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Update quickstart tutorial
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@ -21,12 +21,16 @@ The configuration is the following:
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.. literalinclude:: quickstart.yml
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.. literalinclude:: quickstart.yml
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:language: yaml
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:language: yaml
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Configuration
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=============
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You may :download:`download the file <quickstart.yml>` directly.
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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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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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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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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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Running the simulation
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======================
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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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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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@ -59,6 +63,8 @@ The ``CSV`` file should look like this:
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env,0,variance_d_c,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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env,0,variance_c_d,0.1
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Results and visualization
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=========================
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The environment variables are marked as ``agent_id`` env.
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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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Th exported values are only stored when they change.
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@ -69,3 +75,20 @@ The dynamic graph is exported as a .gexf file which could be visualized with
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Now it is your turn to experiment with the simulation.
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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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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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Soil also includes a web server that allows you to upload your simulations, change parameters, and visualize the results, including a timeline of the network.
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To make it work, you have to install soil like this:
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```
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pip install soil[web]
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```
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Once installed, the soil web UI can be run in two ways:
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```
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soil-web
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OR
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python -m soil.web
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```
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