.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/arima/example_persisting_a_model.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_arima_example_persisting_a_model.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_arima_example_persisting_a_model.py:


=========================
Persisting an ARIMA model
=========================


This example demonstrates how we can persist an ARIMA model to disk after
fitting it. It can then be loaded back up and used to generate forecasts.

.. raw:: html

   <br/>

.. GENERATED FROM PYTHON SOURCE LINES 14-50




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

 .. code-block:: none


    Predictions: array([21966.69716806, 25983.70920106, 30225.30978922, 35417.12496473,
           13011.36188401, 19639.41027934, 21506.58176453, 23674.3399863 ,
           21685.76394592, 23669.77819202, 26955.35256519, 22755.2506242 ,
           19808.16133461, 23578.78185402, 27845.86720549, 32923.89427525,
           10475.68779115, 17024.74534503, 18831.64798473, 20929.54672618,
           18876.02415795, 20792.57513957, 24011.97548591, 19745.03908596,
           16731.45365409, 20435.40472322, 24635.90940413, 29647.31032454,
            7132.5009883 , 13614.94375569, 15355.23772246, 17386.5246592 ,
           15266.39189057, 17116.33184996, 20269.12159506, 15935.57437822,
           12855.37823992, 16492.71854604, 20626.61249293, 25571.40266446,
            2989.98258695,  9405.81460918, 11079.49783278, 13044.17402533,
           10857.43051304, 12640.75972849, 15726.93872979, 11326.78076908,
            8179.97388695, 11750.70344922, 15817.98665226])






|

.. code-block:: Python

    print(__doc__)

    # Author: Taylor Smith <taylor.smith@alkaline-ml.com>

    import pmdarima as pm
    from pmdarima import model_selection
    import joblib  # for persistence
    import os

    # #############################################################################
    # Load the data and split it into separate pieces
    y = pm.datasets.load_wineind()
    train, test = model_selection.train_test_split(y, train_size=125)

    # Fit an ARIMA
    arima = pm.ARIMA(order=(1, 1, 2), seasonal_order=(0, 1, 1, 12))
    arima.fit(y)

    # #############################################################################
    # Persist a model and create predictions after re-loading it
    pickle_tgt = "arima.pkl"
    try:
        # Pickle it
        joblib.dump(arima, pickle_tgt, compress=3)

        # Load the model up, create predictions
        arima_loaded = joblib.load(pickle_tgt)
        preds = arima_loaded.predict(n_periods=test.shape[0])
        print("Predictions: %r" % preds)

    finally:
        # Remove the pickle file at the end of this example
        try:
            os.unlink(pickle_tgt)
        except OSError:
            pass


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

   **Total running time of the script:** (0 minutes 4.200 seconds)


.. _sphx_glr_download_auto_examples_arima_example_persisting_a_model.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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