.. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_intro_summary-exercises_auto_examples_plot_optimize_lidar_complex_data.py: The lidar system, data (2 of 2 datasets) ======================================== Generate a chart of more complex data recorded by the lidar system .. image:: /intro/summary-exercises/auto_examples/images/sphx_glr_plot_optimize_lidar_complex_data_001.png :class: sphx-glr-single-img .. code-block:: python import numpy as np import matplotlib.pyplot as plt waveform_2 = np.load('waveform_2.npy') t = np.arange(len(waveform_2)) fig, ax = plt.subplots(figsize=(8, 6)) plt.plot(t, waveform_2) plt.xlabel('Time [ns]') plt.ylabel('Amplitude [bins]') plt.show() **Total running time of the script:** ( 0 minutes 0.011 seconds) .. _sphx_glr_download_intro_summary-exercises_auto_examples_plot_optimize_lidar_complex_data.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: plot_optimize_lidar_complex_data.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: plot_optimize_lidar_complex_data.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_