.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/RunModel/abaqus_example.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_RunModel_abaqus_example.py>`
        to download the full example code or to run this example in your browser via Binder

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

.. _sphx_glr_auto_examples_RunModel_abaqus_example.py:


Third-party - Abaqus
==================================

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Import the necessary libraries.

.. GENERATED FROM PYTHON SOURCE LINES 12-24

.. code-block:: default

    import glob
    import pickle
    import time
    import os
    from UQpy.distributions import Normal, Uniform
    from UQpy.run_model.RunModel import RunModel
    from UQpy.run_model.model_execution.ThirdPartyModel import ThirdPartyModel
    from UQpy.sampling import MonteCarloSampling

    calling_directory = os.getcwd()
    t = time.time()


.. GENERATED FROM PYTHON SOURCE LINES 25-27

Building the model
There are two probabilistic input variables, the fire load density and the yield strength.

.. GENERATED FROM PYTHON SOURCE LINES 30-33

.. code-block:: default


    var_names = ['qtd', 'fy']


.. GENERATED FROM PYTHON SOURCE LINES 34-35

Create the model object

.. GENERATED FROM PYTHON SOURCE LINES 38-45

.. code-block:: default


    m = ThirdPartyModel(model_script='abaqus_fire_analysis.py', input_template='abaqus_input.py',
                        output_script='extract_abaqus_output.py', var_names=var_names,
                        model_dir='SFE_MCS', )
    abaqus_sfe_model = RunModel(cores_per_task=1, ntasks=24, model=m)
    print('Example: Created the model object.')


.. GENERATED FROM PYTHON SOURCE LINES 46-52

Towards defining the sampling scheme
The fire load density is assumed to be uniformly distributed between 50 :math:`MJ/m^2` and 450 :math:`MJ/m^2`.
The yield strength is assumed to be normally distributed, with the parameters
being: mean = 250 :math:`MPa` and coefficient of variation of :math:`7%`.

Creating samples using MCS.

.. GENERATED FROM PYTHON SOURCE LINES 55-60

.. code-block:: default


    d_n = Normal(loc=50, scale=400)
    d_u = Uniform(location=2.50e8, scale=1.75e7)
    x_mcs = MonteCarloSampling(distributions=[d_n, d_u], samples_number=100, random_state=987979)


.. GENERATED FROM PYTHON SOURCE LINES 61-62

Running simulations using the previously defined model object and samples

.. GENERATED FROM PYTHON SOURCE LINES 65-69

.. code-block:: default


    sample_points = x_mcs.samples
    abaqus_sfe_model.run(samples=sample_points)


.. GENERATED FROM PYTHON SOURCE LINES 70-71

The outputs from the analysis are the values of the performance function.

.. GENERATED FROM PYTHON SOURCE LINES 74-78

.. code-block:: default



    qois = abaqus_sfe_model.qoi_list


.. GENERATED FROM PYTHON SOURCE LINES 79-80

Save the samples and the qois in a dictionary called results with keys 'inputs' and 'outputs'.

.. GENERATED FROM PYTHON SOURCE LINES 83-85

.. code-block:: default

    results = {'inputs': sample_points, 'outputs': qois}


.. GENERATED FROM PYTHON SOURCE LINES 86-87

Pickle the results dictionary in the current directory. The basename and extension of the desired pickle file:

.. GENERATED FROM PYTHON SOURCE LINES 90-93

.. code-block:: default

    res_basename = 'MCS_results'
    res_extension = '.pkl'


.. GENERATED FROM PYTHON SOURCE LINES 94-96

Create a new results file with a larger index than any existing results files with the same name in the current
directory.

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.. code-block:: default

    res_file_list = glob.glob(res_basename + '_???' + res_extension)
    if len(res_file_list) == 0:
        res_file_name = res_basename + '_000' + res_extension
    else:
        max_number = max(res_file_list).split('.')[0].split('_')[-1]
        res_file_name = res_basename + '_%03d' % (int(max_number) + 1) + res_extension

    res_file_name = os.path.join(calling_directory, res_file_name)

.. GENERATED FROM PYTHON SOURCE LINES 108-110

Create a new results file with a larger index than any existing results files with the same name in the current
directory.

.. GENERATED FROM PYTHON SOURCE LINES 113-120

.. code-block:: default


    with open(res_file_name, 'wb') as f:
        pickle.dump(results, f)
    print('Saved the results to ' + res_file_name)

    print('Example: Done!')
    print('Time elapsed: %.2f minutes' % float((time.time() - t) / 60.0))


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

   **Total running time of the script:** ( 0 minutes  0.000 seconds)


.. _sphx_glr_download_auto_examples_RunModel_abaqus_example.py:

.. only:: html

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


    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/SURGroup/UQpy/master?urlpath=lab/tree/notebooks/auto_examples/RunModel/abaqus_example.ipynb
        :alt: Launch binder
        :width: 150 px



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

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

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

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


.. only:: html

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

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