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Quickstart
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----------
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This section shows how to run your first simulation with Soil.
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For installation instructions, see :doc:`installation`.
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There are mainly two parts in a simulation: agent classes and simulation configuration.
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An agent class defines how the agent will behave throughout the simulation.
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The configuration includes things such as number of agents to use and their type, network topology to use, etc.
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.. image:: soil.png
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:width: 80%
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:align: center
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Soil includes several agent classes in the ``soil.agents`` module, and we will use them in this quickstart.
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If you are interested in developing your own agents classes, see :doc:`soil_tutorial`.
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The configuration is the following:
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.. literalinclude:: quickstart.yml
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:language: yaml
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You may :download:`download the file <quickstart.yml>` directly.
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The agent type used, SISa, is a very simple model.
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It only has three states (neutral, content and discontent),
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Its parameters are the probabilities to change from one state to another, either spontaneously or because of contagion from neighboring agents.
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To see the simulation in action, simply point soil to the configuration, and tell it to store the graph and the history of agent states and environment parameters at every point.
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.. code::
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❯ soil --graph --csv quickstart.yml [13:35:29]
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INFO:soil:Using config(s): quickstart
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INFO:soil:Dumping results to soil_output/quickstart : ['csv', 'gexf']
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INFO:soil:Starting simulation quickstart at 13:35:30.
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INFO:soil:Starting Simulation quickstart trial 0 at 13:35:30.
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INFO:soil:Finished Simulation quickstart trial 0 at 13:35:49 in 19.43677067756653 seconds
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INFO:soil:Starting Dumping simulation quickstart trial 0 at 13:35:49.
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INFO:soil:Finished Dumping simulation quickstart trial 0 at 13:35:51 in 1.7733407020568848 seconds
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INFO:soil:Dumping results to soil_output/quickstart
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INFO:soil:Finished simulation quickstart at 13:35:51 in 21.29862952232361 seconds
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The ``CSV`` file should look like this:
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.. code::
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agent_id,t_step,key,value
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env,0,neutral_discontent_spon_prob,0.05
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env,0,neutral_discontent_infected_prob,0.1
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env,0,neutral_content_spon_prob,0.2
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env,0,neutral_content_infected_prob,0.4
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env,0,discontent_neutral,0.2
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env,0,discontent_content,0.05
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env,0,content_discontent,0.05
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env,0,variance_d_c,0.05
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env,0,variance_c_d,0.1
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The environment variables are marked as ``agent_id`` env.
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Th exported values are only stored when they change.
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To find out how to get every key and value at every point in the simulation, check out the :doc:`soil_tutorial`.
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The dynamic graph is exported as a .gexf file which could be visualized with
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`Gephi <https://gephi.org/users/download/>`__.
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Now it is your turn to experiment with the simulation.
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Change some of the parameters, such as the number of agents, the probability of becoming content, or the type of network, and see how the results change.
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