******************************************************
Generate new files with spiking information
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``pyNAVIS`` has three different functionalities to generate new custom artificial files with spiking information.
These are described in the :doc:`Generators class <../pyNAVIS.generators>`:

* :ref:`random_addrs() <random_addrs>`
* :ref:`shift() <shift>`
* :ref:`sweep() <sweep>`


.. _random_addrs:

1. Random addresses
##############################

The ``random_addr()`` function lets you generate a new file with completely random spikes.
The spike rate, the length of the file and the number of channels can be specified to customize the output file.

.. prompt:: python \

    from pyNAVIS import *
    
    f = 1000        # frequency of the spikes generated per channel.
    n_ch = 64       # number of channels (or addresses)
    l = 1000000     # microseconds

    rand_spikes = Generators.random_addrs(freq=f, num_ch=n_ch, length=l, return_save_both=0)

The parameter ``return_save_both`` is set to 0, which means that, instead of saving the information to a file, it will return it in the **sweep_spikes** variable.
Then, you can use that variable to plot the spikes. Here you can see an example of the code that you would need to add to the previous code:

.. prompt:: python \

    import matplotlib.pyplot as plt
    
    rand_settings = MainSettings(num_channels=64, mono_stereo=0, on_off_both=0, bin_size=20000)
    
    Plots.spikegram(rand_spikes, rand_settings)
    Plots.sonogram(rand_spikes, rand_settings)
    Plots.histogram(rand_spikes, rand_settings)

    plt.show()

This will generate the plots that can be seen in the next figure.

.. figure:: /_static/random_addrs.png
   :scale: 100 %   
   :align: center
   :alt: Random addresses plots

.. _shift:

2. Shift
##############################

The ``shift()`` function generates a frequency shift from lower addresses to higher addresses.
To use this function, you can follow the next example:

.. prompt:: python \

    from pyNAVIS import *
    
    f = 10          # number of spikes per channel.
    n_ch = 64       # number of channels (or addresses)
    l = 1000000     # microseconds

    shift_spikes = Generators.shift(freq=f, num_ch=n_ch, length=l, return_save_both=0)

And plot the information with the same code that was used in previous examples.

Here you can see the spikegram of the shift that corresponds to the example:


.. figure:: /_static/shift_Spikegram.png
   :scale: 80 %   
   :align: center
   :alt: Shift spikegram




.. _sweep:

3. Sweep
##############################

The ``sweep()`` is very similar to the ``shift()`` function, but instead of going from lower to higher addresses, it goes back again, doing a full cycle.

See the following example:

.. prompt:: python \

    from pyNAVIS import *
    
    f = 5           # number of spikes per channel and shift.
    c = 5           # total number of cycles to perform
    n_ch = 64       # number of channels (or addresses)
    l = 1000000     # microseconds

    sweep_spikes = Generators.sweep(freq=f, cycles=c, num_ch=n_ch, length=l, return_save_both=0)


And you can also plot the information following the example presented in the ``random_addrs()`` section.

Here you can see the spikegram of the sweep that corresponds to the example:

.. image:: /_static/sweep_Spikegram.png
   :scale: 80 %   
   :align: center
   :alt: Sweep spikegram