abstract.filter

filter(
    *,
    family: Literal[
        'digital',
        'rc',
        'butterworth',
        'bessel',
        'cheby1',
        'rectangular',
        'gaussian',
    ] = 'rc',
    shape: Literal['lp', 'hp', 'bp', 'bs'] = 'lp',
    f_cutoff: Annotated[float, minimum=0, units='Hz']
    | Annotated[
        collections.abc.Sequence[Annotated[float, minimum=0, units='Hz']],
        maxItems=2,
        minItems=2,
    ] = 20000000000.0,
    order: Annotated[int, exclusiveMinimum=0] = 1,
    ripple: Annotated[float, minimum=0, units='dB'] = 0,
    window: str
    | tuple[str, float]
    | tuple[str, float, float]
    | tuple[str, collections.abc.Sequence[float]] = 'hann',
    a: collections.abc.Sequence[complex] = (1.0,),
    b: collections.abc.Sequence[complex] = (),
    taps: Annotated[int, exclusiveMinimum=0] = 101,
    insertion_loss: Annotated[float, minimum=0, units='dB'] = 0,
) -> photonforge.Component

Abstract filter for electrical signals.

Based on FilterTimeStepper.

Args

• family: Filter family.
• shape: Filter shape.
• f_cutoff: Cutoff frequency for low- and high-pass filter shapes. For family=="tunable_lp_rc", this can be an Interpolator to provide the dependency with the input voltage. For band-pass and band-stop shapes, this is a 2-value sequence with low and high cutoff frequencies.
• order: Filter order.
• ripple: Maximum ripple for Chebyshev filters.
• window: Window specification for rectangular filters. Please consult the help for scipy.signal.firwin for valid options.
• a: Recursive (denominator) coefficients for a digital IIR filter.
• b: Direct (numerator) coefficients for a digital FIR or IIR filter.
• taps: Length of rectangular or Gaussian filters.
• insertion_loss: Insertion loss added to the filter response.