import skrf
import jax.numpy as jnp
from pmrf._util import field
from pmrf.frequency import Frequency
from pmrf.models.model import Model
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class Measured(Model):
network: skrf.Network = field(static=True)
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def s(self, freq: Frequency) -> jnp.ndarray:
S_old = jnp.array(self.network.s)
f_old = jnp.array(self.network.f)
f_new = freq.f
n_ports = S_old.shape[1]
# Split into real and imaginary parts
S_real = jnp.real(S_old)
S_imag = jnp.imag(S_old)
# Interpolate each real/imag component independently
def interp_component(S_comp):
return jnp.stack([
jnp.stack([
jnp.interp(f_new, f_old, S_comp[:, i, j], left=jnp.nan, right=jnp.nan)
for j in range(n_ports)
], axis=0)
for i in range(n_ports)
], axis=0) # shape: (n_ports, n_ports, n_freqs_new)
S_real_new = interp_component(S_real)
S_imag_new = interp_component(S_imag)
# Combine and transpose back to (n_freqs_new, n_ports, n_ports)
S_new = (S_real_new + 1j * S_imag_new).transpose(2, 0, 1)
return S_new
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class ListModel(Model):
models: list[Model]
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class DictModel(Model):
models: dict[str, Model]
def __post_init__(self):
for key, value in self.models:
setattr(self, key, value)
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class SModel(Model):
"""
**Overview**
A general model defined by a constant S-parameter matrix.
"""
s_array: jnp.array
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def s(self, _freq: Frequency) -> jnp.ndarray:
"""Returns the S-parameter matrix.
Args:
freq (Frequency): Specifies the frequency to calculate the parameters at.
Returns:
jnp.ndarray: The resultant block-diagonal S-parameter matrix.
"""
nports = self.s_array.shape[1]
nfreq = _freq.npoints
if nfreq != self.s_array.shape[0]:
return jnp.zeros((nfreq, nports, nports))
return self.s_array
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class AModel(Model):
"""
**Overview**
A general model defined by a constant ABCD matrix.
"""
a_array: jnp.array
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def a(self, _freq: Frequency) -> jnp.ndarray:
"""Returns the ABCD matrix.
Args:
freq (Frequency): Specifies the frequency to calculate the parameters at.
Returns:
jnp.ndarray: The resultant block-diagonal ABCD matrix.
"""
nports = self.a_array.shape[1]
nfreq = _freq.npoints
if nfreq != self.a_array.shape[0]:
return jnp.zeros((nfreq, nports, nports))
return self.a_array