Steps 7-8: Run the simulation and analyze the results

Step 7: Run the simulation

Following the definition of custom methods, we can now execute the simulation using the lib_run_simulation method of the Project class for 10 iterations (epochs), saving the data and the graph to files in every iteration (snapshot_period = 1), and run the simulation with the same settings for 1 time only (curr_batch = 1).

my_project.lib_run_simulation(
    epochs = 10,
    snapshot_period = 1,
    curr_batch = 1,
    before_iteration_methods = before_iteration_methods,
    after_iteration_methods = after_iteration_methods,
    after_simulation_methods = after_simulation_methods
)

Step 8: Analyze the results

Option 1: If executed on Google Colab, download the project files and move them to crowd_projects folder on the local device. From Crowd GUI, select the simulation. Inspect the network visualization, draw charts and download visualizations.

Option 2: Conduct data analysis with Python libraries by loading the generated JSON files.

Next: Example 2: Influence maximization