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.. _sphx_glr_auto_examples_01_ImportingData_plot_05_indexing_dnpdata_objects.py:


.. _plot_05_indexing_dnpdata_objects:

==============================================
How to select a slice from a 2D dnpdata object
==============================================

This example demonstrates how to select a slice of a DNPData object.

You can index a DNPData object by specifying the name of the dimension and the index of the slice.

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Import DNPLab and create a set of data
--------------------------------------
Use the lorentzian function to generate a 2d set of lorentzian distributions.

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.. code-block:: Python


    import numpy as np
    from matplotlib.pylab import *

    import dnplab as dnp

    x = np.r_[-50:50:1024j]
    y = np.r_[-10:10:1]

    values = dnp.math.lineshape.lorentzian(x.reshape(-1, 1), y.reshape(1, -1), 0.5)

    data = dnp.DNPData(values, ["f2", "sample"], [x, y])








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To specify a slice based on the index, we use an integer. This will select the slice at index 3.

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.. code-block:: Python


    data_slice_integer = data["sample", 3]  # get slice by index

    # Taking the slice does not remove the sample dimension. We can remove dimensions of length 1 with the squeeze method
    data_slice_integer.squeeze()  # remove "sample" dimension








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In many cases, we want the slice at a specific value of the coordinates. To do this, we use a float to specify the slice location. In python, by adding a period after the number, python interprets the number as a float instead of integer.

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.. code-block:: Python


    data_slice_float = data[
        "sample", 3.0
    ]  # get slice at index closest to coordinates value of 3.
    data_slice_float.squeeze()  # again, we remove the "sample" dimension.








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Plot the result
---------------
Let's plot the 1d slices:

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.. code-block:: Python


    figure()
    dnp.plot(data_slice_integer)
    dnp.plot(data_slice_float)
    xlabel("Frequency (Hz)")
    ylabel("Signal (a.u.)")
    tight_layout()




.. image-sg:: /auto_examples/01_ImportingData/images/sphx_glr_plot_05_indexing_dnpdata_objects_001.png
   :alt: plot 05 indexing dnpdata objects
   :srcset: /auto_examples/01_ImportingData/images/sphx_glr_plot_05_indexing_dnpdata_objects_001.png
   :class: sphx-glr-single-img





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Similarly, we can also slice by specifying a range of values. To do this, we use a tuple specify the minimum and maximum values for the index.

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.. code-block:: Python


    data_slice_range = data["sample", (-3, 3)]








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For an advanced tutorial how indexing works and how to extract individual data slice from a multi-dimensional dnpData object see the :ref:`plot_02_extract_data` tutorial.


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