piel.visual.experimental.frequency.measurement_data_collection
==============================================================

.. py:module:: piel.visual.experimental.frequency.measurement_data_collection


Attributes
----------

.. autoapisummary::

   piel.visual.experimental.frequency.measurement_data_collection.default_skrf_figure_kwargs


Functions
---------

.. autoapisummary::

   piel.visual.experimental.frequency.measurement_data_collection.plot_s_parameter_measurements_to_step_responses
   piel.visual.experimental.frequency.measurement_data_collection.plot_s_parameter_real_and_imaginary
   piel.visual.experimental.frequency.measurement_data_collection.plot_s_parameter_per_component


Module Contents
---------------

.. py:data:: default_skrf_figure_kwargs

.. py:function:: plot_s_parameter_measurements_to_step_responses(data_collection: piel.types.experimental.measurements.data.frequency.VNASParameterMeasurementDataCollection, parameters_list: list = None, network_port_index: int = 0, time_range_s: piel.types.ScalarMetric = None, figure_kwargs: dict = None, **kwargs)

   The goal of this function is that it iterates through a collection of s-parameter networks,
   generates the inverse-fourier-transform step responses and plots them as defined by the plotting infrastructure.
   Note that each step transmission depends on the corresponding input port for the subnetwork it is extracted from,
   as it is derived from the S11 or S22 based on the return loss, hence matching in a real transmission line network.

   It will plot the transformations on top of each other rather than sequentially.
   TODO explore the other caveats of performing transformations this way.
   TODO generalise this functionality for simulation-sparameter networks.


.. py:function:: plot_s_parameter_real_and_imaginary(data_collection: piel.types.experimental.measurements.data.frequency.VNASParameterMeasurementDataCollection, parameters_list: list = None, figure_kwargs: dict = None, s_plot_kwargs: dict = None, **kwargs) -> tuple

.. py:function:: plot_s_parameter_per_component(data_collection: piel.types.experimental.measurements.data.frequency.VNASParameterMeasurementDataCollection, parameters_list: list = None, s_parameter_plot: str = 'plot_s_db', figure_kwargs: dict = None, s_plot_kwargs: dict = None, **kwargs) -> tuple

   A set of two-port s-parameter measurements can have four different s-parameters, S11, S12, S21, S22.
   If we are wanting to visualize them under different operating conditions, it might be desired to create a
   separate plot for each of the s-parameters. This function is designed to do that. It assumes at least two `VNASParameterMeasurementData` are provided.

   Since a VNASParameterMeasurementDataCollection is a collection of VNASParameterMeasurementData,
    we can iterate through the collection and plot the S-parameters in each of the individual 4 set of plots.