.. DO NOT EDIT.
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.. "examples/01_solve.py"
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.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_examples_01_solve.py>`
        to download the full example code.

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

.. _sphx_glr_examples_01_solve.py:


1. Example: Solving
-------------------

Here we create a random row wise flattened matrix M_flat and a random
right hand side for the pentadiagonal equation system.

After solving we calculate the absolute difference between the right hand side
and the product of the matrix (which is transformed to a full quadratic one)
and the solution of the system.

.. GENERATED FROM PYTHON SOURCE LINES 12-28




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

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    1.7475031199865043e-06






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.. code-block:: Python


    import numpy as np

    import pentapy as pp

    size = 1000
    # create a flattened pentadiagonal matrix
    M_flat = (np.random.random((5, size)) - 0.5) * 1e-5
    V = np.random.random(size) * 1e5
    # solve the LES with M_flat as row-wise flattened matrix
    X = pp.solve(M_flat, V, is_flat=True)

    # create the corresponding matrix for checking
    M = pp.create_full(M_flat, col_wise=False)
    # calculate the error
    print(np.max(np.abs(np.dot(M, X) - V)))


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

   **Total running time of the script:** (0 minutes 0.007 seconds)


.. _sphx_glr_download_examples_01_solve.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: 01_solve.ipynb <01_solve.ipynb>`

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

      :download:`Download Python source code: 01_solve.py <01_solve.py>`

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

      :download:`Download zipped: 01_solve.zip <01_solve.zip>`


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

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