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< h1 > Usage< a class = "headerlink" href = "#usage" title = "Permalink to this headline" > ¶< / a > < / h1 >
< p > First of all, you need to install the package. See < a class = "reference internal" href = "installation.html" > < span class = "doc" > Installation< / span > < / a > for installation instructions.< / p >
< div class = "section" id = "simulation-settings" >
< h2 > Simulation Settings< a class = "headerlink" href = "#simulation-settings" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > Once installed, before running a simulation, you need to configure it.< / p >
< ul >
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< li > < p class = "first" > In the Settings JSON file you will find the configuration of the network.< / p >
< div class = "code python highlight-default" > < div class = "highlight" > < pre > < span > < / span > < span class = "p" > {< / span >
< span class = "s2" > " network_type" < / span > < span class = "p" > :< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span >
< span class = "s2" > " number_of_nodes" < / span > < span class = "p" > :< / span > < span class = "mi" > 1000< / span > < span class = "p" > ,< / span >
< span class = "s2" > " max_time" < / span > < span class = "p" > :< / span > < span class = "mi" > 50< / span > < span class = "p" > ,< / span >
< span class = "s2" > " num_trials" < / span > < span class = "p" > :< / span > < span class = "mi" > 1< / span > < span class = "p" > ,< / span >
< span class = "s2" > " timeout" < / span > < span class = "p" > :< / span > < span class = "mi" > 2< / span >
< span class = "p" > }< / span >
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< / pre > < / div >
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< / li >
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< li > < p class = "first" > In the Settings JSON file, you will also find the configuration of the models.< / p >
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< / li >
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< div class = "section" id = "network-types" >
< h2 > Network Types< a class = "headerlink" href = "#network-types" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > There are three types of network implemented, but you could add more.< / p >
< div class = "code python highlight-default" > < div class = "highlight" > < pre > < span > < / span > < span class = "k" > if< / span > < span class = "n" > settings< / span > < span class = "o" > .< / span > < span class = "n" > network_type< / span > < span class = "o" > ==< / span > < span class = "mi" > 0< / span > < span class = "p" > :< / span >
< span class = "n" > G< / span > < span class = "o" > =< / span > < span class = "n" > nx< / span > < span class = "o" > .< / span > < span class = "n" > complete_graph< / span > < span class = "p" > (< / span > < span class = "n" > settings< / span > < span class = "o" > .< / span > < span class = "n" > number_of_nodes< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "n" > settings< / span > < span class = "o" > .< / span > < span class = "n" > network_type< / span > < span class = "o" > ==< / span > < span class = "mi" > 1< / span > < span class = "p" > :< / span >
< span class = "n" > G< / span > < span class = "o" > =< / span > < span class = "n" > nx< / span > < span class = "o" > .< / span > < span class = "n" > barabasi_albert_graph< / span > < span class = "p" > (< / span > < span class = "n" > settings< / span > < span class = "o" > .< / span > < span class = "n" > number_of_nodes< / span > < span class = "p" > ,< / span > < span class = "mi" > 10< / span > < span class = "p" > )< / span >
< span class = "k" > if< / span > < span class = "n" > settings< / span > < span class = "o" > .< / span > < span class = "n" > network_type< / span > < span class = "o" > ==< / span > < span class = "mi" > 2< / span > < span class = "p" > :< / span >
< span class = "n" > G< / span > < span class = "o" > =< / span > < span class = "n" > nx< / span > < span class = "o" > .< / span > < span class = "n" > margulis_gabber_galil_graph< / span > < span class = "p" > (< / span > < span class = "n" > settings< / span > < span class = "o" > .< / span > < span class = "n" > number_of_nodes< / span > < span class = "p" > ,< / span > < span class = "kc" > None< / span > < span class = "p" > )< / span >
< span class = "c1" > # More types of networks can be added here< / span >
< / pre > < / div >
< / div >
< / div >
< div class = "section" id = "models-settings" >
< h2 > Models Settings< a class = "headerlink" href = "#models-settings" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > After having configured the simulation, the next step is setting up the variables of the models.
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For this, you will need to modify the Settings JSON file again.< / p >
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< div class = "code json highlight-default" > < div class = "highlight" > < pre > < span > < / span > < span class = "p" > {< / span >
< span class = "s2" > " agent" < / span > < span class = "p" > :< / span > < span class = "p" > [< / span > < span class = "s2" > " SISaModel" < / span > < span class = "p" > ,< / span > < span class = "s2" > " ControlModelM2" < / span > < span class = "p" > ],< / span >
< span class = "s2" > " neutral_discontent_spon_prob" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.04< / span > < span class = "p" > ,< / span >
< span class = "s2" > " neutral_discontent_infected_prob" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.04< / span > < span class = "p" > ,< / span >
< span class = "s2" > " neutral_content_spon_prob" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.18< / span > < span class = "p" > ,< / span >
< span class = "s2" > " neutral_content_infected_prob" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.02< / span > < span class = "p" > ,< / span >
< span class = "s2" > " discontent_neutral" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.13< / span > < span class = "p" > ,< / span >
< span class = "s2" > " discontent_content" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.07< / span > < span class = "p" > ,< / span >
< span class = "s2" > " variance_d_c" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.02< / span > < span class = "p" > ,< / span >
< span class = "s2" > " content_discontent" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.009< / span > < span class = "p" > ,< / span >
< span class = "s2" > " variance_c_d" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.003< / span > < span class = "p" > ,< / span >
< span class = "s2" > " content_neutral" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.088< / span > < span class = "p" > ,< / span >
< span class = "s2" > " standard_variance" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.055< / span > < span class = "p" > ,< / span >
< span class = "s2" > " prob_neutral_making_denier" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.035< / span > < span class = "p" > ,< / span >
< span class = "s2" > " prob_infect" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.075< / span > < span class = "p" > ,< / span >
< span class = "s2" > " prob_cured_healing_infected" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.035< / span > < span class = "p" > ,< / span >
< span class = "s2" > " prob_cured_vaccinate_neutral" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.035< / span > < span class = "p" > ,< / span >
< span class = "s2" > " prob_vaccinated_healing_infected" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.035< / span > < span class = "p" > ,< / span >
< span class = "s2" > " prob_vaccinated_vaccinate_neutral" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.035< / span > < span class = "p" > ,< / span >
< span class = "s2" > " prob_generate_anti_rumor" < / span > < span class = "p" > :< / span > < span class = "mf" > 0.035< / span >
< span class = "p" > }< / span >
< / pre > < / div >
< / div >
< p > In this file you will define the different models you are going to simulate. You can simulate as many models
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as you want. Each model will be simulated separately.< / p >
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< p > After setting up the models, you have to initialize the parameters of each one. You will find the parameters needed
in the documentation of each model.< / p >
< p > Parameter validation will fail if a required parameter without a default has not been provided.< / p >
< / div >
< div class = "section" id = "running-the-simulation" >
< h2 > Running the Simulation< a class = "headerlink" href = "#running-the-simulation" title = "Permalink to this headline" > ¶< / a > < / h2 >
< p > After setting all the configuration, you will be able to run the simulation. All you need to do is execute:< / p >
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< div class = "code bash highlight-default" > < div class = "highlight" > < pre > < span > < / span > < span class = "n" > python3< / span > < span class = "n" > soil< / span > < span class = "o" > .< / span > < span class = "n" > py< / span >
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< / pre > < / div >
< / div >
< p > The simulation will return a dynamic graph .gexf file which could be visualized with
< a class = "reference external" href = "https://gephi.org/users/download/" > Gephi< / a > .< / p >
< p > It will also return one .png picture for each model simulated.< / p >
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< h3 > < a href = "index.html" > Table Of Contents< / a > < / h3 >
< ul >
< li > < a class = "reference internal" href = "#" > Usage< / a > < ul >
< li > < a class = "reference internal" href = "#simulation-settings" > Simulation Settings< / a > < / li >
< li > < a class = "reference internal" href = "#network-types" > Network Types< / a > < / li >
< li > < a class = "reference internal" href = "#models-settings" > Models Settings< / a > < / li >
< li > < a class = "reference internal" href = "#running-the-simulation" > Running the Simulation< / a > < / li >
< / ul >
< / li >
< / ul >
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< h3 > Related Topics< / h3 >
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< li > < a href = "index.html" > Documentation overview< / a > < ul >
< li > Previous: < a href = "installation.html" title = "previous chapter" > Installation< / a > < / li >
< li > Next: < a href = "models.html" title = "next chapter" > Developing new models< / a > < / li >
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