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

.. only:: html

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

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

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

.. _sphx_glr_examples_mlearning_transformer_plot_pipeline.py:


Transformer pipeline example
============================

In this example, we will create a pipeline of transformers.

.. GENERATED FROM PYTHON SOURCE LINES 27-41

.. code-block:: default

    from __future__ import annotations

    import matplotlib.pyplot as plt
    from gemseo import configure_logger
    from gemseo.mlearning.transformers.pipeline import Pipeline
    from gemseo.mlearning.transformers.scaler.scaler import Scaler
    from numpy import allclose
    from numpy import linspace
    from numpy import matmul
    from numpy import sin

    configure_logger()






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

 .. code-block:: none


    <RootLogger root (INFO)>



.. GENERATED FROM PYTHON SOURCE LINES 42-44

Create dataset
--------------

.. GENERATED FROM PYTHON SOURCE LINES 44-48

.. code-block:: default

    x = linspace(0, 1, 100)[:, None]
    data = sin(10 * x) - 3 * x









.. GENERATED FROM PYTHON SOURCE LINES 49-55

Create transformer pipeline
---------------------------
We create a pipeline of two transformers; the first performing a shift, the
second a scale (both scalers). This could also be achieved using one scaler,
but we here present a pipeline doing these transformations separately for
illustrative purposes.

.. GENERATED FROM PYTHON SOURCE LINES 55-59

.. code-block:: default

    shift = Scaler(offset=5)
    scale = Scaler(coefficient=0.5)
    pipeline = Pipeline(transformers=[shift, scale])








.. GENERATED FROM PYTHON SOURCE LINES 60-63

Transform data
--------------
In order to use the transformer, we have to fit it to the data.

.. GENERATED FROM PYTHON SOURCE LINES 63-65

.. code-block:: default

    pipeline.fit(data)





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

 .. code-block:: none

     WARNING - 13:54:02: The Scaler.fit() function does nothing; the instance of Scaler uses the coefficient and offset passed at its initialization
     WARNING - 13:54:02: The Scaler.fit() function does nothing; the instance of Scaler uses the coefficient and offset passed at its initialization




.. GENERATED FROM PYTHON SOURCE LINES 66-67

Transform data using the pipeline

.. GENERATED FROM PYTHON SOURCE LINES 67-69

.. code-block:: default

    transformed_data = pipeline.transform(data)








.. GENERATED FROM PYTHON SOURCE LINES 70-71

Transform data using individual components of the pipeline

.. GENERATED FROM PYTHON SOURCE LINES 71-73

.. code-block:: default

    only_shifted_data = shift.transform(data)








.. GENERATED FROM PYTHON SOURCE LINES 74-76

Plot data
---------

.. GENERATED FROM PYTHON SOURCE LINES 76-82

.. code-block:: default

    plt.plot(x, data, label="Original data")
    plt.plot(x, transformed_data, label="Shifted and scaled data")
    plt.plot(x, only_shifted_data, label="Shifted but not scaled data")
    plt.legend()
    plt.show()




.. image-sg:: /examples/mlearning/transformer/images/sphx_glr_plot_pipeline_001.png
   :alt: plot pipeline
   :srcset: /examples/mlearning/transformer/images/sphx_glr_plot_pipeline_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 83-85

Compute jacobian
----------------

.. GENERATED FROM PYTHON SOURCE LINES 85-93

.. code-block:: default

    jac = pipeline.compute_jacobian(data)
    only_shift_jac = shift.compute_jacobian(data)
    only_scale_jac = scale.compute_jacobian(only_shifted_data)

    print(jac.shape)
    print(only_shift_jac.shape)
    print(only_scale_jac.shape)
    print(allclose(jac, matmul(only_scale_jac, only_shift_jac)))




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

 .. code-block:: none

    (100, 1, 1)
    (100, 1, 1)
    (100, 1, 1)
    True





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

   **Total running time of the script:** (0 minutes 0.140 seconds)


.. _sphx_glr_download_examples_mlearning_transformer_plot_pipeline.py:

.. only:: html

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




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

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

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

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


.. only:: html

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

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