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

.. only:: html

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

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

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

.. _sphx_glr_examples_gallery_plot_speed_on_track.py:

Speed visualization on track map
======================================

(Example provided by @JSEHV on Github)

.. GENERATED FROM PYTHON SOURCE LINES 6-14

.. code-block:: Python

    import matplotlib as mpl
    import numpy as np
    from matplotlib import pyplot as plt
    from matplotlib.collections import LineCollection

    import fastf1 as ff1









.. GENERATED FROM PYTHON SOURCE LINES 15-17

First, we define some variables that allow us to conveniently control what
we want to plot.

.. GENERATED FROM PYTHON SOURCE LINES 17-24

.. code-block:: Python

    year = 2021
    wknd = 9
    ses = 'R'
    driver = 'RIC'
    colormap = mpl.cm.plasma









.. GENERATED FROM PYTHON SOURCE LINES 25-26

Next, we load the session and select the desired data.

.. GENERATED FROM PYTHON SOURCE LINES 26-37

.. code-block:: Python

    session = ff1.get_session(year, wknd, ses)
    weekend = session.event
    session.load()
    lap = session.laps.pick_driver(driver).pick_fastest()

    # Get telemetry data
    x = lap.telemetry['X']              # values for x-axis
    y = lap.telemetry['Y']              # values for y-axis
    color = lap.telemetry['Speed']      # value to base color gradient on









.. GENERATED FROM PYTHON SOURCE LINES 38-42

Now, we create a set of line segments so that we can color them
individually. This creates the points as a N x 1 x 2 array so that we can
stack points  together easily to get the segments. The segments array for
line collection needs to be (numlines) x (points per line) x 2 (for x and y)

.. GENERATED FROM PYTHON SOURCE LINES 42-46

.. code-block:: Python

    points = np.array([x, y]).T.reshape(-1, 1, 2)
    segments = np.concatenate([points[:-1], points[1:]], axis=1)









.. GENERATED FROM PYTHON SOURCE LINES 47-48

After this, we can actually plot the data.

.. GENERATED FROM PYTHON SOURCE LINES 48-84

.. code-block:: Python


    # We create a plot with title and adjust some setting to make it look good.
    fig, ax = plt.subplots(sharex=True, sharey=True, figsize=(12, 6.75))
    fig.suptitle(f'{weekend.name} {year} - {driver} - Speed', size=24, y=0.97)

    # Adjust margins and turn of axis
    plt.subplots_adjust(left=0.1, right=0.9, top=0.9, bottom=0.12)
    ax.axis('off')


    # After this, we plot the data itself.
    # Create background track line
    ax.plot(lap.telemetry['X'], lap.telemetry['Y'],
            color='black', linestyle='-', linewidth=16, zorder=0)

    # Create a continuous norm to map from data points to colors
    norm = plt.Normalize(color.min(), color.max())
    lc = LineCollection(segments, cmap=colormap, norm=norm,
                        linestyle='-', linewidth=5)

    # Set the values used for colormapping
    lc.set_array(color)

    # Merge all line segments together
    line = ax.add_collection(lc)


    # Finally, we create a color bar as a legend.
    cbaxes = fig.add_axes([0.25, 0.05, 0.5, 0.05])
    normlegend = mpl.colors.Normalize(vmin=color.min(), vmax=color.max())
    legend = mpl.colorbar.ColorbarBase(cbaxes, norm=normlegend, cmap=colormap,
                                       orientation="horizontal")


    # Show the plot
    plt.show()



.. image-sg:: /examples_gallery/images/sphx_glr_plot_speed_on_track_001.png
   :alt: 9 2021 - RIC - Speed
   :srcset: /examples_gallery/images/sphx_glr_plot_speed_on_track_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 5.938 seconds)


.. _sphx_glr_download_examples_gallery_plot_speed_on_track.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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