def cascadeS(S1, S2, *rest):
"""Cascade arrays containing S-parameters.
"""
S1, S2 = make_same_dims(S1, S2)
neworder = tuple([x for x in S1.dims if not isinstance(x, _DimMatrix)])
S1 = S1.reorder_dimensions(*neworder)
S2 = S2.reorder_dimensions(*neworder)
denom = 1 - S1[..., 1, 1] * S2[..., 0, 0]
s1det = det(S1)
s2det = det(S2)
maxshape = tuple(max(x) for x in zip(S1.shape, S2.shape))
res = S1.__class__(np.zeros(maxshape, S1.dtype), dims=S1.dims)
res[..., 0, 0] = S1[..., 0, 0] - S2[..., 0, 0] * s1det
res[..., 0, 1] = S1[..., 0, 1] * S2[..., 0, 1]
res[..., 1, 0] = S1[..., 1, 0] * S2[..., 1, 0]
res[..., 1, 1] = S2[..., 1, 1] - S1[..., 1, 1] * s2det
res = res / denom
res = S1.__class__(res, dims=S1.dims)
return res
def cascadeS(S1, S2, *rest):
"""Cascade arrays containing S-parameters.
"""
S1, S2 = make_same_dims(S1, S2)
neworder = tuple([x for x in S1.dims if not isinstance(x, _DimMatrix)])
S1 = S1.reorder_dimensions(*neworder)
S2 = S2.reorder_dimensions(*neworder)
denom = (1 - S1[..., 1, 1] * S2[..., 0, 0])
s1det = det(S1)
s2det = det(S2)
maxshape = tuple(max(x) for x in zip(S1.shape, S2.shape))
res = S1.__class__(np.zeros(maxshape, S1.dtype), dims=S1.dims)
res[..., 0, 0] = S1[..., 0, 0] - S2[..., 0, 0] * s1det
res[..., 0, 1] = S1[..., 0, 1] * S2[..., 0, 1]
res[..., 1, 0] = S1[..., 1, 0] * S2[..., 1, 0]
res[..., 1, 1] = S2[..., 1, 1] - S1[..., 1, 1] * s2det
res = res / denom
res = S1.__class__(res, dims=S1.dims)
return res
def test_1(self):
res = hfmath.det(self.m)
self.assertAllclose(res, -2)
self.assertEqual(res.shape, (3, ))
self.assertEqual(res.dims, (self.J, ))
