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Code Issues Releases Wiki Activity

WIP: removed stats

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J. Fernando Sánchez 2022-09-16 18:13:39 +02:00
parent 3dc56892c1
commit 0a9c6d8b19
17 changed files with 224 additions and 589 deletions
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1
examples/mesa/mesa.yml
View File

@ -14,7 +14,6 @@ network_agents:
weight: 1
environment_class: social_wealth.MoneyEnv
environment_params:
num_mesa_agents: 5
mesa_agent_type: social_wealth.MoneyAgent
N: 10
width: 50

5
examples/mesa/social_wealth.py
View File

@ -71,10 +71,9 @@ class SocialMoneyAgent(NetworkAgent, MoneyAgent):
class MoneyEnv(Environment):
"""A model with some number of agents."""
def __init__(self, N, width, height, *args, network_params, **kwargs):
def __init__(self, width, height, *args, topologies, **kwargs):
network_params['n'] = N
super().__init__(*args, network_params=network_params, **kwargs)
super().__init__(*args, topologies=topologies, **kwargs)
self.grid = MultiGrid(width, height, False)
# Create agents

4
examples/newsspread/newsspread.py
View File

@ -1,8 +1,8 @@
from soil.agents import FSM, state, default_state, prob
from soil.agents import FSM, NetworkAgent, state, default_state, prob
import logging
class DumbViewer(FSM):
class DumbViewer(FSM, NetworkAgent):
'''
A viewer that gets infected via TV (if it has one) and tries to infect
its neighbors once it's infected.

6
examples/pubcrawl/pubcrawl.py
View File

@ -1,4 +1,4 @@
from soil.agents import FSM, state, default_state
from soil.agents import FSM, NetworkAgent, state, default_state
from soil import Environment
from random import random, shuffle
from itertools import islice
@ -53,7 +53,7 @@ class CityPubs(Environment):
pub['occupancy'] -= 1
class Patron(FSM):
class Patron(FSM, NetworkAgent):
'''Agent that looks for friends to drink with. It will do three things:
1) Look for other patrons to drink with
2) Look for a bar where the agent and other agents in the same group can get in.
@ -151,7 +151,7 @@ class Patron(FSM):
return befriended
class Police(FSM):
class Police(FSM, NetworkAgent):
'''Simple agent to take drunk people out of pubs.'''
level = logging.INFO

8
examples/rabbits/rabbit_agents.py
View File

@ -10,7 +10,7 @@ class Genders(Enum):
female = 'female'
class RabbitModel(FSM):
class RabbitModel(FSM, NetworkAgent):
defaults = {
'age': 0,
@ -110,12 +110,12 @@ class Female(RabbitModel):
self.info('A mother has died carrying a baby!!')
class RandomAccident(NetworkAgent):
class RandomAccident(BaseAgent):
level = logging.DEBUG
def step(self):
rabbits_total = self.topology.number_of_nodes()
rabbits_total = self.env.topology.number_of_nodes()
if 'rabbits_alive' not in self.env:
self.env['rabbits_alive'] = 0
rabbits_alive = self.env.get('rabbits_alive', rabbits_total)
@ -131,5 +131,5 @@ class RandomAccident(NetworkAgent):
self.log('Rabbits alive: {}'.format(self.env['rabbits_alive']))
i.set_state(i.dead)
self.log('Rabbits alive: {}/{}'.format(rabbits_alive, rabbits_total))
if self.count_agents(state_id=RabbitModel.dead.id) == self.topology.number_of_nodes():
if self.env.count_agents(state_id=RabbitModel.dead.id) == self.env.topology.number_of_nodes():
self.die()

155
soil/agents/__init__.py
View File

@ -55,6 +55,7 @@ class BaseAgent(MesaAgent, MutableMapping):
raise Exception()
assert isinstance(unique_id, int)
super().__init__(unique_id=unique_id, model=model)
self.name = str(name) if name else'{}[{}]'.format(type(self).__name__, self.unique_id)
@ -78,6 +79,9 @@ class BaseAgent(MesaAgent, MutableMapping):
if not hasattr(self, k) or getattr(self, k) is None:
setattr(self, k, v)
def __hash__(self):
return hash(self.unique_id)
# TODO: refactor to clean up mesa compatibility
@property
def id(self):
@ -185,16 +189,14 @@ class BaseAgent(MesaAgent, MutableMapping):
# Agent = BaseAgent
class NetworkAgent(BaseAgent):
def __init__(self,
*args,
graph_name: str,
node_id: int = None,
**kwargs,
):
super().__init__(*args, **kwargs)
self.graph_name = graph_name
self.topology = self.env.topologies[self.graph_name]
self.node_id = node_id
@property
def topology(self):
return self.env.topology_for(self.unique_id)
@property
def node_id(self):
return self.env.node_id_for(self.unique_id)
@property
def G(self):
@ -215,15 +217,19 @@ class NetworkAgent(BaseAgent):
it = islice(it, limit)
return list(it)
def iter_agents(self, agents=None, limit_neighbors=False, **kwargs):
def iter_agents(self, unique_id=None, limit_neighbors=False, **kwargs):
if limit_neighbors:
agents = self.topology.neighbors(self.unique_id)
unique_id = [self.topology.nodes[node]['agent_id'] for node in self.topology.neighbors(self.node_id)]
if not unique_id:
return
yield from self.model.agents(unique_id=unique_id, **kwargs)
return self.model.agents(ids=agents, **kwargs)
def subgraph(self, center=True, **kwargs):
include = [self] if center else []
return self.topology.subgraph(n.unique_id for n in list(self.get_agents(**kwargs))+include)
G = self.topology.subgraph(n.node_id for n in list(self.get_agents(**kwargs)+include))
return G
def remove_node(self, unique_id):
self.topology.remove_node(unique_id)
@ -366,7 +372,7 @@ def prob(prob=1):
def calculate_distribution(network_agents=None,
agent_type=None):
agent_class=None):
'''
Calculate the threshold values (thresholds for a uniform distribution)
of an agent distribution given the weights of each agent type.
@ -374,13 +380,13 @@ def calculate_distribution(network_agents=None,
The input has this form: ::
[
{'agent_type': 'agent_type_1',
{'agent_class': 'agent_class_1',
'weight': 0.2,
'state': {
'id': 0
}
},
{'agent_type': 'agent_type_2',
{'agent_class': 'agent_class_2',
'weight': 0.8,
'state': {
'id': 1
@ -389,12 +395,12 @@ def calculate_distribution(network_agents=None,
]
In this example, 20% of the nodes will be marked as type
'agent_type_1'.
'agent_class_1'.
'''
if network_agents:
network_agents = [deepcopy(agent) for agent in network_agents if not hasattr(agent, 'id')]
elif agent_type:
network_agents = [{'agent_type': agent_type}]
elif agent_class:
network_agents = [{'agent_class': agent_class}]
else:
raise ValueError('Specify a distribution or a default agent type')
@ -414,11 +420,11 @@ def calculate_distribution(network_agents=None,
return network_agents
def serialize_type(agent_type, known_modules=[], **kwargs):
if isinstance(agent_type, str):
return agent_type
def serialize_type(agent_class, known_modules=[], **kwargs):
if isinstance(agent_class, str):
return agent_class
known_modules += ['soil.agents']
return serialization.serialize(agent_type, known_modules=known_modules, **kwargs)[1] # Get the name of the class
return serialization.serialize(agent_class, known_modules=known_modules, **kwargs)[1] # Get the name of the class
def serialize_definition(network_agents, known_modules=[]):
@ -430,23 +436,23 @@ def serialize_definition(network_agents, known_modules=[]):
for v in d:
if 'threshold' in v:
del v['threshold']
v['agent_type'] = serialize_type(v['agent_type'],
v['agent_class'] = serialize_type(v['agent_class'],
known_modules=known_modules)
return d
def deserialize_type(agent_type, known_modules=[]):
if not isinstance(agent_type, str):
return agent_type
def deserialize_type(agent_class, known_modules=[]):
if not isinstance(agent_class, str):
return agent_class
known = known_modules + ['soil.agents', 'soil.agents.custom' ]
agent_type = serialization.deserializer(agent_type, known_modules=known)
return agent_type
agent_class = serialization.deserializer(agent_class, known_modules=known)
return agent_class
def deserialize_definition(ind, **kwargs):
d = deepcopy(ind)
for v in d:
v['agent_type'] = deserialize_type(v['agent_type'], **kwargs)
v['agent_class'] = deserialize_type(v['agent_class'], **kwargs)
return d
@ -461,7 +467,7 @@ def _validate_states(states, topology):
return states
def _convert_agent_types(ind, to_string=False, **kwargs):
def _convert_agent_classs(ind, to_string=False, **kwargs):
'''Convenience method to allow specifying agents by class or class name.'''
if to_string:
return serialize_definition(ind, **kwargs)
@ -480,7 +486,7 @@ def _agent_from_definition(definition, value=-1, unique_id=None):
state = {}
if 'state' in d:
state = deepcopy(d['state'])
return d['agent_type'], state
return d['agent_class'], state
raise Exception('Definition for value {} not found in: {}'.format(value, definition))
@ -576,8 +582,11 @@ class AgentView(Mapping, Set):
return group[agent_id]
raise ValueError(f"Agent {agent_id} not found")
def filter(self, *group_ids, **kwargs):
yield from filter_groups(self._agents, group_ids=group_ids, **kwargs)
def filter(self, *args, **kwargs):
yield from filter_groups(self._agents, *args, **kwargs)
def one(self, *args, **kwargs):
return next(filter_groups(self._agents, *args, **kwargs))
def __call__(self, *args, **kwargs):
return list(self.filter(*args, **kwargs))
@ -586,41 +595,57 @@ class AgentView(Mapping, Set):
return any(agent_id in g for g in self._agents)
def __str__(self):
return str(list(a.id for a in self))
return str(list(a.unique_id for a in self))
def __repr__(self):
return f"{self.__class__.__name__}({self})"
def filter_groups(groups, group_ids=None, **kwargs):
def filter_groups(groups, *, group=None, **kwargs):
assert isinstance(groups, dict)
if group_ids:
groups = list(groups[g] for g in group_ids if g in groups)
if group is not None and not isinstance(group, list):
group = [group]
if group:
groups = list(groups[g] for g in group if g in groups)
else:
groups = list(groups.values())
agents = chain.from_iterable(filter_group(g, **kwargs) for g in groups)
yield from agents
def filter_group(group, ids=None, state_id=None, agent_type=None, ignore=None, state=None, **kwargs):
def filter_group(group, *id_args, unique_id=None, state_id=None, agent_class=None, ignore=None, state=None, **kwargs):
'''
Filter agents given as a dict, by the criteria given as arguments (e.g., certain type or state id).
'''
assert isinstance(group, dict)
ids = []
if unique_id is not None:
if isinstance(unique_id, list):
ids += unique_id
else:
ids.append(unique_id)
if id_args:
ids += id_args
if state_id is not None and not isinstance(state_id, (tuple, list)):
state_id = tuple([state_id])
if agent_type is not None:
if agent_class is not None:
agent_class = deserialize_type(agent_class)
try:
agent_type = tuple(agent_type)
agent_class = tuple(agent_class)
except TypeError:
agent_type = tuple([agent_type])
agent_class = tuple([agent_class])
if ids:
agents = (v[aid] for aid in ids if aid in group)
agents = (group[aid] for aid in ids if aid in group)
else:
agents = (a for a in group.values())
@ -631,8 +656,8 @@ def filter_group(group, ids=None, state_id=None, agent_type=None, ignore=None, s
if state_id is not None:
f = filter(lambda agent: agent.get('state_id', None) in state_id, f)
if agent_type is not None:
f = filter(lambda agent: isinstance(agent, agent_type), f)
if agent_class is not None:
f = filter(lambda agent: isinstance(agent, agent_class), f)
state = state or dict()
state.update(kwargs)
@ -660,7 +685,7 @@ def _group_from_config(cfg: config.AgentConfig, default: config.SingleAgentConfi
if cfg.fixed is not None:
agents = _from_fixed(cfg.fixed, topology=cfg.topology, default=default, env=env)
if cfg.distribution:
n = cfg.n or len(env.topologies[cfg.topology])
n = cfg.n or len(env.topologies[cfg.topology or default.topology])
target = n - len(agents)
agents.update(_from_distro(cfg.distribution, target,
topology=cfg.topology or default.topology,
@ -674,6 +699,8 @@ def _group_from_config(cfg: config.AgentConfig, default: config.SingleAgentConfi
else:
filtered = list(agents)
if attrs.n > len(filtered):
raise ValueError(f'Not enough agents to sample. Got {len(filtered)}, expected >= {attrs.n}')
for agent in random.sample(filtered, attrs.n):
agent.state.update(attrs.state)
@ -684,18 +711,20 @@ def _from_fixed(lst: List[config.FixedAgentConfig], topology: str, default: conf
agents = {}
for fixed in lst:
agent_id = fixed.agent_id
if agent_id is None:
agent_id = env.next_id()
agent_id = fixed.agent_id
if agent_id is None:
agent_id = env.next_id()
cls = serialization.deserialize(fixed.agent_class or default.agent_class)
state = fixed.state.copy()
state.update(default.state)
agent = cls(unique_id=agent_id,
model=env,
graph_name=fixed.topology or topology or default.topology,
**state)
agents[agent.unique_id] = agent
cls = serialization.deserialize(fixed.agent_class or default.agent_class)
state = fixed.state.copy()
state.update(default.state)
agent = cls(unique_id=agent_id,
model=env,
**state)
topology = fixed.topology if (fixed.topology is not None) else (topology or default.topology)
if topology:
env.agent_to_node(agent_id, topology, fixed.node_id)
agents[agent.unique_id] = agent
return agents
@ -741,8 +770,12 @@ def _from_distro(distro: List[config.AgentDistro],
cls = classes[idx]
agent_id = env.next_id()
state = d.state.copy()
state.update(default.state)
agent = cls(unique_id=agent_id, model=env, graph_name=d.topology or topology or default.topology, **state)
if default:
state.update(default.state)
agent = cls(unique_id=agent_id, model=env, **state)
topology = d.topology if (d.topology is not None) else topology or default.topology
if topology:
env.agent_to_node(agent.unique_id, topology)
assert agent.name is not None
assert agent.name != 'None'
assert agent.name

19
soil/config.py
View File

@ -7,6 +7,7 @@ import sys
from typing import Any, Callable, Dict, List, Optional, Union, Type
from pydantic import BaseModel, Extra
import networkx as nx
class General(BaseModel):
id: str = 'Unnamed Simulation'
@ -50,9 +51,12 @@ class NetParams(BaseModel, extra=Extra.allow):
class NetConfig(BaseModel):
group: str = 'network'
params: Optional[NetParams]
topology: Optional[Topology]
topology: Optional[Union[Topology, nx.Graph]]
path: Optional[str]
class Config:
arbitrary_types_allowed = True
@staticmethod
def default():
return NetConfig(topology=None, params=None)
@ -77,7 +81,8 @@ class EnvConfig(BaseModel):
class SingleAgentConfig(BaseModel):
agent_class: Optional[Union[Type, str]] = None
agent_id: Optional[int] = None
topology: Optional[str] = 'default'
topology: Optional[str] = None
node_id: Optional[Union[int, str]] = None
name: Optional[str] = None
state: Optional[Dict[str, Any]] = {}
@ -186,9 +191,7 @@ def convert_old(old, strict=True):
if 'agent_id' in agent:
agent['name'] = agent['agent_id']
del agent['agent_id']
agents['environment']['fixed'].append(updated_agent(agent))
else:
agents['environment']['distribution'].append(updated_agent(agent))
agents['environment']['fixed'].append(updated_agent(agent))
by_weight = []
fixed = []
@ -206,10 +209,10 @@ def convert_old(old, strict=True):
if 'agent_type' in old and (not fixed and not by_weight):
agents['network']['topology'] = 'default'
by_weight = [{'agent_type': old['agent_type']}]
by_weight = [{'agent_class': old['agent_type']}]
# TODO: translate states
# TODO: translate states properly
if 'states' in old:
states = old['states']
if isinstance(states, dict):
@ -217,7 +220,7 @@ def convert_old(old, strict=True):
else:
states = enumerate(states)
for (k, v) in states:
override.append({'filter': {'id': k},
override.append({'filter': {'node_id': k},
'state': v
})

264
soil/config_old.py
View File

@ -1,264 +0,0 @@
from pydantic import BaseModel, ValidationError, validator
import yaml
import os
import sys
import networkx as nx
import collections.abc
from . import serialization, utils, basestring, agents
class Config(collections.abc.Mapping):
"""
1) agent type can be specified by name or by class.
2) instead of just one type, a network agents distribution can be used.
The distribution specifies the weight (or probability) of each
agent type in the topology. This is an example distribution: ::
[
{'agent_type': 'agent_type_1',
'weight': 0.2,
'state': {
'id': 0
}
},
{'agent_type': 'agent_type_2',
'weight': 0.8,
'state': {
'id': 1
}
}
]
In this example, 20% of the nodes will be marked as type
'agent_type_1'.
3) if no initial state is given, each node's state will be set
to `{'id': 0}`.
Parameters
---------
name : str, optional
name of the Simulation
group : str, optional
a group name can be used to link simulations
topology (optional): networkx.Graph instance or Node-Link topology as a dict or string (will be loaded with `json_graph.node_link_graph(topology`).
network_params : dict
parameters used to create a topology with networkx, if no topology is given
network_agents : dict
definition of agents to populate the topology with
agent_type : NetworkAgent subclass, optional
Default type of NetworkAgent to use for nodes not specified in network_agents
states : list, optional
List of initial states corresponding to the nodes in the topology. Basic form is a list of integers
whose value indicates the state
dir_path: str, optional
Directory path to load simulation assets (files, modules...)
seed : str, optional
Seed to use for the random generator
num_trials : int, optional
Number of independent simulation runs
max_time : int, optional
Maximum step/time for each simulation
environment_params : dict, optional
Dictionary of globally-shared environmental parameters
environment_agents: dict, optional
Similar to network_agents. Distribution of Agents that control the environment
environment_class: soil.environment.Environment subclass, optional
Class for the environment. It defailts to soil.environment.Environment
"""
__slots__ = 'name', 'agent_type', 'group', 'description', 'network_agents', 'environment_agents', 'states', 'default_state', 'interval', 'network_params', 'seed', 'num_trials', 'max_time', 'topology', 'schedule', 'initial_time', 'environment_params', 'environment_class', 'dir_path', '_added_to_path', 'visualization_params'
def __init__(self, name=None,
group=None,
agent_type='BaseAgent',
network_agents=None,
environment_agents=None,
states=None,
description=None,
default_state=None,
interval=1,
network_params=None,
seed=None,
num_trials=1,
max_time=None,
topology=None,
schedule=None,
initial_time=0,
environment_params={},
environment_class='soil.Environment',
dir_path=None,
visualization_params=None,
):
self.network_params = network_params
self.name = name or 'Unnamed'
self.description = description or 'No simulation description available'
self.seed = str(seed or name)
self.group = group or ''
self.num_trials = num_trials
self.max_time = max_time
self.default_state = default_state or {}
self.dir_path = dir_path or os.getcwd()
self.interval = interval
self.visualization_params = visualization_params or {}
self._added_to_path = list(x for x in [os.getcwd(), self.dir_path] if x not in sys.path)
sys.path += self._added_to_path
self.topology = topology
self.schedule = schedule
self.initial_time = initial_time
self.environment_class = environment_class
self.environment_params = dict(environment_params)
#TODO: Check agent distro vs fixed agents
self.environment_agents = environment_agents or []
self.agent_type = agent_type
self.network_agents = network_agents or {}
self.states = states or {}
def validate(self):
agents._validate_states(self.states,
self._topology)
def calculate(self):
return CalculatedConfig(self)
def restore_path(self):
for added in self._added_to_path:
sys.path.remove(added)
def to_yaml(self):
return yaml.dump(self.to_dict())
def dump_yaml(self, f=None, outdir=None):
if not f and not outdir:
raise ValueError('specify a file or an output directory')
if not f:
f = os.path.join(outdir, '{}.dumped.yml'.format(self.name))
with utils.open_or_reuse(f, 'w') as f:
f.write(self.to_yaml())
def to_yaml(self):
return yaml.dump(self.to_dict())
# TODO: See note on getstate
def to_dict(self):
return dict(self)
def __repr__(self):
return self.to_yaml()
def dump_yaml(self, f=None, outdir=None):
if not f and not outdir:
raise ValueError('specify a file or an output directory')
if not f:
f = os.path.join(outdir, '{}.dumped.yml'.format(self.name))
with utils.open_or_reuse(f, 'w') as f:
f.write(self.to_yaml())
def __getitem__(self, key):
return getattr(self, key)
def __iter__(self):
return (k for k in self.__slots__ if k[0] != '_')
def __len__(self):
return len(self.__slots__)
def dump_pickle(self, f=None, outdir=None):
if not outdir and not f:
raise ValueError('specify a file or an output directory')
if not f:
f = os.path.join(outdir,
'{}.simulation.pickle'.format(self.name))
with utils.open_or_reuse(f, 'wb') as f:
pickle.dump(self, f)
# TODO: remove this. A config should be sendable regardless. Non-pickable objects could be computed via properties and the like
# def __getstate__(self):
# state={}
# for k, v in self.__dict__.items():
# if k[0] != '_':
# state[k] = v
# state['topology'] = json_graph.node_link_data(self.topology)
# state['network_agents'] = agents.serialize_definition(self.network_agents,
# known_modules = [])
# state['environment_agents'] = agents.serialize_definition(self.environment_agents,
# known_modules = [])
# state['environment_class'] = serialization.serialize(self.environment_class,
# known_modules=['soil.environment'])[1] # func, name
# if state['load_module'] is None:
# del state['load_module']
# return state
# # TODO: remove, same as __getstate__
# def __setstate__(self, state):
# self.__dict__ = state
# self.load_module = getattr(self, 'load_module', None)
# if self.dir_path not in sys.path:
# sys.path += [self.dir_path, os.getcwd()]
# self.topology = json_graph.node_link_graph(state['topology'])
# self.network_agents = agents.calculate_distribution(agents._convert_agent_types(self.network_agents))
# self.environment_agents = agents._convert_agent_types(self.environment_agents,
# known_modules=[self.load_module])
# self.environment_class = serialization.deserialize(self.environment_class,
# known_modules=[self.load_module,
# 'soil.environment', ]) # func, name
class CalculatedConfig(Config):
def __init__(self, config):
"""
Returns a configuration object that replaces some "plain" attributes (e.g., `environment_class` string) into
a Python object (`soil.environment.Environment` class).
"""
self._config = config
values = dict(config)
values['environment_class'] = self._environment_class()
values['environment_agents'] = self._environment_agents()
values['topology'] = self._topology()
values['network_agents'] = self._network_agents()
values['agent_type'] = serialization.deserialize(self.agent_type, known_modules=['soil.agents'])
return values
def _topology(self):
topology = self._config.topology
if topology is None:
topology = serialization.load_network(self._config.network_params,
dir_path=self._config.dir_path)
elif isinstance(topology, basestring) or isinstance(topology, dict):
topology = json_graph.node_link_graph(topology)
return nx.Graph(topology)
def _environment_class(self):
return serialization.deserialize(self._config.environment_class,
known_modules=['soil.environment', ]) or Environment
def _environment_agents(self):
return agents._convert_agent_types(self._config.environment_agents)
def _network_agents(self):
distro = agents.calculate_distribution(self._config.network_agents,
self._config.agent_type)
return agents._convert_agent_types(distro)
def _environment_class(self):
return serialization.deserialize(self._config.environment_class,
known_modules=['soil.environment', ]) # func, name

92
soil/environment.py
View File

@ -15,6 +15,7 @@ from networkx.readwrite import json_graph
import networkx as nx
from mesa import Model
from mesa.datacollection import DataCollector
from . import serialization, agents, analysis, utils, time, config, network
@ -41,6 +42,9 @@ class Environment(Model):
interval=1,
agents: Dict[str, config.AgentConfig] = {},
topologies: Dict[str, config.NetConfig] = {},
agent_reporters: Optional[Any] = None,
model_reporters: Optional[Any] = None,
tables: Optional[Any] = None,
**env_params):
super().__init__()
@ -61,6 +65,7 @@ class Environment(Model):
self.topologies = {}
self._node_ids = {}
for (name, cfg) in topologies.items():
self.set_topology(cfg=cfg,
graph=name)
@ -72,6 +77,7 @@ class Environment(Model):
self['SEED'] = seed
self.logger = utils.logger.getChild(self.id)
self.datacollector = DataCollector(model_reporters, agent_reporters, tables)
@property
def topology(self):
@ -79,8 +85,7 @@ class Environment(Model):
@property
def network_agents(self):
yield from self.agents(agent_type=agents.NetworkAgent, iterator=False)
yield from self.agents(agent_class=agents.NetworkAgent)
@staticmethod
def from_config(conf: config.Config, trial_id, **kwargs) -> Environment:
@ -91,9 +96,10 @@ class Environment(Model):
seed = '{}_{}'.format(conf.general.seed, trial_id)
id = '{}_trial_{}'.format(conf.general.id, trial_id).replace('.', '-')
opts = conf.environment.params.copy()
dir_path = conf.general.dir_path
opts.update(conf)
opts.update(kwargs)
env = serialization.deserialize(conf.environment.environment_class)(env_id=id, seed=seed, **opts)
env = serialization.deserialize(conf.environment.environment_class)(env_id=id, seed=seed, dir_path=dir_path, **opts)
return env
@property
@ -103,12 +109,31 @@ class Environment(Model):
raise Exception('The environment has not been scheduled, so it has no sense of time')
def topology_for(self, agent_id):
return self.topologies[self._node_ids[agent_id][0]]
def node_id_for(self, agent_id):
return self._node_ids[agent_id][1]
def set_topology(self, cfg=None, dir_path=None, graph='default'):
self.topologies[graph] = network.from_config(cfg, dir_path=dir_path)
topology = cfg
if not isinstance(cfg, nx.Graph):
topology = network.from_config(cfg, dir_path=dir_path or self.dir_path)
self.topologies[graph] = topology
@property
def agents(self):
return agents.AgentView(self._agents)
def count_agents(self, *args, **kwargs):
return sum(1 for i in self.find_all(*args, **kwargs))
def find_all(self, *args, **kwargs):
return agents.AgentView(self._agents).filter(*args, **kwargs)
def find_one(self, *args, **kwargs):
return agents.AgentView(self._agents).one(*args, **kwargs)
@agents.setter
def agents(self, agents_def: Dict[str, config.AgentConfig]):
@ -117,37 +142,47 @@ class Environment(Model):
for a in d.values():
self.schedule.add(a)
# @property
# def network_agents(self):
# for i in self.G.nodes():
# node = self.G.nodes[i]
# if 'agent' in node:
# yield node['agent']
def init_agent(self, agent_id, agent_definitions, graph='default'):
node = self.topologies[graph].nodes[agent_id]
init = False
state = dict(node)
agent_type = None
if 'agent_type' in self.states.get(agent_id, {}):
agent_type = self.states[agent_id]['agent_type']
elif 'agent_type' in node:
agent_type = node['agent_type']
elif 'agent_type' in self.default_state:
agent_type = self.default_state['agent_type']
agent_class = None
if 'agent_class' in self.states.get(agent_id, {}):
agent_class = self.states[agent_id]['agent_class']
elif 'agent_class' in node:
agent_class = node['agent_class']
elif 'agent_class' in self.default_state:
agent_class = self.default_state['agent_class']
if agent_type:
agent_type = agents.deserialize_type(agent_type)
if agent_class:
agent_class = agents.deserialize_type(agent_class)
elif agent_definitions:
agent_type, state = agents._agent_from_definition(agent_definitions, unique_id=agent_id)
agent_class, state = agents._agent_from_definition(agent_definitions, unique_id=agent_id)
else:
serialization.logger.debug('Skipping node {}'.format(agent_id))
return
return self.set_agent(agent_id, agent_type, state)
return self.set_agent(agent_id, agent_class, state)
def set_agent(self, agent_id, agent_type, state=None, graph='default'):
def agent_to_node(self, agent_id, graph_name='default', node_id=None, shuffle=False):
#TODO: test
if node_id is None:
G = self.topologies[graph_name]
candidates = list(G.nodes(data=True))
if shuffle:
random.shuffle(candidates)
for next_id, data in candidates:
if data.get('agent_id', None) is None:
node_id = next_id
data['agent_id'] = agent_id
break
self._node_ids[agent_id] = (graph_name, node_id)
print(self._node_ids)
def set_agent(self, agent_id, agent_class, state=None, graph='default'):
node = self.topologies[graph].nodes[agent_id]
defstate = deepcopy(self.default_state) or {}
defstate.update(self.states.get(agent_id, {}))
@ -155,9 +190,9 @@ class Environment(Model):
if state:
defstate.update(state)
a = None
if agent_type:
if agent_class:
state = defstate
a = agent_type(model=self,
a = agent_class(model=self,
unique_id=agent_id
)
@ -168,10 +203,10 @@ class Environment(Model):
self.schedule.add(a)
return a
def add_node(self, agent_type, state=None, graph='default'):
def add_node(self, agent_class, state=None, graph='default'):
agent_id = int(len(self.topologies[graph].nodes()))
self.topologies[graph].add_node(agent_id)
a = self.set_agent(agent_id, agent_type, state, graph=graph)
a = self.set_agent(agent_id, agent_class, state, graph=graph)
a['visible'] = True
return a
@ -201,6 +236,7 @@ class Environment(Model):
'''
super().step()
self.schedule.step()
self.datacollector.collect(self)
def run(self, until, *args, **kwargs):
until = until or float('inf')

49
soil/exporters.py
View File

@ -1,5 +1,4 @@
import os
import csv as csvlib
from time import time as current_time
from io import BytesIO
from sqlalchemy import create_engine
@ -59,7 +58,7 @@ class Exporter:
'''Method to call when the simulation starts'''
pass
def sim_end(self, stats):
def sim_end(self):
'''Method to call when the simulation ends'''
pass
@ -67,7 +66,7 @@ class Exporter:
'''Method to call when a trial start'''
pass
def trial_end(self, env, stats):
def trial_end(self, env):
'''Method to call when a trial ends'''
pass
@ -115,31 +114,35 @@ class default(Exporter):
# self.simulation.dump_sqlite(f)
def get_dc_dfs(dc):
dfs = {'env': dc.get_model_vars_dataframe(),
'agents': dc.get_agent_vars_dataframe }
for table_name in dc.tables:
dfs[table_name] = dc.get_table_dataframe(table_name)
yield from dfs.items()
class csv(Exporter):
'''Export the state of each environment (and its agents) in a separate CSV file'''
def trial_end(self, env, stats):
def trial_end(self, env):
with timer('[CSV] Dumping simulation {} trial {} @ dir {}'.format(self.simulation.name,
env.name,
env.id,
self.outdir)):
with self.output('{}.stats.{}.csv'.format(env.name, stats.name)) as f:
statwriter = csvlib.writer(f, delimiter='\t', quotechar='"', quoting=csvlib.QUOTE_ALL)
for stat in stats:
statwriter.writerow(stat)
for (df_name, df) in get_dc_dfs(env.datacollector):
with self.output('{}.stats.{}.csv'.format(env.id, df_name)) as f:
df.to_csv(f)
class gexf(Exporter):
def trial_end(self, env, stats):
def trial_end(self, env):
if self.dry_run:
logger.info('Not dumping GEXF in dry_run mode')
return
with timer('[GEXF] Dumping simulation {} trial {}'.format(self.simulation.name,
env.name)):
with self.output('{}.gexf'.format(env.name), mode='wb') as f:
env.id)):
with self.output('{}.gexf'.format(env.id), mode='wb') as f:
self.dump_gexf(env, f)
def dump_gexf(self, env, f):
@ -159,25 +162,25 @@ class dummy(Exporter):
with self.output('dummy', 'w') as f:
f.write('simulation started @ {}\n'.format(current_time()))
def trial_end(self, env, stats):
def trial_start(self, env):
with self.output('dummy', 'w') as f:
for i in stats:
f.write(','.join(map(str, i)))
f.write('\n')
f.write('trial started@ {}\n'.format(current_time()))
def sim_end(self, stats):
def trial_end(self, env):
with self.output('dummy', 'w') as f:
f.write('trial ended@ {}\n'.format(current_time()))
def sim_end(self):
with self.output('dummy', 'a') as f:
f.write('simulation ended @ {}\n'.format(current_time()))
class graphdrawing(Exporter):
def trial_end(self, env, stats):
def trial_end(self, env):
# Outside effects
f = plt.figure()
nx.draw(env.G, node_size=10, width=0.2, pos=nx.spring_layout(env.G, scale=100), ax=f.add_subplot(111))
with open('graph-{}.png'.format(env.name)) as f:
with open('graph-{}.png'.format(env.id)) as f:
f.savefig(f)
'''

35
soil/simulation.py
View File

@ -16,7 +16,6 @@ from . import serialization, utils, basestring, agents
from .environment import Environment
from .utils import logger
from .exporters import default
from .stats import defaultStats
from .config import Config, convert_old
@ -71,8 +70,8 @@ class Simulation:
**kwargs)
def run_gen(self, parallel=False, dry_run=False,
exporters=[default, ], stats=[], outdir=None, exporter_params={},
stats_params={}, log_level=None,
exporters=[default, ], outdir=None, exporter_params={},
log_level=None,
**kwargs):
'''Run the simulation and yield the resulting environments.'''
if log_level:
@ -85,15 +84,8 @@ class Simulation:
dry_run=dry_run,
outdir=outdir,
**exporter_params)
stats = serialization.deserialize_all(simulation=self,
names=stats,
known_modules=['soil.stats',],
**stats_params)
with utils.timer('simulation {}'.format(self.config.general.id)):
for stat in stats:
stat.sim_start()
for exporter in exporters:
exporter.sim_start()
@ -104,32 +96,13 @@ class Simulation:
for exporter in exporters:
exporter.trial_start(env)
collected = list(stat.trial_end(env) for stat in stats)
saved = self._update_stats(collected, t_step=env.now, trial_id=env.id)
for exporter in exporters:
exporter.trial_end(env, saved)
exporter.trial_end(env)
yield env
collected = list(stat.end() for stat in stats)
saved = self._update_stats(collected)
for stat in stats:
stat.sim_end()
for exporter in exporters:
exporter.sim_end(saved)
def _update_stats(self, collection, **kwargs):
stats = dict(kwargs)
for stat in collection:
stats.update(stat)
return stats
def log_stats(self, stats):
logger.info('Stats: \n{}'.format(yaml.dump(stats, default_flow_style=False)))
exporter.sim_end()
def get_env(self, trial_id=0, **kwargs):
'''Create an environment for a trial of the simulation'''

111
soil/stats.py
View File

@ -1,111 +0,0 @@
import pandas as pd
from collections import Counter
class Stats:
'''
Interface for all stats. It is not necessary, but it is useful
if you don't plan to implement all the methods.
'''
def __init__(self, simulation, name=None):
self.name = name or type(self).__name__
self.simulation = simulation
def sim_start(self):
'''Method to call when the simulation starts'''
pass
def sim_end(self):
'''Method to call when the simulation ends'''
return {}
def trial_start(self, env):
'''Method to call when a trial starts'''
return {}
def trial_end(self, env):
'''Method to call when a trial ends'''
return {}
class distribution(Stats):
'''
Calculate the distribution of agent states at the end of each trial,
the mean value, and its deviation.
'''
def sim_start(self):
self.means = []
self.counts = []
def trial_end(self, env):
df = pd.DataFrame(env.state_to_tuples())
df = df.drop('SEED', axis=1)
ix = df.index[-1]
attrs = df.columns.get_level_values(0)
vc = {}
stats = {
'mean': {},
'count': {},
}
for a in attrs:
t = df.loc[(ix, a)]
try:
stats['mean'][a] = t.mean()
self.means.append(('mean', a, t.mean()))
except TypeError:
pass
for name, count in t.value_counts().iteritems():
if a not in stats['count']:
stats['count'][a] = {}
stats['count'][a][name] = count
self.counts.append(('count', a, name, count))
return stats
def sim_end(self):
dfm = pd.DataFrame(self.means, columns=['metric', 'key', 'value'])
dfc = pd.DataFrame(self.counts, columns=['metric', 'key', 'value', 'count'])
count = {}
mean = {}
if self.means:
res = dfm.groupby(by=['key']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
mean = res['value'].to_dict()
if self.counts:
res = dfc.groupby(by=['key', 'value']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
for k,v in res['count'].to_dict().items():
if k not in count:
count[k] = {}
for tup, times in v.items():
subkey, subcount = tup
if subkey not in count[k]:
count[k][subkey] = {}
count[k][subkey][subcount] = times
return {'count': count, 'mean': mean}
class defaultStats(Stats):
def trial_end(self, env):
c = Counter()
c.update(a.__class__.__name__ for a in env.network_agents)
c2 = Counter()
c2.update(a['id'] for a in env.network_agents)
return {
'network ': {
'n_nodes': env.G.number_of_nodes(),
'n_edges': env.G.number_of_edges(),
},
'agents': {
'model_count': dict(c),
'state_count': dict(c2),
}
}

4
tests/complete_converted.yml
View File

@ -29,11 +29,11 @@ agents:
weight: 0.6
override:
- filter:
id: 0
node_id: 0
state:
name: 'The first node'
- filter:
id: 1
node_id: 1
state:
name: 'The second node'

8
tests/test_config.py
View File

@ -71,11 +71,11 @@ class TestConfig(TestCase):
s = simulation.from_config(cfg)
env = s.get_env()
assert len(env.topologies['default'].nodes) == 10
assert len(env.agents('network')) == 10
assert len(env.agents('environment')) == 1
assert len(env.agents(group='network')) == 10
assert len(env.agents(group='environment')) == 1
assert sum(1 for a in env.agents('network') if isinstance(a, agents.CounterModel)) == 4
assert sum(1 for a in env.agents('network') if isinstance(a, agents.AggregatedCounter)) == 6
assert sum(1 for a in env.agents(group='network', agent_type=agents.CounterModel)) == 4
assert sum(1 for a in env.agents(group='network', agent_type=agents.AggregatedCounter)) == 6
def make_example_test(path, cfg):
def wrapped(self):

7
tests/test_exporters.py
View File

@ -7,8 +7,6 @@ from unittest import TestCase
from soil import exporters
from soil import simulation
from soil.stats import distribution
class Dummy(exporters.Exporter):
started = False
trials = 0
@ -22,13 +20,13 @@ class Dummy(exporters.Exporter):
self.__class__.called_start += 1
self.__class__.started = True
def trial_end(self, env, stats):
def trial_end(self, env):
assert env
self.__class__.trials += 1
self.__class__.total_time += env.now
self.__class__.called_trial += 1
def sim_end(self, stats):
def sim_end(self):
self.__class__.ended = True
self.__class__.called_end += 1
@ -78,7 +76,6 @@ class Exporters(TestCase):
exporters.csv,
exporters.gexf,
],
stats=[distribution,],
dry_run=False,
outdir=tmpdir,
exporter_params={'copy_to': output})

11
tests/test_main.py
View File

@ -10,7 +10,7 @@ from functools import partial
from os.path import join
from soil import (simulation, Environment, agents, network, serialization,
utils)
utils, config)
from soil.time import Delta
ROOT = os.path.abspath(os.path.dirname(__file__))
@ -200,7 +200,6 @@ class TestMain(TestCase):
recovered = yaml.load(serial, Loader=yaml.SafeLoader)
for (k, v) in config.items():
assert recovered[k] == v
# assert config == recovered
def test_configuration_changes(self):
"""
@ -294,11 +293,13 @@ class TestMain(TestCase):
G.add_node(3)
G.add_edge(1, 2)
distro = agents.calculate_distribution(agent_type=agents.NetworkAgent)
env = Environment(name='Test', topology=G, network_agents=distro)
distro[0]['topology'] = 'default'
aconfig = config.AgentConfig(distribution=distro, topology='default')
env = Environment(name='Test', topologies={'default': G}, agents={'network': aconfig})
lst = list(env.network_agents)
a2 = env.get_agent(2)
a3 = env.get_agent(3)
a2 = env.find_one(node_id=2)
a3 = env.find_one(node_id=3)
assert len(a2.subgraph(limit_neighbors=True)) == 2
assert len(a3.subgraph(limit_neighbors=True)) == 1
assert len(a3.subgraph(limit_neighbors=True, center=False)) == 0

34
tests/test_stats.py
View File

@ -1,34 +0,0 @@
from unittest import TestCase
from soil import simulation, stats
from soil.utils import unflatten_dict
class Stats(TestCase):
def test_distribution(self):
'''The distribution exporter should write the number of agents in each state'''
config = {
'name': 'exporter_sim',
'network_params': {
'generator': 'complete_graph',
'n': 4
},
'agent_type': 'CounterModel',
'max_time': 2,
'num_trials': 5,
'environment_params': {}
}
s = simulation.from_config(config)
for env in s.run_simulation(stats=[stats.distribution]):
pass
# stats_res = unflatten_dict(dict(env._history['stats', -1, None]))
allstats = s.get_stats()
for stat in allstats:
assert 'count' in stat
assert 'mean' in stat
if 'trial_id' in stat:
assert stat['mean']['neighbors'] == 3
assert stat['count']['total']['4'] == 4
else:
assert stat['count']['count']['neighbors']['3'] == 20
assert stat['mean']['min']['neighbors'] == stat['mean']['max']['neighbors']