ipkiss3.all.circuit_sim.SMatrix1DSweep

class ipkiss3.all.circuit_sim.SMatrix1DSweep(**kwargs)

A 3D matrix. The first two dimensions are related to the terms, the last dimension is related to a 1D sweep (i.e., wavelength sweep).

Parameters:

sweep_parameter_name: str, required

Name of the parameter that is swept, e.g. ‘frequency’, ‘wavelength’

sweep_parameter_values: required

Values that are swept

sweep_parameter_unit: ( str ), optional, *None allowed*

Unit of the sweep parameter, e.g. ‘GHz’, ‘um’. None = unknown.

n_ports: int and number > 0, optional

The number of simulated ports

symmetric: ( bool, bool_, bool or int ), optional

When True, the matrix is assumed to be symmetrical, and the associated component is a reciprocal component. This means the transmission from port x to y is equal to the transmission from port y to x.

term_modes: OrderedTypedDict, optional

dictionary with { name (type: string) : (term_name(type:string), mode (type: int/str)) } pairs These are the (term-mode) pairs associated with the SMatrix. The dimension of the SMatrix equals len(term_modes) x len(term_modes). This dict is ordered: the order depends on the order they were added. This is useful if you want to ‘bulk’ set the S-matrix, S[:, :] = [[0, 1, 0], [0, 0, 1], [1, 0, 0]] : without the order information, setting these values is ambiguous.

terms: ( OrderedNamedTypedDict ), optional, *None allowed*

When term_modes is not given, we extract it from the the terms The term_modes pairs are added in consequetive blocks for each mode. The term_mode name is the following: - term_name, for the first mode with index 0: in - term_name_mode# for the modes with index higher than 0: in_1, in_2, in_3

data: optional

Stores the raw data of the simulation results

dtype: type, optional

Type of the numpy array. By default, this is a complex number, because the scatter matrix contains both amplitude and phase information.

term_mode_map: optional, *None allowed*

A dictionary that maps term,mode tuples to indices in the data array

static from_touchstone(filename, term_mode_map=None, unit=None)

Imports an S matrix frequency sweep from a touchstone file. More information on the touchstone file format can be found in this document.

Parameters:

filename: str

filename to import

term_mode_map: dict

Maps (term, modenr) to TouchStone port_mode numbers. Use None for first attempting to derive from tool-specific parsing of the file header and when that fails assign default port names

unit: str

When specified, the sweep values will be converted to this unit. e.g. when the unit is ‘um’ the sweep_parameter_values will be in micrometer instead of the unit used in the touchstone file.

Returns:

smatrix: SMatrix1DSweep

1D S matrix sweep

Examples

In this example we import a Touchstone file named ‘smatrix_fdtd.s6p’, made using the IPKISS-Lumerical link. You can download the Touchstone file and try the example below yourself. It represents a component with one input port and two output ports, where each port has 2 modes assigned to it. This configuration produces the number 6 (= 3 ports x 2 modes) in the extension. Also note how the file has a header containing metadata about the ports:

! Touchstone file export IPKISS-Lumerical FDTD link
! Luceda port in:mode 0:0
! Luceda port in:mode 1:1
! Luceda port out2:mode 0:2
! Luceda port out2:mode 1:3
! Luceda port out1:mode 0:4
! Luceda port out1:mode 1:5

This metadata is used by our importer if term_mode_map is set to None. It represents a mapping between ports in IPKISS/Lumerical and the Touchstone port numbers. For example, the second line maps the IPKISS port in:0 (= port in:mode 1) to Touchstone port 0.

import ipkiss3.all as i3
from ipkiss3.io.touchstone import import_touchstone_smatrix
import matplotlib.pyplot as plt
import numpy as np

S = import_touchstone_smatrix('smatrix_fdtd.s6p')

plt.figure()
plt.plot(S.sweep_parameter_values, np.abs(S["out1", "in"])**2, 'o--', label='in->out1', markersize=5)
plt.plot(S.sweep_parameter_values, np.abs(S["out2", "in"])**2, 'o--', label='in->out2', markersize=5)
plt.xlabel('frequency [GHz]')
plt.ylabel('magnitude')
plt.title('S-parameters')
plt.legend()
plt.show()

The next example shows how to set your own term_mode_map:

import ipkiss3.all as i3
from ipkiss3.io.touchstone import import_touchstone_smatrix
import matplotlib.pyplot as plt
import numpy as np
touchstone_4port = '''! 4-port S-parameter data, taken at three frequency points
# GHZ S MA R 50
5.00000 0.60 161.24 0.40 -42.20 0.42 -66.58 0.53 -79.34 !row 1
        0.40 -42.20 0.60 161.20 0.53 -79.34 0.42 -66.58 !row 2
        0.42 -66.58 0.53 -79.34 0.60 161.24 0.40 -42.20 !row 3
        0.53 -79.34 0.42 -66.58 0.40 -42.20 0.60 161.24 !row 4
6.00000 0.57 150.37 0.40 -44.34 0.41 -81.24 0.57 -95.77 !row 1
        0.40 -44.34 0.57 150.37 0.57 -95.77 0.41 -81.24 !row 2
        0.41 -81.24 0.57 -95.77 0.57 150.37 0.40 -44.34 !row 3
        0.57 -95.77 0.41 -81.24 0.40 -44.34 0.57 150.37 !row 4
7.00000 0.50 136.69 0.45 -46.41 0.37 -99.09 0.62 -114.19 !row 1
        0.45 -46.41 0.50 136.69 0.62 -114.19 0.37 -99.09 !row 2
        0.37 -99.09 0.62 -114.19 0.50 136.69 0.45 -46.41 !row 3
        0.62 -114.19 0.37 -99.09 0.45 -46.41 0.50 136.69 !row 4
'''
filename = "touchstone_4port_example.s4p"

with open(filename, 'w') as f:
    f.write(touchstone_4port)

term_mode_map = {
    ("opt1", 0): 0,
    ("opt2", 0): 1,
    ("opt3", 0): 2,
    ("opt4", 0): 3
}

S = import_touchstone_smatrix(filename, term_mode_map=term_mode_map)

plt.figure()
plt.plot(S.sweep_parameter_values, np.abs(S["opt2", "opt1"])**2, 'o--', label='opt1->opt2', markersize=5)
plt.plot(S.sweep_parameter_values, np.abs(S["opt3", "opt1"])**2, 'o--', label='opt1->opt3', markersize=5)
plt.plot(S.sweep_parameter_values, np.abs(S["opt4", "opt1"])**2, 'o--', label='opt1->opt4', markersize=5)
plt.xlabel('frequency [GHz]')
plt.ylabel('magnitude')
plt.title('S-parameters')
plt.legend()
plt.show()

passivity_check()

Check if the SMatrix1DSweep is passive.

Parameters:

smatrix1dsweep: SMatrix1DSweep

stores the SMatrices from a sweep

Returns:

indices: A numpy array that contains the indices of the sweep values that

are not passive

Examples

>>> smat = i3.device_sim.SMatrix1DSweep.from_touchstone('mydc.s4p')
>>> indices = smat.passivity_check()
>>> non_passivity_wls = smat.sweep_parameter_values[indices]
>>> is_passive = len(indices) == 0

reciprocity_check()

Check if the SMatrix1DSweep is reciprocal.

Parameters:

smatrix1dsweep: SMatrix1DSweep

stores the SMatrices from a sweep

Returns:

indices: A numpy array that contains the indices of the sweep values that

are not reciprocal

Examples

>>> smat = i3.device_sim.SMatrix1DSweep.from_touchstone('mydc.s4p')
>>> indices = smat.reciprocity_check()
>>> non_reciprocal_wls = smat.sweep_parameter_values[indices]
>>> is_reciprocal = len(indices) == 0