.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/gallery_examples/01-apdlmath-examples/solve_dense_matrix.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_examples_01-apdlmath-examples_solve_dense_matrix.py>` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_gallery_examples_01-apdlmath-examples_solve_dense_matrix.py: Use APDLMath to Solve a Dense Matrix Linear System -------------------------------------------------- Use the APDLMath module to solve a Dense Matrix Linear System. .. GENERATED FROM PYTHON SOURCE LINES 8-20 .. code-block:: default import time import numpy.linalg as np from ansys.mapdl.core import launch_mapdl # Start MAPDL as a service and create an APDLMath object. mapdl = launch_mapdl() mm = mapdl.math .. GENERATED FROM PYTHON SOURCE LINES 21-23 Allocate a Dense Matrix in the APDLMath workspace .. GENERATED FROM PYTHON SOURCE LINES 23-29 .. code-block:: default mapdl.clear() dim = 1000 a = mm.rand(dim, dim) b = mm.rand(dim) x = mm.zeros(dim) .. GENERATED FROM PYTHON SOURCE LINES 30-33 Copy the matrices as numpy arrays before they are modified by factorization call .. GENERATED FROM PYTHON SOURCE LINES 33-36 .. code-block:: default a_py = a.asarray() b_py = b.asarray() .. GENERATED FROM PYTHON SOURCE LINES 37-39 Solve using APDLMath .. GENERATED FROM PYTHON SOURCE LINES 39-47 .. code-block:: default print(f"Solving a ({dim} x {dim}) dense linear system using MAPDL...") t1 = time.time() s = mm.factorize(a) x = s.solve(b, x) t2 = time.time() print(f"Elapsed time to solve the linear system using Mapdl: {t2 - t1} seconds") .. rst-class:: sphx-glr-script-out .. code-block:: none Solving a (1000 x 1000) dense linear system using MAPDL... Elapsed time to solve the linear system using Mapdl: 0.014746665954589844 seconds .. GENERATED FROM PYTHON SOURCE LINES 48-49 Norm of the MAPDL Solution .. GENERATED FROM PYTHON SOURCE LINES 49-52 .. code-block:: default mm.norm(x) .. rst-class:: sphx-glr-script-out .. code-block:: none 1.0000000000000016 .. GENERATED FROM PYTHON SOURCE LINES 53-55 Solve the solution using numpy .. GENERATED FROM PYTHON SOURCE LINES 55-62 .. code-block:: default print(f"Solving a ({dim} x {dim}) dense linear system using numpy...") t1 = time.time() x_py = np.linalg.solve(a_py, b_py) t2 = time.time() print(f"Elapsed time to solve the linear system using numpy: {t2 - t1} seconds") .. rst-class:: sphx-glr-script-out .. code-block:: none Solving a (1000 x 1000) dense linear system using numpy... Elapsed time to solve the linear system using numpy: 0.08562207221984863 seconds .. GENERATED FROM PYTHON SOURCE LINES 63-65 Norm of the numpy Solution .. GENERATED FROM PYTHON SOURCE LINES 65-67 .. code-block:: default np.linalg.norm(x_py) .. rst-class:: sphx-glr-script-out .. code-block:: none 0.9999999999999987 .. GENERATED FROM PYTHON SOURCE LINES 68-71 Stop mapdl ~~~~~~~~~~ .. GENERATED FROM PYTHON SOURCE LINES 71-72 .. code-block:: default mapdl.exit() .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.403 seconds) .. _sphx_glr_download_examples_gallery_examples_01-apdlmath-examples_solve_dense_matrix.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: solve_dense_matrix.py <solve_dense_matrix.py>` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: solve_dense_matrix.ipynb <solve_dense_matrix.ipynb>` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_