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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_plot_power_spectra_example.py:


Power Spectra Example
===================================

Example of a power spectra plot.

.. GENERATED FROM PYTHON SOURCE LINES 8-78



.. image-sg:: /auto_examples/images/sphx_glr_plot_power_spectra_example_001.png
   :alt: Power Spectra Density, Vector U
   :srcset: /auto_examples/images/sphx_glr_plot_power_spectra_example_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Saving figures to memory, n_iterations: 7






|

.. code-block:: Python

    from gerg_plotting import ScatterPlot, data_from_df
    import pandas as pd
    import matplotlib.pyplot as plt
    import numpy as np

    # Let's read in the example data
    df = pd.read_csv('example_data/sample_tabs_data.csv')

    # Init some base parameters
    samp_freq = 48
    seg_len = 256
    theta_rad = np.deg2rad(55)
    highlight_freqs = [1/10, 1, 2]
    y_limits = (10,10e5)

    # In this first example we will let the power_spectra_density function calculate the PSD for us,
    # we just need to supply a few parameters to the calculation

    # Init data
    data = data_from_df(df)
    # Init ScatterPlot
    scatter = ScatterPlot(data)
    # Plot power spectra density
    scatter.power_spectra_density(var_name='u',sampling_freq=samp_freq,segment_length=seg_len,theta_rad=theta_rad,
                                    highlight_freqs=highlight_freqs)
    # Set the ylimits so the plots all match up
    scatter.ax.set_ylim(*y_limits)
    # Add an informative title
    scatter.ax.set_title('Vector U')
    # scatter.show()

    # Now Let's look at a more advanced use

    # Import the Animator class
    from gerg_plotting import Animator

    # first we need to create a function that will return the figure
    def power_spectra_plot(group):
        '''
        Plot the power spectra of vectors u, v, and w
        '''
        data = data_from_df(group)

        # We can calcluate the PSD using the calcluate_PSD method in the Data object
        psd_freq,psd_u,psd_v,psd_w = data.calcluate_PSD(sampling_freq=samp_freq,segment_length=seg_len,theta_rad=theta_rad)
    
        # Init the subplots
        fig,axes = plt.subplots(nrows=3,figsize=(10,18),layout='constrained')

        # Init the ScatterPlot
        scatter = ScatterPlot(data)
        # Plot the PSD for each vector and set their ylimits
        scatter.power_spectra_density(psd_freq=psd_freq,psd=psd_u,highlight_freqs=highlight_freqs,fig=fig,ax=axes[0])
        scatter.ax.set_title('Vector U')
        scatter.ax.set_ylim(*y_limits)
        scatter.power_spectra_density(psd_freq=psd_freq,psd=psd_v,highlight_freqs=highlight_freqs,fig=fig,ax=axes[1])
        scatter.ax.set_title('Vector V')
        scatter.ax.set_ylim(*y_limits)
        scatter.power_spectra_density(psd_freq=psd_freq,psd=psd_w,highlight_freqs=highlight_freqs,fig=fig,ax=axes[2])
        scatter.ax.set_title('Vector W')
        scatter.ax.set_ylim(*y_limits)
        # Add informative figure title
        scatter.fig.suptitle(f'Auto-spectra at Bin Depth: {group['bin_depth'].min()} m',fontsize=22)
        return scatter.fig

    # Extract groups by bin_depth
    groups = [group for _,group in df.groupby('bin_depth')]

    # Create an animation of the power spectra along depth
    Animator().animate(plotting_function=power_spectra_plot,param_dict={'group':groups},gif_filename='example_plots/power_spectra_example.gif',fps=0.75)


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

   **Total running time of the script:** (0 minutes 17.581 seconds)


.. _sphx_glr_download_auto_examples_plot_power_spectra_example.py:

.. only:: html

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

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

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_power_spectra_example.zip <plot_power_spectra_example.zip>`


.. only:: html

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

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