Network.extrapolate_to_dc(points=None, dc_sparam=None, kind='cubic', coords='cart', **kwargs)[source]

Extrapolate S-parameters down to 0 Hz and interpolate to uniform spacing.

If frequency vector needs to be interpolated aliasing will occur in time-domain. For the best results first frequency point should be a multiple of the frequency step so that points from DC to the first measured point can be added without interpolating rest of the frequency points.

  • points (int or None) – Number of frequency points to be used in interpolation. If None number of points is calculated based on the frequency step size and spacing between 0 Hz and first measured frequency point.

  • dc_sparam (class:npy.ndarray or None) – NxN S-parameters matrix at 0 Hz. If None S-parameters at 0 Hz are determined by linear extrapolation.

  • kind (str or int, default is 'cubic') –

    Specifies the kind of interpolation as a string (‘linear’, ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic, ‘cubic’) or as an integer specifying the order of the spline interpolator to use for scipy.interp1d.

    kind = ‘rational’ uses interpolation by rational polynomials.

    d kwarg controls the degree of rational polynomials when kind is ‘rational’. Defaults to 4.

  • coords (str) – Coordinate system to use for interpolation: ‘cart’ or ‘polar’. ‘cart’ is cartesian is Re/Im, ‘polar’ is unwrapped phase/mag. Passed to Network.interpolate()


result – Extrapolated Network

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