Uniformization: Lower case 's' for function arguments.
@@ -120,7 +120,7 @@ class VectorFitting:
self.history_max_sigma = []
def vector_fit(self, n_poles_real: int = 2, n_poles_cmplx: int = 2, init_pole_spacing: str = 'lin',
- parameter_type: str = 'S', fit_constant: bool = True, fit_proportional: bool = False) -> None:
+ parameter_type: str = 's', fit_constant: bool = True, fit_proportional: bool = False) -> None:
"""
Main work routine performing the vector fit. The results will be stored in the class variables
:attr:`poles`, :attr:`zeros`, :attr:`proportional_coeff` and :attr:`constant_coeff`.
@@ -654,7 +654,7 @@ class VectorFitting:
stsp_S += D + 2j * np.pi * freq * E
return stsp_S
- def passivity_test(self, parameter_type: str = 'S') -> np.ndarray:
+ def passivity_test(self, parameter_type: str = 's') -> np.ndarray:
"""
Evaluates the passivity of reciprocal vector fitted models by means of a half-size test matrix [#]_. Any
existing frequency bands of passivity violations will be returned as a sorted list.
@@ -760,7 +760,7 @@ class VectorFitting:
return np.array(violation_bands)
- def is_passive(self, parameter_type: str = 'S') -> bool:
+ def is_passive(self, parameter_type: str = 's') -> bool:
"""
Returns the passivity status of the model as a boolean value.
@@ -788,7 +788,7 @@ class VectorFitting:
else:
return False
- def passivity_enforce(self, n_samples: int = 100, parameter_type: str = 'S') -> None:
+ def passivity_enforce(self, n_samples: int = 100, parameter_type: str = 's') -> None:
"""
Enforces the passivity of the vector fitted model, if required. This is an implementation of the method
presented in [#]_.
