pole_residue_fit¶
- photonforge.pole_residue_fit(s_matrix, initial_poles=(), min_poles=1, max_poles=30, rms_error_tolerance=0.0001, max_iterations=100, max_stale_iterations=3, loss_factor=0.001, real=False, passive=True, feedthrough=False, delays=None, stable=True)¶
Fit S matrix elements with rational functions sharing a set of poles.
If no initial pole guess is provided, the initial guess is evenly spaced over the provided frequencies, logarithmically if
real
isTrue
and linearly otherwise.- Parameters:
s_matrix – S matrix to be fitted.
initial_poles – Sequence of poles used as initial guess. Complex poles should come in conjugate pairs if
real
isTrue
.min_poles – Minimal number of poles to try. It has no effect when initial pole guesses are provided.
max_poles – Maximal number of poles to try. It has no effect when initial pole guesses are provided.
loss_factor – For complex initial pole guesses, ratio between their real and imaginary parts.
rms_error_tolerance – RMS error level to break the fitting loop.
max_iterations – Maximal number of fitting iterations.
max_stale_iterations – Maximal number of iterations without error progress.
real – Whether the poles come in conjugate pairs, representing a real-valued (non-baseband) system.
passive – Whether to attempt to enforce passivity.
feedthrough – Whether to include a feedthrough (constant) term in the pole-residue model.
delays – Dictionary of explicit time delays (in seconds), one per matrix element. Missing elements have no time delay applied. If a single number is given, this is used as a global delay for all matrix elements. If
"auto"
, the delays are estimated from the provided data.stable – Whether to ensure stability of the poles of the resulting model. Only used for troubleshooting fits.
- Returns:
Tuple with
PoleResidueMatrix
and the fit RMS error.
Note
Including explicit delays in the model can reduce the number of poles required to obtain a good fit. However, if the delays are too large, it can be difficult to obtain a good stable fit.