import os import sys import tempfile import unittest from pathlib import Path import numpy as np import pytest import skrf class VectorFittingTestCase(unittest.TestCase): @pytest.mark.filterwarnings('ignore::UserWarning') def test_ringslot_with_proportional(self): # perform the fit nw = skrf.data.ring_slot vf = skrf.vectorFitting.VectorFitting(nw) vf.vector_fit(n_poles_real=2, n_poles_cmplx=0, fit_proportional=True, fit_constant=True) self.assertLess(vf.get_rms_error(), 0.02) @pytest.mark.filterwarnings('ignore::UserWarning') def test_ringslot_default_log(self): # perform the fit without proportional term nw = skrf.data.ring_slot vf = skrf.vectorFitting.VectorFitting(nw) vf.vector_fit(n_poles_real=4, n_poles_cmplx=0, init_pole_spacing='log') self.assertLess(vf.get_rms_error(), 0.01) @pytest.mark.filterwarnings('ignore::UserWarning') def test_ringslot_without_prop_const(self): # perform the fit without proportional term nw = skrf.data.ring_slot vf = skrf.vectorFitting.VectorFitting(nw) vf.vector_fit(n_poles_real=4, n_poles_cmplx=0, fit_proportional=False, fit_constant=False) self.assertLess(vf.get_rms_error(), 0.01) @pytest.mark.filterwarnings('ignore::UserWarning') def test_ringslot_custompoles(self): # perform the fit with custom initial poles nw = skrf.data.ring_slot vf = skrf.vectorFitting.VectorFitting(nw) vf.poles = 2 * np.pi * np.array([-100e9, -10e9 + 100e9j]) vf.vector_fit(init_pole_spacing='custom') self.assertLess(vf.get_rms_error(), 0.01) def test_190ghz_measured(self): # perform the fit without proportional term s2p_file = Path(__file__).parent.parent.parent / 'doc/source/examples/vectorfitting/190ghz_tx_measured.S2P' nw = skrf.network.Network(s2p_file) vf = skrf.vectorFitting.VectorFitting(nw) vf.vector_fit(n_poles_real=4, n_poles_cmplx=4, fit_proportional=False, fit_constant=True) self.assertLess(vf.get_rms_error(), 0.02) def test_no_convergence(self): s2p_file = Path(__file__).parent.parent.parent / 'doc/source/examples/vectorfitting/190ghz_tx_measured.S2P' # perform a bad fit that does not converge and check if a RuntimeWarning is given nw = skrf.network.Network(s2p_file) vf = skrf.vectorFitting.VectorFitting(nw) with pytest.warns(RuntimeWarning) as record: vf.vector_fit(n_poles_real=0, n_poles_cmplx=5, fit_proportional=False, fit_constant=True) assert len(record) == 1 def test_dc_enforcement(self): # perform the fit on data including a dc sample (0 Hz) s4p_file = Path(__file__).parent / 'cst_example_4ports.s4p' nw = skrf.Network(s4p_file) vf = skrf.VectorFitting(nw) vf.auto_fit() # rough check on fit quality self.assertLess(vf.get_rms_error(), 0.2) # evaluate model error at the dc point (real part) # the dc point should always be real (it still often has a tiny imaginary part) vf_fit = np.empty(nw.nports ** 2, dtype=complex) abs_real_errors = np.empty(nw.nports ** 2) for i in range(nw.nports): for j in range(nw.nports): vf_ij = vf.get_model_response(i, j, nw.f[0]) vf_fit[i * nw.nports + j] = vf_ij abs_real_errors[i * nw.nports + j] = np.abs(np.real(vf_ij - nw.s[0, i, j])) self.assertTrue(np.all(abs_real_errors < 1e-10)) def test_read_write_npz(self): # fit ring slot example network nw = skrf.data.ring_slot vf = skrf.vectorFitting.VectorFitting(nw) with pytest.warns(UserWarning) as record: vf.vector_fit(n_poles_real=3, n_poles_cmplx=0) self.assertTrue(len(record) == 1) # export (write) fitted parameters to .npz file in tmp directory with tempfile.TemporaryDirectory() as name: vf.write_npz(name) # create a new vector fitting instance and import (read) those fitted parameters vf2 = skrf.vectorFitting.VectorFitting(nw) vf2.read_npz(os.path.join(name, f'coefficients_{nw.name}.npz')) # compare both sets of parameters self.assertTrue(np.allclose(vf.poles, vf2.poles)) self.assertTrue(np.allclose(vf.residues, vf2.residues)) self.assertTrue(np.allclose(vf.proportional_coeff, vf2.proportional_coeff)) self.assertTrue(np.allclose(vf.constant_coeff, vf2.constant_coeff)) @pytest.mark.skipif("matplotlib" in sys.modules, reason="Raise Error only if matplotlib is not installed.") def test_matplotlib_missing(self): vf = skrf.vectorFitting.VectorFitting(skrf.data.ring_slot) with self.assertRaises(RuntimeError): vf.plot_convergence() def test_passivity_enforcement(self): vf = skrf.VectorFitting(None) # non-passive example parameters from Gustavsen's passivity assessment paper: vf.poles = np.array([-1, -5 + 6j]) vf.residues = np.array([[0.3, 4 + 5j], [0.1, 2 + 3j], [0.1, 2 + 3j], [0.4, 3 + 4j]]) vf.constant_coeff = np.array([0.2, 0.1, 0.1, 0.3]) vf.proportional_coeff = np.array([0.0, 0.0, 0.0, 0.0]) # test if model is not passive violation_bands = vf.passivity_test() self.assertTrue(np.allclose(violation_bands, np.array([4.2472, 16.434]) / 2 / np.pi, rtol=1e-3, atol=1e-3)) self.assertFalse(vf.is_passive()) # enforce passivity with default settings vf.passivity_enforce(f_max=2) # check if model is now passive self.assertTrue(vf.is_passive()) def test_autofit(self): vf = skrf.VectorFitting(skrf.data.ring_slot) vf.auto_fit() self.assertTrue(vf.get_model_order(vf.poles) == 6) self.assertTrue(np.sum(vf.poles.imag == 0.0) == 0) self.assertTrue(np.sum(vf.poles.imag > 0.0) == 3) self.assertLess(vf.get_rms_error(), 1e-05) suite = unittest.TestLoader().loadTestsFromTestCase(VectorFittingTestCase) unittest.TextTestRunner(verbosity=2).run(suite)