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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_plot_opt_prob.py:


Plotting optimization problem
=============================
An example of how to use the :func:`niceplots.utils.plot_opt_prob` function to plot a constrained 2D optimization problem.
This example plots the 2D Rosenbrock function with a quadratic equality constraint and 3 circular inequality
constraints, which has an optimum at (1, 1).

.. GENERATED FROM PYTHON SOURCE LINES 8-84



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_opt_prob_001.svg
         :alt: plot opt prob
         :srcset: /auto_examples/images/sphx_glr_plot_opt_prob_001.svg
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/images/sphx_glr_plot_opt_prob_002.svg
         :alt: plot opt prob
         :srcset: /auto_examples/images/sphx_glr_plot_opt_prob_002.svg
         :class: sphx-glr-multi-img





.. code-block:: Python


    # ==============================================================================
    # Standard Python modules
    # ==============================================================================

    # ==============================================================================
    # External Python modules
    # ==============================================================================
    import matplotlib.pyplot as plt
    import niceplots

    # ==============================================================================
    # Extension modules
    # ==============================================================================

    plt.style.use(niceplots.get_style())
    colors = niceplots.get_colors()


    def Rosenbrock(x, y):
        return (1 - x) ** 2 + 100 * (y - x**2) ** 2


    def circleCon1(x, y):
        return x**2 + y**2 - 2


    def circleCon2(x, y):
        return (x - 1.5) ** 2 + y**2 - 2


    def circleCon3(x, y):
        return x**2 + (y - 1.5) ** 2 - 2


    def eqCon(x, y):
        return x - y**2


    # --- Some fake optimiser path ---
    optX = [0.8, 1.2, 1.015384614926278, 0.9999252638670815, 1.0]
    optY = [1.4, 1.3, 1.0626373624736707, 0.9999644713547426, 1.0]

    for conStyle in ["shaded", "hashed"]:
        fig, ax = plt.subplots(figsize=(8, 8))
        ax.set_aspect("equal")
        niceplots.plot_opt_prob(
            Rosenbrock,
            xRange=[0, 1.5],
            yRange=[0, 1.5],
            ineqCon=[circleCon1, circleCon2, circleCon3],
            eqCon=eqCon,
            nPoints=31,
            optPoint=[1.0, 1.0],
            conStyle=conStyle,
            ax=ax,
            colors=None,
            cmap=None,
            levels=50,
            labelAxes=True,
        )

        # --- Plot the optimiser's path to the optimum ---
        ax.plot(
            optX,
            optY,
            "-o",
            c=colors["Axis"],
            markeredgecolor="w",
            linewidth=2.0,
            markersize=8,
            clip_on=False,
        )

        # Save figures
        niceplots.save_figs(fig, f"opt_prob-{conStyle}", ["png", "svg"])


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

   **Total running time of the script:** (0 minutes 3.481 seconds)


.. _sphx_glr_download_auto_examples_plot_opt_prob.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_