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

.. only:: html

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

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

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

.. _sphx_glr_csi_add_noise_tutorial.py:


CSI Augmentation.adding_noise Tutorial
==============================================================

.. GENERATED FROM PYTHON SOURCE LINES 6-9

.. code-block:: Python


    # !pip install pysensing








.. GENERATED FROM PYTHON SOURCE LINES 10-12

In this tutorial, we will be implementing a simple csi.augmentation.adding_noise tutorial using the pysensing library.


.. GENERATED FROM PYTHON SOURCE LINES 12-20

.. code-block:: Python

    import sys
    sys.path.append('../..')
    import pysensing.csi.augmentation.adding_noise as adding_noise
    import pysensing.csi.dataset.get_dataloader as load_data
    import matplotlib.pyplot as plt
    import numpy as np
    from scipy import signal








.. GENERATED FROM PYTHON SOURCE LINES 21-23

Load the data
-----------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 23-68

.. code-block:: Python


    # Define the plot function

    def plot_csi_heatmap(csi_data):
        """
        Plot WiFi CSI heatmap.

        """
        data_shape = csi_data.shape

        if len(data_shape) == 2:
            csi_to_plot = csi_data
        elif len(data_shape) > 2:
            csi_to_plot = csi_data.reshape(-1, data_shape[-1])
        else:
            raise ValueError("The input data should have at least 2 dimensions.")
    
        plt.figure(figsize=(15, 8))
        plt.imshow(csi_to_plot, aspect='auto', cmap='viridis')
        plt.colorbar(label='CSI Amplitude')
        plt.title('WiFi CSI Heatmap')
        plt.xlabel('Time Index')
        plt.ylabel('Subcarrier Index / Flattened Antenna-Subcarrier Index')
        plt.show()
    
    
    def plot_spec(csi):
        _, _, csi_spectrogram = signal.stft(csi, window='hann', nperseg=256, noverlap=128)
        specgram = np.abs(csi_spectrogram) 
        plt.figure(figsize=(10,5))
        plt.imshow(specgram.squeeze(), aspect='auto', origin='lower', cmap='inferno')
        plt.colorbar(label='CSI Amplitude')
        plt.xlabel('Time (s)')
        plt.ylabel('Frequency (Hz)')

    # Load the data

    _, test_loader = load_data.load_classification_dataset('UT_HAR',batch_size=1)
    example_csi_data_list = []
    for data in test_loader:
        data, label = data
        example_csi_data_list.append(data)

    example_csi_data = np.concatenate(example_csi_data_list, axis=-1)
    plot_csi_heatmap(example_csi_data)



.. image-sg:: /csi/images/sphx_glr_add_noise_tutorial_001.png
   :alt: WiFi CSI Heatmap
   :srcset: /csi/images/sphx_glr_add_noise_tutorial_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    /data1/msc/zyj/yunjiao_csi/1028/yunjiao_csi/tutorials/csi_source/data/csi
    using dataset: UT-HAR DATA




.. GENERATED FROM PYTHON SOURCE LINES 69-72

1. dropout
------------------------
Use dropout augmentation

.. GENERATED FROM PYTHON SOURCE LINES 72-80

.. code-block:: Python


    csi_process = adding_noise.dropout(dropout_prob=0.2)
    plot_spec(example_csi_data.squeeze()[2])
    reduced_csi_data = csi_process(example_csi_data)
    plot_spec(reduced_csi_data.squeeze()[2])
    plot_csi_heatmap(reduced_csi_data)





.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /csi/images/sphx_glr_add_noise_tutorial_002.png
         :alt: add noise tutorial
         :srcset: /csi/images/sphx_glr_add_noise_tutorial_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /csi/images/sphx_glr_add_noise_tutorial_003.png
         :alt: add noise tutorial
         :srcset: /csi/images/sphx_glr_add_noise_tutorial_003.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /csi/images/sphx_glr_add_noise_tutorial_004.png
         :alt: WiFi CSI Heatmap
         :srcset: /csi/images/sphx_glr_add_noise_tutorial_004.png
         :class: sphx-glr-multi-img





.. GENERATED FROM PYTHON SOURCE LINES 81-84

2. guassian noise
------------------------
add gaussian noise

.. GENERATED FROM PYTHON SOURCE LINES 84-90

.. code-block:: Python


    csi_process = adding_noise.add_noise(noise_std=0.02)
    reduced_csi_data = csi_process(example_csi_data)
    plot_csi_heatmap(reduced_csi_data)





.. image-sg:: /csi/images/sphx_glr_add_noise_tutorial_005.png
   :alt: WiFi CSI Heatmap
   :srcset: /csi/images/sphx_glr_add_noise_tutorial_005.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 91-92

And that's it. We're done with our CSI augmentation.adding_noise tutorials. Thanks for reading.


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

   **Total running time of the script:** (0 minutes 6.199 seconds)


.. _sphx_glr_download_csi_add_noise_tutorial.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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