:py:mod:`aeroshield.controller`
===============================

.. py:module:: aeroshield.controller


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

Classes
~~~~~~~

.. autoapisummary::

   aeroshield.controller.AeroController




.. py:class:: AeroController(aero_shield: aeroshield.aeroshield.AeroShield)


   .. py:method:: variables() -> None

      Define variables to be used by the controller or saved during the experiment.


   .. py:method:: add_tracked_variable(name: str, size: Optional[int] = 1) -> dict[str, int]

      Add a variable to the list of variables whose value should be tracked during the experiment and returned afterwards.
      Variables should be instance variables of the class, otherwise they won't be accessible!

      :param name: Name of the variable, without 'self.'
      :type name: str
      :param size: Size of the variable, e.g. 3 for a three-dimensional position vector. Defaults to 1, i.e. single values.
      :type size: int, optional
      :return: A copy of the current map of tracked variables and their respective size.
      :rtype: dict[str, int]


   .. py:method:: controller(t: float, dt: float, ref: float, pot: float, angle: float) -> float

      Implement the controller here. You can subclass AeroController and overwrite the controller.

      :param t: Time since start of run in seconds.
      :type t: float
      :param dt: Length of current time step in seconds.
      :type dt: float
      :param ref: reference value for the current step.
      :type ref: float
      :param pot: potentiometer value in percent.
      :type pot: float
      :param angle: calibrated angle in degrees.
      :type angle: float
      :return: input value for motor. the motor value will be saturated (int between 0 and 255 incl.) afterwards
      :rtype: float


   .. py:method:: run(freq: int, cycles: int, ref: Optional[float | int | Iterable[float | int]] = None, live_plotter: Optional[aeroshield.plotting.LivePlotter] = None) -> numpy.ndarray

      Run the controller on the AeroShield.

      :param freq: Desired frequency of the loop.
      :type freq: int
      :param cycles: Number of cycles to run the experiment.
      :type duration: int
      :param ref: The reference to follow should have a lenght equal to freq * time.
      :type ref: np.ndarray[float|int]
      :param live_plotter: Optional. LivePlotter instance to use for displaying a live plot.
      :type live_plotter: LivePlotter


   .. py:method:: _update_hist(hist: numpy.ndarray[float], cntr: int, t: float, ref: float, pot: float, angle: float, motor: float)

      Update hist array with variables of the current iteration (cntr). If variables were added to `extra_hist_vars`, add them to the hist as well.

      :param hist: array to update.
      :type hist: np.ndarray[float]
      :param cntr: Iteration counter. Provides the first index to hist.
      :type cntr: int
      :param t: Time.
      :type t: float
      :param ref: Current reference value.
      :type ref: float
      :param angle: Current pendulum angle
      :type angle: float
      :param motor: Current Motor value.
      :type motor: float