mirror of
https://github.com/gsi-upm/soil
synced 2024-11-24 11:52:29 +00:00
2e28b36f6e
* Upgrade to python3.7 and pandas 0.3.4 because pandas has dropped support for python 3.4 -> There are some API changes in pandas, and I've update the code accordingly. * Set pytest as the default test runner
308 lines
10 KiB
Python
308 lines
10 KiB
Python
from unittest import TestCase
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import os
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import yaml
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import networkx as nx
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from functools import partial
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from os.path import join
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from soil import simulation, Environment, agents, utils, history
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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 CustomAgent(agents.BaseAgent):
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def step(self):
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self.state['neighbors'] = self.count_agents(state_id=0,
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limit_neighbors=True)
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class TestMain(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 = {
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'dry_run': True,
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'network_params': {
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'path': join(ROOT, 'test.gexf')
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}
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}
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G = utils.load_network(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 = {
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'dry_run': True,
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'network_params': {
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'path': join(ROOT, 'unknown.extension')
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}
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}
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G = utils.load_network(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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config = {
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'dry_run': True,
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'network_params': {
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'generator': 'barabasi_albert_graph'
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}
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}
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with self.assertRaises(TypeError):
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G = utils.load_network(config['network_params'])
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config['network_params']['n'] = 100
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config['network_params']['m'] = 10
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G = utils.load_network(config['network_params'])
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assert len(G) == 100
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def test_empty_simulation(self):
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"""A simulation with a base behaviour should do nothing"""
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config = {
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'dry_run': True,
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'network_params': {
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'path': join(ROOT, 'test.gexf')
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},
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'agent_type': 'BaseAgent',
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'environment_params': {
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}
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}
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s = simulation.from_config(config)
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s.run_simulation(dry_run=True)
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def test_counter_agent(self):
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"""
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The initial states should be applied to the agent and the
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agent should be able to update its state."""
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config = {
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'name': 'CounterAgent',
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'dry_run': True,
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'network_params': {
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'path': join(ROOT, 'test.gexf')
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},
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'agent_type': 'CounterModel',
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'states': [{'times': 10}, {'times': 20}],
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'max_time': 2,
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'num_trials': 1,
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'environment_params': {
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}
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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.get_agent(0)['times', 0] == 11
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assert env.get_agent(0)['times', 1] == 12
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assert env.get_agent(1)['times', 0] == 21
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assert env.get_agent(1)['times', 1] == 22
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def test_counter_agent_history(self):
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"""
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The evolution of the state should be recorded in the logging agent
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"""
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config = {
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'name': 'CounterAgent',
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'dry_run': True,
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'network_params': {
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'path': join(ROOT, 'test.gexf')
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},
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'network_agents': [{
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'agent_type': 'AggregatedCounter',
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'weight': 1,
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'state': {'id': 0}
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}],
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'max_time': 10,
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'environment_params': {
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}
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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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for agent in env.network_agents:
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last = 0
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assert len(agent[None, None]) == 10
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for step, total in sorted(agent['total', None]):
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assert total == last + 2
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last = total
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def test_custom_agent(self):
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"""Allow for search of neighbors with a certain state_id"""
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config = {
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'dry_run': True,
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'network_params': {
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'path': join(ROOT, 'test.gexf')
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},
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'network_agents': [{
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'agent_type': CustomAgent,
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'weight': 1,
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'state': {'id': 0}
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}],
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'max_time': 10,
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'environment_params': {
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}
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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.get_agent(0).state['neighbors'] == 1
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def test_torvalds_example(self):
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"""A complete example from a documentation should work."""
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config = utils.load_file(join(EXAMPLES, 'torvalds.yml'))[0]
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config['network_params']['path'] = join(EXAMPLES,
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config['network_params']['path'])
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s = simulation.from_config(config)
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s.dry_run = True
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env = s.run_simulation()[0]
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for a in env.network_agents:
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skill_level = a.state['skill_level']
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if a.id == 'Torvalds':
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assert skill_level == 'God'
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assert a.state['total'] == 3
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assert a.state['neighbors'] == 2
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elif a.id == 'balkian':
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assert skill_level == 'developer'
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assert a.state['total'] == 3
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assert a.state['neighbors'] == 1
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else:
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assert skill_level == 'beginner'
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assert a.state['total'] == 3
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assert a.state['neighbors'] == 1
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def test_yaml(self):
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"""
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The YAML version of a newly created simulation
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should be equivalent to the configuration file used
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"""
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with utils.timer('loading'):
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config = utils.load_file(join(EXAMPLES, 'complete.yml'))[0]
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s = simulation.from_config(config)
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s.dry_run = True
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with utils.timer('serializing'):
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serial = s.to_yaml()
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with utils.timer('recovering'):
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recovered = yaml.load(serial)
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with utils.timer('deleting'):
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del recovered['topology']
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assert config == recovered
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def test_configuration_changes(self):
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"""
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The configuration should not change after running
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the simulation.
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"""
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config = utils.load_file(join(EXAMPLES, 'complete.yml'))[0]
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s = simulation.from_config(config)
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s.dry_run = True
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for i in range(5):
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s.run_simulation(dry_run=True)
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nconfig = s.to_dict()
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del nconfig['topology']
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assert config == nconfig
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def test_row_conversion(self):
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env = Environment(dry_run=True)
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env['test'] = 'test_value'
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res = list(env.history_to_tuples())
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assert len(res) == len(env.environment_params)
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env._now = 1
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env['test'] = 'second_value'
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res = list(env.history_to_tuples())
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assert env['env', 0, 'test' ] == 'test_value'
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assert env['env', 1, 'test' ] == 'second_value'
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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(topology=G, dry_run=True)
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env.dump_gexf('/tmp/dump-gexf')
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def test_save_graph(self):
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'''
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The history_to_graph method should return a valid networkx graph.
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The state of the agent should be encoded as intervals in the nx graph.
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'''
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G = nx.cycle_graph(5)
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distribution = agents.calculate_distribution(None, agents.BaseAgent)
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env = Environment(topology=G, network_agents=distribution, dry_run=True)
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env[0, 0, 'testvalue'] = 'start'
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env[0, 10, 'testvalue'] = 'finish'
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nG = env.history_to_graph()
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values = nG.node[0]['attr_testvalue']
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assert ('start', 0, 10) in values
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assert ('finish', 10, None) in values
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def test_serialize_class(self):
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ser, name = utils.serialize(agents.BaseAgent)
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assert name == 'soil.agents.BaseAgent'
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assert ser == agents.BaseAgent
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class CustomAgent(agents.BaseAgent):
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pass
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ser, name = utils.serialize(CustomAgent)
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assert name == 'test_main.CustomAgent'
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assert ser == CustomAgent
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def test_serialize_builtin_types(self):
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for i in [1, None, True, False, {}, [], list(), dict()]:
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ser, name = utils.serialize(i)
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assert type(ser) == str
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des = utils.deserialize(name, ser)
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assert i == des
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def test_serialize_agent_type(self):
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'''A class from soil.agents should be serialized without the module part'''
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ser = agents.serialize_type(CustomAgent)
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assert ser == 'test_main.CustomAgent'
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ser = agents.serialize_type(agents.BaseAgent)
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assert ser == 'BaseAgent'
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def test_deserialize_agent_distribution(self):
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agent_distro = [
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{
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'agent_type': 'CounterModel',
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'weight': 1
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},
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{
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'agent_type': 'test_main.CustomAgent',
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'weight': 2
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},
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]
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converted = agents.deserialize_distribution(agent_distro)
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assert converted[0]['agent_type'] == agents.CounterModel
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assert converted[1]['agent_type'] == CustomAgent
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def test_serialize_agent_distribution(self):
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agent_distro = [
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{
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'agent_type': agents.CounterModel,
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'weight': 1
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},
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{
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'agent_type': CustomAgent,
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'weight': 2
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},
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]
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converted = agents.serialize_distribution(agent_distro)
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assert converted[0]['agent_type'] == 'CounterModel'
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assert converted[1]['agent_type'] == 'test_main.CustomAgent'
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def test_history(self):
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'''Test storing in and retrieving from history (sqlite)'''
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h = history.History()
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h.save_record(agent_id=0, t_step=0, key="test", value="hello")
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assert h[0, 0, "test"] == "hello"
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