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

.. only:: html

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

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

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

.. _sphx_glr_examples_dataset_creation_plot_dataset_from_array.py:


Dataset from a NumPy array
==========================

In this example, we will see how to build a :class:`.Dataset` from an NumPy array.

.. GENERATED FROM PYTHON SOURCE LINES 27-37

.. code-block:: default

    from __future__ import annotations

    from gemseo import configure_logger
    from gemseo.datasets.dataset import Dataset
    from numpy import concatenate
    from numpy.random import rand

    configure_logger()






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

 .. code-block:: none


    <RootLogger root (INFO)>



.. GENERATED FROM PYTHON SOURCE LINES 38-46

Let us consider three parameters :math:`x_1`, :math:`x_2` and :math:`x_3`
of size 1, 2 and 3 respectively.
We generate 5 random samples of the inputs where

- x_1 is stored in the first column,
- x_2 is stored in the 2nd and 3rd columns

and 5 random samples of the outputs:

.. GENERATED FROM PYTHON SOURCE LINES 46-51

.. code-block:: default

    n_samples = 5
    inputs = rand(n_samples, 3)
    outputs = rand(n_samples, 3)
    data = concatenate((inputs, outputs), 1)








.. GENERATED FROM PYTHON SOURCE LINES 52-56

A dataset with default names
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
We create a :class:`.Dataset` from the NumPy array only
and let GEMSEO give default names to its columns:

.. GENERATED FROM PYTHON SOURCE LINES 56-59

.. code-block:: default

    dataset = Dataset.from_array(data)
    dataset






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
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            text-align: left;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr>
          <th>GROUP</th>
          <th colspan="6" halign="left">parameters</th>
        </tr>
        <tr>
          <th>VARIABLE</th>
          <th>x_0</th>
          <th>x_1</th>
          <th>x_2</th>
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          <td>0.884586</td>
          <td>0.705865</td>
          <td>0.491662</td>
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        <tr>
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          <td>0.902215</td>
          <td>0.310880</td>
          <td>0.021208</td>
          <td>0.039995</td>
          <td>0.773718</td>
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        </tr>
        <tr>
          <th>2</th>
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          <td>0.792577</td>
          <td>0.203123</td>
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          <td>0.110868</td>
          <td>0.176658</td>
          <td>0.650542</td>
          <td>0.962812</td>
        </tr>
        <tr>
          <th>4</th>
          <td>0.493227</td>
          <td>0.437936</td>
          <td>0.655254</td>
          <td>0.565650</td>
          <td>0.567926</td>
          <td>0.386245</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 60-63

A dataset with custom names
~~~~~~~~~~~~~~~~~~~~~~~~~~~
We can also pass the names and sizes of the variables:

.. GENERATED FROM PYTHON SOURCE LINES 63-67

.. code-block:: default

    names_to_sizes = {"x_1": 1, "x_2": 2, "y_1": 3}
    dataset = Dataset.from_array(data, ["x_1", "x_2", "y_1"], names_to_sizes)
    dataset






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    <div>
    <style scoped>
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            text-align: left;
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    <table border="1" class="dataframe">
      <thead>
        <tr>
          <th>GROUP</th>
          <th colspan="6" halign="left">parameters</th>
        </tr>
        <tr>
          <th>VARIABLE</th>
          <th>x_1</th>
          <th colspan="2" halign="left">x_2</th>
          <th colspan="3" halign="left">y_1</th>
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        <tr>
          <th>COMPONENT</th>
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          <td>0.884586</td>
          <td>0.705865</td>
          <td>0.491662</td>
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        <tr>
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          <td>0.902215</td>
          <td>0.310880</td>
          <td>0.021208</td>
          <td>0.039995</td>
          <td>0.773718</td>
          <td>0.912503</td>
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          <td>0.408196</td>
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          <td>0.603613</td>
          <td>0.488699</td>
          <td>0.792577</td>
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          <td>0.176658</td>
          <td>0.650542</td>
          <td>0.962812</td>
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          <th>4</th>
          <td>0.493227</td>
          <td>0.437936</td>
          <td>0.655254</td>
          <td>0.565650</td>
          <td>0.567926</td>
          <td>0.386245</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 68-74

.. warning::

   The number of variables names must be equal to the number of columns of
   the data array. Otherwise, the user has to specify the sizes of the
   different variables by means of a dictionary and be careful that the
   total size is equal to this number of columns.

.. GENERATED FROM PYTHON SOURCE LINES 76-79

A dataset with custom groups
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
We can also use the notions of groups of variables:

.. GENERATED FROM PYTHON SOURCE LINES 79-83

.. code-block:: default

    groups = {"x_1": "inputs", "x_2": "inputs", "y_1": "outputs"}
    dataset = Dataset.from_array(data, ["x_1", "x_2", "y_1"], names_to_sizes, groups)
    dataset






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    <div>
    <style scoped>
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        <tr>
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          <th colspan="3" halign="left">inputs</th>
          <th colspan="3" halign="left">outputs</th>
        </tr>
        <tr>
          <th>VARIABLE</th>
          <th>x_1</th>
          <th colspan="2" halign="left">x_2</th>
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          <td>0.631043</td>
          <td>0.019469</td>
          <td>0.733367</td>
          <td>0.884586</td>
          <td>0.705865</td>
          <td>0.491662</td>
        </tr>
        <tr>
          <th>1</th>
          <td>0.902215</td>
          <td>0.310880</td>
          <td>0.021208</td>
          <td>0.039995</td>
          <td>0.773718</td>
          <td>0.912503</td>
        </tr>
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          <td>0.408196</td>
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          <td>0.176658</td>
          <td>0.650542</td>
          <td>0.962812</td>
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          <td>0.493227</td>
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          <td>0.567926</td>
          <td>0.386245</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 84-90

.. note::

   The groups are specified by means of a dictionary
   where indices are the variables names and values are the groups.
   If a variable is missing,
   the default group :attr:`.Dataset.DEFAULT_GROUP` is considered.


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

   **Total running time of the script:** (0 minutes 0.018 seconds)


.. _sphx_glr_download_examples_dataset_creation_plot_dataset_from_array.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_dataset_from_array.py <plot_dataset_from_array.py>`

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

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


.. only:: html

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

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