.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples_gallery/advanced_pdes/custom_noise.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_advanced_pdes_custom_noise.py>`
        to download the full example code.

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

.. _sphx_glr_examples_gallery_advanced_pdes_custom_noise.py:


Custom noise
============

This example solves a diffusion equation with a custom noise.

.. GENERATED FROM PYTHON SOURCE LINES 7-38



.. image-sg:: /examples_gallery/advanced_pdes/images/sphx_glr_custom_noise_001.png
   :alt: custom noise
   :srcset: /examples_gallery/advanced_pdes/images/sphx_glr_custom_noise_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


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.. code-block:: Python


    import numpy as np
    from numba import jit

    from pde import DiffusionPDE, ScalarField, UnitGrid


    class DiffusionCustomNoisePDE(DiffusionPDE):
        """Diffusion PDE with custom noise implementations."""

        def noise_realization(self, state, t):
            """Numpy implementation of spatially-dependent noise."""
            noise_field = ScalarField.random_uniform(state.grid, -self.noise, self.noise)
            return state.grid.cell_coords[..., 0] * noise_field

        def make_noise_realization_numba(self, state):
            """Numba implementation of spatially-dependent noise."""
            noise = float(self.noise)
            x_values = state.grid.cell_coords[..., 0]

            @jit
            def noise_realization(state_data, t):
                return x_values * np.random.uniform(-noise, noise, size=state_data.shape)  # noqa: NPY002

            return noise_realization


    eq = DiffusionCustomNoisePDE(diffusivity=0.1, noise=0.1)  # define the pde
    state = ScalarField.random_uniform(UnitGrid([64, 64]))  # generate initial condition
    result = eq.solve(state, t_range=10, dt=0.01)
    result.plot()


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

   **Total running time of the script:** (0 minutes 0.603 seconds)


.. _sphx_glr_download_examples_gallery_advanced_pdes_custom_noise.py:

.. only:: html

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

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

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

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

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

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

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