*****************************
:py:mod:`wildboar.utils.plot`
*****************************

.. py:module:: wildboar.utils.plot

.. autoapi-nested-parse::

   Plotting utilities.

   ..
       !! processed by numpydoc !!




Functions
---------

.. autoapisummary::

   wildboar.utils.plot.plot_frequency_domain
   wildboar.utils.plot.plot_time_domain




.. raw:: html

   <br />

.. py:function:: plot_frequency_domain(x, y=None, *, ax=None, n_samples=100, jitter=False, spectrum='amplitude', sample_spacing=1, bins=None, cmap='Dark2')

   
   Plot the samples in the frequency domain.


   :Parameters:

       **x** : array-like of shape (n_sample, n_timestep)
           The samples.

       **y** : array-like of shape (n_samples, ), optional
           The labels.

       **ax** : Axes, optional
           The matplotlib Axes-object.

       **n_samples** : int, optional
           The maximum number of samples to plot. If n_samples is larger than the number
           of samples in x or None, all samples are plotted.

       **jitter** : bool, optional
           Add jitter to the amplitude lines.

       **spectrum** : {"amplitude", "phase"}, optional
           The spectrum.

       **sample_spacing** : int, optional
           The frequency domain sample spacing.

       **bins** : bool, optional
           Show the frequency bins.

       **cmap** : str, optional
           The colormap.



   :Returns:

       Axes
           The axes object that has been plotted.










   .. rubric:: Examples

   >>> from wildboar.utils.plot import plot_frequency_domain
   >>> from wildboar.datasets import load_gun_point
   >>> X, y = load_gun_point()
   >>> plot_frequency_domain(X, y, n_sample=10)

   ..
       !! processed by numpydoc !!

.. py:function:: plot_time_domain(x, y=None, *, n_samples=100, ax=None, alpha=0.5, linewidth=0.5, zorder=-1, cmap='Dark2', show_legend=8)

   
   Plot the samples in the time domain.


   :Parameters:

       **x** : array-like of shape (n_sample, n_timestep)
           The samples.

       **y** : array-like of shape (n_samples, ), optional
           The labels, assumed to be discrete labels.

       **n_samples** : int, optional
           The maximum number of samples to plot. If n_samples is larger than the number
           of samples in x or None, all samples are plotted.

       **ax** : Axes, optional
           The matplotlib Axes-object.

       **alpha** : float, optional
           The opacity of the samples.

       **linewidth** : float, optional
           The width of the sample lines.

       **zorder** : int, optional
           The order where the samples are plotted. By default we plot the samples
           at -1.

       **cmap** : str, optional
           The colormap used to colorize samples according to its label.

       **show_legend** : bool or int, optional
           Whether the legend of labels are show.
           
           - if bool, show the legend if y is not None
           - if int, show the legend if the number of labels are lower than the
             show_legend parameter value



   :Returns:

       Axes
           The axes object that has been plotted.










   .. rubric:: Examples

   >>> from wildboar.utils.plot import plot_time_domain
   >>> from wildboar.datasets import load_gun_point
   >>> X, y = load_gun_point()
   >>> plot_time_domain(X, y, n_sample=10)

   ..
       !! processed by numpydoc !!