mirror of
https://github.com/gsi-upm/soil
synced 2024-11-14 15:32:29 +00:00
198 lines
6.3 KiB
ReStructuredText
198 lines
6.3 KiB
ReStructuredText
Quickstart
|
|
----------
|
|
|
|
This section shows how to run simulations from simulation configuration files.
|
|
First of all, you need to install the package (See :doc:`installation`)
|
|
|
|
Simulation configuration files are ``json`` or ``yaml`` files that define all the parameters of a simulation.
|
|
Here's an example (``example.yml``).
|
|
|
|
.. code:: yaml
|
|
|
|
---
|
|
name: MyExampleSimulation
|
|
max_time: 50
|
|
num_trials: 3
|
|
interval: 2
|
|
network_params:
|
|
network_type: barabasi_albert_graph
|
|
n: 100
|
|
m: 2
|
|
agent_distribution:
|
|
- agent_type: SISaModel
|
|
weight: 1
|
|
state:
|
|
id: content
|
|
- agent_type: SISaModel
|
|
weight: 1
|
|
state:
|
|
id: discontent
|
|
- agent_type: SISaModel
|
|
weight: 8
|
|
state:
|
|
id: neutral
|
|
environment_params:
|
|
prob_infect: 0.075
|
|
|
|
|
|
This example configuration will run three trials of a simulation containing a randomly generated network.
|
|
The 100 nodes in the network will be SISaModel agents, 10% of them will start in the content state, 10% in the discontent state, and the remaining 80% in the neutral state.
|
|
All agents will have access to the environment, which only contains one variable, ``prob_infected``.
|
|
The state of the agents will be updated every 2 seconds (``interval``).
|
|
|
|
Now run the simulation with the command line tool:
|
|
|
|
.. code:: bash
|
|
|
|
soil example.yml
|
|
|
|
Once the simulation finishes, its results will be stored in a folder named ``MyExampleSimulation``.
|
|
Four types of objects are saved by default: a pickle of the simulation; a ``YAML`` representation of the simulation (which can be used to re-launch it); and for every trial, a csv file with the content of the state of every network node and the environment parameters at every step of the simulation, as well as the network in gephi format (``gexf``).
|
|
|
|
|
|
.. code::
|
|
|
|
soil_output
|
|
├── Sim_prob_0
|
|
│ ├── Sim_prob_0.dumped.yml
|
|
│ ├── Sim_prob_0.simulation.pickle
|
|
│ ├── Sim_prob_0_trial_0.environment.csv
|
|
│ └── Sim_prob_0_trial_0.gexf
|
|
|
|
|
|
Network
|
|
=======
|
|
|
|
The network topology for the simulation can be loaded from an existing network file or generated with one of the random network generation methods from networkx.
|
|
|
|
Loading a network
|
|
#################
|
|
|
|
To load an existing network, specify its path in the configuration:
|
|
|
|
.. code:: yaml
|
|
|
|
---
|
|
network_params:
|
|
path: /tmp/mynetwork.gexf
|
|
|
|
Soil will try to guess what networkx method to use to read the file based on its extension.
|
|
However, we only test using ``gexf`` files.
|
|
|
|
Generating a random network
|
|
###########################
|
|
|
|
To generate a random network using one of networkx's built-in methods, specify the `graph generation algorithm <https://networkx.github.io/documentation/development/reference/generators.html>`_ and other parameters.
|
|
For example, the following configuration is equivalent to :code:`nx.complete_graph(100)`:
|
|
|
|
.. code:: yaml
|
|
|
|
network_params:
|
|
network_type: complete_graph
|
|
n: 100
|
|
|
|
Environment
|
|
============
|
|
The environment is the place where the shared state of the simulation is stored.
|
|
For instance, the probability of disease outbreak.
|
|
The configuration file may specify the initial value of the environment parameters:
|
|
|
|
.. code:: yaml
|
|
|
|
environment_params:
|
|
daily_probability_of_earthquake: 0.001
|
|
number_of_earthquakes: 0
|
|
|
|
Any agent has unrestricted access to the environment.
|
|
However, for the sake of simplicity, we recommend limiting environment updates to environment agents.
|
|
|
|
Agents
|
|
======
|
|
Agents are a way of modelling behavior.
|
|
Agents can be characterized with two variables: an agent type (``agent_type``) and its state.
|
|
Only one agent is executed at a time (generally, every ``interval`` seconds), and it has access to its state and the environment parameters.
|
|
Through the environment, it can access the network topology and the state of other agents.
|
|
|
|
There are three three types of agents according to how they are added to the simulation: network agents and environment agent.
|
|
|
|
Network Agents
|
|
##############
|
|
Network agents are attached to a node in the topology.
|
|
The configuration file allows you to specify how agents will be mapped to topology nodes.
|
|
|
|
The simplest way is to specify a single type of agent.
|
|
Hence, every node in the network will be associated to an agent of that type.
|
|
|
|
.. code:: yaml
|
|
|
|
agent_type: SISaModel
|
|
|
|
It is also possible to add more than one type of agent to the simulation, and to control the ratio of each type (using the ``weight`` property).
|
|
For instance, with following configuration, it is five times more likely for a node to be assigned a CounterModel type than a SISaModel type.
|
|
|
|
.. code:: yaml
|
|
|
|
agent_distribution:
|
|
- agent_type: SISaModel
|
|
weight: 1
|
|
- agent_type: CounterModel
|
|
weight: 5
|
|
|
|
In addition to agent type, you may also add a custom initial state to the distribution.
|
|
This is very useful to add the same agent type with different states.
|
|
e.g., to populate the network with SISaModel, roughly 10% of them with a discontent state:
|
|
|
|
.. code:: yaml
|
|
|
|
agent_distribution:
|
|
- agent_type: SISaModel
|
|
weight: 9
|
|
state:
|
|
id: neutral
|
|
- agent_type: SISaModel
|
|
weight: 1
|
|
state:
|
|
id: discontent
|
|
|
|
Lastly, the configuration may include initial state for one or more nodes.
|
|
For instance, to add a state for the two nodes in this configuration:
|
|
|
|
.. code:: yaml
|
|
|
|
agent_type: SISaModel
|
|
network:
|
|
network_type: complete_graph
|
|
n: 2
|
|
states:
|
|
- id: content
|
|
- id: discontent
|
|
|
|
|
|
Or to add state only to specific nodes (by ``id``).
|
|
For example, to apply special skills to Linux Torvalds in a simulation:
|
|
|
|
.. literalinclude:: ../examples/torvalds.yml
|
|
:language: yaml
|
|
|
|
|
|
Environment Agents
|
|
##################
|
|
In addition to network agents, more agents can be added to the simulation.
|
|
These agens are programmed in much the same way as network agents, the only difference is that they will not be assigned to network nodes.
|
|
|
|
|
|
.. code::
|
|
|
|
environment_agents:
|
|
- agent_type: MyAgent
|
|
state:
|
|
mood: happy
|
|
- agent_type: DummyAgent
|
|
|
|
|
|
Visualizing the results
|
|
=======================
|
|
|
|
The simulation will return a dynamic graph .gexf file which could be visualized with
|
|
`Gephi <https://gephi.org/users/download/>`__.
|