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Merge pull request #311 from ahmedfgad/github-actions
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‎docs/source/visualize.rst

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@@ -10,11 +10,15 @@ visualization in PyGAD.
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This section discusses the different options to visualize the results in
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PyGAD through these methods:
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1. ``plot_fitness()``: Create plots for the fitness.
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1. ``plot_fitness()``: Creates plots for the fitness.
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2. ``plot_genes()``: Create plots for the genes.
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2. ``plot_genes()``: Creates plots for the genes.
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3. ``plot_new_solution_rate()``: Create plots for the new solution rate.
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3. ``plot_new_solution_rate()``: Creates plots for the new solution
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rate.
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4. ``plot_pareto_front_curve()``: Creates plots for the pareto front for
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multi-objective problems.
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In the following code, the ``save_solutions`` flag is set to ``True``
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which means all solutions are saved in the ``solutions`` attribute. The
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9. ``save_dir``: Directory to save the figure.
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.. _plottypeplot:
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.. _plottype=plot:
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``plot_type="plot"``
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~~~~~~~~~~~~~~~~~~~~
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ga_instance.plot_fitness()
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# ga_instance.plot_fitness(plot_type="plot")
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.. image:: https://user-images.githubusercontent.com/16560492/122472609-d02f5280-cf8e-11eb-88a7-f9366ff6e7c6.png
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:alt:
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|image1|
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.. _plottypescatter:
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.. _plottype=scatter:
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``plot_type="scatter"``
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~~~~~~~~~~~~~~~~~~~~~~~
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ga_instance.plot_fitness(plot_type="scatter")
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.. image:: https://user-images.githubusercontent.com/16560492/122473159-75e2c180-cf8f-11eb-942d-31279b286dbd.png
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:alt:
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|image2|
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.. _plottypebar:
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.. _plottype=bar:
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``plot_type="bar"``
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~~~~~~~~~~~~~~~~~~~
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ga_instance.plot_fitness(plot_type="bar")
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.. image:: https://user-images.githubusercontent.com/16560492/122473340-b7736c80-cf8f-11eb-89c5-4f7db3b653cc.png
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:alt:
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|image3|
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New Solution Rate
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=================
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8. ``save_dir``: Directory to save the figure.
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.. _plottypeplot-2:
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.. _plottype=plot-2:
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``plot_type="plot"``
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~~~~~~~~~~~~~~~~~~~~
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population (i.e. the value assigned to the ``sol_per_pop`` parameter in
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the constructor of the ``pygad.GA`` class) which is 10 in this example.
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.. image:: https://user-images.githubusercontent.com/16560492/122475815-3322e880-cf93-11eb-9648-bf66f823234b.png
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:alt:
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|image4|
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.. _plottypescatter-2:
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.. _plottype=scatter-2:
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``plot_type="scatter"``
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~~~~~~~~~~~~~~~~~~~~~~~
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ga_instance.plot_new_solution_rate(plot_type="scatter")
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.. image:: https://user-images.githubusercontent.com/16560492/122476108-adec0380-cf93-11eb-80ac-7588bf90492f.png
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:alt:
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|image5|
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.. _plottypebar-2:
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.. _plottype=bar-2:
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``plot_type="bar"``
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~~~~~~~~~~~~~~~~~~~
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ga_instance.plot_new_solution_rate(plot_type="bar")
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.. image:: https://user-images.githubusercontent.com/16560492/122476173-c2c89700-cf93-11eb-9e77-d39737cd3a96.png
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:alt:
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|image6|
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Genes
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=====
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An exception is raised if:
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- ``solutions="all"`` while ``save_solutions=False`` in the constructor
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of the ``pygad.GA`` class. .
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- ``solutions="all"`` while ``save_solutions=False`` in the constructor
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of the ``pygad.GA`` class. .
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- ``solutions="best"`` while ``save_best_solutions=False`` in the
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constructor of the ``pygad.GA`` class. .
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- ``solutions="best"`` while ``save_best_solutions=False`` in the
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constructor of the ``pygad.GA`` class. .
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.. _graphtypeplot:
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.. _graphtype=plot:
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``graph_type="plot"``
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~~~~~~~~~~~~~~~~~~~~~
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the relationship between the gene values and the generation numbers is
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represented as a continuous plot, scattered points, or bars.
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.. _plottypeplot-3:
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.. _plottype=plot-3:
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``plot_type="plot"``
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^^^^^^^^^^^^^^^^^^^^
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ga_instance.plot_genes(graph_type="plot",
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plot_type="plot")
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.. image:: https://user-images.githubusercontent.com/16560492/122477158-4a62d580-cf95-11eb-8c93-9b6e74cb814c.png
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:alt:
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|image7|
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As the default value for the ``solutions`` parameter is ``"all"``, then
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the following method calls generate the same plot.
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plot_type="plot",
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solutions="all")
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.. _plottypescatter-3:
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.. _plottype=scatter-3:
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``plot_type="scatter"``
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^^^^^^^^^^^^^^^^^^^^^^^
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plot_type="scatter",
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solutions='all')
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.. image:: https://user-images.githubusercontent.com/16560492/122477273-73836600-cf95-11eb-828f-f357c7b0f815.png
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:alt:
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|image8|
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.. _plottypebar-3:
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.. _plottype=bar-3:
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``plot_type="bar"``
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^^^^^^^^^^^^^^^^^^^
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plot_type="bar",
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solutions='all')
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.. image:: https://user-images.githubusercontent.com/16560492/122477370-99106f80-cf95-11eb-8643-865b55e6b844.png
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:alt:
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|image9|
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.. _graphtypeboxplot:
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.. _graphtype=boxplot:
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``graph_type="boxplot"``
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~~~~~~~~~~~~~~~~~~~~~~~~
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ga_instance.plot_genes(graph_type="boxplot",
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solutions='all')
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.. image:: https://user-images.githubusercontent.com/16560492/122479260-beeb4380-cf98-11eb-8f08-23707929b12c.png
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:alt:
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|image10|
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.. _graphtypehistogram:
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.. _graphtype=histogram:
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``graph_type="histogram"``
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ga_instance.plot_genes(graph_type="histogram",
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solutions='all')
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.. image:: https://user-images.githubusercontent.com/16560492/122477314-8007be80-cf95-11eb-9c95-da3f49204151.png
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:alt:
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|image11|
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All the previous figures can be created for only the best solutions by
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setting ``solutions="best"``.
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Pareto Front
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============
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.. _plotparetofrontcurve:
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``plot_pareto_front_curve()``
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-----------------------------
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The ``plot_pareto_front_curve()`` method creates the Pareto front curve
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for multi-objective optimization problems. It creates, shows, and
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returns a figure that shows the Pareto front curve and points
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representing the fitness. It only works when 2 objectives are used.
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It works only after completing at least 1 generation. If no generation
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is completed (at least 1), an exception is raised.
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This method accepts the following parameters:
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1. ``title``: Title of the figure.
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2. ``xlabel``: X-axis label.
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3. ``ylabel``: Y-axis label.
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4. ``linewidth``: Line width of the plot. Defaults to ``3``.
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5. ``font_size``: Font size for the labels and title. Defaults to
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``14``.
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6. ``label``: The label used for the legend.
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7. ``color``: Color of the plot which defaults to the royal blue color
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``#FF6347``.
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8. ``color_fitness``: Color of the fitness points which defaults to the
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tomato red color ``#4169E1``.
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9. ``grid``: Either ``True`` or ``False`` to control the visibility of
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the grid.
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10. ``alpha``: The transparency of the pareto front curve.
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11. ``marker``: The marker of the fitness points.
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12. ``save_dir``: Directory to save the figure.
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This is an example of calling the ``plot_pareto_front_curve()`` method.
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.. code:: python
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ga_instance.plot_pareto_front_curve()
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|image12|
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.. |image1| image:: https://user-images.githubusercontent.com/16560492/122472609-d02f5280-cf8e-11eb-88a7-f9366ff6e7c6.png
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.. |image2| image:: https://user-images.githubusercontent.com/16560492/122473159-75e2c180-cf8f-11eb-942d-31279b286dbd.png
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.. |image3| image:: https://user-images.githubusercontent.com/16560492/122473340-b7736c80-cf8f-11eb-89c5-4f7db3b653cc.png
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.. |image4| image:: https://user-images.githubusercontent.com/16560492/122475815-3322e880-cf93-11eb-9648-bf66f823234b.png
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.. |image5| image:: https://user-images.githubusercontent.com/16560492/122476108-adec0380-cf93-11eb-80ac-7588bf90492f.png
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.. |image6| image:: https://user-images.githubusercontent.com/16560492/122476173-c2c89700-cf93-11eb-9e77-d39737cd3a96.png
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.. |image7| image:: https://user-images.githubusercontent.com/16560492/122477158-4a62d580-cf95-11eb-8c93-9b6e74cb814c.png
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.. |image8| image:: https://user-images.githubusercontent.com/16560492/122477273-73836600-cf95-11eb-828f-f357c7b0f815.png
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.. |image9| image:: https://user-images.githubusercontent.com/16560492/122477370-99106f80-cf95-11eb-8643-865b55e6b844.png
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.. |image10| image:: https://user-images.githubusercontent.com/16560492/122479260-beeb4380-cf98-11eb-8f08-23707929b12c.png
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.. |image11| image:: https://user-images.githubusercontent.com/16560492/122477314-8007be80-cf95-11eb-9c95-da3f49204151.png
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.. |image12| image:: https://github.com/user-attachments/assets/606d853c-7370-41a0-8ddb-857a4c6c7fb9

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