interpolated s-parameters value over the target frequency range.

load_sparameters(data_folder, filename)[source]

Decides whether to load sparameters from npz file or from a raw sparam file or from a look-up table (for tunable components with attributes).

Parameters

  • data_folder (pathlib.Path) – The location of the data folder containing s-parameter data files and a look up table.

  • filename (str) – File name of the component.

Returns

sparameters (numpy.ndarray) – Array of the component’s s-parameters.

plot_sparameters(ports=None, show_freq=True, scale='log')[source]

Plot the component’s S-parameters.

Parameters

  • ports (list, optional) – List of lists that contains the desired S-parameters, e.g., [[1,1],[1,2],[2,1],[2,2]]. Defaults to None.

  • show_freq (bool, optional) – Flag to determine whether to plot with respect to frequency or wavelength. Defaults to True.

  • scale (str, optional) – Plotting y axis scale, options available: [“log”, “abs”, “abs_sq”]. Defaults to “log”.

write_sparameters(dirpath, filename, f_data, s_data)[source]

Export the simulated s-parameters to a file.

Parameters

  • dirpath (pathlib.Path) – Directory of the filed to be saved.

  • filename (str) – Name of the file to be saved.

  • f_data (numpy.ndarray) – Frequency range data to be exported.

  • s_data (numpy.ndarray) – S-parameter data to be exported.

class opics.components.compoundElement(f, s, nets=None)[source]

Bases: opics.components.componentModel

Defines the properties of a compound element or simulated component. A compound element is a collection of connected components, inherits componentModel OPICS class.

opics.network module

class opics.network.Network(networkID=None)[source]

Bases: object

specifies the network

add_component(cls, componentID=None)[source]

add component to a network

connect(component_A, port_A, component_B, port_B)[source]

connect two components together

global_to_local_ports(net_id, nets)[source]

returns which components the net_id refers to and their corresponding local ports

initiate_global_netlist()[source]

initiates a global netlist with negative indices, overwrite indices that are used in the circuit with positive values

simulate_network()[source]

function to trigger the simulation of the network

opics.network.interpolate(output_freq=None, input_freq=None, s_parameters=None)[source]

interpolates s-parameters

opics.sparam_ops module

opics.sparam_ops.connect_s(A, k, B, l, create_composite_matrix=True)[source]

connect two n-port networks’ s-matrices together.

specifically, connect port k on network A to port l on network B. The resultant network has nports = (A.rank + B.rank-2). This function operates on, and returns s-matrices. The function connect() operates on Network types.

Parameters

  • A (numpy.ndarray) – S-parameter matrix of A, shape is fxnxn

  • k (int) – port index on A (port indices start from 0)

  • B (numpy.ndarray) – S-parameter matrix of B, shape is fxnxn

  • l (int) – port index on B

Returns

C (numpy.ndarray) – new S-parameter matrix

Notes

internally, this function creates a larger composite network and calls the innerconnect_s() function. see that function for more details about the implementation

See also

connect

operates on Network types

innerconnect_s

function which implements the connection connection algorithm

opics.sparam_ops.innerconnect_s(A, k, l)[source]

connect two ports of a single n-port network’s s-matrix.

Specifically, connect port k to port l on A. This results in a (n-2)-port network. This function operates on, and returns s-matrices. The function innerconnect() operates on Network types.

Parameters

  • A (numpy.ndarray) – S-parameter matrix of A, shape is fxnxn

  • k (int) – port index on A (port indices start from 0)

  • l (int) – port index on A

Returns

C (numpy.ndarray) – new S-parameter matrix

Notes

The algorithm used to calculate the resultant network is called a ‘sub-network growth’, can be found in 1. The original paper describing the algorithm is given in 2.

References

1

Compton, R.C.; , “Perspectives in microwave circuit analysis,” Circuits and Systems, 1989., Proceedings of the 32nd Midwest Symposium on , vol., no., pp.716-718 vol.2, 14-16 Aug 1989. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=101955&isnumber=3167

2

Filipsson, Gunnar; , “A New General Computer Algorithm for S-Matrix Calculation of Interconnected Multiports,” Microwave Conference, 1981. 11th European , vol., no., pp.700-704, 7-11 Sept. 1981. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4131699&isnumber=4131585

opics.utils module

opics.utils.LUT_processor(filedir, lutfilename, lutdata, nports, sparam_attr, verbose=False)[source]

process look up table data

opics.utils.LUT_reader(filedir, lutfilename, lutdata)[source]

reads look up table data

opics.utils.NetlistProcessor(spice_filepath, Network, libraries, c_, circuitData)[source]

process a spice netlist to setup and simulate a circuit.

opics.utils.fromSI(value_)[source]

converts from SI unit values to metric

Parameters

value (str) – a value in SI units, e.g. 1.3u

Returns

float – the value in metric units.

class opics.utils.netlistParser(mainfile_path)[source]

Bases: object

A netlist parser to read spi files generated by SiEPIC tools

readfile()[source]
opics.utils.universal_sparam_filereader(nports, sfilename, sfiledir, format_type='auto')[source]

Function to automatically detect the sparameter file format and use appropriate method to delimit and format sparam data

This function is a unified version of sparameter reader function defined in https://github.com/BYUCamachoLab/simphony