Merge branch 'master' into CircuitPerformance

.github/workflows/publish.yml

@@ -0,0 +1,35 @@
+# This workflows will upload a Python Package using uv when a release is created
+# reference:
+# https://github.com/astral-sh/trusted-publishing-examples/blob/main/.github/workflows/release.yml
+
+name: Publish on PyPI
+
+on:
+  release:
+    types:
+      - created
+
+jobs:
+  build_and_deploy:
+
+    runs-on: ubuntu-latest
+
+    permissions:
+      # IMPORTANT: this permission is mandatory for trusted publishing
+      id-token: write
+
+    steps:
+      - name: Checkout Project
+        uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+
+      - name: Set Up Python
+        run: uv python install
+
+      - name: Build Package
+        run: uv build
+
+      - name: Publish to PyPi
+        run: uv publish  --trusted-publishing always

conda.recipe/meta.yaml

@@ -1,5 +1,5 @@
 {% set name = "scikit-rf" %}
-{% set version = "1.3.0" %}
+{% set version = "1.5.0" %}
 {% set hash_val = "8223204281599ba14b685d7e28b7e361" %}
 
 package:

doc/source/contributing/index.rst

@@ -126,7 +126,7 @@ To run all the tests (except the virtual instruments)
     cd scikit-rf
     # Create environment and install dependencies, needed only once.
     python -m venv .venv
-    python -e[test,visa,netw,xlsx,plot,docs,testspice]
+    pip install -e .[test,visa,netw,xlsx,plot,docs,testspice] --compile
 
     # Activate Environment, needed for all following steps.
     # on Linux Systems

pyproject.toml

@@ -133,7 +133,8 @@ select = ["B", "E", "F", "FA", "I", "NPY", "UP", "W"]
 
 # Ignore some rules for all files
 # E741: ambiguous-variable-name
-ignore = ["E741"]
+# UP031: Use format specifiers instead of percent format
+ignore = ["E741", "UP031"]
 
 [tool.ruff.lint.per-file-ignores]
 # Ignore some rules for some specific files

skrf/__init__.py

@@ -3,7 +3,7 @@
 implemented in Python.
 """
 
-__version__ = '1.3.0'
+__version__ = '1.5.0'
 ## Import all  module names for coherent reference of name-space
 #import io
 

skrf/constants.py

@@ -111,7 +111,7 @@
 S_DEF_HFSS_DEFAULT = 'traveling'
 
 FrequencyUnitT = Literal["Hz", "kHz", "MHz", "GHz", "THz"]
-FREQ_UNITS = {"Hz": 1.0, "kHz": 1e3, "MHz": 1e6, "GHz": 1e9, "THz": 1e12}
+FREQ_UNITS: dict[FrequencyUnitT, float] = {"Hz": 1.0, "kHz": 1e3, "MHz": 1e6, "GHz": 1e9, "THz": 1e12}
 
 SweepTypeT = Literal["lin", "log"]
 CoordT = Literal["cart", "polar"]

skrf/io/csv.py

@@ -47,20 +47,23 @@
 
 
 """
+from __future__ import annotations
+
 import os
 from warnings import warn
 
 import numpy as np
 
 from .. import mathFunctions as mf
 from .. import util
+from ..constants import FREQ_UNITS, FrequencyUnitT
 from ..frequency import Frequency
 from ..network import Network
 
 # delayed imports
 # from pandas import Series, Index, DataFrame
 
-def read_pna_csv(filename, *args, **kwargs):
+def read_pna_csv(filename, *args, **kwargs) -> tuple[str, str, np.ndarray]:
     r"""
     Reads data from a csv file written by an Agilient PNA.
 
@@ -134,6 +137,17 @@ def read_pna_csv(filename, *args, **kwargs):
     # pna uses unicode coding for degree symbol, but we dont need that
     header = header.replace('\xb0','deg').rstrip('\n').rstrip('\r')
 
+    units_dict: dict[str, FrequencyUnitT] = {k.lower(): k for k in FREQ_UNITS.keys()}
+
+    # Get the frequency unit from the header and convert to Hz
+    unit_raw = header.split(',')[0].strip('Freq')[1:-1]
+    try:
+        unit_tmp = unit_raw.lower()
+        if unit_tmp in units_dict:
+            data[:, 0] *= FREQ_UNITS[units_dict[unit_tmp]]
+    except Exception as exc:
+        raise ValueError(f"Could not parse frequency unit '{unit_raw}'") from exc
+
     return header, comments, data
 
 def pna_csv_2_df(filename):
@@ -166,7 +180,7 @@ def pna_csv_2_ntwks2(filename, *args, **kwargs):
     header, comments, d = read_pna_csv(filename)
     ntwk_dict  = {}
     param_set=set([k[:3] for k in df.columns])
-    f = df.index.values*1e-9
+    f = df.index.values
     for param in param_set:
         try:
             s = mf.dbdeg_2_reim(
@@ -179,7 +193,7 @@ def pna_csv_2_ntwks2(filename, *args, **kwargs):
                 df[f'{param} (IMAG)'].values,
                 )
 
-        ntwk_dict[param] = Network(f=f, s=s, name=param, comments=comments)
+        ntwk_dict[param] = Network(f=f, s=s, name=param, comments=comments, f_unit='Hz')
 
 
     try:
@@ -216,8 +230,8 @@ def pna_csv_2_ntwks3(filename):
 
     # set impedance to 50 Ohm (doesn't matter for now)
     z0 = np.ones(np.shape(d)[0])*50
-    # read f values, convert to GHz
-    f = d[:,0]/1e9
+    # read f values
+    f = d[:,0]
 
     name = os.path.splitext(os.path.basename(filename))[0]
 
@@ -236,7 +250,7 @@ def pna_csv_2_ntwks3(filename):
             elif 's22' in h.lower() and 'db' in h.lower():
                 s[:,1,1] = mf.dbdeg_2_reim(d[:,k+1], d[:,k+2])
 
-        n = Network(f=f,s=s,z0=z0, name = name)
+        n = Network(f=f,s=s,z0=z0, name = name, f_unit="Hz")
         return n
 
     else:
@@ -619,16 +633,16 @@ def pna_csv_2_ntwks(filename):
 
     if (d.shape[1]-1)/2 == 0 :
         # this isnt complex data
-        f = d[:,0]*1e-9
+        f = d[:,0]
         if 'db' in header.lower():
             s = mf.db_2_mag(d[:,1])
         else:
             raise (NotImplementedError)
         name = os.path.splitext(os.path.basename(filename))[0]
-        return Network(f=f, s=s, name=name, comments=comments)
+        return Network(f=f, s=s, name=name, comments=comments, f_unit='Hz')
     else:
         for k in range(int((d.shape[1]-1)/2)):
-            f = d[:,0]*1e-9
+            f = d[:,0]
             name = names[k]
             print((names[k], names[k+1]))
             if 'db' in names[k].lower() and 'deg' in names[k+1].lower():
@@ -640,23 +654,17 @@ def pna_csv_2_ntwks(filename):
                 s = d[:,k*2+1]+1j*d[:,k*2+2]
 
             ntwk_list.append(
-                Network(f=f, s=s, name=name, comments=comments)
+                Network(f=f, s=s, name=name, comments=comments, f_unit='Hz')
                 )
 
     return ntwk_list
 
 def pna_csv_2_freq(filename):
     warn("deprecated", DeprecationWarning, stacklevel=2)
     header, comments, d = read_pna_csv(filename)
-    #try to pull out frequency unit
-    cols = pna_csv_header_split(filename)
-    try:
-        f_unit = cols[0].split('(')[1].split(')')[0]
-    except  Exception:
-        f_unit = 'hz'
 
     f = d[:,0]
-    return Frequency.from_f(f, unit = f_unit)
+    return Frequency.from_f(f, unit = "Hz")
 
 
 def pna_csv_2_scalar_ntwks(filename, *args, **kwargs):
@@ -683,15 +691,8 @@ def pna_csv_2_scalar_ntwks(filename, *args, **kwargs):
 
     cols = pna_csv_header_split(filename)
 
-
-    #try to pull out frequency unit
-    try:
-        f_unit = cols[0].split('(')[1].split(')')[0]
-    except  Exception:
-        f_unit = 'hz'
-
     f = d[:,0]
-    freq = Frequency.from_f(f, unit = f_unit)
+    freq = Frequency.from_f(f, unit = 'Hz')
 
     # loop through columns and create a single network for each column
     ntwk_list = []

skrf/io/tests/test_csv.py

@@ -1,5 +1,6 @@
 import os
 import unittest
+import warnings
 
 import numpy as np
 import pytest
@@ -19,8 +20,8 @@ def setUp(self):
         name for pna_csv_reim.csv file, then reads it in.
         """
         self.test_dir = os.path.dirname(os.path.abspath(__file__))+'/'
-        filename = os.path.join(self.test_dir, 'pna_csv_reim.csv')
-        self.acsv = rf.AgilentCSV(filename)
+        self.filename = os.path.join(self.test_dir, 'pna_csv_reim.csv')
+        self.acsv = rf.AgilentCSV(self.filename)
 
     def test_columns(self):
         """
@@ -64,3 +65,17 @@ def test_scalar_networks(self):
         This only tests for execution, not accuracy
         """
         a = self.acsv.scalar_networks
+
+    def test_read_pna_csv(self):
+        """
+        This tests reading of a csv file written by an Agilient PNA.
+        """
+        with warnings.catch_warnings(record=True) as w:
+            with self.assertWarns(DeprecationWarning):
+                header, comment, data = rf.read_pna_csv(self.filename)
+
+        self.assertEqual(header, 'Freq(Hz),"A,1"(REAL),"A,1"(IMAG),"R1,1"(REAL),"R1,1"(IMAG)')
+        self.assertEqual(comment, 'this is a comment\nline\n')
+        self.assertTrue((data == np.array([[750000000000, 1, 2, 3, 4],
+                                    [1100000000000, 5, 6, 7,8],
+                                ])).all())

skrf/io/touchstone.py

@@ -537,7 +537,7 @@ def load_file(self, fid: typing.TextIO):
         if state.matrix_format == "full":
             self.s[:] = s_flat
         else:
-            index = np.tril_indices(state.rank) if state.matrix_format == "lower" else np.triu_indices(self.rank)
+            index = np.tril_indices(state.rank) if state.matrix_format == "lower" else np.triu_indices(state.rank)
             index_flat = np.ravel_multi_index(index, (state.rank, state.rank))
             self.s[:, index_flat] = s_flat
 
@@ -546,8 +546,12 @@ def load_file(self, fid: typing.TextIO):
         else:
             self.s = self.s.reshape((-1, state.rank, state.rank))
 
-        if state.matrix_format != "full":
-            self.s = np.nanmax((self.s, self.s.transpose(0, 2, 1)), axis=0)
+        if state.matrix_format == "upper":
+            index_lower = np.tril_indices(state.rank)
+            self.s[(...,*index_lower)] = self.s.transpose(0, 2, 1)[(...,*index_lower)]
+        elif state.matrix_format == "lower":
+            index_upper = np.triu_indices(state.rank)
+            self.s[(...,*index_upper)] = self.s.transpose(0, 2, 1)[(...,*index_upper)]
 
         self.port_modes = np.array(["S"] * state.rank)
         if state.mixed_mode_order:

skrf/media/definedAEpTandZ0.py

@@ -18,8 +18,9 @@
 from __future__ import annotations
 
 import warnings
+from typing import Sequence
 
-from numpy import imag, log, ones, pi, real, sqrt
+from numpy import imag, log, ndarray, ones, pi, real, sqrt
 from scipy.constants import c
 
 from ..constants import NumberLike
@@ -32,7 +33,7 @@ class DefinedAEpTandZ0(Media):
     Transmission line medium defined by A, Ep, Tand and Z0.
 
     This medium is defined by attenuation `A`, relative permittivity `Ep_r`,
-    loss angle `tand` and characteristic impedance `Z0`.
+    loss angle `tand` and nominal impedance `Z0`.
 
     Djirdjevic [#Djordjevic]_ / Svennson [#Svensson]_ dispersion model
     is provided for dielectric. Default behaviour is frequency invariant.
@@ -51,7 +52,7 @@ class DefinedAEpTandZ0(Media):
         (Default is None)
     A : number, array-like, default 0.0
         Attenuation due to conductor loss in dB/m/sqrt(Hz)
-        The attenuation :math:`A(f)`at frequency :math:`f` is:
+        The attenuation :math:`A(f)` at frequency :math:`f` is:
 
         .. math::
 
@@ -86,14 +87,43 @@ class DefinedAEpTandZ0(Media):
     tanD : number, array-like, default 0.0
         Dielectric relative permittivity loss tangent :math:`\tan\delta`. See `ep_r`.
     z0 : number, array-like, default 50.0
-        Quasi-static characteristic impedance of the medium.
+        Quasi-static nominal impedance of the medium.
+        Because of the dispersion introduced by the conductor and dielectric
+        losses, the characteristic impedance can be frequency-dependent with an
+        imaginary part. The characteristic impedance is computed with an RLGC
+        model.
+        If the impedance parameter is array-like, the characteristic impedance
+        is assigned to this value without modification.
+
+        .. math::
+
+            R = 2 Z_n \alpha_{conductor}
+
+        .. math::
+
+            L = \frac{Z_n \sqrt{\epsilon_r}}{C_0}
+
+        .. math::
+
+            G = \frac{2}{Z_n} \alpha_{dielectric}
+
+        .. math::
+
+            C = \frac{\sqrt{\epsilon_r}}{C_0 Z_n}
+
+        .. math::
+
+            Z_0 = \sqrt{\frac{R + j\omega L}{G + j\omega C}}
+
+        where :math:`Z_n` is the nominal impedance and :math:`Z_0` is the
+        characteristic impedance.
     Z0 : number, array-like, or None
         deprecated parameter, only emmit a deprecation warning.
     f_low : number, default 1e3, optional
-        Low frequency in Hz for  for Djirdjevic/Svennson dispersion model.
+        Low frequency in Hz for  for Djordjevic/Svennson dispersion model.
         See `ep_r`.
     f_high : number, default 1e12, optional
-        High frequency in Hz for  for Djirdjevic/Svennson dispersion model.
+        High frequency in Hz for for Djordjevic/Svennson dispersion model.
         See `ep_r`.
     f_ep : number, default 1e9, , optional
         Specification frequency in Hz for  for Djirdjevic/Svennson dispersion model.
@@ -139,10 +169,25 @@ def __init__(self, frequency: Frequency| None = None,
         Media.__init__(self, frequency=frequency, z0_port=z0_port)
         self.A, self.f_A = A, f_A
         self.ep_r, self.tanD = ep_r, tanD
-        self.z0_characteristic = z0
+
         self.f_low, self.f_high, self.f_ep = f_low, f_high, f_ep
         self.model = model
 
+        if isinstance(z0, (Sequence, ndarray)):
+            # keep raw impedance for characteristic impedance
+            self.z0_characteristic = z0
+        else:
+            # z0 is the nominal impedance. Compute characteristic impedance with
+            # an RLGC model based on alpha conductor and alpha dielectric.
+            self.Zn = z0
+            self.R = 2 * self.Zn * self.alpha_conductor
+            self.L = self.Zn * sqrt(self.ep_r) / c
+            self.G = 2 / self.Zn * self.alpha_dielectric
+            self.C = sqrt(ep_r) / c / self.Zn
+            self.z0_characteristic = sqrt(
+                (self.R + 1j * self.frequency.w * self.L) /
+                (self.G + 1j * self.frequency.w * self.C))
+
         if Z0 is not None:
             # warns of deprecation
             warnings.warn(