def test_conversions(self):
#Converting to other format and back to S-parameters should return the original network
tinyfloat = 1e-12
for test_z0 in (50, 10, 90+10j, 4-100j):
for test_ntwk in (self.ntwk1, self.ntwk2, self.ntwk3):
ntwk = rf.Network(s=test_ntwk.s, f=test_ntwk.f, z0=test_z0)
self.assertTrue((abs(rf.a2s(rf.s2a(ntwk.s, test_z0), test_z0)-ntwk.s) < tinyfloat).all())
self.assertTrue((abs(rf.z2s(rf.s2z(ntwk.s, test_z0), test_z0)-ntwk.s) < tinyfloat).all())
self.assertTrue((abs(rf.y2s(rf.s2y(ntwk.s, test_z0), test_z0)-ntwk.s) < tinyfloat).all())
self.assertTrue((abs(rf.t2s(rf.s2t(ntwk.s))-ntwk.s) < tinyfloat).all())
def test_conversions(self):
#Converting to other format and back to S-parameters should return the original network
tinyfloat = 1e-12
for test_z0 in (50, 10, 90+10j, 4-100j):
for test_ntwk in (self.ntwk1, self.ntwk2, self.ntwk3):
ntwk = rf.Network(s=test_ntwk.s, f=test_ntwk.f, z0=test_z0)
self.assertTrue((abs(rf.a2s(rf.s2a(ntwk.s, test_z0), test_z0)-ntwk.s) < tinyfloat).all())
self.assertTrue((abs(rf.z2s(rf.s2z(ntwk.s, test_z0), test_z0)-ntwk.s) < tinyfloat).all())
self.assertTrue((abs(rf.y2s(rf.s2y(ntwk.s, test_z0), test_z0)-ntwk.s) < tinyfloat).all())
self.assertTrue((abs(rf.t2s(rf.s2t(ntwk.s))-ntwk.s) < tinyfloat).all())
def test_conversions(self):
#Converting to other format and back to S-parameters should return the original network
for test_z0 in (50, 10, 90+10j, 4-100j):
for test_ntwk in (self.ntwk1, self.ntwk2, self.ntwk3):
ntwk = rf.Network(s=test_ntwk.s, f=test_ntwk.f, z0=test_z0)
npy.testing.assert_allclose(rf.a2s(rf.s2a(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.z2s(rf.s2z(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.y2s(rf.s2y(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.h2s(rf.s2h(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.t2s(rf.s2t(ntwk.s)), ntwk.s)
npy.testing.assert_allclose(rf.t2s(rf.s2t(self.Fix.s)), self.Fix.s)
def test_conversions(self):
#Converting to other format and back to S-parameters should return the original network
s_random = npy.random.uniform(-10, 10, (self.freq.npoints, 2, 2)) + 1j * npy.random.uniform(-10, 10, (self.freq.npoints, 2, 2))
ntwk_random = rf.Network(s=s_random, frequency=self.freq)
for test_z0 in (50, 10, 90+10j, 4-100j):
for test_ntwk in (self.ntwk1, self.ntwk2, self.ntwk3, ntwk_random):
ntwk = rf.Network(s=test_ntwk.s, f=test_ntwk.f, z0=test_z0)
npy.testing.assert_allclose(rf.a2s(rf.s2a(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.z2s(rf.s2z(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.y2s(rf.s2y(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.h2s(rf.s2h(ntwk.s, test_z0), test_z0), ntwk.s)
npy.testing.assert_allclose(rf.t2s(rf.s2t(ntwk.s)), ntwk.s)
npy.testing.assert_allclose(rf.t2s(rf.s2t(self.Fix.s)), self.Fix.s)
