Common Average Re-Referencing
=============================


.. currentmodule:: basic.car
.. autofunction:: run


The following example shows how to apply car.

.. code:: python
   
   import numpy as np
   import finn.basic.common_average_rereferncing as car
   
   import matplotlib
   matplotlib.use("Qt5agg")
   import matplotlib.pyplot as plt
   
   import random
   
   def main():
      #Configure sample data
      channel_count = 256
      frequency = [random.randint(5, 50) for _ in range(channel_count)]
      data_range = np.arange(0, 10000)
      frequency_sampling = 200
      
      #Configure noise data
      frequency_noise = 50
      shared_noise_strength = 10
      random_noise_strength = 1
      
      #Generate some sample data
      raw_data = [None for _ in range(channel_count)]
      for idx in range(channel_count):
          genuine_signal = np.sin(2 * np.pi * frequency[idx] * data_range / frequency_sampling)
          shared_noise_signal = np.sin(2 * np.pi * frequency_noise * data_range / frequency_sampling)
          * shared_noise_strength
          random_noise_signal = np.random.random(len(data_range)) * random_noise_strength
        
          raw_data[idx] = genuine_signal + shared_noise_signal + random_noise_signal
      raw_data = np.asarray(raw_data)
        
      car_data = car.run(raw_data)
    
      #visualize result
      (fig, axes) = plt.subplots(3, 2)
      fig.suptitle("Peaks are supposedly at %i, %i and %iHz" % (frequency[0], frequency[1], frequency[2]))
      for idx in range(3):
          axes[idx, 0].psd(raw_data[idx, :], NFFT = frequency_sampling, Fs = frequency_sampling)
          axes[idx, 1].psd(car_data[idx, :], NFFT = frequency_sampling, Fs = frequency_sampling)
    
      plt.show(block = True)

    main()

While there is an artifact at 50Hz on the left side (pre car application), this artifact is gone on the right side. As this artifact was introduced by the shared reference, applying a car filter removed the artifact:
    
.. image:: img/car.png