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soil/tests/test_main.py
J. Fernando Sánchez 2e28b36f6e Python3.7, testing and bug fixes
* 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
2018-12-08 18:53:06 +01:00

308 lines
10 KiB
Python

from unittest import TestCase
import os
import yaml
import networkx as nx
from functools import partial
from os.path import join
from soil import simulation, Environment, agents, utils, history
ROOT = os.path.abspath(os.path.dirname(__file__))
EXAMPLES = join(ROOT, '..', 'examples')
class CustomAgent(agents.BaseAgent):
def step(self):
self.state['neighbors'] = self.count_agents(state_id=0,
limit_neighbors=True)
class TestMain(TestCase):
def test_load_graph(self):
"""
Load a graph from file if the extension is known.
Raise an exception otherwise.
"""
config = {
'dry_run': True,
'network_params': {
'path': join(ROOT, 'test.gexf')
}
}
G = utils.load_network(config['network_params'])
assert G
assert len(G) == 2
with self.assertRaises(AttributeError):
config = {
'dry_run': True,
'network_params': {
'path': join(ROOT, 'unknown.extension')
}
}
G = utils.load_network(config['network_params'])
print(G)
def test_generate_barabasi(self):
"""
If no path is given, a generator and network parameters
should be used to generate a network
"""
config = {
'dry_run': True,
'network_params': {
'generator': 'barabasi_albert_graph'
}
}
with self.assertRaises(TypeError):
G = utils.load_network(config['network_params'])
config['network_params']['n'] = 100
config['network_params']['m'] = 10
G = utils.load_network(config['network_params'])
assert len(G) == 100
def test_empty_simulation(self):
"""A simulation with a base behaviour should do nothing"""
config = {
'dry_run': True,
'network_params': {
'path': join(ROOT, 'test.gexf')
},
'agent_type': 'BaseAgent',
'environment_params': {
}
}
s = simulation.from_config(config)
s.run_simulation(dry_run=True)
def test_counter_agent(self):
"""
The initial states should be applied to the agent and the
agent should be able to update its state."""
config = {
'name': 'CounterAgent',
'dry_run': True,
'network_params': {
'path': join(ROOT, 'test.gexf')
},
'agent_type': 'CounterModel',
'states': [{'times': 10}, {'times': 20}],
'max_time': 2,
'num_trials': 1,
'environment_params': {
}
}
s = simulation.from_config(config)
env = s.run_simulation(dry_run=True)[0]
assert env.get_agent(0)['times', 0] == 11
assert env.get_agent(0)['times', 1] == 12
assert env.get_agent(1)['times', 0] == 21
assert env.get_agent(1)['times', 1] == 22
def test_counter_agent_history(self):
"""
The evolution of the state should be recorded in the logging agent
"""
config = {
'name': 'CounterAgent',
'dry_run': True,
'network_params': {
'path': join(ROOT, 'test.gexf')
},
'network_agents': [{
'agent_type': 'AggregatedCounter',
'weight': 1,
'state': {'id': 0}
}],
'max_time': 10,
'environment_params': {
}
}
s = simulation.from_config(config)
env = s.run_simulation(dry_run=True)[0]
for agent in env.network_agents:
last = 0
assert len(agent[None, None]) == 10
for step, total in sorted(agent['total', None]):
assert total == last + 2
last = total
def test_custom_agent(self):
"""Allow for search of neighbors with a certain state_id"""
config = {
'dry_run': True,
'network_params': {
'path': join(ROOT, 'test.gexf')
},
'network_agents': [{
'agent_type': CustomAgent,
'weight': 1,
'state': {'id': 0}
}],
'max_time': 10,
'environment_params': {
}
}
s = simulation.from_config(config)
env = s.run_simulation(dry_run=True)[0]
assert env.get_agent(0).state['neighbors'] == 1
def test_torvalds_example(self):
"""A complete example from a documentation should work."""
config = utils.load_file(join(EXAMPLES, 'torvalds.yml'))[0]
config['network_params']['path'] = join(EXAMPLES,
config['network_params']['path'])
s = simulation.from_config(config)
s.dry_run = True
env = s.run_simulation()[0]
for a in env.network_agents:
skill_level = a.state['skill_level']
if a.id == 'Torvalds':
assert skill_level == 'God'
assert a.state['total'] == 3
assert a.state['neighbors'] == 2
elif a.id == 'balkian':
assert skill_level == 'developer'
assert a.state['total'] == 3
assert a.state['neighbors'] == 1
else:
assert skill_level == 'beginner'
assert a.state['total'] == 3
assert a.state['neighbors'] == 1
def test_yaml(self):
"""
The YAML version of a newly created simulation
should be equivalent to the configuration file used
"""
with utils.timer('loading'):
config = utils.load_file(join(EXAMPLES, 'complete.yml'))[0]
s = simulation.from_config(config)
s.dry_run = True
with utils.timer('serializing'):
serial = s.to_yaml()
with utils.timer('recovering'):
recovered = yaml.load(serial)
with utils.timer('deleting'):
del recovered['topology']
assert config == recovered
def test_configuration_changes(self):
"""
The configuration should not change after running
the simulation.
"""
config = utils.load_file(join(EXAMPLES, 'complete.yml'))[0]
s = simulation.from_config(config)
s.dry_run = True
for i in range(5):
s.run_simulation(dry_run=True)
nconfig = s.to_dict()
del nconfig['topology']
assert config == nconfig
def test_row_conversion(self):
env = Environment(dry_run=True)
env['test'] = 'test_value'
res = list(env.history_to_tuples())
assert len(res) == len(env.environment_params)
env._now = 1
env['test'] = 'second_value'
res = list(env.history_to_tuples())
assert env['env', 0, 'test' ] == 'test_value'
assert env['env', 1, 'test' ] == 'second_value'
def test_save_geometric(self):
"""
There is a bug in networkx that prevents it from creating a GEXF file
from geometric models. We should work around it.
"""
G = nx.random_geometric_graph(20, 0.1)
env = Environment(topology=G, dry_run=True)
env.dump_gexf('/tmp/dump-gexf')
def test_save_graph(self):
'''
The history_to_graph method should return a valid networkx graph.
The state of the agent should be encoded as intervals in the nx graph.
'''
G = nx.cycle_graph(5)
distribution = agents.calculate_distribution(None, agents.BaseAgent)
env = Environment(topology=G, network_agents=distribution, dry_run=True)
env[0, 0, 'testvalue'] = 'start'
env[0, 10, 'testvalue'] = 'finish'
nG = env.history_to_graph()
values = nG.node[0]['attr_testvalue']
assert ('start', 0, 10) in values
assert ('finish', 10, None) in values
def test_serialize_class(self):
ser, name = utils.serialize(agents.BaseAgent)
assert name == 'soil.agents.BaseAgent'
assert ser == agents.BaseAgent
class CustomAgent(agents.BaseAgent):
pass
ser, name = utils.serialize(CustomAgent)
assert name == 'test_main.CustomAgent'
assert ser == CustomAgent
def test_serialize_builtin_types(self):
for i in [1, None, True, False, {}, [], list(), dict()]:
ser, name = utils.serialize(i)
assert type(ser) == str
des = utils.deserialize(name, ser)
assert i == des
def test_serialize_agent_type(self):
'''A class from soil.agents should be serialized without the module part'''
ser = agents.serialize_type(CustomAgent)
assert ser == 'test_main.CustomAgent'
ser = agents.serialize_type(agents.BaseAgent)
assert ser == 'BaseAgent'
def test_deserialize_agent_distribution(self):
agent_distro = [
{
'agent_type': 'CounterModel',
'weight': 1
},
{
'agent_type': 'test_main.CustomAgent',
'weight': 2
},
]
converted = agents.deserialize_distribution(agent_distro)
assert converted[0]['agent_type'] == agents.CounterModel
assert converted[1]['agent_type'] == CustomAgent
def test_serialize_agent_distribution(self):
agent_distro = [
{
'agent_type': agents.CounterModel,
'weight': 1
},
{
'agent_type': CustomAgent,
'weight': 2
},
]
converted = agents.serialize_distribution(agent_distro)
assert converted[0]['agent_type'] == 'CounterModel'
assert converted[1]['agent_type'] == 'test_main.CustomAgent'
def test_history(self):
'''Test storing in and retrieving from history (sqlite)'''
h = history.History()
h.save_record(agent_id=0, t_step=0, key="test", value="hello")
assert h[0, 0, "test"] == "hello"