tidy3d.plugins.dispersion.AdvancedFitterParam#
- class AdvancedFitterParam[source]#
Bases:
Tidy3dBaseModel
Advanced fitter parameters
- Parameters:
bound_amp (Attribute:
bound_amp
) –Type
Optional[NonNegativeFloat]
Default
= None
Units
Hz
Description
Upper bound of real and imagniary part of oscillator strength
c
in the modelPoleResidue
(The default ‘None’ will trigger automatic setup based on the frequency range of interest).bound_f (Attribute:
bound_f
) –Type
Optional[NonNegativeFloat]
Default
= None
Units
Hz
Description
Upper bound of real and imaginary part of
a
that corresponds to pole damping rate and frequency in the modelPoleResidue
(The default ‘None’ will trigger automatic setup based on the frequency range of interest).bound_f_lower (Attribute:
bound_f_lower
) –Type
NonNegativeFloat
Default
= 0.0
Units
Hz
Description
Lower bound of imaginary part of
a
that corresponds to pole frequency in the modelPoleResidue
.bound_eps_inf (Attribute:
bound_eps_inf
) –Type
ConstrainedFloatValue
Default
= 10.0
Description
Upper bound of epsilon at infinity frequency. It must be no less than 1.
constraint (Attribute:
constraint
) –Type
Literal[‘hard’, ‘soft’]
Default
= hard
Description
Stability constraint: ‘hard’ constraints are generally recommended since they are faster to compute per iteration, and they often require fewer iterations to converge since the search space is smaller. But sometimes the search space is so restrictive that all good solutions are missed, then please try the ‘soft’ constraints for larger search space. However, both constraints improve stability equally well.
nlopt_maxeval (Attribute:
nlopt_maxeval
) –Type
PositiveInt
Default
= 5000
Description
Number of iterations in each inner optimization.
random_seed (Attribute:
random_seed
) –Type
Optional[ConstrainedIntValue]
Default
= 0
Description
The fitting tool performs global optimizations with random starting coefficients. With the same random seed, one obtains identical results when re-running the fitter; on the other hand, if one wants to re-run the fitter several times to obtain the best results, the value of the seed should be changed, or set to
None
so that the starting coefficients are different each time.
Attributes
Methods
- bound_amp#
- bound_f#
- bound_f_lower#
- bound_eps_inf#
- constraint#
- nlopt_maxeval#
- random_seed#
- __hash__()#
Hash method.