mirror of
https://github.com/gsi-upm/soil
synced 2024-09-21 07:41:43 +00:00
a1262edd2a
Treating time and conditions as the same entity was getting confusing, and it added a lot of unnecessary abstraction in a critical part (the scheduler). The scheduling queue now has the time as a floating number (faster), the agent id (for ties) and the condition, as well as the agent. The first three elements (time, id, condition) can be considered as the "key" for the event. To allow for agent execution to be "randomized" within every step, a new parameter has been added to the scheduler, which makes it add a random number to the key in order to change the ordering. `EventedAgent.received` now checks the messages before returning control to the user by default.
111 lines
3.9 KiB
Python
111 lines
3.9 KiB
Python
from unittest import TestCase
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import io
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import os
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import networkx as nx
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from os.path import join
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from soil import config, network, environment, agents, simulation
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from test_main import CustomAgent
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ROOT = os.path.abspath(os.path.dirname(__file__))
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EXAMPLES = join(ROOT, "..", "examples")
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class TestNetwork(TestCase):
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def test_load_graph(self):
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"""
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Load a graph from file if the extension is known.
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Raise an exception otherwise.
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"""
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config = {"network_params": {"path": join(ROOT, "test.gexf")}}
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G = network.from_config(config["network_params"])
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assert G
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assert len(G) == 2
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with self.assertRaises(AttributeError):
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config = {"network_params": {"path": join(ROOT, "unknown.extension")}}
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G = network.from_config(config["network_params"])
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print(G)
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def test_generate_barabasi(self):
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"""
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If no path is given, a generator and network parameters
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should be used to generate a network
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"""
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cfg = {"params": {"generator": "barabasi_albert_graph"}}
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with self.assertRaises(Exception):
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G = network.from_config(cfg)
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cfg["params"]["n"] = 100
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cfg["params"]["m"] = 10
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G = network.from_config(cfg)
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assert len(G) == 100
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def test_save_geometric(self):
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"""
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There is a bug in networkx that prevents it from creating a GEXF file
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from geometric models. We should work around it.
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"""
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G = nx.random_geometric_graph(20, 0.1)
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env = environment.NetworkEnvironment(topology=G)
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f = io.BytesIO()
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assert env.G
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network.dump_gexf(env.G, f)
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def test_networkenvironment_creation(self):
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"""Networkenvironment should accept netconfig as parameters"""
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model_params = {
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"topology": {"path": join(ROOT, "test.gexf")},
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"agents": {
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"topology": True,
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"distribution": [
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{
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"agent_class": CustomAgent,
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}
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],
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},
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}
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env = environment.Environment(**model_params)
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assert env.G
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env.step()
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assert len(env.G) == 2
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assert len(env.agents) == 2
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assert env.agents[1].count_agents(state_id="normal") == 2
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assert env.agents[1].count_agents(state_id="normal", limit_neighbors=True) == 1
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assert env.agents[0].count_neighbors() == 1
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def test_custom_agent_neighbors(self):
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"""Allow for search of neighbors with a certain state_id"""
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config = {
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"model_params": {
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"topology": {"path": join(ROOT, "test.gexf")},
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"agents": {
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"topology": True,
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"distribution": [{"weight": 1, "agent_class": CustomAgent}],
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},
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},
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"max_time": 10,
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}
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s = simulation.from_config(config)
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env = s.run_simulation(dry_run=True)[0]
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assert env.agents[1].count_agents(state_id="normal") == 2
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assert env.agents[1].count_agents(state_id="normal", limit_neighbors=True) == 1
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assert env.agents[0].count_neighbors() == 1
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def test_subgraph(self):
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"""An agent should be able to subgraph the global topology"""
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G = nx.Graph()
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G.add_node(3)
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G.add_edge(1, 2)
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distro = agents.calculate_distribution(agent_class=agents.NetworkAgent)
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aconfig = config.AgentConfig(distribution=distro, topology=True)
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env = environment.Environment(name="Test", topology=G, agents=aconfig)
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lst = list(env.network_agents)
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a2 = env.find_one(node_id=2)
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a3 = env.find_one(node_id=3)
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assert len(a2.subgraph(limit_neighbors=True)) == 2
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assert len(a3.subgraph(limit_neighbors=True)) == 1
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assert len(a3.subgraph(limit_neighbors=True, center=False)) == 0
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assert len(a3.subgraph(agent_class=agents.NetworkAgent)) == 3
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