.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_vector_plot_0_vector.py>`     to download the full example code
    .. rst-class:: sphx-glr-example-title

    .. _sphx_glr_auto_examples_vector_plot_0_vector.py:


Vector, 1D{2} dataset
---------------------

The 1D{2} datasets are one-dimensional, :math:`d=1`, with two-component
dependent variable, :math:`p=2`. Such datasets are more common with the
weather forecast, such as the wind velocity predicting at a location
as a function of time.

The following is an example of a simulated 1D vector field dataset.


.. code-block:: default

    import csdmpy as cp

    filename = "https://osu.box.com/shared/static/w63851uqruzhz6kx9rx5qgk3or2pot9l.csdf"
    vector_data = cp.load(filename)
    print(vector_data.data_structure)





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

 Out:

 .. code-block:: none

    {
      "csdm": {
        "version": "1.0",
        "read_only": true,
        "timestamp": "2019-02-12T10:00:00Z",
        "dimensions": [
          {
            "type": "linear",
            "count": 10,
            "increment": "1.0 m",
            "quantity_name": "length",
            "reciprocal": {
              "quantity_name": "wavenumber"
            }
          }
        ],
        "dependent_variables": [
          {
            "type": "internal",
            "numeric_type": "float32",
            "quantity_type": "vector_2",
            "components": [
              [
                "0.6907923, 0.31292602, ..., 0.40570852, 0.7005596"
              ],
              [
                "0.5603441, 0.06866818, ..., 0.48200375, 0.15077808"
              ]
            ]
          }
        ]
      }
    }




The tuple of the dimension and dependent variable instances from this example
are


.. code-block:: default


    x = vector_data.dimensions
    y = vector_data.dependent_variables








with coordinates


.. code-block:: default


    print(x[0].coordinates)





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

 Out:

 .. code-block:: none

    [0. 1. 2. 3. 4. 5. 6. 7. 8. 9.] m




In this example, the components of the dependent variable are
vectors as seen from the
:attr:`~csdmpy.DependentVariable.quantity_type`
attribute of the corresponding dependent variable instance.


.. code-block:: default


    print(y[0].quantity_type)





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

 Out:

 .. code-block:: none

    vector_2




From the value `vector_2`, `vector` indicates a vector dataset, while `2`
indicates the number of vector components.

**Visualizing the dataset**


.. code-block:: default


    cp.plot(vector_data)



.. image:: /auto_examples/vector/images/sphx_glr_plot_0_vector_001.png
    :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 0 minutes  1.196 seconds)


.. _sphx_glr_download_auto_examples_vector_plot_0_vector.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_0_vector.py <plot_0_vector.py>`



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

     :download:`Download Jupyter notebook: plot_0_vector.ipynb <plot_0_vector.ipynb>`


.. only:: html

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

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