bam.simulate
============

.. py:module:: bam.simulate


Classes
-------

.. autoapisummary::

   bam.simulate.Simulator


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

.. py:class:: Simulator(model: bam.model.Model)

   Single-axis pendulum simulator used during identification.

   Implements the BAM simulation loop: firmware control law → motor torque →
   friction budget → stopping-torque clipping → Euler integration.  Used by
   ``bam.fit`` to roll out a model against recorded logs and compute the
   identification loss.

   :param model: BAM friction model to simulate.


   .. py:attribute:: screen
      :value: None



   .. py:attribute:: model


   .. py:method:: reset(q: float = 0.0, dq: float = 0.0)

      Resets the simulation to a given state



   .. py:method:: step(control: None | float, torque_enable: bool, dt: float)

      Advance the simulation by one timestep.

      :param control: Control signal sent to the actuator (voltage, current,
          or torque depending on the actuator type). ``None`` is treated as zero.
      :param torque_enable: Whether the actuator is powered. When ``False``
          the motor torque is zero and only gravity and friction act.
      :param dt: Timestep [s].



   .. py:method:: rollout_log(log: dict, reset_period: float = None, simulate_control: bool = False)

      Roll out the model against a recorded log and return predicted trajectories.

      :param log: Processed log dict as returned by :meth:`bam.logs.Logs.make_batch`
          or loaded directly from a processed JSON file.
      :param reset_period: If set, re-synchronize the simulator state to the
          log at this interval [s]. Useful when error accumulation destabilizes
          long rollouts.
      :param simulate_control: If ``True``, recompute the control signal from
          the simulated state using the firmware control law. If ``False``,
          use the control values recorded in the log.
      :returns: Tuple ``(positions, velocities, controls)`` — lists of values
          at each timestep.