JuliaApprox
JuliaApprox(julia_obj)Base class for rational function approximations.
Wraps Julia’s AbstractApproximation type, providing methods for evaluating approximations, analyzing their properties, and managing the approximation history.
Attributes: julia: The underlying Julia approximation object.
Methods
| Name | Description |
|---|---|
| check | Check the quality of the approximation. |
| degree | Get the total degree of the approximation. |
| degrees | Get the numerator and denominator degrees. |
| get | Get a property from the underlying Julia object. |
| isempty | Check if the approximation is empty/undefined. |
| poles | Compute the poles of the approximation. |
| residues | Compute poles and their residues. |
| rewind | Rewind the approximation history by n steps. |
| roots | Compute the zeros of the approximation. |
check
JuliaApprox.check()Check the quality of the approximation.
Returns: Approximation quality metrics from Julia.
degree
JuliaApprox.degree()Get the total degree of the approximation.
Returns: int: Maximum of numerator and denominator degrees.
degrees
JuliaApprox.degrees()Get the numerator and denominator degrees.
Returns: tuple: (numerator_degree, denominator_degree).
get
JuliaApprox.get(field)Get a property from the underlying Julia object.
Args: field: Name of the property to retrieve.
Returns: The value of the requested property.
isempty
JuliaApprox.isempty()Check if the approximation is empty/undefined.
Returns: bool: True if the approximation is empty.
poles
JuliaApprox.poles()Compute the poles of the approximation.
Returns: np.ndarray: Array of pole locations in the complex plane.
residues
JuliaApprox.residues()Compute poles and their residues.
Returns: tuple: (poles, residues) as numpy arrays.
rewind
JuliaApprox.rewind(n=1)Rewind the approximation history by n steps.
Args: n: Number of steps to rewind (default: 1).
roots
JuliaApprox.roots()Compute the zeros of the approximation.
Returns: np.ndarray: Array of zero locations in the complex plane.