.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples_gallery/random_field_actor.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_gallery_random_field_actor.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_gallery_random_field_actor.py:


Random field actor
==================

Demonstrates a custom actor class that sets a field to random values

.. GENERATED FROM PYTHON SOURCE LINES 8-51



.. image-sg:: /examples_gallery/images/sphx_glr_random_field_actor_001.png
   :alt: random field actor
   :srcset: /examples_gallery/images/sphx_glr_random_field_actor_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


      0%|          | 0/10.0 [00:00<?, ?it/s]
    Initializing:   0%|          | 0/10.0 [00:00<?, ?it/s]
      0%|          | 0/10.0 [00:00<?, ?it/s]              
     10%|█         | 1.0/10.0 [00:00<00:02,  3.50it/s]
     20%|██        | 2.0/10.0 [00:00<00:01,  7.00it/s]
     90%|█████████ | 9.0/10.0 [00:00<00:00, 31.47it/s]
     90%|█████████ | 9.0/10.0 [00:00<00:00, 31.46it/s]
    100%|██████████| 10.0/10.0 [00:00<00:00, 34.95it/s]
    100%|██████████| 10.0/10.0 [00:00<00:00, 34.94it/s]






|

.. code-block:: Python


    import numba as nb
    import numpy as np

    from pde import UnitGrid

    import emulsim


    class RandomFieldActor(emulsim.ActorBase):
        """Actor that sets a new random field each time step."""

        def evolve(self, elements, t, dt):
            # mandatory python implementation of the background evolution
            (field,) = elements
            field.data = np.random.uniform(0, 0.1, field.data.shape)

        def make_evolver_numba(self, elements):
            """Implementing the compiled version is optional."""

            # this function is optional and can be used to speed up calculations
            @nb.jit
            def evolver(elements_state, t: float, dt: float):
                """Evolve the diffusion equation explicitly."""
                (field_state,) = elements_state
                for i in range(field_state.size):
                    field_state.flat[i] = np.random.uniform(0, 0.1)

            return evolver  # type: ignore


    # set up state
    element = emulsim.ScalarFieldElement(parameters={"grid": UnitGrid([32, 32])})
    state = emulsim.State({"field": element})

    # set up simulation
    simulation = emulsim.Simulation(state)
    simulation.add_actor("field", RandomFieldActor())

    # run simulation
    result = simulation.run(t_range=10)

    result.plot()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.352 seconds)


.. _sphx_glr_download_examples_gallery_random_field_actor.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: random_field_actor.ipynb <random_field_actor.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: random_field_actor.py <random_field_actor.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: random_field_actor.zip <random_field_actor.zip>`