.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_1D_1_examples_plot_6_Mass.py>`     to download the full example code
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_auto_examples_1D_1_examples_plot_6_Mass.py:


Mass spectrometry (sparse) dataset
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

The following mass spectrometry data of acetone is an example of a sparse dataset.
Here, the CSDM data file holds a sparse dependent variable. Upon import, the components
of the dependent variable sparsely populates the coordinate grid. The
remaining unpopulated coordinates are assigned a zero value.


.. code-block:: default

    import csdmpy as cp

    filename = "https://osu.box.com/shared/static/ul3rajps49zfuz9ozj3j5xsjmgeuybuy.csdf"
    mass_spec = cp.load(filename)
    print(mass_spec.data_structure)





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

 Out:

 .. code-block:: none

    {
      "csdm": {
        "version": "1.0",
        "read_only": true,
        "timestamp": "2019-06-23T17:53:26Z",
        "description": "MASS spectrum of acetone",
        "dimensions": [
          {
            "type": "linear",
            "count": 51,
            "increment": "1.0",
            "coordinates_offset": "10.0",
            "label": "m/z"
          }
        ],
        "dependent_variables": [
          {
            "type": "internal",
            "name": "acetone",
            "numeric_type": "float32",
            "quantity_type": "scalar",
            "component_labels": [
              "relative abundance"
            ],
            "components": [
              [
                "0.0, 0.0, ..., 10.0, 0.0"
              ]
            ]
          }
        ]
      }
    }




Here, the coordinates along the dimension are


.. code-block:: default

    print(mass_spec.dimensions[0].coordinates)





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

 Out:

 .. code-block:: none

    [10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27.
     28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45.
     46. 47. 48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60.]




and the corresponding components of the dependent variable,


.. code-block:: default

    print(mass_spec.dependent_variables[0].components[0])





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

 Out:

 .. code-block:: none

    [   0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.
        0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.
        0.    0.    0.    9.    9.   49.    0.    0.   79. 1000.   19.    0.
        0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.    0.
      270.   10.    0.]




Note, only eight values were listed in the dependent variable's `components`
attribute in the `.csdf` file. The remaining component values were set to zero.


.. code-block:: default

    cp.plot(mass_spec)



.. image:: /auto_examples/1D_1_examples/images/sphx_glr_plot_6_Mass_001.png
    :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 0 minutes  1.133 seconds)


.. _sphx_glr_download_auto_examples_1D_1_examples_plot_6_Mass.py:


.. only :: html

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



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

     :download:`Download Python source code: plot_6_Mass.py <plot_6_Mass.py>`



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

     :download:`Download Jupyter notebook: plot_6_Mass.ipynb <plot_6_Mass.ipynb>`


.. only:: html

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

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