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

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

.. _sphx_glr_auto_examples_create_signal_from_tabular_data.py:


Creates a signal1D from tabular data
====================================

This example creates a signal from tabular data, where the signal axis is given by an array
of data values (the ``x`` column) and the tabular data are ordered in columns with 5 columns
containing each 20 values and each column corresponding to a position in the
navigation space (linescan).

.. GENERATED FROM PYTHON SOURCE LINES 10-14

.. code-block:: Python


    import numpy as np
    import hyperspy.api as hs








.. GENERATED FROM PYTHON SOURCE LINES 15-16

Create a set of tabular data:

.. GENERATED FROM PYTHON SOURCE LINES 16-20

.. code-block:: Python


    x = np.linspace(0, 10, 20)
    y = np.random.default_rng().random((20, 5))








.. GENERATED FROM PYTHON SOURCE LINES 21-22

Define the axes of the signal and then create the signal:

.. GENERATED FROM PYTHON SOURCE LINES 22-32

.. code-block:: Python


    axes = [
        # length of the navigation axis
        dict(size=y.shape[1], scale=0.1, name="Position", units="nm"),
        # use values to define non-uniform axis for the signal axis
        dict(axis=x, name="Energy", units="eV"),
        ]

    s = hs.signals.Signal1D(y.T, axes=axes)








.. GENERATED FROM PYTHON SOURCE LINES 33-36

Convert the non-uniform signal axis to a uniform axis, because non-uniform axes do not
support all functionalities of HyperSpy.
In this case, the error introduced during conversion to uniform `scale` is negligeable.

.. GENERATED FROM PYTHON SOURCE LINES 36-39

.. code-block:: Python


    s.axes_manager.signal_axes[0].convert_to_uniform_axis()








.. GENERATED FROM PYTHON SOURCE LINES 40-41

Set title of the dataset and label for the data axis:

.. GENERATED FROM PYTHON SOURCE LINES 41-45

.. code-block:: Python


    s.metadata.set_item("General.title", "Random test data")
    s.metadata.set_item("Signal.quantity", "Intensity (counts)")








.. GENERATED FROM PYTHON SOURCE LINES 46-47

Plot the dataset:

.. GENERATED FROM PYTHON SOURCE LINES 47-51

.. code-block:: Python


    s.plot()
    # Choose the second figure as gallery thumbnail:
    # sphinx_gallery_thumbnail_number = 2



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/create_signal/images/sphx_glr_from_tabular_data_001.png
         :alt: Random test data Navigator
         :srcset: /auto_examples/create_signal/images/sphx_glr_from_tabular_data_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/create_signal/images/sphx_glr_from_tabular_data_002.png
         :alt: Random test data Signal
         :srcset: /auto_examples/create_signal/images/sphx_glr_from_tabular_data_002.png
         :class: sphx-glr-multi-img






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

   **Total running time of the script:** (0 minutes 0.596 seconds)


.. _sphx_glr_download_auto_examples_create_signal_from_tabular_data.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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