skrf.plotting.plot_minmax_bounds_component(self, attribute, m=0, n=0, type='shade', n_deviations=3, alpha=0.3, color_error=None, markevery_error=20, ax=None, ppf=None, kwargs_error=None, **kwargs)[source]

Plots mean value of the NetworkSet with +/- uncertainty bounds in an Network’s attribute.

This is designed to represent uncertainty in a scalar component of the s-parameter. For example plotting the uncertainty in the magnitude would be expressed by

\[mean(|s|) \pm std(|s|)\]

The order of mean and abs is important.

  • attribute (str) – attribute of Network type to analyze

  • m (int) – first index of attribute matrix

  • n (int) – second index of attribute matrix

  • type (str) – [‘shade’ | ‘bar’], type of plot to draw

  • n_deviations (int) – number of std deviations to plot as bounds

  • alpha (float) – passed to matplotlib.fill_between() command. [number, 0-1]

  • color_error (str) – color of the +- std dev fill shading. Default is None.

  • markevery_error (float) – tbd

  • type – if type==’bar’, this controls frequency of error bars

  • ax (matplotlib axe object) – Axes to plot on. Default is None.

  • ppf (function) –

    post processing function. a function applied to the

    upper and lower bounds. Default is None


    dictionary of kwargs to pass to the fill_between or errorbar plot command depending on value of type.

  • **kwargs – passed to Network.plot_s_re command used to plot mean response

  • self (NetworkSet)

  • kwargs_error (dict)


For phase uncertainty you probably want s_deg_unwrap, or similar. Uncertainty for wrapped phase blows up at +-pi.