.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/04_perform_full_mat.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_examples_04_perform_full_mat.py>`
        to download the full example code.

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

.. _sphx_glr_examples_04_perform_full_mat.py:


4. Example: Performance for full matrices
-----------------------------------------

Here we compare all algorithms for solving pentadiagonal systems provided
by pentapy (except umf) using a full quadratic matrix as input.

To use this script you need to have the following packages installed:

    * scipy
    * perfplot
    * matplotlib

.. GENERATED FROM PYTHON SOURCE LINES 14-69



.. image-sg:: /examples/images/sphx_glr_04_perform_full_mat_001.png
   :alt: 04 perform full mat
   :srcset: /examples/images/sphx_glr_04_perform_full_mat_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Overall ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00
    Kernels ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00






|

.. code-block:: Python


    import numpy as np
    import perfplot

    from pentapy import solve, tools


    def get_les(size):
        mat = (np.random.random((5, size)) - 0.5) * 1e-5
        V = np.array(np.random.random(size) * 1e5)
        M = tools.create_full(mat)
        return M, V


    def solve_1(in_val):
        """PTRANS-I"""
        mat, V = in_val
        return solve(mat, V, is_flat=False, solver=1)


    def solve_2(in_val):
        """PTRANS-II"""
        mat, V = in_val
        return solve(mat, V, is_flat=False, solver=2)


    def solve_3(in_val):
        mat, V = in_val
        return solve(mat, V, is_flat=False, solver=3)


    def solve_4(in_val):
        mat, V = in_val
        return solve(mat, V, is_flat=False, solver=4)


    def solve_5(in_val):
        mat, V = in_val
        return np.linalg.solve(mat, V)


    perfplot.show(
        setup=get_les,
        kernels=[solve_1, solve_2, solve_3, solve_4, solve_5],
        labels=[
            "PTRANS-I",
            "PTRANS-II",
            "scipy.linalg.solve_banded",
            "scipy.sparse.linalg.spsolve",
            "numpy.linalg.solve",
        ],
        n_range=[2**k for k in range(2, 13)],
        xlabel="Size [n]",
        logy=True,
    )


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

   **Total running time of the script:** (0 minutes 36.172 seconds)


.. _sphx_glr_download_examples_04_perform_full_mat.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: 04_perform_full_mat.ipynb <04_perform_full_mat.ipynb>`

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

      :download:`Download Python source code: 04_perform_full_mat.py <04_perform_full_mat.py>`

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

      :download:`Download zipped: 04_perform_full_mat.zip <04_perform_full_mat.zip>`


.. only:: html

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

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