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3 Commits

Author SHA1 Message Date
J. Fernando Sánchez
0efcd24d90 Improve exporters 2022-10-16 21:57:30 +02:00
J. Fernando Sánchez
78833a9e08 Formatted with black 2022-10-16 17:58:19 +02:00
J. Fernando Sánchez
d9947c2c52 WIP: all tests pass
Documentation needs some improvement

The API has been simplified to only allow for ONE topology per
NetworkEnvironment.
This covers the main use case, and simplifies the code.
2022-10-16 17:56:23 +02:00
48 changed files with 1884 additions and 1529 deletions

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@ -5,14 +5,20 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
## [0.3 UNRELEASED]
### Added
* Simple debugging capabilities, with a custom `pdb.Debugger` subclass that exposes commands to list agents and their status and set breakpoints on states (for FSM agents)
* Simple debugging capabilities in `soil.debugging`, with a custom `pdb.Debugger` subclass that exposes commands to list agents and their status and set breakpoints on states (for FSM agents). Try it with `soil --debug <simulation file>`
* Ability to run
* Ability to
* The `soil.exporters` module to export the results of datacollectors (model.datacollector) into files at the end of trials/simulations
* A modular set of classes for environments/models. Now the ability to configure the agents through an agent definition and a topology through a network configuration is split into two classes (`soil.agents.BaseEnvironment` for agents, `soil.agents.NetworkEnvironment` to add topology).
* FSM agents can now have generators as states. They work similar to normal states, with one caveat. Only `time` values can be yielded, not a state. This is because the state will not change, it will be resumed after the yield, at the appropriate time. The return value *can* be a state, or a `(state, time)` tuple, just like in normal states.
### Changed
* Configuration schema is very different now. Check `soil.config` for more information. We are also using Pydantic for (de)serialization.
* There may be more than one topology/network in the simulation
* Agents are split into groups now. Each group may be assigned a given set of agents or an agent distribution, and a network topology to be assigned to.
* Ability
### Removed
* Any `tsih` and `History` integration in the main classes. To record the state of environments/agents, just use a datacollector. In some cases this may be slower or consume more memory than the previous system. However, few cases actually used the full potential of the history, and it came at the cost of unnecessary complexity and worse performance for the majority of cases.
## [0.20.7]
### Changed
* Creating a `time.When` from another `time.When` does not nest them anymore (it returns the argument)

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@ -10,19 +10,14 @@ seed: "CompleteSeed!"
model_class: Environment
model_params:
am_i_complete: true
topologies:
default:
params:
generator: complete_graph
n: 10
another_graph:
params:
generator: complete_graph
n: 2
topology:
params:
generator: complete_graph
n: 12
environment:
agents:
agent_class: CounterModel
topology: default
topology: true
state:
times: 1
# In this group we are not specifying any topology
@ -30,25 +25,23 @@ model_params:
- name: 'Environment Agent 1'
agent_class: BaseAgent
group: environment
topology: null
topology: false
hidden: true
state:
times: 10
- agent_class: CounterModel
id: 0
group: other_counters
topology: another_graph
group: fixed_counters
state:
times: 1
total: 0
- agent_class: CounterModel
topology: another_graph
group: other_counters
group: fixed_counters
id: 1
distribution:
- agent_class: CounterModel
weight: 1
group: general_counters
group: distro_counters
state:
times: 3
- agent_class: AggregatedCounter

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@ -1,63 +0,0 @@
---
version: '2'
id: simple
group: tests
dir_path: "/tmp/"
num_trials: 3
max_steps: 100
interval: 1
seed: "CompleteSeed!"
model_class: "soil.Environment"
model_params:
topologies:
default:
params:
generator: complete_graph
n: 10
another_graph:
params:
generator: complete_graph
n: 2
agents:
# The values here will be used as default values for any agent
agent_class: CounterModel
topology: default
state:
times: 1
# This specifies a distribution of agents, each with a `weight` or an explicit number of agents
distribution:
- agent_class: CounterModel
weight: 1
# This is inherited from the default settings
#topology: default
state:
times: 3
- agent_class: AggregatedCounter
topology: default
weight: 0.2
fixed:
- name: 'Environment Agent 1'
# All the other agents will assigned to the 'default' group
group: environment
# Do not count this agent towards total limits
hidden: true
agent_class: soil.BaseAgent
topology: null
state:
times: 10
- agent_class: CounterModel
topology: another_graph
id: 0
state:
times: 1
total: 0
- agent_class: CounterModel
topology: another_graph
id: 1
override:
# 2 agents that match this filter will be updated to match the state {times: 5}
- filter:
agent_class: AggregatedCounter
n: 2
state:
times: 5

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@ -15,6 +15,7 @@ class Fibonacci(FSM):
prev, self['prev'] = self['prev'], max([self.now, self['prev']])
return None, self.env.timeout(prev)
class Odds(FSM):
'''Agent that only executes in odd t_steps'''
@default_state
@ -23,9 +24,8 @@ class Odds(FSM):
self.log('Stopping at {}'.format(self.now))
return None, self.env.timeout(1+self.now%2)
if __name__ == '__main__':
import logging
logging.basicConfig(level=logging.INFO)
from soil import Simulation
s = Simulation(network_agents=[{'ids': [0], 'agent_class': Fibonacci},
{'ids': [1], 'agent_class': Odds}],

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@ -8,17 +8,12 @@ interval: 1
seed: '1'
model_class: social_wealth.MoneyEnv
model_params:
topologies:
default:
params:
generator: social_wealth.graph_generator
n: 5
generator: social_wealth.graph_generator
agents:
topology: true
distribution:
- agent_class: social_wealth.SocialMoneyAgent
topology: default
weight: 1
mesa_agent_class: social_wealth.MoneyAgent
N: 10
width: 50
height: 50

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@ -2,6 +2,7 @@ from mesa.visualization.ModularVisualization import ModularServer
from soil.visualization import UserSettableParameter
from mesa.visualization.modules import ChartModule, NetworkModule, CanvasGrid
from social_wealth import MoneyEnv, graph_generator, SocialMoneyAgent
import networkx as nx
class MyNetwork(NetworkModule):
@ -13,15 +14,16 @@ def network_portrayal(env):
# The model ensures there is 0 or 1 agent per node
portrayal = dict()
wealths = {node_id: data['agent'].wealth for (node_id, data) in env.G.nodes(data=True)}
portrayal["nodes"] = [
{
"id": agent_id,
"size": env.get_agent(agent_id).wealth,
# "color": "#CC0000" if not agents or agents[0].wealth == 0 else "#007959",
"color": "#CC0000",
"label": f"{agent_id}: {env.get_agent(agent_id).wealth}",
}
for (agent_id) in env.G.nodes
"id": node_id,
"size": 2*(wealth+1),
"color": "#CC0000" if wealth == 0 else "#007959",
# "color": "#CC0000",
"label": f"{node_id}: {wealth}",
} for (node_id, wealth) in wealths.items()
]
portrayal["edges"] = [
@ -29,7 +31,6 @@ def network_portrayal(env):
for edge_id, (source, target) in enumerate(env.G.edges)
]
return portrayal
@ -55,7 +56,7 @@ def gridPortrayal(agent):
}
grid = MyNetwork(network_portrayal, 500, 500, library="sigma")
grid = MyNetwork(network_portrayal, 500, 500)
chart = ChartModule(
[{"Label": "Gini", "Color": "Black"}], data_collector_name="datacollector"
)
@ -70,7 +71,6 @@ model_params = {
1,
description="Choose how many agents to include in the model",
),
"network_agents": [{"agent_class": SocialMoneyAgent}],
"height": UserSettableParameter(
"slider",
"height",
@ -89,12 +89,15 @@ model_params = {
1,
description="Grid width",
),
"network_params": {
'generator': graph_generator
},
"agent_class": UserSettableParameter('choice', 'Agent class', value='MoneyAgent',
choices=['MoneyAgent', 'SocialMoneyAgent']),
"generator": graph_generator,
}
canvas_element = CanvasGrid(gridPortrayal, model_params["width"].value, model_params["height"].value, 500, 500)
canvas_element = CanvasGrid(gridPortrayal,
model_params["width"].value,
model_params["height"].value, 500, 500)
server = ModularServer(

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@ -10,7 +10,7 @@ from mesa.batchrunner import BatchRunner
import networkx as nx
from soil import NetworkAgent, Environment
from soil import NetworkAgent, Environment, serialization
def compute_gini(model):
agent_wealths = [agent.wealth for agent in model.agents]
@ -19,15 +19,16 @@ def compute_gini(model):
B = sum( xi * (N-i) for i,xi in enumerate(x) ) / (N*sum(x))
return (1 + (1/N) - 2*B)
class MoneyAgent(MesaAgent):
"""
A MESA agent with fixed initial wealth.
It will only share wealth with neighbors based on grid proximity
"""
def __init__(self, unique_id, model):
def __init__(self, unique_id, model, wealth=1):
super().__init__(unique_id=unique_id, model=model)
self.wealth = 1
self.wealth = wealth
def move(self):
possible_steps = self.model.grid.get_neighborhood(
@ -45,7 +46,7 @@ class MoneyAgent(MesaAgent):
self.wealth -= 1
def step(self):
self.info("Crying wolf", self.pos)
print("Crying wolf", self.pos)
self.move()
if self.wealth > 0:
self.give_money()
@ -58,8 +59,8 @@ class SocialMoneyAgent(NetworkAgent, MoneyAgent):
cellmates = set(self.model.grid.get_cell_list_contents([self.pos]))
friends = set(self.get_neighboring_agents())
self.info("Trying to give money")
self.debug("Cellmates: ", cellmates)
self.debug("Friends: ", friends)
self.info("Cellmates: ", cellmates)
self.info("Friends: ", friends)
nearby_friends = list(cellmates & friends)
@ -68,14 +69,29 @@ class SocialMoneyAgent(NetworkAgent, MoneyAgent):
other.wealth += 1
self.wealth -= 1
def graph_generator(n=5):
G = nx.Graph()
for ix in range(n):
G.add_edge(0, ix)
return G
class MoneyEnv(Environment):
"""A model with some number of agents."""
def __init__(self, width, height, *args, topologies, **kwargs):
def __init__(self, width, height, N, generator=graph_generator,
agent_class=SocialMoneyAgent,
topology=None, **kwargs):
super().__init__(*args, topologies=topologies, **kwargs)
generator = serialization.deserialize(generator)
agent_class = serialization.deserialize(agent_class, globs=globals())
topology = generator(n=N)
super().__init__(topology=topology,
N=N,
**kwargs)
self.grid = MultiGrid(width, height, False)
self.populate_network(agent_class=agent_class)
# Create agents
for agent in self.agents:
x = self.random.randrange(self.grid.width)
@ -87,17 +103,9 @@ class MoneyEnv(Environment):
agent_reporters={"Wealth": "wealth"})
def graph_generator(n=5):
G = nx.Graph()
for ix in range(n):
G.add_edge(0, ix)
return G
if __name__ == '__main__':
G = graph_generator()
fixed_params = {"topology": G,
fixed_params = {"generator": nx.complete_graph,
"width": 10,
"network_agents": [{"agent_class": SocialMoneyAgent,
'weight': 1}],
@ -116,4 +124,3 @@ if __name__ == '__main__':
run_data = batch_run.get_model_vars_dataframe()
run_data.head()
print(run_data.Gini)

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@ -126,7 +126,7 @@ class Patron(FSM, NetworkAgent):
success depend on both agents' openness.
'''
if force or self['openness'] > self.random.random():
self.model.add_edge(self, other_agent)
self.add_edge(self, other_agent)
self.info('Made some friend {}'.format(other_agent))
return True
return False

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@ -1,4 +1,4 @@
from soil.agents import FSM, state, default_state, BaseAgent, NetworkAgent
from soil import FSM, state, default_state, BaseAgent, NetworkAgent, Environment
from soil.time import Delta
from enum import Enum
from collections import Counter
@ -6,7 +6,23 @@ import logging
import math
class RabbitModel(FSM, NetworkAgent):
class RabbitEnv(Environment):
@property
def num_rabbits(self):
return self.count_agents(agent_class=Rabbit)
@property
def num_males(self):
return self.count_agents(agent_class=Male)
@property
def num_females(self):
return self.count_agents(agent_class=Female)
class Rabbit(FSM, NetworkAgent):
sexual_maturity = 30
life_expectancy = 300
@ -35,7 +51,7 @@ class RabbitModel(FSM, NetworkAgent):
self.die()
class Male(RabbitModel):
class Male(Rabbit):
max_females = 5
mating_prob = 0.001
@ -56,8 +72,8 @@ class Male(RabbitModel):
break # Take a break
class Female(RabbitModel):
gestation = 100
class Female(Rabbit):
gestation = 30
@state
def fertile(self):
@ -72,10 +88,10 @@ class Female(RabbitModel):
self.pregnancy = -1
self.set_state(self.pregnant, when=self.now)
self.number_of_babies = int(8+4*self.random.random())
self.debug('I am pregnant')
@state
def pregnant(self):
self.debug('I am pregnant')
self.age += 1
self.pregnancy += 1
@ -88,7 +104,6 @@ class Female(RabbitModel):
state = {}
agent_class = self.random.choice([Male, Female])
child = self.model.add_node(agent_class=agent_class,
topology=self.topology,
**state)
child.add_edge(self)
try:
@ -113,18 +128,23 @@ class RandomAccident(BaseAgent):
level = logging.INFO
def step(self):
rabbits_alive = self.model.topology.number_of_nodes()
rabbits_alive = self.model.G.number_of_nodes()
if not rabbits_alive:
return self.die()
prob_death = self.model.get('prob_death', 1e-100)*math.floor(math.log10(max(1, rabbits_alive)))
self.debug('Killing some rabbits with prob={}!'.format(prob_death))
for i in self.iter_agents(agent_class=RabbitModel):
if i.state.id == i.dead.id:
for i in self.iter_agents(agent_class=Rabbit):
if i.state_id == i.dead.id:
continue
if self.prob(prob_death):
self.info('I killed a rabbit: {}'.format(i.id))
rabbits_alive -= 1
i.set_state(i.dead)
self.debug('Rabbits alive: {}'.format(rabbits_alive))
if __name__ == '__main__':
from soil import easy
sim = easy('rabbits.yml')
sim.run()

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@ -7,21 +7,18 @@ description: null
group: null
interval: 1.0
max_time: 100
model_class: soil.environment.Environment
model_class: rabbit_agents.RabbitEnv
model_params:
agents:
topology: default
agent_class: rabbit_agents.RabbitModel
topology: true
distribution:
- agent_class: rabbit_agents.Male
topology: default
weight: 1
- agent_class: rabbit_agents.Female
topology: default
weight: 1
fixed:
- agent_class: rabbit_agents.RandomAccident
topology: null
topology: false
hidden: true
state:
group: environment
@ -29,13 +26,17 @@ model_params:
group: network
mating_prob: 0.1
prob_death: 0.001
topologies:
default:
topology:
directed: true
links: []
nodes:
- id: 1
- id: 0
topology:
fixed:
directed: true
links: []
nodes:
- id: 1
- id: 0
model_reporters:
num_males: 'num_males'
num_females: 'num_females'
num_rabbits: |
py:lambda env: env.num_males + env.num_females
extra:
visualization_params: {}

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@ -10,18 +10,16 @@ max_time: 100
model_class: soil.environment.Environment
model_params:
agents:
topology: default
topology: true
agent_class: rabbit_agents.RabbitModel
distribution:
- agent_class: rabbit_agents.Male
topology: default
weight: 1
- agent_class: rabbit_agents.Female
topology: default
weight: 1
fixed:
- agent_class: rabbit_agents.RandomAccident
topology: null
topology: false
hidden: true
state:
group: environment
@ -29,13 +27,12 @@ model_params:
group: network
mating_prob: 0.1
prob_death: 0.001
topologies:
default:
topology:
directed: true
links: []
nodes:
- id: 1
- id: 0
topology:
fixed:
directed: true
links: []
nodes:
- id: 1
- id: 0
extra:
visualization_params: {}

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@ -4,7 +4,6 @@ Example of a fully programmatic simulation, without definition files.
'''
from soil import Simulation, agents
from soil.time import Delta
import logging
@ -40,5 +39,4 @@ s = Simulation(name='Programmatic',
dry_run=True)
logging.basicConfig(level=logging.INFO)
envs = s.run()

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@ -5,6 +5,6 @@ pyyaml>=5.1
pandas>=1
SALib>=1.3
Jinja2
Mesa>=1
Mesa>=1.1
pydantic>=1.9
sqlalchemy>=1.4

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@ -53,6 +53,6 @@ setup(
include_package_data=True,
entry_points={
'console_scripts':
['soil = soil.__init__:main',
['soil = soil.__main__:main',
'soil-web = soil.web.__init__:main']
})

View File

@ -21,93 +21,165 @@ from . import serialization
from .utils import logger
from .time import *
def main(cfg='simulation.yml', **kwargs):
def main(
cfg="simulation.yml",
exporters=None,
parallel=None,
output="soil_output",
*,
do_run=False,
debug=False,
**kwargs,
):
import argparse
from . import simulation
logger.info('Running SOIL version: {}'.format(__version__))
logger.info("Running SOIL version: {}".format(__version__))
parser = argparse.ArgumentParser(description='Run a SOIL simulation')
parser.add_argument('file', type=str,
nargs="?",
default=cfg,
help='Configuration file for the simulation (e.g., YAML or JSON)')
parser.add_argument('--version', action='store_true',
help='Show version info and exit')
parser.add_argument('--module', '-m', type=str,
help='file containing the code of any custom agents.')
parser.add_argument('--dry-run', '--dry', action='store_true',
help='Do not store the results of the simulation to disk, show in terminal instead.')
parser.add_argument('--pdb', action='store_true',
help='Use a pdb console in case of exception.')
parser.add_argument('--debug', action='store_true',
help='Run a customized version of a pdb console to debug a simulation.')
parser.add_argument('--graph', '-g', action='store_true',
help='Dump each trial\'s network topology as a GEXF graph. Defaults to false.')
parser.add_argument('--csv', action='store_true',
help='Dump all data collected in CSV format. Defaults to false.')
parser.add_argument('--level', type=str,
help='Logging level')
parser.add_argument('--output', '-o', type=str, default="soil_output",
help='folder to write results to. It defaults to the current directory.')
parser.add_argument('--synchronous', action='store_true',
help='Run trials serially and synchronously instead of in parallel. Defaults to false.')
parser.add_argument('-e', '--exporter', action='append',
help='Export environment and/or simulations using this exporter')
parser.add_argument('--only-convert', '--convert', action='store_true',
help='Do not run the simulation, only convert the configuration file(s) and output them.')
parser = argparse.ArgumentParser(description="Run a SOIL simulation")
parser.add_argument(
"file",
type=str,
nargs="?",
default=cfg,
help="Configuration file for the simulation (e.g., YAML or JSON)",
)
parser.add_argument(
"--version", action="store_true", help="Show version info and exit"
)
parser.add_argument(
"--module",
"-m",
type=str,
help="file containing the code of any custom agents.",
)
parser.add_argument(
"--dry-run",
"--dry",
action="store_true",
help="Do not store the results of the simulation to disk, show in terminal instead.",
)
parser.add_argument(
"--pdb", action="store_true", help="Use a pdb console in case of exception."
)
parser.add_argument(
"--debug",
action="store_true",
help="Run a customized version of a pdb console to debug a simulation.",
)
parser.add_argument(
"--graph",
"-g",
action="store_true",
help="Dump each trial's network topology as a GEXF graph. Defaults to false.",
)
parser.add_argument(
"--csv",
action="store_true",
help="Dump all data collected in CSV format. Defaults to false.",
)
parser.add_argument("--level", type=str, help="Logging level")
parser.add_argument(
"--output",
"-o",
type=str,
default=output or "soil_output",
help="folder to write results to. It defaults to the current directory.",
)
if parallel is None:
parser.add_argument(
"--synchronous",
action="store_true",
help="Run trials serially and synchronously instead of in parallel. Defaults to false.",
)
parser.add_argument(
"-e",
"--exporter",
action="append",
default=[],
help="Export environment and/or simulations using this exporter",
)
parser.add_argument("--set",
metavar="KEY=VALUE",
action='append',
help="Set a number of parameters that will be passed to the simulation."
"(do not put spaces before or after the = sign). "
"If a value contains spaces, you should define "
"it with double quotes: "
'foo="this is a sentence". Note that '
"values are always treated as strings.")
parser.add_argument(
"--only-convert",
"--convert",
action="store_true",
help="Do not run the simulation, only convert the configuration file(s) and output them.",
)
parser.add_argument(
"--set",
metavar="KEY=VALUE",
action="append",
help="Set a number of parameters that will be passed to the simulation."
"(do not put spaces before or after the = sign). "
"If a value contains spaces, you should define "
"it with double quotes: "
'foo="this is a sentence". Note that '
"values are always treated as strings.",
)
args = parser.parse_args()
logger.setLevel(getattr(logging, (args.level or 'INFO').upper()))
logger.setLevel(getattr(logging, (args.level or "INFO").upper()))
if args.version:
return
if parallel is None:
parallel = not args.synchronous
exporters = exporters or [
"default",
]
for exp in args.exporter:
if exp not in exporters:
exporters.append(exp)
if args.csv:
exporters.append("csv")
if args.graph:
exporters.append("gexf")
if os.getcwd() not in sys.path:
sys.path.append(os.getcwd())
if args.module:
importlib.import_module(args.module)
if output is None:
output = args.output
logger.info('Loading config file: {}'.format(args.file))
logger.info("Loading config file: {}".format(args.file))
if args.pdb or args.debug:
debug = debug or args.debug
if args.pdb or debug:
args.synchronous = True
if args.debug:
os.environ['SOIL_DEBUG'] = 'true'
res = []
try:
exporters = list(args.exporter or ['default', ])
if args.csv:
exporters.append('csv')
if args.graph:
exporters.append('gexf')
exp_params = {}
if args.dry_run:
exp_params['copy_to'] = sys.stdout
if not os.path.exists(args.file):
logger.error('Please, input a valid file')
logger.error("Please, input a valid file")
return
for sim in simulation.iter_from_config(args.file):
for sim in simulation.iter_from_config(
args.file,
dry_run=args.dry_run,
exporters=exporters,
parallel=parallel,
outdir=output,
exporter_params=exp_params,
**kwargs,
):
if args.set:
for s in args.set:
k, v = s.split('=', 1)[:2]
k, v = s.split("=", 1)[:2]
v = eval(v)
tail, *head = k.rsplit('.', 1)[::-1]
tail, *head = k.rsplit(".", 1)[::-1]
target = sim
if head:
for part in head[0].split('.'):
for part in head[0].split("."):
try:
target = getattr(target, part)
except AttributeError:
@ -117,30 +189,34 @@ def main(cfg='simulation.yml', **kwargs):
except AttributeError:
target[tail] = v
if args.only_convert:
print(sim.to_yaml())
continue
sim.run_simulation(dry_run=args.dry_run,
exporters=exporters,
parallel=(not args.synchronous),
outdir=args.output,
exporter_params=exp_params,
**kwargs)
if args.only_convert:
print(sim.to_yaml())
continue
if do_run:
res.append(sim.run())
else:
print("not running")
res.append(sim)
except Exception as ex:
if args.pdb:
from .debugging import post_mortem
print(traceback.format_exc())
post_mortem()
else:
raise
if debug:
from .debugging import set_trace
def easy(cfg, debug=False):
sim = simulation.from_config(cfg)
if debug or os.environ.get('SOIL_DEBUG'):
from .debugging import setup
setup(sys._getframe().f_back)
return sim
if __name__ == '__main__':
main()
os.environ["SOIL_DEBUG"] = "true"
set_trace()
return res
def easy(cfg, debug=False, **kwargs):
return main(cfg, **kwargs)[0]
if __name__ == "__main__":
main(do_run=True)

View File

@ -1,4 +1,9 @@
from . import main
from . import main as init_main
if __name__ == '__main__':
main()
def main():
init_main(do_run=True)
if __name__ == "__main__":
init_main(do_run=True)

View File

@ -7,6 +7,7 @@ class BassModel(FSM):
innovation_prob
imitation_prob
"""
sentimentCorrelation = 0
def step(self):
@ -21,7 +22,7 @@ class BassModel(FSM):
else:
aware_neighbors = self.get_neighboring_agents(state_id=self.aware.id)
num_neighbors_aware = len(aware_neighbors)
if self.prob((self['imitation_prob']*num_neighbors_aware)):
if self.prob((self["imitation_prob"] * num_neighbors_aware)):
self.sentimentCorrelation = 1
return self.aware

View File

@ -6,42 +6,54 @@ class BigMarketModel(FSM):
Settings:
Names:
enterprises [Array]
tweet_probability_enterprises [Array]
Users:
tweet_probability_users
tweet_relevant_probability
tweet_probability_about [Array]
sentiment_about [Array]
"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.enterprises = self.env.environment_params['enterprises']
self.enterprises = self.env.environment_params["enterprises"]
self.type = ""
if self.id < len(self.enterprises): # Enterprises
self.set_state(self.enterprise.id)
self.type = "Enterprise"
self.tweet_probability = environment.environment_params['tweet_probability_enterprises'][self.id]
self.tweet_probability = environment.environment_params[
"tweet_probability_enterprises"
][self.id]
else: # normal users
self.type = "User"
self.set_state(self.user.id)
self.tweet_probability = environment.environment_params['tweet_probability_users']
self.tweet_relevant_probability = environment.environment_params['tweet_relevant_probability']
self.tweet_probability_about = environment.environment_params['tweet_probability_about'] # List
self.sentiment_about = environment.environment_params['sentiment_about'] # List
self.tweet_probability = environment.environment_params[
"tweet_probability_users"
]
self.tweet_relevant_probability = environment.environment_params[
"tweet_relevant_probability"
]
self.tweet_probability_about = environment.environment_params[
"tweet_probability_about"
] # List
self.sentiment_about = environment.environment_params[
"sentiment_about"
] # List
@state
def enterprise(self):
if self.random.random() < self.tweet_probability: # Tweets
aware_neighbors = self.get_neighboring_agents(state_id=self.number_of_enterprises) # Nodes neighbour users
aware_neighbors = self.get_neighboring_agents(
state_id=self.number_of_enterprises
) # Nodes neighbour users
for x in aware_neighbors:
if self.random.uniform(0,10) < 5:
if self.random.uniform(0, 10) < 5:
x.sentiment_about[self.id] += 0.1 # Increments for enterprise
else:
x.sentiment_about[self.id] -= 0.1 # Decrements for enterprise
@ -49,15 +61,19 @@ class BigMarketModel(FSM):
# Establecemos limites
if x.sentiment_about[self.id] > 1:
x.sentiment_about[self.id] = 1
if x.sentiment_about[self.id]< -1:
if x.sentiment_about[self.id] < -1:
x.sentiment_about[self.id] = -1
x.attrs['sentiment_enterprise_%s'% self.enterprises[self.id]] = x.sentiment_about[self.id]
x.attrs[
"sentiment_enterprise_%s" % self.enterprises[self.id]
] = x.sentiment_about[self.id]
@state
def user(self):
if self.random.random() < self.tweet_probability: # Tweets
if self.random.random() < self.tweet_relevant_probability: # Tweets something relevant
if (
self.random.random() < self.tweet_relevant_probability
): # Tweets something relevant
# Tweet probability per enterprise
for i in range(len(self.enterprises)):
random_num = self.random.random()
@ -65,23 +81,29 @@ class BigMarketModel(FSM):
# The condition is fulfilled, sentiments are evaluated towards that enterprise
if self.sentiment_about[i] < 0:
# NEGATIVO
self.userTweets("negative",i)
self.userTweets("negative", i)
elif self.sentiment_about[i] == 0:
# NEUTRO
pass
else:
# POSITIVO
self.userTweets("positive",i)
for i in range(len(self.enterprises)): # So that it never is set to 0 if there are not changes (logs)
self.attrs['sentiment_enterprise_%s'% self.enterprises[i]] = self.sentiment_about[i]
self.userTweets("positive", i)
for i in range(
len(self.enterprises)
): # So that it never is set to 0 if there are not changes (logs)
self.attrs[
"sentiment_enterprise_%s" % self.enterprises[i]
] = self.sentiment_about[i]
def userTweets(self, sentiment,enterprise):
aware_neighbors = self.get_neighboring_agents(state_id=self.number_of_enterprises) # Nodes neighbours users
def userTweets(self, sentiment, enterprise):
aware_neighbors = self.get_neighboring_agents(
state_id=self.number_of_enterprises
) # Nodes neighbours users
for x in aware_neighbors:
if sentiment == "positive":
x.sentiment_about[enterprise] +=0.003
x.sentiment_about[enterprise] += 0.003
elif sentiment == "negative":
x.sentiment_about[enterprise] -=0.003
x.sentiment_about[enterprise] -= 0.003
else:
pass
@ -91,4 +113,6 @@ class BigMarketModel(FSM):
if x.sentiment_about[enterprise] < -1:
x.sentiment_about[enterprise] = -1
x.attrs['sentiment_enterprise_%s'% self.enterprises[enterprise]] = x.sentiment_about[enterprise]
x.attrs[
"sentiment_enterprise_%s" % self.enterprises[enterprise]
] = x.sentiment_about[enterprise]

View File

@ -15,9 +15,9 @@ class CounterModel(NetworkAgent):
# Outside effects
total = len(list(self.model.schedule._agents))
neighbors = len(list(self.get_neighboring_agents()))
self['times'] = self.get('times', 0) + 1
self['neighbors'] = neighbors
self['total'] = total
self["times"] = self.get("times", 0) + 1
self["neighbors"] = neighbors
self["total"] = total
class AggregatedCounter(NetworkAgent):
@ -32,9 +32,9 @@ class AggregatedCounter(NetworkAgent):
def step(self):
# Outside effects
self['times'] += 1
self["times"] += 1
neighbors = len(list(self.get_neighboring_agents()))
self['neighbors'] += neighbors
self["neighbors"] += neighbors
total = len(list(self.model.schedule.agents))
self['total'] += total
self.debug('Running for step: {}. Total: {}'.format(self.now, total))
self["total"] += total
self.debug("Running for step: {}. Total: {}".format(self.now, total))

View File

@ -2,20 +2,20 @@ from scipy.spatial import cKDTree as KDTree
import networkx as nx
from . import NetworkAgent, as_node
class Geo(NetworkAgent):
'''In this type of network, nodes have a "pos" attribute.'''
"""In this type of network, nodes have a "pos" attribute."""
def geo_search(self, radius, node=None, center=False, **kwargs):
'''Get a list of nodes whose coordinates are closer than *radius* to *node*.'''
"""Get a list of nodes whose coordinates are closer than *radius* to *node*."""
node = as_node(node if node is not None else self)
G = self.subgraph(**kwargs)
pos = nx.get_node_attributes(G, 'pos')
pos = nx.get_node_attributes(G, "pos")
if not pos:
return []
nodes, coords = list(zip(*pos.items()))
kdtree = KDTree(coords) # Cannot provide generator.
indices = kdtree.query_ball_point(pos[node], radius)
return [nodes[i] for i in indices if center or (nodes[i] != node)]

View File

@ -11,10 +11,10 @@ class IndependentCascadeModel(BaseAgent):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.innovation_prob = self.env.environment_params['innovation_prob']
self.imitation_prob = self.env.environment_params['imitation_prob']
self.state['time_awareness'] = 0
self.state['sentimentCorrelation'] = 0
self.innovation_prob = self.env.environment_params["innovation_prob"]
self.imitation_prob = self.env.environment_params["imitation_prob"]
self.state["time_awareness"] = 0
self.state["sentimentCorrelation"] = 0
def step(self):
self.behaviour()
@ -23,25 +23,27 @@ class IndependentCascadeModel(BaseAgent):
aware_neighbors_1_time_step = []
# Outside effects
if self.prob(self.innovation_prob):
if self.state['id'] == 0:
self.state['id'] = 1
self.state['sentimentCorrelation'] = 1
self.state['time_awareness'] = self.env.now # To know when they have been infected
if self.state["id"] == 0:
self.state["id"] = 1
self.state["sentimentCorrelation"] = 1
self.state[
"time_awareness"
] = self.env.now # To know when they have been infected
else:
pass
return
# Imitation effects
if self.state['id'] == 0:
if self.state["id"] == 0:
aware_neighbors = self.get_neighboring_agents(state_id=1)
for x in aware_neighbors:
if x.state['time_awareness'] == (self.env.now-1):
if x.state["time_awareness"] == (self.env.now - 1):
aware_neighbors_1_time_step.append(x)
num_neighbors_aware = len(aware_neighbors_1_time_step)
if self.prob(self.imitation_prob*num_neighbors_aware):
self.state['id'] = 1
self.state['sentimentCorrelation'] = 1
if self.prob(self.imitation_prob * num_neighbors_aware):
self.state["id"] = 1
self.state["sentimentCorrelation"] = 1
else:
pass

View File

@ -23,36 +23,49 @@ class SpreadModelM2(BaseAgent):
def __init__(self, model=None, unique_id=0, state=()):
super().__init__(model=environment, unique_id=unique_id, state=state)
# Use a single generator with the same seed as `self.random`
random = np.random.default_rng(seed=self._seed)
self.prob_neutral_making_denier = random.normal(environment.environment_params['prob_neutral_making_denier'],
environment.environment_params['standard_variance'])
self.prob_neutral_making_denier = random.normal(
environment.environment_params["prob_neutral_making_denier"],
environment.environment_params["standard_variance"],
)
self.prob_infect = random.normal(environment.environment_params['prob_infect'],
environment.environment_params['standard_variance'])
self.prob_infect = random.normal(
environment.environment_params["prob_infect"],
environment.environment_params["standard_variance"],
)
self.prob_cured_healing_infected = random.normal(environment.environment_params['prob_cured_healing_infected'],
environment.environment_params['standard_variance'])
self.prob_cured_vaccinate_neutral = random.normal(environment.environment_params['prob_cured_vaccinate_neutral'],
environment.environment_params['standard_variance'])
self.prob_cured_healing_infected = random.normal(
environment.environment_params["prob_cured_healing_infected"],
environment.environment_params["standard_variance"],
)
self.prob_cured_vaccinate_neutral = random.normal(
environment.environment_params["prob_cured_vaccinate_neutral"],
environment.environment_params["standard_variance"],
)
self.prob_vaccinated_healing_infected = random.normal(environment.environment_params['prob_vaccinated_healing_infected'],
environment.environment_params['standard_variance'])
self.prob_vaccinated_vaccinate_neutral = random.normal(environment.environment_params['prob_vaccinated_vaccinate_neutral'],
environment.environment_params['standard_variance'])
self.prob_generate_anti_rumor = random.normal(environment.environment_params['prob_generate_anti_rumor'],
environment.environment_params['standard_variance'])
self.prob_vaccinated_healing_infected = random.normal(
environment.environment_params["prob_vaccinated_healing_infected"],
environment.environment_params["standard_variance"],
)
self.prob_vaccinated_vaccinate_neutral = random.normal(
environment.environment_params["prob_vaccinated_vaccinate_neutral"],
environment.environment_params["standard_variance"],
)
self.prob_generate_anti_rumor = random.normal(
environment.environment_params["prob_generate_anti_rumor"],
environment.environment_params["standard_variance"],
)
def step(self):
if self.state['id'] == 0: # Neutral
if self.state["id"] == 0: # Neutral
self.neutral_behaviour()
elif self.state['id'] == 1: # Infected
elif self.state["id"] == 1: # Infected
self.infected_behaviour()
elif self.state['id'] == 2: # Cured
elif self.state["id"] == 2: # Cured
self.cured_behaviour()
elif self.state['id'] == 3: # Vaccinated
elif self.state["id"] == 3: # Vaccinated
self.vaccinated_behaviour()
def neutral_behaviour(self):
@ -61,7 +74,7 @@ class SpreadModelM2(BaseAgent):
infected_neighbors = self.get_neighboring_agents(state_id=1)
if len(infected_neighbors) > 0:
if self.prob(self.prob_neutral_making_denier):
self.state['id'] = 3 # Vaccinated making denier
self.state["id"] = 3 # Vaccinated making denier
def infected_behaviour(self):
@ -69,7 +82,7 @@ class SpreadModelM2(BaseAgent):
neutral_neighbors = self.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors:
if self.prob(self.prob_infect):
neighbor.state['id'] = 1 # Infected
neighbor.state["id"] = 1 # Infected
def cured_behaviour(self):
@ -77,13 +90,13 @@ class SpreadModelM2(BaseAgent):
neutral_neighbors = self.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors:
if self.prob(self.prob_cured_vaccinate_neutral):
neighbor.state['id'] = 3 # Vaccinated
neighbor.state["id"] = 3 # Vaccinated
# Cure
infected_neighbors = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors:
if self.prob(self.prob_cured_healing_infected):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
def vaccinated_behaviour(self):
@ -91,19 +104,19 @@ class SpreadModelM2(BaseAgent):
infected_neighbors = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors:
if self.prob(self.prob_cured_healing_infected):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
# Vaccinate
neutral_neighbors = self.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors:
if self.prob(self.prob_cured_vaccinate_neutral):
neighbor.state['id'] = 3 # Vaccinated
neighbor.state["id"] = 3 # Vaccinated
# Generate anti-rumor
infected_neighbors_2 = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors_2:
if self.prob(self.prob_generate_anti_rumor):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
class ControlModelM2(BaseAgent):
@ -112,63 +125,76 @@ class ControlModelM2(BaseAgent):
prob_neutral_making_denier
prob_infect
prob_cured_healing_infected
prob_cured_vaccinate_neutral
prob_vaccinated_healing_infected
prob_vaccinated_vaccinate_neutral
prob_generate_anti_rumor
"""
def __init__(self, model=None, unique_id=0, state=()):
super().__init__(model=environment, unique_id=unique_id, state=state)
self.prob_neutral_making_denier = np.random.normal(environment.environment_params['prob_neutral_making_denier'],
environment.environment_params['standard_variance'])
self.prob_neutral_making_denier = np.random.normal(
environment.environment_params["prob_neutral_making_denier"],
environment.environment_params["standard_variance"],
)
self.prob_infect = np.random.normal(environment.environment_params['prob_infect'],
environment.environment_params['standard_variance'])
self.prob_infect = np.random.normal(
environment.environment_params["prob_infect"],
environment.environment_params["standard_variance"],
)
self.prob_cured_healing_infected = np.random.normal(environment.environment_params['prob_cured_healing_infected'],
environment.environment_params['standard_variance'])
self.prob_cured_vaccinate_neutral = np.random.normal(environment.environment_params['prob_cured_vaccinate_neutral'],
environment.environment_params['standard_variance'])
self.prob_cured_healing_infected = np.random.normal(
environment.environment_params["prob_cured_healing_infected"],
environment.environment_params["standard_variance"],
)
self.prob_cured_vaccinate_neutral = np.random.normal(
environment.environment_params["prob_cured_vaccinate_neutral"],
environment.environment_params["standard_variance"],
)
self.prob_vaccinated_healing_infected = np.random.normal(environment.environment_params['prob_vaccinated_healing_infected'],
environment.environment_params['standard_variance'])
self.prob_vaccinated_vaccinate_neutral = np.random.normal(environment.environment_params['prob_vaccinated_vaccinate_neutral'],
environment.environment_params['standard_variance'])
self.prob_generate_anti_rumor = np.random.normal(environment.environment_params['prob_generate_anti_rumor'],
environment.environment_params['standard_variance'])
self.prob_vaccinated_healing_infected = np.random.normal(
environment.environment_params["prob_vaccinated_healing_infected"],
environment.environment_params["standard_variance"],
)
self.prob_vaccinated_vaccinate_neutral = np.random.normal(
environment.environment_params["prob_vaccinated_vaccinate_neutral"],
environment.environment_params["standard_variance"],
)
self.prob_generate_anti_rumor = np.random.normal(
environment.environment_params["prob_generate_anti_rumor"],
environment.environment_params["standard_variance"],
)
def step(self):
if self.state['id'] == 0: # Neutral
if self.state["id"] == 0: # Neutral
self.neutral_behaviour()
elif self.state['id'] == 1: # Infected
elif self.state["id"] == 1: # Infected
self.infected_behaviour()
elif self.state['id'] == 2: # Cured
elif self.state["id"] == 2: # Cured
self.cured_behaviour()
elif self.state['id'] == 3: # Vaccinated
elif self.state["id"] == 3: # Vaccinated
self.vaccinated_behaviour()
elif self.state['id'] == 4: # Beacon-off
elif self.state["id"] == 4: # Beacon-off
self.beacon_off_behaviour()
elif self.state['id'] == 5: # Beacon-on
elif self.state["id"] == 5: # Beacon-on
self.beacon_on_behaviour()
def neutral_behaviour(self):
self.state['visible'] = False
self.state["visible"] = False
# Infected
infected_neighbors = self.get_neighboring_agents(state_id=1)
if len(infected_neighbors) > 0:
if self.random(self.prob_neutral_making_denier):
self.state['id'] = 3 # Vaccinated making denier
self.state["id"] = 3 # Vaccinated making denier
def infected_behaviour(self):
@ -176,69 +202,69 @@ class ControlModelM2(BaseAgent):
neutral_neighbors = self.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors:
if self.prob(self.prob_infect):
neighbor.state['id'] = 1 # Infected
self.state['visible'] = False
neighbor.state["id"] = 1 # Infected
self.state["visible"] = False
def cured_behaviour(self):
self.state['visible'] = True
self.state["visible"] = True
# Vaccinate
neutral_neighbors = self.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors:
if self.prob(self.prob_cured_vaccinate_neutral):
neighbor.state['id'] = 3 # Vaccinated
neighbor.state["id"] = 3 # Vaccinated
# Cure
infected_neighbors = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors:
if self.prob(self.prob_cured_healing_infected):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
def vaccinated_behaviour(self):
self.state['visible'] = True
self.state["visible"] = True
# Cure
infected_neighbors = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors:
if self.prob(self.prob_cured_healing_infected):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
# Vaccinate
neutral_neighbors = self.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors:
if self.prob(self.prob_cured_vaccinate_neutral):
neighbor.state['id'] = 3 # Vaccinated
neighbor.state["id"] = 3 # Vaccinated
# Generate anti-rumor
infected_neighbors_2 = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors_2:
if self.prob(self.prob_generate_anti_rumor):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
def beacon_off_behaviour(self):
self.state['visible'] = False
self.state["visible"] = False
infected_neighbors = self.get_neighboring_agents(state_id=1)
if len(infected_neighbors) > 0:
self.state['id'] == 5 # Beacon on
self.state["id"] == 5 # Beacon on
def beacon_on_behaviour(self):
self.state['visible'] = False
self.state["visible"] = False
# Cure (M2 feature added)
infected_neighbors = self.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors:
if self.prob(self.prob_generate_anti_rumor):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
neutral_neighbors_infected = neighbor.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors_infected:
if self.prob(self.prob_generate_anti_rumor):
neighbor.state['id'] = 3 # Vaccinated
neighbor.state["id"] = 3 # Vaccinated
infected_neighbors_infected = neighbor.get_neighboring_agents(state_id=1)
for neighbor in infected_neighbors_infected:
if self.prob(self.prob_generate_anti_rumor):
neighbor.state['id'] = 2 # Cured
neighbor.state["id"] = 2 # Cured
# Vaccinate
neutral_neighbors = self.get_neighboring_agents(state_id=0)
for neighbor in neutral_neighbors:
if self.prob(self.prob_cured_vaccinate_neutral):
neighbor.state['id'] = 3 # Vaccinated
neighbor.state["id"] = 3 # Vaccinated

View File

@ -6,25 +6,25 @@ class SISaModel(FSM):
"""
Settings:
neutral_discontent_spon_prob
neutral_discontent_infected_prob
neutral_content_spon_prob
neutral_content_infected_prob
discontent_neutral
discontent_content
variance_d_c
content_discontent
variance_c_d
content_neutral
standard_variance
"""
@ -33,24 +33,32 @@ class SISaModel(FSM):
random = np.random.default_rng(seed=self._seed)
self.neutral_discontent_spon_prob = random.normal(self.env['neutral_discontent_spon_prob'],
self.env['standard_variance'])
self.neutral_discontent_infected_prob = random.normal(self.env['neutral_discontent_infected_prob'],
self.env['standard_variance'])
self.neutral_content_spon_prob = random.normal(self.env['neutral_content_spon_prob'],
self.env['standard_variance'])
self.neutral_content_infected_prob = random.normal(self.env['neutral_content_infected_prob'],
self.env['standard_variance'])
self.neutral_discontent_spon_prob = random.normal(
self.env["neutral_discontent_spon_prob"], self.env["standard_variance"]
)
self.neutral_discontent_infected_prob = random.normal(
self.env["neutral_discontent_infected_prob"], self.env["standard_variance"]
)
self.neutral_content_spon_prob = random.normal(
self.env["neutral_content_spon_prob"], self.env["standard_variance"]
)
self.neutral_content_infected_prob = random.normal(
self.env["neutral_content_infected_prob"], self.env["standard_variance"]
)
self.discontent_neutral = random.normal(self.env['discontent_neutral'],
self.env['standard_variance'])
self.discontent_content = random.normal(self.env['discontent_content'],
self.env['variance_d_c'])
self.discontent_neutral = random.normal(
self.env["discontent_neutral"], self.env["standard_variance"]
)
self.discontent_content = random.normal(
self.env["discontent_content"], self.env["variance_d_c"]
)
self.content_discontent = random.normal(self.env['content_discontent'],
self.env['variance_c_d'])
self.content_neutral = random.normal(self.env['content_neutral'],
self.env['standard_variance'])
self.content_discontent = random.normal(
self.env["content_discontent"], self.env["variance_c_d"]
)
self.content_neutral = random.normal(
self.env["content_neutral"], self.env["standard_variance"]
)
@state
def neutral(self):
@ -88,7 +96,9 @@ class SISaModel(FSM):
return self.neutral
# Superinfected
discontent_neighbors = self.count_neighboring_agents(state_id=self.discontent.id)
discontent_neighbors = self.count_neighboring_agents(
state_id=self.discontent.id
)
if self.prob(scontent_neighbors * self.content_discontent):
self.discontent
return self.content

View File

@ -5,27 +5,31 @@ class SentimentCorrelationModel(BaseAgent):
"""
Settings:
outside_effects_prob
anger_prob
joy_prob
sadness_prob
disgust_prob
"""
def __init__(self, environment, unique_id=0, state=()):
super().__init__(model=environment, unique_id=unique_id, state=state)
self.outside_effects_prob = environment.environment_params['outside_effects_prob']
self.anger_prob = environment.environment_params['anger_prob']
self.joy_prob = environment.environment_params['joy_prob']
self.sadness_prob = environment.environment_params['sadness_prob']
self.disgust_prob = environment.environment_params['disgust_prob']
self.state['time_awareness'] = []
self.outside_effects_prob = environment.environment_params[
"outside_effects_prob"
]
self.anger_prob = environment.environment_params["anger_prob"]
self.joy_prob = environment.environment_params["joy_prob"]
self.sadness_prob = environment.environment_params["sadness_prob"]
self.disgust_prob = environment.environment_params["disgust_prob"]
self.state["time_awareness"] = []
for i in range(4): # In this model we have 4 sentiments
self.state['time_awareness'].append(0) # 0-> Anger, 1-> joy, 2->sadness, 3 -> disgust
self.state['sentimentCorrelation'] = 0
self.state["time_awareness"].append(
0
) # 0-> Anger, 1-> joy, 2->sadness, 3 -> disgust
self.state["sentimentCorrelation"] = 0
def step(self):
self.behaviour()
@ -39,63 +43,73 @@ class SentimentCorrelationModel(BaseAgent):
angry_neighbors = self.get_neighboring_agents(state_id=1)
for x in angry_neighbors:
if x.state['time_awareness'][0] > (self.env.now-500):
if x.state["time_awareness"][0] > (self.env.now - 500):
angry_neighbors_1_time_step.append(x)
num_neighbors_angry = len(angry_neighbors_1_time_step)
joyful_neighbors = self.get_neighboring_agents(state_id=2)
for x in joyful_neighbors:
if x.state['time_awareness'][1] > (self.env.now-500):
if x.state["time_awareness"][1] > (self.env.now - 500):
joyful_neighbors_1_time_step.append(x)
num_neighbors_joyful = len(joyful_neighbors_1_time_step)
sad_neighbors = self.get_neighboring_agents(state_id=3)
for x in sad_neighbors:
if x.state['time_awareness'][2] > (self.env.now-500):
if x.state["time_awareness"][2] > (self.env.now - 500):
sad_neighbors_1_time_step.append(x)
num_neighbors_sad = len(sad_neighbors_1_time_step)
disgusted_neighbors = self.get_neighboring_agents(state_id=4)
for x in disgusted_neighbors:
if x.state['time_awareness'][3] > (self.env.now-500):
if x.state["time_awareness"][3] > (self.env.now - 500):
disgusted_neighbors_1_time_step.append(x)
num_neighbors_disgusted = len(disgusted_neighbors_1_time_step)
anger_prob = self.anger_prob+(len(angry_neighbors_1_time_step)*self.anger_prob)
joy_prob = self.joy_prob+(len(joyful_neighbors_1_time_step)*self.joy_prob)
sadness_prob = self.sadness_prob+(len(sad_neighbors_1_time_step)*self.sadness_prob)
disgust_prob = self.disgust_prob+(len(disgusted_neighbors_1_time_step)*self.disgust_prob)
anger_prob = self.anger_prob + (
len(angry_neighbors_1_time_step) * self.anger_prob
)
joy_prob = self.joy_prob + (len(joyful_neighbors_1_time_step) * self.joy_prob)
sadness_prob = self.sadness_prob + (
len(sad_neighbors_1_time_step) * self.sadness_prob
)
disgust_prob = self.disgust_prob + (
len(disgusted_neighbors_1_time_step) * self.disgust_prob
)
outside_effects_prob = self.outside_effects_prob
num = self.random.random()
if num<outside_effects_prob:
self.state['id'] = self.random.randint(1, 4)
if num < outside_effects_prob:
self.state["id"] = self.random.randint(1, 4)
self.state['sentimentCorrelation'] = self.state['id'] # It is stored when it has been infected for the dynamic network
self.state['time_awareness'][self.state['id']-1] = self.env.now
self.state['sentiment'] = self.state['id']
self.state["sentimentCorrelation"] = self.state[
"id"
] # It is stored when it has been infected for the dynamic network
self.state["time_awareness"][self.state["id"] - 1] = self.env.now
self.state["sentiment"] = self.state["id"]
if num < anger_prob:
if(num<anger_prob):
self.state["id"] = 1
self.state["sentimentCorrelation"] = 1
self.state["time_awareness"][self.state["id"] - 1] = self.env.now
elif num < joy_prob + anger_prob and num > anger_prob:
self.state['id'] = 1
self.state['sentimentCorrelation'] = 1
self.state['time_awareness'][self.state['id']-1] = self.env.now
elif (num<joy_prob+anger_prob and num>anger_prob):
self.state["id"] = 2
self.state["sentimentCorrelation"] = 2
self.state["time_awareness"][self.state["id"] - 1] = self.env.now
elif num < sadness_prob + anger_prob + joy_prob and num > joy_prob + anger_prob:
self.state['id'] = 2
self.state['sentimentCorrelation'] = 2
self.state['time_awareness'][self.state['id']-1] = self.env.now
elif (num<sadness_prob+anger_prob+joy_prob and num>joy_prob+anger_prob):
self.state["id"] = 3
self.state["sentimentCorrelation"] = 3
self.state["time_awareness"][self.state["id"] - 1] = self.env.now
elif (
num < disgust_prob + sadness_prob + anger_prob + joy_prob
and num > sadness_prob + anger_prob + joy_prob
):
self.state['id'] = 3
self.state['sentimentCorrelation'] = 3
self.state['time_awareness'][self.state['id']-1] = self.env.now
elif (num<disgust_prob+sadness_prob+anger_prob+joy_prob and num>sadness_prob+anger_prob+joy_prob):
self.state["id"] = 4
self.state["sentimentCorrelation"] = 4
self.state["time_awareness"][self.state["id"] - 1] = self.env.now
self.state['id'] = 4
self.state['sentimentCorrelation'] = 4
self.state['time_awareness'][self.state['id']-1] = self.env.now
self.state['sentiment'] = self.state['id']
self.state["sentiment"] = self.state["id"]

View File

@ -20,13 +20,13 @@ from typing import Dict, List
from .. import serialization, utils, time, config
def as_node(agent):
if isinstance(agent, BaseAgent):
return agent.id
return agent
IGNORED_FIELDS = ('model', 'logger')
IGNORED_FIELDS = ("model", "logger")
class DeadAgent(Exception):
@ -43,13 +43,18 @@ class MetaAgent(ABCMeta):
defaults.update(i._defaults)
new_nmspc = {
'_defaults': defaults,
"_defaults": defaults,
}
for attr, func in namespace.items():
if isinstance(func, types.FunctionType) or isinstance(func, property) or attr[0] == '_':
if (
isinstance(func, types.FunctionType)
or isinstance(func, property)
or isinstance(func, classmethod)
or attr[0] == "_"
):
new_nmspc[attr] = func
elif attr == 'defaults':
elif attr == "defaults":
defaults.update(func)
else:
defaults[attr] = copy(func)
@ -69,12 +74,7 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
Any attribute that is not preceded by an underscore (`_`) will also be added to its state.
"""
def __init__(self,
unique_id,
model,
name=None,
interval=None,
**kwargs):
def __init__(self, unique_id, model, name=None, interval=None, **kwargs):
# Check for REQUIRED arguments
# Initialize agent parameters
if isinstance(unique_id, MesaAgent):
@ -82,16 +82,19 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
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)
self.name = (
str(name) if name else "{}[{}]".format(type(self).__name__, self.unique_id)
)
self.alive = True
self.interval = interval or self.get('interval', 1)
logger = utils.logger.getChild(getattr(self.model, 'id', self.model)).getChild(self.name)
self.logger = logging.LoggerAdapter(logger, {'agent_name': self.name})
self.interval = interval or self.get("interval", 1)
logger = utils.logger.getChild(getattr(self.model, "id", self.model)).getChild(
self.name
)
self.logger = logging.LoggerAdapter(logger, {"agent_name": self.name})
if hasattr(self, 'level'):
if hasattr(self, "level"):
self.logger.setLevel(self.level)
for (k, v) in self._defaults.items():
@ -113,27 +116,26 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
def id(self):
return self.unique_id
@property
def state(self):
'''
Return the agent itself, which behaves as a dictionary.
This method shouldn't be used, but is kept here for backwards compatibility.
'''
return self
@state.setter
def state(self, value):
if not value:
return
for k, v in value.items():
self[k] = v
@classmethod
def from_dict(cls, model, attrs, warn_extra=True):
ignored = {}
args = {}
for k, v in attrs.items():
if k in inspect.signature(cls).parameters:
args[k] = v
else:
ignored[k] = v
if ignored and warn_extra:
utils.logger.info(
f"Ignoring the following arguments for agent class { agent_class.__name__ }: { ignored }"
)
return cls(model=model, **args)
def __getitem__(self, key):
try:
return getattr(self, key)
except AttributeError:
raise KeyError(f'key {key} not found in agent')
raise KeyError(f"key {key} not found in agent")
def __delitem__(self, key):
return delattr(self, key)
@ -151,7 +153,7 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
return self.items()
def keys(self):
return (k for k in self.__dict__ if k[0] != '_' and k not in IGNORED_FIELDS)
return (k for k in self.__dict__ if k[0] != "_" and k not in IGNORED_FIELDS)
def items(self, keys=None, skip=None):
keys = keys if keys is not None else self.keys()
@ -159,7 +161,7 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
if skip:
return filter(lambda x: x[0] not in skip, it)
return it
def get(self, key, default=None):
return self[key] if key in self else default
@ -172,7 +174,7 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
return None
def die(self):
self.info(f'agent dying')
self.info(f"agent dying")
self.alive = False
return time.NEVER
@ -189,9 +191,9 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
for k, v in kwargs:
message += " {k}={v} ".format(k, v)
extra = {}
extra['now'] = self.now
extra['unique_id'] = self.unique_id
extra['agent_name'] = self.name
extra["now"] = self.now
extra["unique_id"] = self.unique_id
extra["agent_name"] = self.name
return self.logger.log(level, message, extra=extra)
def debug(self, *args, **kwargs):
@ -217,10 +219,10 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
content = dict(self.items(keys=keys))
if pretty and content:
d = content
content = '\n'
content = "\n"
for k, v in d.items():
content += f'- {k}: {v}\n'
content = textwrap.indent(content, ' ')
content += f"- {k}: {v}\n"
content = textwrap.indent(content, " ")
return f"{repr(self)}{content}"
def __repr__(self):
@ -228,32 +230,43 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
class NetworkAgent(BaseAgent):
def __init__(self, *args, topology, node_id, **kwargs):
super().__init__(*args, **kwargs)
self.topology = topology
self.node_id = node_id
self.G = self.model.topologies[topology]
assert topology is not None
assert node_id is not None
self.G = topology
assert self.G
self.node_id = node_id
def count_neighboring_agents(self, state_id=None, **kwargs):
return len(self.get_neighboring_agents(state_id=state_id, **kwargs))
def get_neighboring_agents(self, state_id=None, **kwargs):
return self.get_agents(limit_neighbors=True, state_id=state_id, **kwargs)
def get_neighboring_agents(self, **kwargs):
return list(self.iter_agents(limit_neighbors=True, **kwargs))
def iter_agents(self, unique_id=None, limit_neighbors=False, **kwargs):
def add_edge(self, other):
self.topology.add_edge(self.node_id, other.node_id)
@property
def node(self):
return self.topology.nodes[self.node_id]
def iter_agents(self, unique_id=None, *, limit_neighbors=False, **kwargs):
unique_ids = None
if isinstance(unique_id, list):
unique_ids = set(unique_id)
elif unique_id is not None:
unique_ids = set([unique_id,])
unique_ids = set(
[
unique_id,
]
)
if limit_neighbors:
neighbor_ids = set()
for node_id in self.G.neighbors(self.node_id):
if self.G.nodes[node_id].get('agent_id') is not None:
if self.G.nodes[node_id].get("agent") is not None:
neighbor_ids.add(node_id)
if unique_ids:
unique_ids = unique_ids & neighbor_ids
@ -266,7 +279,9 @@ class NetworkAgent(BaseAgent):
def subgraph(self, center=True, **kwargs):
include = [self] if center else []
G = self.G.subgraph(n.node_id for n in list(self.get_agents(**kwargs)+include))
G = self.G.subgraph(
n.node_id for n in list(self.get_agents(**kwargs) + include)
)
return G
def remove_node(self):
@ -274,11 +289,19 @@ class NetworkAgent(BaseAgent):
def add_edge(self, other, edge_attr_dict=None, *edge_attrs):
if self.node_id not in self.G.nodes(data=False):
raise ValueError('{} not in list of existing agents in the network'.format(self.unique_id))
raise ValueError(
"{} not in list of existing agents in the network".format(
self.unique_id
)
)
if other.node_id not in self.G.nodes(data=False):
raise ValueError('{} not in list of existing agents in the network'.format(other))
raise ValueError(
"{} not in list of existing agents in the network".format(other)
)
self.G.add_edge(self.node_id, other.node_id, edge_attr_dict=edge_attr_dict, *edge_attrs)
self.G.add_edge(
self.node_id, other.node_id, edge_attr_dict=edge_attr_dict, *edge_attrs
)
def die(self, remove=True):
if remove:
@ -288,11 +311,11 @@ class NetworkAgent(BaseAgent):
def state(name=None):
def decorator(func, name=None):
'''
"""
A state function should return either a state id, or a tuple (state_id, when)
The default value for state_id is the current state id.
The default value for when is the interval defined in the environment.
'''
"""
if inspect.isgeneratorfunction(func):
orig_func = func
@ -342,32 +365,38 @@ class MetaFSM(MetaAgent):
# Add new states
for attr, func in namespace.items():
if hasattr(func, 'id'):
if hasattr(func, "id"):
if func.is_default:
default_state = func
states[func.id] = func
namespace.update({
'_default_state': default_state,
'_states': states,
})
namespace.update(
{
"_default_state": default_state,
"_states": states,
}
)
return super(MetaFSM, mcls).__new__(mcls=mcls, name=name, bases=bases, namespace=namespace)
return super(MetaFSM, mcls).__new__(
mcls=mcls, name=name, bases=bases, namespace=namespace
)
class FSM(BaseAgent, metaclass=MetaFSM):
def __init__(self, *args, **kwargs):
super(FSM, self).__init__(*args, **kwargs)
if not hasattr(self, 'state_id'):
if not hasattr(self, "state_id"):
if not self._default_state:
raise ValueError('No default state specified for {}'.format(self.unique_id))
raise ValueError(
"No default state specified for {}".format(self.unique_id)
)
self.state_id = self._default_state.id
self._coroutine = None
self.set_state(self.state_id)
def step(self):
self.debug(f'Agent {self.unique_id} @ state {self.state_id}')
self.debug(f"Agent {self.unique_id} @ state {self.state_id}")
default_interval = super().step()
next_state = self._states[self.state_id](self)
@ -380,7 +409,9 @@ class FSM(BaseAgent, metaclass=MetaFSM):
elif len(when) == 1:
when = when[0]
else:
raise ValueError('Too many values returned. Only state (and time) allowed')
raise ValueError(
"Too many values returned. Only state (and time) allowed"
)
except TypeError:
pass
@ -390,10 +421,10 @@ class FSM(BaseAgent, metaclass=MetaFSM):
return when or default_interval
def set_state(self, state, when=None):
if hasattr(state, 'id'):
if hasattr(state, "id"):
state = state.id
if state not in self._states:
raise ValueError('{} is not a valid state'.format(state))
raise ValueError("{} is not a valid state".format(state))
self.state_id = state
if when is not None:
self.model.schedule.add(self, when=when)
@ -408,23 +439,22 @@ class FSM(BaseAgent, metaclass=MetaFSM):
def prob(prob, random):
'''
"""
A true/False uniform distribution with a given probability.
To be used like this:
.. code-block:: python
if prob(0.3):
do_something()
'''
"""
r = random.random()
return r < prob
def calculate_distribution(network_agents=None,
agent_class=None):
'''
def calculate_distribution(network_agents=None, agent_class=None):
"""
Calculate the threshold values (thresholds for a uniform distribution)
of an agent distribution given the weights of each agent type.
@ -447,26 +477,28 @@ def calculate_distribution(network_agents=None,
In this example, 20% of the nodes will be marked as type
'agent_class_1'.
'''
"""
if network_agents:
network_agents = [deepcopy(agent) for agent in network_agents if not hasattr(agent, 'id')]
network_agents = [
deepcopy(agent) for agent in network_agents if not hasattr(agent, "id")
]
elif agent_class:
network_agents = [{'agent_class': agent_class}]
network_agents = [{"agent_class": agent_class}]
else:
raise ValueError('Specify a distribution or a default agent type')
raise ValueError("Specify a distribution or a default agent type")
# Fix missing weights and incompatible types
for x in network_agents:
x['weight'] = float(x.get('weight', 1))
x["weight"] = float(x.get("weight", 1))
# Calculate the thresholds
total = sum(x['weight'] for x in network_agents)
total = sum(x["weight"] for x in network_agents)
acc = 0
for v in network_agents:
if 'ids' in v:
if "ids" in v:
continue
upper = acc + (v['weight']/total)
v['threshold'] = [acc, upper]
upper = acc + (v["weight"] / total)
v["threshold"] = [acc, upper]
acc = upper
return network_agents
@ -474,28 +506,29 @@ def calculate_distribution(network_agents=None,
def serialize_type(agent_class, known_modules=[], **kwargs):
if isinstance(agent_class, str):
return agent_class
known_modules += ['soil.agents']
return serialization.serialize(agent_class, known_modules=known_modules, **kwargs)[1] # Get the name of the class
known_modules += ["soil.agents"]
return serialization.serialize(agent_class, known_modules=known_modules, **kwargs)[
1
] # Get the name of the class
def serialize_definition(network_agents, known_modules=[]):
'''
"""
When serializing an agent distribution, remove the thresholds, in order
to avoid cluttering the YAML definition file.
'''
"""
d = deepcopy(list(network_agents))
for v in d:
if 'threshold' in v:
del v['threshold']
v['agent_class'] = serialize_type(v['agent_class'],
known_modules=known_modules)
if "threshold" in v:
del v["threshold"]
v["agent_class"] = serialize_type(v["agent_class"], known_modules=known_modules)
return d
def deserialize_type(agent_class, known_modules=[]):
if not isinstance(agent_class, str):
return agent_class
known = known_modules + ['soil.agents', 'soil.agents.custom' ]
known = known_modules + ["soil.agents", "soil.agents.custom"]
agent_class = serialization.deserializer(agent_class, known_modules=known)
return agent_class
@ -503,12 +536,12 @@ def deserialize_type(agent_class, known_modules=[]):
def deserialize_definition(ind, **kwargs):
d = deepcopy(ind)
for v in d:
v['agent_class'] = deserialize_type(v['agent_class'], **kwargs)
v["agent_class"] = deserialize_type(v["agent_class"], **kwargs)
return d
def _validate_states(states, topology):
'''Validate states to avoid ignoring states during initialization'''
"""Validate states to avoid ignoring states during initialization"""
states = states or []
if isinstance(states, dict):
for x in states:
@ -519,7 +552,7 @@ def _validate_states(states, topology):
def _convert_agent_classs(ind, to_string=False, **kwargs):
'''Convenience method to allow specifying agents by class or class name.'''
"""Convenience method to allow specifying agents by class or class name."""
if to_string:
return serialize_definition(ind, **kwargs)
return deserialize_definition(ind, **kwargs)
@ -603,12 +636,10 @@ def _convert_agent_classs(ind, to_string=False, **kwargs):
class AgentView(Mapping, Set):
"""A lazy-loaded list of agents.
"""
"""A lazy-loaded list of agents."""
__slots__ = ("_agents",)
def __init__(self, agents):
self._agents = agents
@ -651,11 +682,20 @@ class AgentView(Mapping, Set):
return f"{self.__class__.__name__}({self})"
def filter_agents(agents, *id_args, unique_id=None, state_id=None, agent_class=None, ignore=None, state=None,
limit=None, **kwargs):
'''
def filter_agents(
agents,
*id_args,
unique_id=None,
state_id=None,
agent_class=None,
ignore=None,
state=None,
limit=None,
**kwargs,
):
"""
Filter agents given as a dict, by the criteria given as arguments (e.g., certain type or state id).
'''
"""
assert isinstance(agents, dict)
ids = []
@ -688,7 +728,7 @@ def filter_agents(agents, *id_args, unique_id=None, state_id=None, agent_class=N
f = filter(lambda x: x not in ignore, f)
if state_id is not None:
f = filter(lambda agent: agent.get('state_id', None) in state_id, f)
f = filter(lambda agent: agent.get("state_id", None) in state_id, f)
if agent_class is not None:
f = filter(lambda agent: isinstance(agent, agent_class), f)
@ -697,7 +737,7 @@ def filter_agents(agents, *id_args, unique_id=None, state_id=None, agent_class=N
state.update(kwargs)
for k, v in state.items():
f = filter(lambda agent: agent.state.get(k, None) == v, f)
f = filter(lambda agent: getattr(agent, k, None) == v, f)
if limit is not None:
f = islice(f, limit)
@ -705,123 +745,143 @@ def filter_agents(agents, *id_args, unique_id=None, state_id=None, agent_class=N
yield from f
def from_config(cfg: config.AgentConfig, random, topologies: Dict[str, nx.Graph] = None) -> List[Dict[str, Any]]:
'''
def from_config(
cfg: config.AgentConfig, random, topology: nx.Graph = None
) -> List[Dict[str, Any]]:
"""
This function turns an agentconfig into a list of individual "agent specifications", which are just a dictionary
with the parameters that the environment will use to construct each agent.
This function does NOT return a list of agents, mostly because some attributes to the agent are not known at the
time of calling this function, such as `unique_id`.
'''
"""
default = cfg or config.AgentConfig()
if not isinstance(cfg, config.AgentConfig):
cfg = config.AgentConfig(**cfg)
return _agents_from_config(cfg, topologies=topologies, random=random)
return _agents_from_config(cfg, topology=topology, random=random)
def _agents_from_config(cfg: config.AgentConfig,
topologies: Dict[str, nx.Graph],
random) -> List[Dict[str, Any]]:
def _agents_from_config(
cfg: config.AgentConfig, topology: nx.Graph, random
) -> List[Dict[str, Any]]:
if cfg and not isinstance(cfg, config.AgentConfig):
cfg = config.AgentConfig(**cfg)
agents = []
assigned = defaultdict(int)
assigned_total = 0
assigned_network = 0
if cfg.fixed is not None:
agents, counts = _from_fixed(cfg.fixed, topology=cfg.topology, default=cfg)
assigned.update(counts)
agents, assigned_total, assigned_network = _from_fixed(
cfg.fixed, topology=cfg.topology, default=cfg
)
n = cfg.n
if cfg.distribution:
topo_size = {top: len(topologies[top]) for top in topologies}
topo_size = len(topology) if topology else 0
grouped = defaultdict(list)
networked = []
total = []
for d in cfg.distribution:
if d.strategy == config.Strategy.topology:
topology = d.topology if ('topology' in d.__fields_set__) else cfg.topology
if not topology:
raise ValueError('The "topology" strategy only works if the topology parameter is specified')
if topology not in topo_size:
raise ValueError(f'Unknown topology selected: { topology }. Make sure the topology has been defined')
topo = d.topology if ("topology" in d.__fields_set__) else cfg.topology
if not topo:
raise ValueError(
'The "topology" strategy only works if the topology parameter is set to True'
)
if not topo_size:
raise ValueError(
f"Topology does not have enough free nodes to assign one to the agent"
)
grouped[topology].append(d)
networked.append(d)
if d.strategy == config.Strategy.total:
if not cfg.n:
raise ValueError('Cannot use the "total" strategy without providing the total number of agents')
raise ValueError(
'Cannot use the "total" strategy without providing the total number of agents'
)
total.append(d)
for (topo, distro) in grouped.items():
if not topologies or topo not in topo_size:
raise ValueError(
'You need to specify a target number of agents for the distribution \
or a configuration with a topology, along with a dictionary with \
all the available topologies')
n = len(topologies[topo])
target = topo_size[topo] - assigned[topo]
new_agents = _from_distro(cfg.distribution, target,
topology=topo,
default=cfg,
random=random)
assigned[topo] += len(new_agents)
if networked:
new_agents = _from_distro(
networked,
n=topo_size - assigned_network,
topology=topo,
default=cfg,
random=random,
)
assigned_total += len(new_agents)
assigned_network += len(new_agents)
agents += new_agents
if total:
remaining = n - sum(assigned.values())
agents += _from_distro(total, remaining,
topology='', # DO NOT assign to any topology
default=cfg,
random=random)
remaining = n - assigned_total
agents += _from_distro(total, n=remaining, default=cfg, random=random)
if sum(assigned.values()) != sum(topo_size.values()):
utils.logger.warn(f'The total number of agents does not match the total number of nodes in '
'every topology. This may be due to a definition error: assigned: '
f'{ assigned } total sizes: { topo_size }')
if assigned_network < topo_size:
utils.logger.warn(
f"The total number of agents does not match the total number of nodes in "
"every topology. This may be due to a definition error: assigned: "
f"{ assigned } total size: { topo_size }"
)
return agents
def _from_fixed(lst: List[config.FixedAgentConfig], topology: str, default: config.SingleAgentConfig) -> List[Dict[str, Any]]:
def _from_fixed(
lst: List[config.FixedAgentConfig],
topology: bool,
default: config.SingleAgentConfig,
) -> List[Dict[str, Any]]:
agents = []
counts = {}
counts_total = 0
counts_network = 0
for fixed in lst:
agent = {}
if default:
agent = default.state.copy()
agent.update(fixed.state)
cls = serialization.deserialize(fixed.agent_class or (default and default.agent_class))
agent['agent_class'] = cls
topo = fixed.topology if ('topology' in fixed.__fields_set__) else topology or default.topology
cls = serialization.deserialize(
fixed.agent_class or (default and default.agent_class)
)
agent["agent_class"] = cls
topo = (
fixed.topology
if ("topology" in fixed.__fields_set__)
else topology or default.topology
)
if topo:
agent['topology'] = topo
agent["topology"] = True
counts_network += 1
if not fixed.hidden:
counts[topo] = counts.get(topo, 0) + 1
counts_total += 1
agents.append(agent)
return agents, counts
return agents, counts_total, counts_network
def _from_distro(distro: List[config.AgentDistro],
n: int,
topology: str,
default: config.SingleAgentConfig,
random) -> List[Dict[str, Any]]:
def _from_distro(
distro: List[config.AgentDistro],
n: int,
topology: str,
default: config.SingleAgentConfig,
random,
) -> List[Dict[str, Any]]:
agents = []
if n is None:
if any(lambda dist: dist.n is None, distro):
raise ValueError('You must provide a total number of agents, or the number of each type')
raise ValueError(
"You must provide a total number of agents, or the number of each type"
)
n = sum(dist.n for dist in distro)
weights = list(dist.weight if dist.weight is not None else 1 for dist in distro)
@ -834,30 +894,40 @@ def _from_distro(distro: List[config.AgentDistro],
# So instead we calculate our own distribution to make sure the actual ratios are close to what we would expect
# Calculate how many times each has to appear
indices = list(chain.from_iterable([idx] * int(n*chunk) for (idx, n) in enumerate(norm)))
indices = list(
chain.from_iterable([idx] * int(n * chunk) for (idx, n) in enumerate(norm))
)
# Complete with random agents following the original weight distribution
if len(indices) < n:
indices += random.choices(list(range(len(distro))), weights=[d.weight for d in distro], k=n-len(indices))
indices += random.choices(
list(range(len(distro))),
weights=[d.weight for d in distro],
k=n - len(indices),
)
# Deserialize classes for efficiency
classes = list(serialization.deserialize(i.agent_class or default.agent_class) for i in distro)
classes = list(
serialization.deserialize(i.agent_class or default.agent_class) for i in distro
)
# Add them in random order
random.shuffle(indices)
for idx in indices:
d = distro[idx]
agent = d.state.copy()
cls = classes[idx]
agent['agent_class'] = cls
agent["agent_class"] = cls
if default:
agent.update(default.state)
# agent = cls(unique_id=agent_id, model=env, **state)
topology = d.topology if ('topology' in d.__fields_set__) else topology or default.topology
topology = (
d.topology
if ("topology" in d.__fields_set__)
else topology or default.topology
)
if topology:
agent['topology'] = topology
agent["topology"] = topology
agents.append(agent)
return agents
@ -876,4 +946,5 @@ try:
from .Geo import Geo
except ImportError:
import sys
print('Could not load the Geo Agent, scipy is not installed', file=sys.stderr)
print("Could not load the Geo Agent, scipy is not installed", file=sys.stderr)

View File

@ -19,6 +19,7 @@ import networkx as nx
# Could use TypeAlias in python >= 3.10
nodeId = int
class Node(BaseModel):
id: nodeId
state: Optional[Dict[str, Any]] = {}
@ -38,12 +39,12 @@ class Topology(BaseModel):
class NetParams(BaseModel, extra=Extra.allow):
generator: Union[Callable, str]
n: int
n: int
class NetConfig(BaseModel):
params: Optional[NetParams]
topology: Optional[Union[Topology, nx.Graph]]
fixed: Optional[Union[Topology, nx.Graph]]
path: Optional[str]
class Config:
@ -54,14 +55,15 @@ class NetConfig(BaseModel):
return NetConfig(topology=None, params=None)
@root_validator
def validate_all(cls, values):
if 'params' not in values and 'topology' not in values:
raise ValueError('You must specify either a topology or the parameters to generate a graph')
def validate_all(cls, values):
if "params" not in values and "topology" not in values:
raise ValueError(
"You must specify either a topology or the parameters to generate a graph"
)
return values
class EnvConfig(BaseModel):
@staticmethod
def default():
return EnvConfig()
@ -70,7 +72,7 @@ class EnvConfig(BaseModel):
class SingleAgentConfig(BaseModel):
agent_class: Optional[Union[Type, str]] = None
unique_id: Optional[int] = None
topology: Optional[str] = None
topology: Optional[bool] = False
node_id: Optional[Union[int, str]] = None
state: Optional[Dict[str, Any]] = {}
@ -80,9 +82,11 @@ class FixedAgentConfig(SingleAgentConfig):
hidden: Optional[bool] = False # Do not count this agent towards total agent count
@root_validator
def validate_all(cls, values):
if values.get('agent_id', None) is not None and values.get('n', 1) > 1:
raise ValueError(f"An agent_id can only be provided when there is only one agent ({values.get('n')} given)")
def validate_all(cls, values):
if values.get("unique_id", None) is not None and values.get("n", 1) > 1:
raise ValueError(
f"An unique_id can only be provided when there is only one agent ({values.get('n')} given)"
)
return values
@ -91,8 +95,8 @@ class OverrideAgentConfig(FixedAgentConfig):
class Strategy(Enum):
topology = 'topology'
total = 'total'
topology = "topology"
total = "total"
class AgentDistro(SingleAgentConfig):
@ -102,7 +106,6 @@ class AgentDistro(SingleAgentConfig):
class AgentConfig(SingleAgentConfig):
n: Optional[int] = None
topology: Optional[str]
distribution: Optional[List[AgentDistro]] = None
fixed: Optional[List[FixedAgentConfig]] = None
override: Optional[List[OverrideAgentConfig]] = None
@ -112,16 +115,20 @@ class AgentConfig(SingleAgentConfig):
return AgentConfig()
@root_validator
def validate_all(cls, values):
if 'distribution' in values and ('n' not in values and 'topology' not in values):
raise ValueError("You need to provide the number of agents or a topology to extract the value from.")
def validate_all(cls, values):
if "distribution" in values and (
"n" not in values and "topology" not in values
):
raise ValueError(
"You need to provide the number of agents or a topology to extract the value from."
)
return values
class Config(BaseModel, extra=Extra.allow):
version: Optional[str] = '1'
version: Optional[str] = "1"
name: str = 'Unnamed Simulation'
name: str = "Unnamed Simulation"
description: Optional[str] = None
group: str = None
dir_path: Optional[str] = None
@ -141,45 +148,48 @@ class Config(BaseModel, extra=Extra.allow):
def from_raw(cls, cfg):
if isinstance(cfg, Config):
return cfg
if cfg.get('version', '1') == '1' and any(k in cfg for k in ['agents', 'agent_class', 'topology', 'environment_class']):
if cfg.get("version", "1") == "1" and any(
k in cfg for k in ["agents", "agent_class", "topology", "environment_class"]
):
return convert_old(cfg)
return Config(**cfg)
def convert_old(old, strict=True):
'''
"""
Try to convert old style configs into the new format.
This is still a work in progress and might not work in many cases.
'''
"""
utils.logger.warning('The old configuration format is deprecated. The converted file MAY NOT yield the right results')
utils.logger.warning(
"The old configuration format is deprecated. The converted file MAY NOT yield the right results"
)
new = old.copy()
network = {}
if 'topology' in old:
del new['topology']
network['topology'] = old['topology']
if "topology" in old:
del new["topology"]
network["topology"] = old["topology"]
if 'network_params' in old and old['network_params']:
del new['network_params']
for (k, v) in old['network_params'].items():
if k == 'path':
network['path'] = v
if "network_params" in old and old["network_params"]:
del new["network_params"]
for (k, v) in old["network_params"].items():
if k == "path":
network["path"] = v
else:
network.setdefault('params', {})[k] = v
network.setdefault("params", {})[k] = v
topologies = {}
topology = None
if network:
topologies['default'] = network
topology = network
agents = {'fixed': [], 'distribution': []}
agents = {"fixed": [], "distribution": []}
def updated_agent(agent):
'''Convert an agent definition'''
"""Convert an agent definition"""
newagent = dict(agent)
return newagent
@ -187,80 +197,74 @@ def convert_old(old, strict=True):
fixed = []
override = []
if 'environment_agents' in new:
if "environment_agents" in new:
for agent in new['environment_agents']:
agent.setdefault('state', {})['group'] = 'environment'
if 'agent_id' in agent:
agent['state']['name'] = agent['agent_id']
del agent['agent_id']
agent['hidden'] = True
agent['topology'] = None
for agent in new["environment_agents"]:
agent.setdefault("state", {})["group"] = "environment"
if "agent_id" in agent:
agent["state"]["name"] = agent["agent_id"]
del agent["agent_id"]
agent["hidden"] = True
agent["topology"] = False
fixed.append(updated_agent(agent))
del new['environment_agents']
del new["environment_agents"]
if "agent_class" in old:
del new["agent_class"]
agents["agent_class"] = old["agent_class"]
if 'agent_class' in old:
del new['agent_class']
agents['agent_class'] = old['agent_class']
if "default_state" in old:
del new["default_state"]
agents["state"] = old["default_state"]
if 'default_state' in old:
del new['default_state']
agents['state'] = old['default_state']
if "network_agents" in old:
agents["topology"] = True
if 'network_agents' in old:
agents['topology'] = 'default'
agents.setdefault("state", {})["group"] = "network"
agents.setdefault('state', {})['group'] = 'network'
for agent in new['network_agents']:
for agent in new["network_agents"]:
agent = updated_agent(agent)
if 'agent_id' in agent:
agent['state']['name'] = agent['agent_id']
del agent['agent_id']
if "agent_id" in agent:
agent["state"]["name"] = agent["agent_id"]
del agent["agent_id"]
fixed.append(agent)
else:
by_weight.append(agent)
del new['network_agents']
del new["network_agents"]
if 'agent_class' in old and (not fixed and not by_weight):
agents['topology'] = 'default'
by_weight = [{'agent_class': old['agent_class'], 'weight': 1}]
if "agent_class" in old and (not fixed and not by_weight):
agents["topology"] = True
by_weight = [{"agent_class": old["agent_class"], "weight": 1}]
# TODO: translate states properly
if 'states' in old:
del new['states']
states = old['states']
if "states" in old:
del new["states"]
states = old["states"]
if isinstance(states, dict):
states = states.items()
else:
states = enumerate(states)
for (k, v) in states:
override.append({'filter': {'node_id': k},
'state': v})
agents['override'] = override
agents['fixed'] = fixed
agents['distribution'] = by_weight
override.append({"filter": {"node_id": k}, "state": v})
agents["override"] = override
agents["fixed"] = fixed
agents["distribution"] = by_weight
model_params = {}
if 'environment_params' in new:
del new['environment_params']
model_params = dict(old['environment_params'])
if "environment_params" in new:
del new["environment_params"]
model_params = dict(old["environment_params"])
if 'environment_class' in old:
del new['environment_class']
new['model_class'] = old['environment_class']
if "environment_class" in old:
del new["environment_class"]
new["model_class"] = old["environment_class"]
if 'dump' in old:
del new['dump']
new['dry_run'] = not old['dump']
if "dump" in old:
del new["dump"]
new["dry_run"] = not old["dump"]
model_params['topologies'] = topologies
model_params['agents'] = agents
model_params["topology"] = topology
model_params["agents"] = agents
return Config(version='2',
model_params=model_params,
**new)
return Config(version="2", model_params=model_params, **new)

View File

@ -1,6 +1,6 @@
from mesa import DataCollector as MDC
class SoilDataCollector(MDC):
class SoilDataCollector(MDC):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)

View File

@ -18,9 +18,9 @@ def wrapcmd(func):
known = globals()
known.update(self.curframe.f_globals)
known.update(self.curframe.f_locals)
known['agent'] = known.get('self', None)
known['model'] = known.get('self', {}).get('model')
known['attrs'] = arg.strip().split()
known["agent"] = known.get("self", None)
known["model"] = known.get("self", {}).get("model")
known["attrs"] = arg.strip().split()
exec(func.__code__, known, known)
@ -29,10 +29,12 @@ def wrapcmd(func):
class Debug(pdb.Pdb):
def __init__(self, *args, skip_soil=False, **kwargs):
skip = kwargs.get('skip', [])
skip = kwargs.get("skip", [])
skip.append("soil")
if skip_soil:
skip.append('soil.*')
skip.append('mesa.*')
skip.append("soil")
skip.append("soil.*")
skip.append("mesa.*")
super(Debug, self).__init__(*args, skip=skip, **kwargs)
self.prompt = "[soil-pdb] "
@ -40,7 +42,7 @@ class Debug(pdb.Pdb):
def _soil_agents(model, attrs=None, pretty=True, **kwargs):
for agent in model.agents(**kwargs):
d = agent
print(' - ' + indent(agent.to_str(keys=attrs, pretty=pretty), ' '))
print(" - " + indent(agent.to_str(keys=attrs, pretty=pretty), " "))
@wrapcmd
def do_soil_agents():
@ -50,14 +52,20 @@ class Debug(pdb.Pdb):
@wrapcmd
def do_soil_list():
return Debug._soil_agents(model, attrs=['state_id'], pretty=False)
return Debug._soil_agents(model, attrs=["state_id"], pretty=False)
do_sl = do_soil_list
def do_continue_state(self, arg):
self.do_break_state(arg, temporary=True)
return self.do_continue("")
do_cs = do_continue_state
@wrapcmd
def do_soil_self():
def do_soil_agent():
if not agent:
print('No agent available')
print("No agent available")
return
keys = None
@ -70,46 +78,56 @@ class Debug(pdb.Pdb):
print(agent.to_str(pretty=True, keys=keys))
do_ss = do_soil_self
do_aa = do_soil_agent
def do_break_state(self, arg: str, temporary=False):
'''
def do_break_state(self, arg: str, instances=None, temporary=False):
"""
Break before a specified state is stepped into.
'''
"""
klass = None
state = arg.strip()
state = arg
if not state:
self.error("Specify at least a state name")
return
comma = arg.find(':')
if comma > 0:
state = arg[comma+1:].lstrip()
klass = arg[:comma].rstrip()
klass = eval(klass,
self.curframe.f_globals,
self.curframe_locals)
state, *tokens = state.lstrip().split()
if tokens:
instances = list(eval(token) for token in tokens)
colon = state.find(":")
if colon > 0:
klass = state[:colon].rstrip()
state = state[colon + 1 :].strip()
print(klass, state, tokens)
klass = eval(klass, self.curframe.f_globals, self.curframe_locals)
if klass:
klasses = [klass]
else:
klasses = [k for k in self.curframe.f_globals.values() if isinstance(k, type) and issubclass(k, FSM)]
print(klasses)
if not klasses:
self.error('No agent classes found')
klasses = [
k
for k in self.curframe.f_globals.values()
if isinstance(k, type) and issubclass(k, FSM)
]
if not klasses:
self.error("No agent classes found")
for klass in klasses:
try:
func = getattr(klass, state)
except AttributeError:
self.error(f"State {state} not found in class {klass}")
continue
if hasattr(func, '__func__'):
if hasattr(func, "__func__"):
func = func.__func__
code = func.__code__
#use co_name to identify the bkpt (function names
#could be aliased, but co_name is invariant)
# use co_name to identify the bkpt (function names
# could be aliased, but co_name is invariant)
funcname = code.co_name
lineno = code.co_firstlineno
filename = code.co_filename
@ -117,35 +135,56 @@ class Debug(pdb.Pdb):
# Check for reasonable breakpoint
line = self.checkline(filename, lineno)
if not line:
raise ValueError('no line found')
raise ValueError("no line found")
# now set the break point
cond = None
if instances:
cond = f"self.unique_id in { repr(instances) }"
existing = self.get_breaks(filename, line)
if existing:
self.message("Breakpoint already exists at %s:%d" %
(filename, line))
self.message("Breakpoint already exists at %s:%d" % (filename, line))
continue
err = self.set_break(filename, line, temporary, cond, funcname)
if err:
self.error(err)
else:
bp = self.get_breaks(filename, line)[-1]
self.message("Breakpoint %d at %s:%d" %
(bp.number, bp.file, bp.line))
self.message("Breakpoint %d at %s:%d" % (bp.number, bp.file, bp.line))
do_bs = do_break_state
def do_break_state_self(self, arg: str, temporary=False):
"""
Break before a specified state is stepped into, for the current agent
"""
agent = self.curframe.f_locals.get("self")
if not agent:
self.error("No current agent.")
self.error("Try this again when the debugger is stopped inside an agent")
return
def setup(frame=None):
debugger = Debug()
arg = f"{agent.__class__.__name__}:{ arg } {agent.unique_id}"
return self.do_break_state(arg)
do_bss = do_break_state_self
debugger = None
def set_trace(frame=None, **kwargs):
global debugger
if debugger is None:
debugger = Debug(**kwargs)
frame = frame or sys._getframe().f_back
debugger.set_trace(frame)
def debug_env():
if os.environ.get('SOIL_DEBUG'):
return setup(frame=sys._getframe().f_back)
def post_mortem(traceback=None):
p = Debug()
global debugger
if debugger is None:
debugger = Debug(**kwargs)
t = sys.exc_info()[2]
p.reset()
p.interaction(None, t)
debugger.reset()
debugger.interaction(None, t)

View File

@ -5,6 +5,7 @@ import sqlite3
import math
import random
import logging
import inspect
from typing import Any, Dict, Optional, Union
from collections import namedtuple
@ -21,9 +22,6 @@ from mesa.datacollection import DataCollector
from . import agents as agentmod, config, serialization, utils, time, network
Record = namedtuple('Record', 'dict_id t_step key value')
class BaseEnvironment(Model):
"""
The environment is key in a simulation. It controls how agents interact,
@ -37,20 +35,24 @@ class BaseEnvironment(Model):
:meth:`soil.environment.Environment.get` method.
"""
def __init__(self,
id='unnamed_env',
seed='default',
schedule=None,
dir_path=None,
interval=1,
agent_class=None,
agents: [tuple[type, Dict[str, Any]]] = {},
agent_reporters: Optional[Any] = None,
model_reporters: Optional[Any] = None,
tables: Optional[Any] = None,
**env_params):
def __init__(
self,
id="unnamed_env",
seed="default",
schedule=None,
dir_path=None,
interval=1,
agent_class=None,
agents: [tuple[type, Dict[str, Any]]] = {},
agent_reporters: Optional[Any] = None,
model_reporters: Optional[Any] = None,
tables: Optional[Any] = None,
**env_params,
):
super().__init__(seed=seed)
self.env_params = env_params or {}
self.current_id = -1
self.id = id
@ -63,11 +65,8 @@ class BaseEnvironment(Model):
self.agent_class = agent_class or agentmod.BaseAgent
self.init_agents(agents)
self.env_params = env_params or {}
self.interval = interval
self.init_agents(agents)
self.logger = utils.logger.getChild(self.id)
@ -77,17 +76,27 @@ class BaseEnvironment(Model):
tables=tables,
)
def _read_single_agent(self, agent):
def _agent_from_dict(self, agent):
"""
Translate an agent dictionary into an agent
"""
agent = dict(**agent)
cls = agent.pop('agent_class', None) or self.agent_class
unique_id = agent.pop('unique_id', None)
cls = agent.pop("agent_class", None) or self.agent_class
unique_id = agent.pop("unique_id", None)
if unique_id is None:
unique_id = self.next_id()
return serialization.deserialize(cls)(unique_id=unique_id,
model=self, **agent)
return serialization.deserialize(cls)(unique_id=unique_id, model=self, **agent)
def init_agents(self, agents: Union[config.AgentConfig, [Dict[str, Any]]] = {}):
"""
Initialize the agents in the model from either a `soil.config.AgentConfig` or a list of
dictionaries that each describes an agent.
If given a list of dictionaries, an agent will be created for each dictionary. The agent
class can be specified through the `agent_class` key. The rest of the items will be used
as parameters to the agent.
"""
if not agents:
return
@ -98,14 +107,11 @@ class BaseEnvironment(Model):
lst = config.AgentConfig(**agents)
if lst.override:
override = lst.override
lst = agentmod.from_config(lst,
topologies=getattr(self, 'topologies', None),
random=self.random)
lst = self._agent_dict_from_config(lst)
#TODO: check override is working again. It cannot (easily) be part of agents.from_config anymore,
# TODO: check override is working again. It cannot (easily) be part of agents.from_config anymore,
# because it needs attribute such as unique_id, which are only present after init
new_agents = [self._read_single_agent(agent) for agent in lst]
new_agents = [self._agent_from_dict(agent) for agent in lst]
for a in new_agents:
self.schedule.add(a)
@ -115,6 +121,8 @@ class BaseEnvironment(Model):
for attr, value in rule.state.items():
setattr(agent, attr, value)
def _agent_dict_from_config(self, cfg):
return agentmod.from_config(cfg, random=self.random)
@property
def agents(self):
@ -122,7 +130,7 @@ class BaseEnvironment(Model):
def find_one(self, *args, **kwargs):
return agentmod.AgentView(self.schedule._agents).one(*args, **kwargs)
def count_agents(self, *args, **kwargs):
return sum(1 for i in self.agents(*args, **kwargs))
@ -130,15 +138,16 @@ class BaseEnvironment(Model):
def now(self):
if self.schedule:
return self.schedule.time
raise Exception('The environment has not been scheduled, so it has no sense of time')
raise Exception(
"The environment has not been scheduled, so it has no sense of time"
)
def add_agent(self, agent_id, agent_class, **kwargs):
def add_agent(self, agent_class, unique_id=None, **kwargs):
a = None
if agent_class:
a = agent_class(model=self,
unique_id=agent_id,
**kwargs)
if unique_id is None:
unique_id = self.next_id()
a = agent_class(model=self, unique_id=unique_id, **args)
self.schedule.add(a)
return a
@ -151,16 +160,16 @@ class BaseEnvironment(Model):
for k, v in kwargs:
message += " {k}={v} ".format(k, v)
extra = {}
extra['now'] = self.now
extra['id'] = self.id
extra["now"] = self.now
extra["id"] = self.id
return self.logger.log(level, message, extra=extra)
def step(self):
'''
"""
Advance one step in the simulation, and update the data collection and scheduler appropriately
'''
"""
super().step()
self.logger.info(f'--- Step {self.now:^5} ---')
self.logger.info(f"--- Step {self.now:^5} ---")
self.schedule.step()
self.datacollector.collect(self)
@ -168,10 +177,10 @@ class BaseEnvironment(Model):
return key in self.env_params
def get(self, key, default=None):
'''
"""
Get the value of an environment attribute.
Return `default` if the value is not set.
'''
"""
return self.env_params.get(key, default)
def __getitem__(self, key):
@ -180,123 +189,110 @@ class BaseEnvironment(Model):
def __setitem__(self, key, value):
return self.env_params.__setitem__(key, value)
def _agent_to_tuples(self, agent, now=None):
if now is None:
now = self.now
for k, v in agent.state.items():
yield Record(dict_id=agent.id,
t_step=now,
key=k,
value=v)
def state_to_tuples(self, agent_id=None, now=None):
if now is None:
now = self.now
if agent_id:
agent = self.agents[agent_id]
yield from self._agent_to_tuples(agent, now)
return
for k, v in self.env_params.items():
yield Record(dict_id='env',
t_step=now,
key=k,
value=v)
for agent in self.agents:
yield from self._agent_to_tuples(agent, now)
def __str__(self):
return str(self.env_params)
class NetworkEnvironment(BaseEnvironment):
"""
The NetworkEnvironment is an environment that includes one or more networkx.Graph intances
and methods to associate agents to nodes and vice versa.
"""
def __init__(self, *args, topology: nx.Graph = None, topologies: Dict[str, config.NetConfig] = {}, **kwargs):
agents = kwargs.pop('agents', None)
def __init__(
self, *args, topology: Union[config.NetConfig, nx.Graph] = None, **kwargs
):
agents = kwargs.pop("agents", None)
super().__init__(*args, agents=None, **kwargs)
self._node_ids = {}
assert not hasattr(self, 'topologies')
if topology is not None:
if topologies:
raise ValueError('Please, provide either a single topology or a dictionary of them')
topologies = {'default': topology}
self.topologies = {}
for (name, cfg) in topologies.items():
self.set_topology(cfg=cfg, graph=name)
self._set_topology(topology)
self.init_agents(agents)
def init_agents(self, *args, **kwargs):
"""Initialize the agents from a"""
super().init_agents(*args, **kwargs)
for agent in self.schedule._agents.values():
if hasattr(agent, "node_id"):
self._init_node(agent)
def _read_single_agent(self, agent, unique_id=None):
def _init_node(self, agent):
"""
Make sure the node for a given agent has the proper attributes.
"""
self.G.nodes[agent.node_id]["agent"] = agent
def _agent_dict_from_config(self, cfg):
return agentmod.from_config(cfg, topology=self.G, random=self.random)
def _agent_from_dict(self, agent, unique_id=None):
agent = dict(agent)
if agent.get('topology', None) is not None:
topology = agent.get('topology')
if unique_id is None:
unique_id = self.next_id()
if topology:
node_id = self.agent_to_node(unique_id, graph_name=topology, node_id=agent.get('node_id'))
agent['node_id'] = node_id
agent['topology'] = topology
agent['unique_id'] = unique_id
if not agent.get("topology", False):
return super()._agent_from_dict(agent)
return super()._read_single_agent(agent)
if unique_id is None:
unique_id = self.next_id()
node_id = agent.get("node_id", None)
if node_id is None:
node_id = network.find_unassigned(self.G, random=self.random)
agent["node_id"] = node_id
agent["unique_id"] = unique_id
agent["topology"] = self.G
node_attrs = self.G.nodes[node_id]
node_attrs.update(agent)
agent = node_attrs
@property
def topology(self):
return self.topologies['default']
a = super()._agent_from_dict(agent)
self._init_node(a)
def set_topology(self, cfg=None, dir_path=None, graph='default'):
topology = cfg
if not isinstance(cfg, nx.Graph):
topology = network.from_config(cfg, dir_path=dir_path or self.dir_path)
return a
self.topologies[graph] = topology
def _set_topology(self, cfg=None, dir_path=None):
if cfg is None:
cfg = nx.Graph()
elif not isinstance(cfg, nx.Graph):
cfg = network.from_config(cfg, dir_path=dir_path or self.dir_path)
def topology_for(self, unique_id):
return self.topologies[self._node_ids[unique_id][0]]
self.G = cfg
@property
def network_agents(self):
yield from self.agents(agent_class=agentmod.NetworkAgent)
for a in self.schedule._agents:
if isinstance(a, agentmod.NetworkAgent):
yield a
def agent_to_node(self, unique_id, graph_name='default',
node_id=None, shuffle=False):
node_id = network.agent_to_node(G=self.topologies[graph_name],
agent_id=unique_id,
node_id=node_id,
shuffle=shuffle,
random=self.random)
def add_node(self, agent_class, unique_id=None, node_id=None, **kwargs):
if unique_id is None:
unique_id = self.next_id()
if node_id is None:
node_id = network.find_unassigned(
G=self.G, shuffle=True, random=self.random
)
self._node_ids[unique_id] = (graph_name, node_id)
return node_id
if node_id in G.nodes:
self.G.nodes[node_id]["agent"] = None # Reserve
else:
self.G.add_node(node_id)
def add_node(self, agent_class, topology, **kwargs):
unique_id = self.next_id()
self.topologies[topology].add_node(unique_id)
node_id = self.agent_to_node(unique_id=unique_id, node_id=unique_id, graph_name=topology)
a = self.add_agent(unique_id=unique_id, agent_class=agent_class, node_id=node_id, topology=topology, **kwargs)
a['visible'] = True
a = self.add_agent(
unique_id=unique_id, agent_class=agent_class, node_id=node_id, **kwargs
)
a["visible"] = True
return a
def add_edge(self, agent1, agent2, start=None, graph='default', **attrs):
agent1 = agent1.node_id
agent2 = agent2.node_id
return self.topologies[graph].add_edge(agent1, agent2, start=start)
def agent_for_node_id(self, node_id):
return self.G.nodes[node_id].get("agent")
def add_agent(self, unique_id, state=None, graph='default', **kwargs):
node = self.topologies[graph].nodes[unique_id]
node_state = node.get('state', {})
if node_state:
node_state.update(state or {})
state = node_state
a = super().add_agent(unique_id, state=state, **kwargs)
node['agent'] = a
return a
def node_id_for(self, agent_id):
return self._node_ids[agent_id][1]
def populate_network(self, agent_class, weights=None, **agent_params):
if not hasattr(agent_class, "len"):
agent_class = [agent_class]
weights = None
for (node_id, node) in self.G.nodes(data=True):
if "agent" in node:
continue
a_class = self.random.choices(agent_class, weights)[0]
self.add_agent(node_id=node_id, agent_class=a_class, **agent_params)
Environment = NetworkEnvironment

View File

@ -1,4 +1,5 @@
import os
import sys
from time import time as current_time
from io import BytesIO
from sqlalchemy import create_engine
@ -9,7 +10,7 @@ import networkx as nx
from .serialization import deserialize
from .utils import open_or_reuse, logger, timer
from .utils import try_backup, open_or_reuse, logger, timer
from . import utils, network
@ -23,54 +24,58 @@ class DryRunner(BytesIO):
def write(self, txt):
if self.__copy_to:
self.__copy_to.write('{}:::{}'.format(self.__fname, txt))
self.__copy_to.write("{}:::{}".format(self.__fname, txt))
try:
super().write(txt)
except TypeError:
super().write(bytes(txt, 'utf-8'))
super().write(bytes(txt, "utf-8"))
def close(self):
content = '(binary data not shown)'
content = "(binary data not shown)"
try:
content = self.getvalue().decode()
except UnicodeDecodeError:
pass
logger.info('**Not** written to {} (dry run mode):\n\n{}\n\n'.format(self.__fname, content))
logger.info(
"**Not** written to {} (dry run mode):\n\n{}\n\n".format(
self.__fname, content
)
)
super().close()
class Exporter:
'''
"""
Interface for all exporters. It is not necessary, but it is useful
if you don't plan to implement all the methods.
'''
"""
def __init__(self, simulation, outdir=None, dry_run=None, copy_to=None):
self.simulation = simulation
outdir = outdir or os.path.join(os.getcwd(), 'soil_output')
self.outdir = os.path.join(outdir,
simulation.group or '',
simulation.name)
outdir = outdir or os.path.join(os.getcwd(), "soil_output")
self.outdir = os.path.join(outdir, simulation.group or "", simulation.name)
self.dry_run = dry_run
if copy_to is None and dry_run:
copy_to = sys.stdout
self.copy_to = copy_to
def sim_start(self):
'''Method to call when the simulation starts'''
"""Method to call when the simulation starts"""
pass
def sim_end(self):
'''Method to call when the simulation ends'''
"""Method to call when the simulation ends"""
pass
def trial_start(self, env):
'''Method to call when a trial start'''
"""Method to call when a trial start"""
pass
def trial_end(self, env):
'''Method to call when a trial ends'''
"""Method to call when a trial ends"""
pass
def output(self, f, mode='w', **kwargs):
def output(self, f, mode="w", **kwargs):
if self.dry_run:
f = DryRunner(f, copy_to=self.copy_to)
else:
@ -83,97 +88,121 @@ class Exporter:
class default(Exporter):
'''Default exporter. Writes sqlite results, as well as the simulation YAML'''
"""Default exporter. Writes sqlite results, as well as the simulation YAML"""
def sim_start(self):
if not self.dry_run:
logger.info('Dumping results to %s', self.outdir)
with self.output(self.simulation.name + '.dumped.yml') as f:
f.write(self.simulation.to_yaml())
else:
logger.info('NOT dumping results')
if self.dry_run:
logger.info("NOT dumping results")
return
logger.info("Dumping results to %s", self.outdir)
with self.output(self.simulation.name + ".dumped.yml") as f:
f.write(self.simulation.to_yaml())
self.dbpath = os.path.join(self.outdir, f"{self.simulation.name}.sqlite")
try_backup(self.dbpath, move=True)
def trial_end(self, env):
if not self.dry_run:
with timer('Dumping simulation {} trial {}'.format(self.simulation.name,
env.id)):
engine = create_engine('sqlite:///{}.sqlite'.format(env.id), echo=False)
if self.dry_run:
logger.info("Running in DRY_RUN mode, the database will NOT be created")
return
dc = env.datacollector
for (t, df) in get_dc_dfs(dc):
df.to_sql(t, con=engine, if_exists='append')
with timer(
"Dumping simulation {} trial {}".format(self.simulation.name, env.id)
):
engine = create_engine(f"sqlite:///{self.dbpath}", echo=False)
dc = env.datacollector
for (t, df) in get_dc_dfs(dc, trial_id=env.id):
df.to_sql(t, con=engine, if_exists="append")
def get_dc_dfs(dc):
dfs = {'env': dc.get_model_vars_dataframe(),
'agents': dc.get_agent_vars_dataframe() }
def get_dc_dfs(dc, trial_id=None):
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()
if trial_id:
for (name, df) in dfs.items():
df['trial_id'] = trial_id
yield from dfs.items()
class csv(Exporter):
'''Export the state of each environment (and its agents) in a separate CSV file'''
"""Export the state of each environment (and its agents) in a separate CSV file"""
def trial_end(self, env):
with timer('[CSV] Dumping simulation {} trial {} @ dir {}'.format(self.simulation.name,
env.id,
self.outdir)):
for (df_name, df) in get_dc_dfs(env.datacollector):
with self.output('{}.{}.csv'.format(env.id, df_name)) as f:
with timer(
"[CSV] Dumping simulation {} trial {} @ dir {}".format(
self.simulation.name, env.id, self.outdir
)
):
for (df_name, df) in get_dc_dfs(env.datacollector, trial_id=env.id):
with self.output("{}.{}.csv".format(env.id, df_name)) as f:
df.to_csv(f)
#TODO: reimplement GEXF exporting without history
# TODO: reimplement GEXF exporting without history
class gexf(Exporter):
def trial_end(self, env):
if self.dry_run:
logger.info('Not dumping GEXF in dry_run mode')
logger.info("Not dumping GEXF in dry_run mode")
return
with timer('[GEXF] Dumping simulation {} trial {}'.format(self.simulation.name,
env.id)):
with self.output('{}.gexf'.format(env.id), mode='wb') as f:
with timer(
"[GEXF] Dumping simulation {} trial {}".format(self.simulation.name, env.id)
):
with self.output("{}.gexf".format(env.id), mode="wb") as f:
network.dump_gexf(env.history_to_graph(), f)
self.dump_gexf(env, f)
class dummy(Exporter):
def sim_start(self):
with self.output('dummy', 'w') as f:
f.write('simulation started @ {}\n'.format(current_time()))
with self.output("dummy", "w") as f:
f.write("simulation started @ {}\n".format(current_time()))
def trial_start(self, env):
with self.output('dummy', 'w') as f:
f.write('trial started@ {}\n'.format(current_time()))
with self.output("dummy", "w") as f:
f.write("trial started@ {}\n".format(current_time()))
def trial_end(self, env):
with self.output('dummy', 'w') as f:
f.write('trial ended@ {}\n'.format(current_time()))
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()))
with self.output("dummy", "a") as f:
f.write("simulation ended @ {}\n".format(current_time()))
class graphdrawing(Exporter):
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.id)) as f:
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.id)) as f:
f.savefig(f)
'''
"""
Convert an environment into a NetworkX graph
'''
"""
def env_to_graph(env, history=None):
G = nx.Graph(env.G)
for agent in env.network_agents:
attributes = {'agent': str(agent.__class__)}
attributes = {"agent": str(agent.__class__)}
lastattributes = {}
spells = []
lastvisible = False
@ -181,7 +210,7 @@ def env_to_graph(env, history=None):
if not history:
history = sorted(list(env.state_to_tuples()))
for _, t_step, attribute, value in history:
if attribute == 'visible':
if attribute == "visible":
nowvisible = value
if nowvisible and not lastvisible:
laststep = t_step
@ -190,7 +219,7 @@ def env_to_graph(env, history=None):
lastvisible = nowvisible
continue
key = 'attr_' + attribute
key = "attr_" + attribute
if key not in attributes:
attributes[key] = list()
if key not in lastattributes:

View File

@ -9,6 +9,7 @@ import networkx as nx
from . import config, serialization, basestring
def from_config(cfg: config.NetConfig, dir_path: str = None):
if not isinstance(cfg, config.NetConfig):
cfg = config.NetConfig(**cfg)
@ -19,60 +20,67 @@ def from_config(cfg: config.NetConfig, dir_path: str = None):
path = os.path.join(dir_path, path)
extension = os.path.splitext(path)[1][1:]
kwargs = {}
if extension == 'gexf':
kwargs['version'] = '1.2draft'
kwargs['node_type'] = int
if extension == "gexf":
kwargs["version"] = "1.2draft"
kwargs["node_type"] = int
try:
method = getattr(nx.readwrite, 'read_' + extension)
method = getattr(nx.readwrite, "read_" + extension)
except AttributeError:
raise AttributeError('Unknown format')
raise AttributeError("Unknown format")
return method(path, **kwargs)
if cfg.params:
net_args = cfg.params.dict()
net_gen = net_args.pop('generator')
net_gen = net_args.pop("generator")
if dir_path not in sys.path:
sys.path.append(dir_path)
method = serialization.deserializer(net_gen,
known_modules=['networkx.generators',])
method = serialization.deserializer(
net_gen,
known_modules=[
"networkx.generators",
],
)
return method(**net_args)
if isinstance(cfg.topology, config.Topology):
cfg = cfg.topology.dict()
if isinstance(cfg.fixed, config.Topology):
cfg = cfg.fixed.dict()
if isinstance(cfg, str) or isinstance(cfg, dict):
return nx.json_graph.node_link_graph(cfg)
return nx.Graph()
def agent_to_node(G, agent_id, node_id=None, shuffle=False, random=random):
'''
def find_unassigned(G, shuffle=False, random=random):
"""
Link an agent to a node in a topology.
If node_id is None, a node without an agent_id will be found.
'''
#TODO: test
if node_id is None:
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
break
"""
# TODO: test
candidates = list(G.nodes(data=True))
if shuffle:
random.shuffle(candidates)
for next_id, data in candidates:
if "agent" not in data:
node_id = next_id
break
if node_id is None:
raise ValueError(f"Not enough nodes in topology to assign one to agent {agent_id}")
G.nodes[node_id]['agent_id'] = agent_id
return node_id
def dump_gexf(G, f):
for node in G.nodes():
if 'pos' in G.nodes[node]:
G.nodes[node]['viz'] = {"position": {"x": G.nodes[node]['pos'][0], "y": G.nodes[node]['pos'][1], "z": 0.0}}
del (G.nodes[node]['pos'])
if "pos" in G.nodes[node]:
G.nodes[node]["viz"] = {
"position": {
"x": G.nodes[node]["pos"][0],
"y": G.nodes[node]["pos"][1],
"z": 0.0,
}
}
del G.nodes[node]["pos"]
nx.write_gexf(G, f, version="1.2draft")

View File

@ -15,49 +15,14 @@ import networkx as nx
from jinja2 import Template
logger = logging.getLogger('soil')
# def load_network(network_params, dir_path=None):
# G = nx.Graph()
# if not network_params:
# return G
# if 'path' in network_params:
# path = network_params['path']
# if dir_path and not os.path.isabs(path):
# path = os.path.join(dir_path, path)
# extension = os.path.splitext(path)[1][1:]
# kwargs = {}
# if extension == 'gexf':
# kwargs['version'] = '1.2draft'
# kwargs['node_type'] = int
# try:
# method = getattr(nx.readwrite, 'read_' + extension)
# except AttributeError:
# raise AttributeError('Unknown format')
# G = method(path, **kwargs)
# elif 'generator' in network_params:
# net_args = network_params.copy()
# net_gen = net_args.pop('generator')
# if dir_path not in sys.path:
# sys.path.append(dir_path)
# method = deserializer(net_gen,
# known_modules=['networkx.generators',])
# G = method(**net_args)
# return G
logger = logging.getLogger("soil")
def load_file(infile):
folder = os.path.dirname(infile)
if folder not in sys.path:
sys.path.append(folder)
with open(infile, 'r') as f:
with open(infile, "r") as f:
return list(chain.from_iterable(map(expand_template, load_string(f))))
@ -66,14 +31,15 @@ def load_string(string):
def expand_template(config):
if 'template' not in config:
if "template" not in config:
yield config
return
if 'vars' not in config:
raise ValueError(('You must provide a definition of variables'
' for the template.'))
if "vars" not in config:
raise ValueError(
("You must provide a definition of variables" " for the template.")
)
template = config['template']
template = config["template"]
if not isinstance(template, str):
template = yaml.dump(template)
@ -85,9 +51,9 @@ def expand_template(config):
blank_str = template.render({k: 0 for k in params[0].keys()})
blank = list(load_string(blank_str))
if len(blank) > 1:
raise ValueError('Templates must not return more than one configuration')
if 'name' in blank[0]:
raise ValueError('Templates cannot be named, use group instead')
raise ValueError("Templates must not return more than one configuration")
if "name" in blank[0]:
raise ValueError("Templates cannot be named, use group instead")
for ps in params:
string = template.render(ps)
@ -96,32 +62,32 @@ def expand_template(config):
def params_for_template(config):
sampler_config = config.get('sampler', {'N': 100})
sampler = sampler_config.pop('method', 'SALib.sample.morris.sample')
sampler_config = config.get("sampler", {"N": 100})
sampler = sampler_config.pop("method", "SALib.sample.morris.sample")
sampler = deserializer(sampler)
bounds = config['vars']['bounds']
bounds = config["vars"]["bounds"]
problem = {
'num_vars': len(bounds),
'names': list(bounds.keys()),
'bounds': list(v for v in bounds.values())
"num_vars": len(bounds),
"names": list(bounds.keys()),
"bounds": list(v for v in bounds.values()),
}
samples = sampler(problem, **sampler_config)
lists = config['vars'].get('lists', {})
lists = config["vars"].get("lists", {})
names = list(lists.keys())
values = list(lists.values())
combs = list(product(*values))
allnames = names + problem['names']
allvalues = [(list(i[0])+list(i[1])) for i in product(combs, samples)]
allnames = names + problem["names"]
allvalues = [(list(i[0]) + list(i[1])) for i in product(combs, samples)]
params = list(map(lambda x: dict(zip(allnames, x)), allvalues))
return params
def load_files(*patterns, **kwargs):
for pattern in patterns:
for i in glob(pattern, **kwargs):
for i in glob(pattern, **kwargs, recursive=True):
for cfg in load_file(i):
path = os.path.abspath(i)
yield Config.from_raw(cfg), path
@ -136,22 +102,24 @@ def load_config(cfg):
yield from load_files(cfg)
builtins = importlib.import_module('builtins')
builtins = importlib.import_module("builtins")
KNOWN_MODULES = ['soil', ]
KNOWN_MODULES = [
"soil",
]
def name(value, known_modules=KNOWN_MODULES):
'''Return a name that can be imported, to serialize/deserialize an object'''
"""Return a name that can be imported, to serialize/deserialize an object"""
if value is None:
return 'None'
return "None"
if not isinstance(value, type): # Get the class name first
value = type(value)
tname = value.__name__
if hasattr(builtins, tname):
return tname
modname = value.__module__
if modname == '__main__':
if modname == "__main__":
return tname
if known_modules and modname in known_modules:
return tname
@ -161,17 +129,17 @@ def name(value, known_modules=KNOWN_MODULES):
module = importlib.import_module(kmod)
if hasattr(module, tname):
return tname
return '{}.{}'.format(modname, tname)
return "{}.{}".format(modname, tname)
def serializer(type_):
if type_ != 'str' and hasattr(builtins, type_):
if type_ != "str" and hasattr(builtins, type_):
return repr
return lambda x: x
def serialize(v, known_modules=KNOWN_MODULES):
'''Get a text representation of an object.'''
"""Get a text representation of an object."""
tname = name(v, known_modules=known_modules)
func = serializer(tname)
return func(v), tname
@ -196,9 +164,9 @@ IS_CLASS = re.compile(r"<class '(.*)'>")
def deserializer(type_, known_modules=KNOWN_MODULES):
if type(type_) != str: # Already deserialized
return type_
if type_ == 'str':
return lambda x='': x
if type_ == 'None':
if type_ == "str":
return lambda x="": x
if type_ == "None":
return lambda x=None: None
if hasattr(builtins, type_): # Check if it's a builtin type
cls = getattr(builtins, type_)
@ -208,8 +176,8 @@ def deserializer(type_, known_modules=KNOWN_MODULES):
modname, tname = match.group(1).rsplit(".", 1)
module = importlib.import_module(modname)
cls = getattr(module, tname)
return getattr(cls, 'deserialize', cls)
return getattr(cls, "deserialize", cls)
# Otherwise, see if we can find the module and the class
options = []
@ -217,7 +185,7 @@ def deserializer(type_, known_modules=KNOWN_MODULES):
if mod:
options.append((mod, type_))
if '.' in type_: # Fully qualified module
if "." in type_: # Fully qualified module
module, type_ = type_.rsplit(".", 1)
options.append((module, type_))
@ -226,27 +194,37 @@ def deserializer(type_, known_modules=KNOWN_MODULES):
try:
module = importlib.import_module(modname)
cls = getattr(module, tname)
return getattr(cls, 'deserialize', cls)
return getattr(cls, "deserialize", cls)
except (ImportError, AttributeError) as ex:
errors.append((modname, tname, ex))
raise Exception('Could not find type {}. Tried: {}'.format(type_, errors))
raise ValueError('Could not find type "{}". Tried: {}'.format(type_, errors))
def deserialize(type_, value=None, **kwargs):
'''Get an object from a text representation'''
def deserialize(type_, value=None, globs=None, **kwargs):
"""Get an object from a text representation"""
if not isinstance(type_, str):
return type_
des = deserializer(type_, **kwargs)
if globs and type_ in globs:
des = globs[type_]
else:
try:
des = deserializer(type_, **kwargs)
except ValueError as ex:
try:
des = eval(type_)
except Exception:
raise ex
if value is None:
return des
return des(value)
def deserialize_all(names, *args, known_modules=KNOWN_MODULES, **kwargs):
'''Return the list of deserialized objects'''
"""Return the list of deserialized objects"""
# TODO: remove
print("SERIALIZATION", kwargs)
objects = []
for name in names:
mod = deserialize(name, known_modules=known_modules)
objects.append(mod(*args, **kwargs))
return objects

View File

@ -1,5 +1,5 @@
import os
from time import time as current_time, strftime
from time import time as current_time, strftime
import importlib
import sys
import yaml
@ -11,22 +11,21 @@ import networkx as nx
from textwrap import dedent
from dataclasses import dataclass, field, asdict
from typing import Any, Dict, Union, Optional
from typing import Any, Dict, Union, Optional, List
from networkx.readwrite import json_graph
from functools import partial
import pickle
from . import serialization, utils, basestring, agents
from . import serialization, exporters, utils, basestring, agents
from .environment import Environment
from .utils import logger, run_and_return_exceptions
from .exporters import default
from .time import INFINITY
from .config import Config, convert_old
#TODO: change documentation for simulation
# TODO: change documentation for simulation
@dataclass
class Simulation:
"""
@ -35,74 +34,105 @@ class Simulation:
config (optional): :class:`config.Config`
name of the Simulation
kwargs: parameters to use to initialize a new configuration, if one has not been provided.
kwargs: parameters to use to initialize a new configuration, if one not been provided.
"""
version: str = '2'
name: str = 'Unnamed simulation'
description: Optional[str] = ''
version: str = "2"
name: str = "Unnamed simulation"
description: Optional[str] = ""
group: str = None
model_class: Union[str, type] = 'soil.Environment'
model_class: Union[str, type] = "soil.Environment"
model_params: dict = field(default_factory=dict)
seed: str = field(default_factory=lambda: current_time())
dir_path: str = field(default_factory=lambda: os.getcwd())
max_time: float = float('inf')
max_time: float = float("inf")
max_steps: int = -1
interval: int = 1
num_trials: int = 3
parallel: Optional[bool] = None
exporters: Optional[List[str]] = field(default_factory=list)
outdir: Optional[str] = None
exporter_params: Optional[Dict[str, Any]] = field(default_factory=dict)
dry_run: bool = False
extra: Dict[str, Any] = field(default_factory=dict)
@classmethod
def from_dict(cls, env):
def from_dict(cls, env, **kwargs):
ignored = {k: v for k, v in env.items()
if k not in inspect.signature(cls).parameters}
ignored = {
k: v for k, v in env.items() if k not in inspect.signature(cls).parameters
}
kwargs = {k:v for k, v in env.items() if k not in ignored}
d = {k: v for k, v in env.items() if k not in ignored}
if ignored:
kwargs.setdefault('extra', {}).update(ignored)
d.setdefault("extra", {}).update(ignored)
if ignored:
print(f'Warning: Ignoring these parameters (added to "extra"): { ignored }')
d.update(kwargs)
return cls(**kwargs)
return cls(**d)
def run_simulation(self, *args, **kwargs):
return self.run(*args, **kwargs)
def run(self, *args, **kwargs):
'''Run the simulation and return the list of resulting environments'''
logger.info(dedent('''
"""Run the simulation and return the list of resulting environments"""
logger.info(
dedent(
"""
Simulation:
---
''') +
self.to_yaml())
"""
)
+ self.to_yaml()
)
return list(self.run_gen(*args, **kwargs))
def run_gen(self, parallel=False, dry_run=False,
exporters=[default, ], outdir=None, exporter_params={},
log_level=None,
**kwargs):
'''Run the simulation and yield the resulting environments.'''
def run_gen(
self,
parallel=False,
dry_run=None,
exporters=None,
outdir=None,
exporter_params={},
log_level=None,
**kwargs,
):
"""Run the simulation and yield the resulting environments."""
if log_level:
logger.setLevel(log_level)
logger.info('Using exporters: %s', exporters or [])
logger.info('Output directory: %s', outdir)
exporters = serialization.deserialize_all(exporters,
simulation=self,
known_modules=['soil.exporters', ],
dry_run=dry_run,
outdir=outdir,
**exporter_params)
outdir = outdir or self.outdir
logger.info("Using exporters: %s", exporters or [])
logger.info("Output directory: %s", outdir)
if dry_run is None:
dry_run = self.dry_run
if exporters is None:
exporters = self.exporters
if not exporter_params:
exporter_params = self.exporter_params
with utils.timer('simulation {}'.format(self.name)):
exporters = serialization.deserialize_all(
exporters,
simulation=self,
known_modules=[
"soil.exporters",
],
dry_run=dry_run,
outdir=outdir,
**exporter_params,
)
with utils.timer("simulation {}".format(self.name)):
for exporter in exporters:
exporter.sim_start()
for env in utils.run_parallel(func=self.run_trial,
iterable=range(int(self.num_trials)),
parallel=parallel,
log_level=log_level,
**kwargs):
for env in utils.run_parallel(
func=self.run_trial,
iterable=range(int(self.num_trials)),
parallel=parallel,
log_level=log_level,
**kwargs,
):
for exporter in exporters:
exporter.trial_start(env)
@ -115,28 +145,36 @@ class Simulation:
for exporter in exporters:
exporter.sim_end()
def get_env(self, trial_id=0, **kwargs):
'''Create an environment for a trial of the simulation'''
def get_env(self, trial_id=0, model_params=None, **kwargs):
"""Create an environment for a trial of the simulation"""
def deserialize_reporters(reporters):
for (k, v) in reporters.items():
if isinstance(v, str) and v.startswith('py:'):
reporters[k] = serialization.deserialize(value.lsplit(':', 1)[1])
if isinstance(v, str) and v.startswith("py:"):
reporters[k] = serialization.deserialize(v.split(":", 1)[1])
return reporters
model_params = self.model_params.copy()
model_params.update(kwargs)
params = self.model_params.copy()
if model_params:
params.update(model_params)
params.update(kwargs)
agent_reporters = deserialize_reporters(model_params.pop('agent_reporters', {}))
model_reporters = deserialize_reporters(model_params.pop('model_reporters', {}))
agent_reporters = deserialize_reporters(params.pop("agent_reporters", {}))
model_reporters = deserialize_reporters(params.pop("model_reporters", {}))
env = serialization.deserialize(self.model_class)
return env(id=f'{self.name}_trial_{trial_id}',
seed=f'{self.seed}_trial_{trial_id}',
dir_path=self.dir_path,
agent_reporters=agent_reporters,
model_reporters=model_reporters,
**model_params)
env = serialization.deserialize(self.model_class)
return env(
id=f"{self.name}_trial_{trial_id}",
seed=f"{self.seed}_trial_{trial_id}",
dir_path=self.dir_path,
agent_reporters=agent_reporters,
model_reporters=model_reporters,
**params,
)
def run_trial(self, trial_id=None, until=None, log_file=False, log_level=logging.INFO, **opts):
def run_trial(
self, trial_id=None, until=None, log_file=False, log_level=logging.INFO, **opts
):
"""
Run a single trial of the simulation
@ -145,73 +183,78 @@ class Simulation:
logger.setLevel(log_level)
model = self.get_env(trial_id, **opts)
trial_id = trial_id if trial_id is not None else current_time()
with utils.timer('Simulation {} trial {}'.format(self.name, trial_id)):
return self.run_model(model=model, trial_id=trial_id, until=until, log_level=log_level)
with utils.timer("Simulation {} trial {}".format(self.name, trial_id)):
return self.run_model(
model=model, trial_id=trial_id, until=until, log_level=log_level
)
def run_model(self, model, until=None, **opts):
# Set-up trial environment and graph
until = float(until or self.max_time or 'inf')
until = float(until or self.max_time or "inf")
# Set up agents on nodes
def is_done():
return False
if until and hasattr(model.schedule, 'time'):
if until and hasattr(model.schedule, "time"):
prev = is_done
def is_done():
return prev() or model.schedule.time >= until
if self.max_steps and self.max_steps > 0 and hasattr(model.schedule, 'steps'):
if self.max_steps and self.max_steps > 0 and hasattr(model.schedule, "steps"):
prev_steps = is_done
def is_done():
return prev_steps() or model.schedule.steps >= self.max_steps
newline = '\n'
logger.info(dedent(f'''
newline = "\n"
logger.info(
dedent(
f"""
Model stats:
Agents (total: { model.schedule.get_agent_count() }):
- { (newline + ' - ').join(str(a) for a in model.schedule.agents) }'''
f'''
- { (newline + ' - ').join(str(a) for a in model.schedule.agents) }
Topologies (size):
- { dict( (k, len(v)) for (k, v) in model.topologies.items()) }
''' if getattr(model, "topologies", None) else ''
))
Topology size: { len(model.G) if hasattr(model, "G") else 0 }
"""
)
)
while not is_done():
utils.logger.debug(f'Simulation time {model.schedule.time}/{until}. Next: {getattr(model.schedule, "next_time", model.schedule.time + self.interval)}')
utils.logger.debug(
f'Simulation time {model.schedule.time}/{until}. Next: {getattr(model.schedule, "next_time", model.schedule.time + self.interval)}'
)
model.step()
return model
def to_dict(self):
d = asdict(self)
if not isinstance(d['model_class'], str):
d['model_class'] = serialization.name(d['model_class'])
d['model_params'] = serialization.serialize_dict(d['model_params'])
d['dir_path'] = str(d['dir_path'])
d['version'] = '2'
if not isinstance(d["model_class"], str):
d["model_class"] = serialization.name(d["model_class"])
d["model_params"] = serialization.serialize_dict(d["model_params"])
d["dir_path"] = str(d["dir_path"])
d["version"] = "2"
return d
def to_yaml(self):
return yaml.dump(self.to_dict())
def iter_from_config(*cfgs):
def iter_from_config(*cfgs, **kwargs):
for config in cfgs:
configs = list(serialization.load_config(config))
for config, path in configs:
d = dict(config)
if 'dir_path' not in d:
d['dir_path'] = os.path.dirname(path)
yield Simulation.from_dict(d)
if "dir_path" not in d:
d["dir_path"] = os.path.dirname(path)
yield Simulation.from_dict(d, **kwargs)
def from_config(conf_or_path):
lst = list(iter_from_config(conf_or_path))
if len(lst) > 1:
raise AttributeError('Provide only one configuration')
raise AttributeError("Provide only one configuration")
return lst[0]

View File

@ -6,7 +6,8 @@ from .utils import logger
from mesa import Agent as MesaAgent
INFINITY = float('inf')
INFINITY = float("inf")
class When:
def __init__(self, time):
@ -42,7 +43,7 @@ class TimedActivation(BaseScheduler):
self._next = {}
self._queue = []
self.next_time = 0
self.logger = logger.getChild(f'time_{ self.model }')
self.logger = logger.getChild(f"time_{ self.model }")
def add(self, agent: MesaAgent, when=None):
if when is None:
@ -51,7 +52,7 @@ class TimedActivation(BaseScheduler):
self._queue.remove((self._next[agent.unique_id], agent.unique_id))
del self._agents[agent.unique_id]
heapify(self._queue)
heappush(self._queue, (when, agent.unique_id))
self._next[agent.unique_id] = when
super().add(agent)
@ -62,7 +63,7 @@ class TimedActivation(BaseScheduler):
an agent will signal when it wants to be scheduled next.
"""
self.logger.debug(f'Simulation step {self.next_time}')
self.logger.debug(f"Simulation step {self.next_time}")
if not self.model.running:
return
@ -71,18 +72,22 @@ class TimedActivation(BaseScheduler):
while self._queue and self._queue[0][0] == self.time:
(when, agent_id) = heappop(self._queue)
self.logger.debug(f'Stepping agent {agent_id}')
self.logger.debug(f"Stepping agent {agent_id}")
agent = self._agents[agent_id]
returned = agent.step()
if not agent.alive:
if not getattr(agent, "alive", True):
self.remove(agent)
continue
when = (returned or Delta(1)).abs(self.time)
if when < self.time:
raise Exception("Cannot schedule an agent for a time in the past ({} < {})".format(when, self.time))
raise Exception(
"Cannot schedule an agent for a time in the past ({} < {})".format(
when, self.time
)
)
self._next[agent_id] = when
heappush(self._queue, (when, agent_id))
@ -96,4 +101,4 @@ class TimedActivation(BaseScheduler):
return self.time
self.next_time = self._queue[0][0]
self.logger.debug(f'Next step: {self.next_time}')
self.logger.debug(f"Next step: {self.next_time}")

View File

@ -4,57 +4,77 @@ import os
import traceback
from functools import partial
from shutil import copyfile
from shutil import copyfile, move
from multiprocessing import Pool
from contextlib import contextmanager
logger = logging.getLogger('soil')
logger = logging.getLogger("soil")
logger.setLevel(logging.INFO)
timeformat = "%H:%M:%S"
if os.environ.get('SOIL_VERBOSE', ''):
if os.environ.get("SOIL_VERBOSE", ""):
logformat = "[%(levelname)-5.5s][%(asctime)s][%(name)s]: %(message)s"
else:
logformat = "[%(levelname)-5.5s][%(asctime)s] %(message)s"
logFormatter = logging.Formatter(logformat, timeformat)
consoleHandler = logging.StreamHandler()
consoleHandler.setFormatter(logFormatter)
logger.addHandler(consoleHandler)
logging.basicConfig(
level=logging.INFO,
handlers=[
consoleHandler,
],
)
@contextmanager
def timer(name='task', pre="", function=logger.info, to_object=None):
def timer(name="task", pre="", function=logger.info, to_object=None):
start = current_time()
function('{}Starting {} at {}.'.format(pre, name,
strftime("%X", gmtime(start))))
function("{}Starting {} at {}.".format(pre, name, strftime("%X", gmtime(start))))
yield start
end = current_time()
function('{}Finished {} at {} in {} seconds'.format(pre, name,
strftime("%X", gmtime(end)),
str(end-start)))
function(
"{}Finished {} at {} in {} seconds".format(
pre, name, strftime("%X", gmtime(end)), str(end - start)
)
)
if to_object:
to_object.start = start
to_object.end = end
def safe_open(path, mode='r', backup=True, **kwargs):
def try_backup(path, move=False):
if not os.path.exists(path):
return None
outdir = os.path.dirname(path)
if outdir and not os.path.exists(outdir):
os.makedirs(outdir)
if backup and 'w' in mode and os.path.exists(path):
creation = os.path.getctime(path)
stamp = strftime('%Y-%m-%d_%H.%M.%S', localtime(creation))
creation = os.path.getctime(path)
stamp = strftime("%Y-%m-%d_%H.%M.%S", localtime(creation))
backup_dir = os.path.join(outdir, 'backup')
if not os.path.exists(backup_dir):
os.makedirs(backup_dir)
newpath = os.path.join(backup_dir, '{}@{}'.format(os.path.basename(path),
stamp))
backup_dir = os.path.join(outdir, "backup")
if not os.path.exists(backup_dir):
os.makedirs(backup_dir)
newpath = os.path.join(
backup_dir, "{}@{}".format(os.path.basename(path), stamp)
)
if move:
move(path, newpath)
else:
copyfile(path, newpath)
return newpath
def safe_open(path, mode="r", backup=True, **kwargs):
outdir = os.path.dirname(path)
if outdir and not os.path.exists(outdir):
os.makedirs(outdir)
if backup and "w" in mode:
try_backup(path)
return open(path, mode=mode, **kwargs)
@ -63,24 +83,26 @@ def open_or_reuse(f, *args, **kwargs):
try:
with safe_open(f, *args, **kwargs) as f:
yield f
except (AttributeError, TypeError):
except (AttributeError, TypeError) as ex:
yield f
def flatten_dict(d):
if not isinstance(d, dict):
return d
return dict(_flatten_dict(d))
def _flatten_dict(d, prefix=''):
def _flatten_dict(d, prefix=""):
if not isinstance(d, dict):
# print('END:', prefix, d)
yield prefix, d
return
if prefix:
prefix = prefix + '.'
prefix = prefix + "."
for k, v in d.items():
# print(k, v)
res = list(_flatten_dict(v, prefix='{}{}'.format(prefix, k)))
res = list(_flatten_dict(v, prefix="{}{}".format(prefix, k)))
# print('RES:', res)
yield from res
@ -92,7 +114,7 @@ def unflatten_dict(d):
if not isinstance(k, str):
target[k] = v
continue
tokens = k.split('.')
tokens = k.split(".")
if len(tokens) < 2:
target[k] = v
continue
@ -105,27 +127,28 @@ def unflatten_dict(d):
def run_and_return_exceptions(func, *args, **kwargs):
'''
"""
A wrapper for run_trial that catches exceptions and returns them.
It is meant for async simulations.
'''
"""
try:
return func(*args, **kwargs)
except Exception as ex:
if ex.__cause__ is not None:
ex = ex.__cause__
ex.message = ''.join(traceback.format_exception(type(ex), ex, ex.__traceback__)[:])
ex.message = "".join(
traceback.format_exception(type(ex), ex, ex.__traceback__)[:]
)
return ex
def run_parallel(func, iterable, parallel=False, **kwargs):
if parallel and not os.environ.get('SOIL_DEBUG', None):
if parallel and not os.environ.get("SOIL_DEBUG", None):
p = Pool()
wrapped_func = partial(run_and_return_exceptions,
func, **kwargs)
wrapped_func = partial(run_and_return_exceptions, func, **kwargs)
for i in p.imap_unordered(wrapped_func, iterable):
if isinstance(i, Exception):
logger.error('Trial failed:\n\t%s', i.message)
logger.error("Trial failed:\n\t%s", i.message)
continue
yield i
else:

View File

@ -4,7 +4,7 @@ import logging
logger = logging.getLogger(__name__)
ROOT = os.path.dirname(__file__)
DEFAULT_FILE = os.path.join(ROOT, 'VERSION')
DEFAULT_FILE = os.path.join(ROOT, "VERSION")
def read_version(versionfile=DEFAULT_FILE):
@ -12,9 +12,10 @@ def read_version(versionfile=DEFAULT_FILE):
with open(versionfile) as f:
return f.read().strip()
except IOError: # pragma: no cover
logger.error(('Running an unknown version of {}.'
'Be careful!.').format(__name__))
return '0.0'
logger.error(
("Running an unknown version of {}." "Be careful!.").format(__name__)
)
return "0.0"
__version__ = read_version()

View File

@ -1,5 +1,6 @@
from mesa.visualization.UserParam import UserSettableParameter
class UserSettableParameter(UserSettableParameter):
def __str__(self):
return self.value

View File

@ -20,6 +20,7 @@ from tornado.concurrent import run_on_executor
from concurrent.futures import ThreadPoolExecutor
from ..simulation import Simulation
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
@ -31,140 +32,183 @@ LOGGING_INTERVAL = 0.5
# Workaround to let Soil load the required modules
sys.path.append(ROOT)
class PageHandler(tornado.web.RequestHandler):
""" Handler for the HTML template which holds the visualization. """
"""Handler for the HTML template which holds the visualization."""
def get(self):
self.render('index.html', port=self.application.port,
name=self.application.name)
self.render(
"index.html", port=self.application.port, name=self.application.name
)
class SocketHandler(tornado.websocket.WebSocketHandler):
""" Handler for websocket. """
"""Handler for websocket."""
executor = ThreadPoolExecutor(max_workers=MAX_WORKERS)
def open(self):
if self.application.verbose:
logger.info('Socket opened!')
logger.info("Socket opened!")
def check_origin(self, origin):
return True
def on_message(self, message):
""" Receiving a message from the websocket, parse, and act accordingly. """
"""Receiving a message from the websocket, parse, and act accordingly."""
msg = tornado.escape.json_decode(message)
if msg['type'] == 'config_file':
if msg["type"] == "config_file":
if self.application.verbose:
print(msg['data'])
print(msg["data"])
self.config = list(yaml.load_all(msg['data']))
self.config = list(yaml.load_all(msg["data"]))
if len(self.config) > 1:
error = 'Please, provide only one configuration.'
error = "Please, provide only one configuration."
if self.application.verbose:
logger.error(error)
self.write_message({'type': 'error',
'error': error})
self.write_message({"type": "error", "error": error})
return
self.config = self.config[0]
self.send_log('INFO.' + self.simulation_name,
'Using config: {name}'.format(name=self.config['name']))
self.send_log(
"INFO." + self.simulation_name,
"Using config: {name}".format(name=self.config["name"]),
)
if 'visualization_params' in self.config:
self.write_message({'type': 'visualization_params',
'data': self.config['visualization_params']})
self.name = self.config['name']
if "visualization_params" in self.config:
self.write_message(
{
"type": "visualization_params",
"data": self.config["visualization_params"],
}
)
self.name = self.config["name"]
self.run_simulation()
settings = []
for key in self.config['environment_params']:
if type(self.config['environment_params'][key]) == float or type(self.config['environment_params'][key]) == int:
if self.config['environment_params'][key] <= 1:
setting_type = 'number'
for key in self.config["environment_params"]:
if (
type(self.config["environment_params"][key]) == float
or type(self.config["environment_params"][key]) == int
):
if self.config["environment_params"][key] <= 1:
setting_type = "number"
else:
setting_type = 'great_number'
elif type(self.config['environment_params'][key]) == bool:
setting_type = 'boolean'
setting_type = "great_number"
elif type(self.config["environment_params"][key]) == bool:
setting_type = "boolean"
else:
setting_type = 'undefined'
setting_type = "undefined"
settings.append({
'label': key,
'type': setting_type,
'value': self.config['environment_params'][key]
})
settings.append(
{
"label": key,
"type": setting_type,
"value": self.config["environment_params"][key],
}
)
self.write_message({'type': 'settings',
'data': settings})
self.write_message({"type": "settings", "data": settings})
elif msg['type'] == 'get_trial':
elif msg["type"] == "get_trial":
if self.application.verbose:
logger.info('Trial {} requested!'.format(msg['data']))
self.send_log('INFO.' + __name__, 'Trial {} requested!'.format(msg['data']))
self.write_message({'type': 'get_trial',
'data': self.get_trial(int(msg['data']))})
logger.info("Trial {} requested!".format(msg["data"]))
self.send_log("INFO." + __name__, "Trial {} requested!".format(msg["data"]))
self.write_message(
{"type": "get_trial", "data": self.get_trial(int(msg["data"]))}
)
elif msg['type'] == 'run_simulation':
elif msg["type"] == "run_simulation":
if self.application.verbose:
logger.info('Running new simulation for {name}'.format(name=self.config['name']))
self.send_log('INFO.' + self.simulation_name, 'Running new simulation for {name}'.format(name=self.config['name']))
self.config['environment_params'] = msg['data']
logger.info(
"Running new simulation for {name}".format(name=self.config["name"])
)
self.send_log(
"INFO." + self.simulation_name,
"Running new simulation for {name}".format(name=self.config["name"]),
)
self.config["environment_params"] = msg["data"]
self.run_simulation()
elif msg['type'] == 'download_gexf':
G = self.trials[ int(msg['data']) ].history_to_graph()
elif msg["type"] == "download_gexf":
G = self.trials[int(msg["data"])].history_to_graph()
for node in G.nodes():
if 'pos' in G.nodes[node]:
G.nodes[node]['viz'] = {"position": {"x": G.nodes[node]['pos'][0], "y": G.nodes[node]['pos'][1], "z": 0.0}}
del (G.nodes[node]['pos'])
writer = nx.readwrite.gexf.GEXFWriter(version='1.2draft')
if "pos" in G.nodes[node]:
G.nodes[node]["viz"] = {
"position": {
"x": G.nodes[node]["pos"][0],
"y": G.nodes[node]["pos"][1],
"z": 0.0,
}
}
del G.nodes[node]["pos"]
writer = nx.readwrite.gexf.GEXFWriter(version="1.2draft")
writer.add_graph(G)
self.write_message({'type': 'download_gexf',
'filename': self.config['name'] + '_trial_' + str(msg['data']),
'data': tostring(writer.xml).decode(writer.encoding) })
self.write_message(
{
"type": "download_gexf",
"filename": self.config["name"] + "_trial_" + str(msg["data"]),
"data": tostring(writer.xml).decode(writer.encoding),
}
)
elif msg['type'] == 'download_json':
G = self.trials[ int(msg['data']) ].history_to_graph()
elif msg["type"] == "download_json":
G = self.trials[int(msg["data"])].history_to_graph()
for node in G.nodes():
if 'pos' in G.nodes[node]:
G.nodes[node]['viz'] = {"position": {"x": G.nodes[node]['pos'][0], "y": G.nodes[node]['pos'][1], "z": 0.0}}
del (G.nodes[node]['pos'])
self.write_message({'type': 'download_json',
'filename': self.config['name'] + '_trial_' + str(msg['data']),
'data': nx.node_link_data(G) })
if "pos" in G.nodes[node]:
G.nodes[node]["viz"] = {
"position": {
"x": G.nodes[node]["pos"][0],
"y": G.nodes[node]["pos"][1],
"z": 0.0,
}
}
del G.nodes[node]["pos"]
self.write_message(
{
"type": "download_json",
"filename": self.config["name"] + "_trial_" + str(msg["data"]),
"data": nx.node_link_data(G),
}
)
else:
if self.application.verbose:
logger.info('Unexpected message!')
logger.info("Unexpected message!")
def update_logging(self):
try:
if (not self.log_capture_string.closed and self.log_capture_string.getvalue()):
for i in range(len(self.log_capture_string.getvalue().split('\n')) - 1):
self.send_log('INFO.' + self.simulation_name, self.log_capture_string.getvalue().split('\n')[i])
if (
not self.log_capture_string.closed
and self.log_capture_string.getvalue()
):
for i in range(len(self.log_capture_string.getvalue().split("\n")) - 1):
self.send_log(
"INFO." + self.simulation_name,
self.log_capture_string.getvalue().split("\n")[i],
)
self.log_capture_string.truncate(0)
self.log_capture_string.seek(0)
finally:
if self.capture_logging:
tornado.ioloop.IOLoop.current().call_later(LOGGING_INTERVAL, self.update_logging)
tornado.ioloop.IOLoop.current().call_later(
LOGGING_INTERVAL, self.update_logging
)
def on_close(self):
if self.application.verbose:
logger.info('Socket closed!')
logger.info("Socket closed!")
def send_log(self, logger, logging):
self.write_message({'type': 'log',
'logger': logger,
'logging': logging})
self.write_message({"type": "log", "logger": logger, "logging": logging})
@property
def simulation_name(self):
return self.config.get('name', 'NoSimulationRunning')
return self.config.get("name", "NoSimulationRunning")
@run_on_executor
def nonblocking(self, config):
@ -174,28 +218,31 @@ class SocketHandler(tornado.websocket.WebSocketHandler):
@tornado.gen.coroutine
def run_simulation(self):
# Run simulation and capture logs
logger.info('Running simulation!')
if 'visualization_params' in self.config:
del self.config['visualization_params']
logger.info("Running simulation!")
if "visualization_params" in self.config:
del self.config["visualization_params"]
with self.logging(self.simulation_name):
try:
config = dict(**self.config)
config['outdir'] = os.path.join(self.application.outdir, config['name'])
config['dump'] = self.application.dump
config["outdir"] = os.path.join(self.application.outdir, config["name"])
config["dump"] = self.application.dump
self.trials = yield self.nonblocking(config)
self.write_message({'type': 'trials',
'data': list(trial.name for trial in self.trials) })
self.write_message(
{
"type": "trials",
"data": list(trial.name for trial in self.trials),
}
)
except Exception as ex:
error = 'Something went wrong:\n\t{}'.format(ex)
error = "Something went wrong:\n\t{}".format(ex)
logging.info(error)
self.write_message({'type': 'error',
'error': error})
self.send_log('ERROR.' + self.simulation_name, error)
self.write_message({"type": "error", "error": error})
self.send_log("ERROR." + self.simulation_name, error)
def get_trial(self, trial):
logger.info('Available trials: %s ' % len(self.trials))
logger.info('Ask for : %s' % trial)
logger.info("Available trials: %s " % len(self.trials))
logger.info("Ask for : %s" % trial)
trial = self.trials[trial]
G = trial.history_to_graph()
return nx.node_link_data(G)
@ -215,25 +262,28 @@ class SocketHandler(tornado.websocket.WebSocketHandler):
self.logger_application.removeHandler(ch)
self.capture_logging = False
return self.capture_logging
class ModularServer(tornado.web.Application):
""" Main visualization application. """
"""Main visualization application."""
port = 8001
page_handler = (r'/', PageHandler)
socket_handler = (r'/ws', SocketHandler)
static_handler = (r'/(.*)', tornado.web.StaticFileHandler,
{'path': os.path.join(ROOT, 'static')})
local_handler = (r'/local/(.*)', tornado.web.StaticFileHandler,
{'path': ''})
page_handler = (r"/", PageHandler)
socket_handler = (r"/ws", SocketHandler)
static_handler = (
r"/(.*)",
tornado.web.StaticFileHandler,
{"path": os.path.join(ROOT, "static")},
)
local_handler = (r"/local/(.*)", tornado.web.StaticFileHandler, {"path": ""})
handlers = [page_handler, socket_handler, static_handler, local_handler]
settings = {'debug': True,
'template_path': ROOT + '/templates'}
settings = {"debug": True, "template_path": ROOT + "/templates"}
def __init__(
self, dump=False, outdir="output", name="SOIL", verbose=True, *args, **kwargs
):
def __init__(self, dump=False, outdir='output', name='SOIL', verbose=True, *args, **kwargs):
self.verbose = verbose
self.name = name
self.dump = dump
@ -243,12 +293,12 @@ class ModularServer(tornado.web.Application):
super().__init__(self.handlers, **self.settings)
def launch(self, port=None):
""" Run the app. """
"""Run the app."""
if port is not None:
self.port = port
url = 'http://127.0.0.1:{PORT}'.format(PORT=self.port)
print('Interface starting at {url}'.format(url=url))
url = "http://127.0.0.1:{PORT}".format(PORT=self.port)
print("Interface starting at {url}".format(url=url))
self.listen(self.port)
# webbrowser.open(url)
tornado.ioloop.IOLoop.instance().start()
@ -263,12 +313,22 @@ def run(*args, **kwargs):
def main():
import argparse
parser = argparse.ArgumentParser(description='Visualization of a Graph Model')
parser = argparse.ArgumentParser(description="Visualization of a Graph Model")
parser.add_argument('--name', '-n', nargs=1, default='SOIL', help='name of the simulation')
parser.add_argument('--dump', '-d', help='dumping results in folder output', action='store_true')
parser.add_argument('--port', '-p', nargs=1, default=8001, help='port for launching the server')
parser.add_argument('--verbose', '-v', help='verbose mode', action='store_true')
parser.add_argument(
"--name", "-n", nargs=1, default="SOIL", help="name of the simulation"
)
parser.add_argument(
"--dump", "-d", help="dumping results in folder output", action="store_true"
)
parser.add_argument(
"--port", "-p", nargs=1, default=8001, help="port for launching the server"
)
parser.add_argument("--verbose", "-v", help="verbose mode", action="store_true")
args = parser.parse_args()
run(name=args.name, port=(args.port[0] if isinstance(args.port, list) else args.port), verbose=args.verbose)
run(
name=args.name,
port=(args.port[0] if isinstance(args.port, list) else args.port),
verbose=args.verbose,
)

View File

@ -2,4 +2,4 @@ from . import main
if __name__ == "__main__":
main()
main()

View File

@ -4,20 +4,33 @@ from simulator import Simulator
def run(simulator, name="SOIL", port=8001, verbose=False):
server = ModularServer(simulator, name=(name[0] if isinstance(name, list) else name), verbose=verbose)
server = ModularServer(
simulator, name=(name[0] if isinstance(name, list) else name), verbose=verbose
)
server.port = port
server.launch()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Visualization of a Graph Model')
parser = argparse.ArgumentParser(description="Visualization of a Graph Model")
parser.add_argument('--name', '-n', nargs=1, default='SOIL', help='name of the simulation')
parser.add_argument('--dump', '-d', help='dumping results in folder output', action='store_true')
parser.add_argument('--port', '-p', nargs=1, default=8001, help='port for launching the server')
parser.add_argument('--verbose', '-v', help='verbose mode', action='store_true')
parser.add_argument(
"--name", "-n", nargs=1, default="SOIL", help="name of the simulation"
)
parser.add_argument(
"--dump", "-d", help="dumping results in folder output", action="store_true"
)
parser.add_argument(
"--port", "-p", nargs=1, default=8001, help="port for launching the server"
)
parser.add_argument("--verbose", "-v", help="verbose mode", action="store_true")
args = parser.parse_args()
soil = Simulator(dump=args.dump)
run(soil, name=args.name, port=(args.port[0] if isinstance(args.port, list) else args.port), verbose=args.verbose)
run(
soil,
name=args.name,
port=(args.port[0] if isinstance(args.port, list) else args.port),
verbose=args.verbose,
)

View File

@ -9,17 +9,16 @@ interval: 1
seed: "CompleteSeed!"
model_class: Environment
model_params:
topologies:
default:
params:
generator: complete_graph
n: 4
topology:
params:
generator: complete_graph
n: 4
agents:
agent_class: CounterModel
state:
group: network
times: 1
topology: 'default'
topology: true
distribution:
- agent_class: CounterModel
weight: 0.25
@ -42,7 +41,7 @@ model_params:
fixed:
- agent_class: BaseAgent
hidden: true
topology: null
topology: false
state:
name: 'Environment Agent 1'
times: 10

View File

@ -4,12 +4,14 @@ import pytest
from soil import agents, environment
from soil import time as stime
class Dead(agents.FSM):
@agents.default_state
@agents.state
def only(self):
return self.die()
class TestMain(TestCase):
def test_die_raises_exception(self):
d = Dead(unique_id=0, model=environment.Environment())
@ -20,5 +22,5 @@ class TestMain(TestCase):
def test_die_returns_infinity(self):
d = Dead(unique_id=0, model=environment.Environment())
ret = d.step().abs(0)
print(ret, 'next')
print(ret, "next")
assert ret == stime.INFINITY

View File

@ -7,9 +7,9 @@ from os.path import join
from soil import simulation, serialization, config, network, agents, utils
ROOT = os.path.abspath(os.path.dirname(__file__))
EXAMPLES = join(ROOT, '..', 'examples')
EXAMPLES = join(ROOT, "..", "examples")
FORCE_TESTS = os.environ.get('FORCE_TESTS', '')
FORCE_TESTS = os.environ.get("FORCE_TESTS", "")
def isequal(a, b):
@ -24,7 +24,6 @@ def isequal(a, b):
class TestConfig(TestCase):
def test_conversion(self):
expected = serialization.load_file(join(ROOT, "complete_converted.yml"))[0]
old = serialization.load_file(join(ROOT, "old_complete.yml"))[0]
@ -38,7 +37,7 @@ class TestConfig(TestCase):
The configuration should not change after running
the simulation.
"""
config = serialization.load_file(join(EXAMPLES, 'complete.yml'))[0]
config = serialization.load_file(join(EXAMPLES, "complete.yml"))[0]
s = simulation.from_config(config)
init_config = copy.copy(s.to_dict())
@ -47,11 +46,8 @@ class TestConfig(TestCase):
# del nconfig['to
isequal(init_config, nconfig)
def test_topology_config(self):
netconfig = config.NetConfig(**{
'path': join(ROOT, 'test.gexf')
})
netconfig = config.NetConfig(**{"path": join(ROOT, "test.gexf")})
net = network.from_config(netconfig, dir_path=ROOT)
assert len(net.nodes) == 2
assert len(net.edges) == 1
@ -62,36 +58,33 @@ class TestConfig(TestCase):
network agents are initialized properly.
"""
cfg = {
'name': 'CounterAgent',
'network_params': {
'path': join(ROOT, 'test.gexf')
},
'agent_class': 'CounterModel',
"name": "CounterAgent",
"network_params": {"path": join(ROOT, "test.gexf")},
"agent_class": "CounterModel",
# 'states': [{'times': 10}, {'times': 20}],
'max_time': 2,
'dry_run': True,
'num_trials': 1,
'environment_params': {
}
"max_time": 2,
"dry_run": True,
"num_trials": 1,
"environment_params": {},
}
conf = config.convert_old(cfg)
s = simulation.from_config(conf)
env = s.get_env()
assert len(env.topologies['default'].nodes) == 2
assert len(env.topologies['default'].edges) == 1
assert len(env.G.nodes) == 2
assert len(env.G.edges) == 1
assert len(env.agents) == 2
assert env.agents[0].G == env.topologies['default']
assert env.agents[0].G == env.G
def test_agents_from_config(self):
'''We test that the known complete configuration produces
the right agents in the right groups'''
"""We test that the known complete configuration produces
the right agents in the right groups"""
cfg = serialization.load_file(join(ROOT, "complete_converted.yml"))[0]
s = simulation.from_config(cfg)
env = s.get_env()
assert len(env.topologies['default'].nodes) == 4
assert len(env.agents(group='network')) == 4
assert len(env.agents(group='environment')) == 1
assert len(env.G.nodes) == 4
assert len(env.agents(group="network")) == 4
assert len(env.agents(group="environment")) == 1
def test_yaml(self):
"""
@ -100,16 +93,17 @@ class TestConfig(TestCase):
Values not present in the original config file should have reasonable
defaults.
"""
with utils.timer('loading'):
config = serialization.load_file(join(EXAMPLES, 'complete.yml'))[0]
with utils.timer("loading"):
config = serialization.load_file(join(EXAMPLES, "complete.yml"))[0]
s = simulation.from_config(config)
with utils.timer('serializing'):
with utils.timer("serializing"):
serial = s.to_yaml()
with utils.timer('recovering'):
with utils.timer("recovering"):
recovered = yaml.load(serial, Loader=yaml.SafeLoader)
for (k, v) in config.items():
assert recovered[k] == v
def make_example_test(path, cfg):
def wrapped(self):
root = os.getcwd()
@ -133,18 +127,19 @@ def make_example_test(path, cfg):
# assert env.now <= config['max_time'] # But not further than allowed
# except KeyError:
# pass
return wrapped
def add_example_tests():
for config, path in serialization.load_files(
join(EXAMPLES, '*', '*.yml'),
join(EXAMPLES, '*.yml'),
join(EXAMPLES, "*", "*.yml"),
join(EXAMPLES, "*.yml"),
):
p = make_example_test(path=path, cfg=config)
fname = os.path.basename(path)
p.__name__ = 'test_example_file_%s' % fname
p.__doc__ = '%s should be a valid configuration' % fname
p.__name__ = "test_example_file_%s" % fname
p.__doc__ = "%s should be a valid configuration" % fname
setattr(TestConfig, p.__name__, p)
del p

View File

@ -5,9 +5,9 @@ from os.path import join
from soil import serialization, simulation, config
ROOT = os.path.abspath(os.path.dirname(__file__))
EXAMPLES = join(ROOT, '..', 'examples')
EXAMPLES = join(ROOT, "..", "examples")
FORCE_TESTS = os.environ.get('FORCE_TESTS', '')
FORCE_TESTS = os.environ.get("FORCE_TESTS", "")
class TestExamples(TestCase):
@ -23,31 +23,31 @@ def make_example_test(path, cfg):
s.max_steps = 100
s.num_trials = 1
assert isinstance(cfg, config.Config)
if getattr(cfg, 'skip_test', False) and not FORCE_TESTS:
self.skipTest('Example ignored.')
if getattr(cfg, "skip_test", False) and not FORCE_TESTS:
self.skipTest("Example ignored.")
envs = s.run_simulation(dry_run=True)
assert envs
for env in envs:
assert env
try:
n = cfg.model_params['network_params']['n']
n = cfg.model_params["network_params"]["n"]
assert len(list(env.network_agents)) == n
except KeyError:
pass
assert env.schedule.steps > 0 # It has run
assert env.schedule.steps <= s.max_steps # But not further than allowed
return wrapped
def add_example_tests():
for cfg, path in serialization.load_files(
join(EXAMPLES, '*', '*.yml'),
join(EXAMPLES, '*.yml'),
join(EXAMPLES, "**", "*.yml"),
):
p = make_example_test(path=path, cfg=config.Config.from_raw(cfg))
fname = os.path.basename(path)
p.__name__ = 'test_example_file_%s' % fname
p.__doc__ = '%s should be a valid configuration' % fname
p.__name__ = "test_example_file_%s" % fname
p.__doc__ = "%s should be a valid configuration" % fname
setattr(TestExamples, p.__name__, p)
del p

View File

@ -2,6 +2,7 @@ import os
import io
import tempfile
import shutil
import sqlite3
from unittest import TestCase
from soil import exporters
@ -40,14 +41,10 @@ class Exporters(TestCase):
num_trials = 5
max_time = 2
config = {
'name': 'exporter_sim',
'model_params': {
'agents': [{
'agent_class': agents.BaseAgent
}]
},
'max_time': max_time,
'num_trials': num_trials,
"name": "exporter_sim",
"model_params": {"agents": [{"agent_class": agents.BaseAgent}]},
"max_time": max_time,
"num_trials": num_trials,
}
s = simulation.from_config(config)
@ -64,40 +61,52 @@ class Exporters(TestCase):
assert Dummy.total_time == max_time * num_trials
def test_writing(self):
'''Try to write CSV, sqlite and YAML (without dry_run)'''
"""Try to write CSV, sqlite and YAML (without dry_run)"""
n_trials = 5
config = {
'name': 'exporter_sim',
'network_params': {
'generator': 'complete_graph',
'n': 4
},
'agent_class': 'CounterModel',
'max_time': 2,
'num_trials': n_trials,
'dry_run': False,
'environment_params': {}
"name": "exporter_sim",
"network_params": {"generator": "complete_graph", "n": 4},
"agent_class": "CounterModel",
"max_time": 2,
"num_trials": n_trials,
"dry_run": False,
"environment_params": {},
}
output = io.StringIO()
s = simulation.from_config(config)
tmpdir = tempfile.mkdtemp()
envs = s.run_simulation(exporters=[
exporters.default,
exporters.csv,
],
dry_run=False,
outdir=tmpdir,
exporter_params={'copy_to': output})
envs = s.run_simulation(
exporters=[
exporters.default,
exporters.csv,
],
model_params={
"agent_reporters": {"times": "times"},
"model_reporters": {
"constant": lambda x: 1,
},
},
dry_run=False,
outdir=tmpdir,
exporter_params={"copy_to": output},
)
result = output.getvalue()
simdir = os.path.join(tmpdir, s.group or '', s.name)
with open(os.path.join(simdir, '{}.dumped.yml'.format(s.name))) as f:
simdir = os.path.join(tmpdir, s.group or "", s.name)
with open(os.path.join(simdir, "{}.dumped.yml".format(s.name))) as f:
result = f.read()
assert result
try:
for e in envs:
with open(os.path.join(simdir, '{}.env.csv'.format(e.id))) as f:
db = sqlite3.connect(os.path.join(simdir, f"{s.name}.sqlite"))
cur = db.cursor()
agent_entries = cur.execute("SELECT * from agents").fetchall()
env_entries = cur.execute("SELECT * from env").fetchall()
assert len(agent_entries) > 0
assert len(env_entries) > 0
with open(os.path.join(simdir, "{}.env.csv".format(e.id))) as f:
result = f.read()
assert result
finally:

View File

@ -6,60 +6,55 @@ import networkx as nx
from functools import partial
from os.path import join
from soil import (simulation, Environment, agents, network, serialization,
utils, config)
from soil import simulation, Environment, agents, network, serialization, utils, config
from soil.time import Delta
ROOT = os.path.abspath(os.path.dirname(__file__))
EXAMPLES = join(ROOT, '..', 'examples')
EXAMPLES = join(ROOT, "..", "examples")
class CustomAgent(agents.FSM, agents.NetworkAgent):
@agents.default_state
@agents.state
def normal(self):
self.neighbors = self.count_agents(state_id='normal',
limit_neighbors=True)
self.neighbors = self.count_agents(state_id="normal", limit_neighbors=True)
@agents.state
def unreachable(self):
return
class TestMain(TestCase):
def test_empty_simulation(self):
"""A simulation with a base behaviour should do nothing"""
config = {
'model_params': {
'network_params': {
'path': join(ROOT, 'test.gexf')
},
'agent_class': 'BaseAgent',
"model_params": {
"network_params": {"path": join(ROOT, "test.gexf")},
"agent_class": "BaseAgent",
}
}
s = simulation.from_config(config)
s.run_simulation(dry_run=True)
def test_network_agent(self):
"""
The initial states should be applied to the agent and the
agent should be able to update its state."""
config = {
'name': 'CounterAgent',
'num_trials': 1,
'max_time': 2,
'model_params': {
'network_params': {
'generator': nx.complete_graph,
'n': 2,
"name": "CounterAgent",
"num_trials": 1,
"max_time": 2,
"model_params": {
"network_params": {
"generator": nx.complete_graph,
"n": 2,
},
'agent_class': 'CounterModel',
'states': {
0: {'times': 10},
1: {'times': 20},
"agent_class": "CounterModel",
"states": {
0: {"times": 10},
1: {"times": 20},
},
}
},
}
s = simulation.from_config(config)
@ -68,48 +63,41 @@ class TestMain(TestCase):
The initial states should be applied to the agent and the
agent should be able to update its state."""
config = {
'version': '2',
'name': 'CounterAgent',
'dry_run': True,
'num_trials': 1,
'max_time': 2,
'model_params': {
'topologies': {
'default': {
'path': join(ROOT, 'test.gexf')
}
"version": "2",
"name": "CounterAgent",
"dry_run": True,
"num_trials": 1,
"max_time": 2,
"model_params": {
"topology": {"path": join(ROOT, "test.gexf")},
"agents": {
"agent_class": "CounterModel",
"topology": True,
"fixed": [{"state": {"times": 10}}, {"state": {"times": 20}}],
},
'agents': {
'agent_class': 'CounterModel',
'topology': 'default',
'fixed': [{'state': {'times': 10}}, {'state': {'times': 20}}],
}
}
},
}
s = simulation.from_config(config)
env = s.get_env()
assert isinstance(env.agents[0], agents.CounterModel)
assert env.agents[0].G == env.topologies['default']
assert env.agents[0]['times'] == 10
assert env.agents[0]['times'] == 10
assert env.agents[0].G == env.G
assert env.agents[0]["times"] == 10
assert env.agents[0]["times"] == 10
env.step()
assert env.agents[0]['times'] == 11
assert env.agents[1]['times'] == 21
assert env.agents[0]["times"] == 11
assert env.agents[1]["times"] == 21
def test_init_and_count_agents(self):
"""Agents should be properly initialized and counting should filter them properly"""
#TODO: separate this test into two or more test cases
# TODO: separate this test into two or more test cases
config = {
'max_time': 10,
'model_params': {
'agents': [{'agent_class': CustomAgent, 'weight': 1, 'topology': 'default'},
{'agent_class': CustomAgent, 'weight': 3, 'topology': 'default'},
"max_time": 10,
"model_params": {
"agents": [
{"agent_class": CustomAgent, "weight": 1, "topology": True},
{"agent_class": CustomAgent, "weight": 3, "topology": True},
],
'topologies': {
'default': {
'path': join(ROOT, 'test.gexf')
}
},
"topology": {"path": join(ROOT, "test.gexf")},
},
}
s = simulation.from_config(config)
@ -120,40 +108,45 @@ class TestMain(TestCase):
assert env.count_agents(weight=3) == 1
assert env.count_agents(agent_class=CustomAgent) == 2
def test_torvalds_example(self):
"""A complete example from a documentation should work."""
config = serialization.load_file(join(EXAMPLES, 'torvalds.yml'))[0]
config['model_params']['network_params']['path'] = join(EXAMPLES,
config['model_params']['network_params']['path'])
config = serialization.load_file(join(EXAMPLES, "torvalds.yml"))[0]
config["model_params"]["network_params"]["path"] = join(
EXAMPLES, config["model_params"]["network_params"]["path"]
)
s = simulation.from_config(config)
env = s.run_simulation(dry_run=True)[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
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
assert skill_level == "beginner"
assert a.state["total"] == 3
assert a.state["neighbors"] == 1
def test_serialize_class(self):
ser, name = serialization.serialize(agents.BaseAgent, known_modules=[])
assert name == 'soil.agents.BaseAgent'
assert name == "soil.agents.BaseAgent"
assert ser == agents.BaseAgent
ser, name = serialization.serialize(agents.BaseAgent, known_modules=['soil', ])
assert name == 'BaseAgent'
ser, name = serialization.serialize(
agents.BaseAgent,
known_modules=[
"soil",
],
)
assert name == "BaseAgent"
assert ser == agents.BaseAgent
ser, name = serialization.serialize(CustomAgent)
assert name == 'test_main.CustomAgent'
assert name == "test_main.CustomAgent"
assert ser == CustomAgent
pickle.dumps(ser)
@ -166,72 +159,63 @@ class TestMain(TestCase):
assert i == des
def test_serialize_agent_class(self):
'''A class from soil.agents should be serialized without the module part'''
"""A class from soil.agents should be serialized without the module part"""
ser = agents.serialize_type(CustomAgent)
assert ser == 'test_main.CustomAgent'
assert ser == "test_main.CustomAgent"
ser = agents.serialize_type(agents.BaseAgent)
assert ser == 'BaseAgent'
assert ser == "BaseAgent"
pickle.dumps(ser)
def test_deserialize_agent_distribution(self):
agent_distro = [
{
'agent_class': 'CounterModel',
'weight': 1
},
{
'agent_class': 'test_main.CustomAgent',
'weight': 2
},
{"agent_class": "CounterModel", "weight": 1},
{"agent_class": "test_main.CustomAgent", "weight": 2},
]
converted = agents.deserialize_definition(agent_distro)
assert converted[0]['agent_class'] == agents.CounterModel
assert converted[1]['agent_class'] == CustomAgent
assert converted[0]["agent_class"] == agents.CounterModel
assert converted[1]["agent_class"] == CustomAgent
pickle.dumps(converted)
def test_serialize_agent_distribution(self):
agent_distro = [
{
'agent_class': agents.CounterModel,
'weight': 1
},
{
'agent_class': CustomAgent,
'weight': 2
},
{"agent_class": agents.CounterModel, "weight": 1},
{"agent_class": CustomAgent, "weight": 2},
]
converted = agents.serialize_definition(agent_distro)
assert converted[0]['agent_class'] == 'CounterModel'
assert converted[1]['agent_class'] == 'test_main.CustomAgent'
assert converted[0]["agent_class"] == "CounterModel"
assert converted[1]["agent_class"] == "test_main.CustomAgent"
pickle.dumps(converted)
def test_templates(self):
'''Loading a template should result in several configs'''
configs = serialization.load_file(join(EXAMPLES, 'template.yml'))
"""Loading a template should result in several configs"""
configs = serialization.load_file(join(EXAMPLES, "template.yml"))
assert len(configs) > 0
def test_until(self):
config = {
'name': 'until_sim',
'model_params': {
'network_params': {},
'agents': {
'fixed': [{
'agent_class': agents.BaseAgent,
}]
"name": "until_sim",
"model_params": {
"network_params": {},
"agents": {
"fixed": [
{
"agent_class": agents.BaseAgent,
}
]
},
},
'max_time': 2,
'num_trials': 50,
"max_time": 2,
"num_trials": 50,
}
s = simulation.from_config(config)
runs = list(s.run_simulation(dry_run=True))
over = list(x.now for x in runs if x.now > 2)
assert len(runs) == config['num_trials']
assert len(runs) == config["num_trials"]
assert len(over) == 0
def test_fsm(self):
'''Basic state change'''
"""Basic state change"""
class ToggleAgent(agents.FSM):
@agents.default_state
@agents.state
@ -250,7 +234,8 @@ class TestMain(TestCase):
assert a.state_id == a.ping.id
def test_fsm_when(self):
'''Basic state change'''
"""Basic state change"""
class ToggleAgent(agents.FSM):
@agents.default_state
@agents.state

View File

@ -1,4 +1,4 @@
'''
"""
Mesa-SOIL integration tests
We have to test that:
@ -8,13 +8,15 @@ We have to test that:
- Mesa visualizations work with SOIL simulations
'''
"""
from mesa import Agent, Model
from mesa.time import RandomActivation
from mesa.space import MultiGrid
class MoneyAgent(Agent):
""" An agent with fixed initial wealth."""
"""An agent with fixed initial wealth."""
def __init__(self, unique_id, model):
super().__init__(unique_id, model)
self.wealth = 1
@ -33,15 +35,15 @@ class MoneyAgent(Agent):
def move(self):
possible_steps = self.model.grid.get_neighborhood(
self.pos,
moore=True,
include_center=False)
self.pos, moore=True, include_center=False
)
new_position = self.random.choice(possible_steps)
self.model.grid.move_agent(self, new_position)
class MoneyModel(Model):
"""A model with some number of agents."""
def __init__(self, N, width, height):
self.num_agents = N
self.grid = MultiGrid(width, height, True)
@ -58,7 +60,7 @@ class MoneyModel(Model):
self.grid.place_agent(a, (x, y))
def step(self):
'''Advance the model by one step.'''
"""Advance the model by one step."""
self.schedule.step()

View File

@ -10,7 +10,7 @@ from soil import config, network, environment, agents, simulation
from test_main import CustomAgent
ROOT = os.path.abspath(os.path.dirname(__file__))
EXAMPLES = join(ROOT, '..', 'examples')
EXAMPLES = join(ROOT, "..", "examples")
class TestNetwork(TestCase):
@ -19,21 +19,13 @@ class TestNetwork(TestCase):
Load a graph from file if the extension is known.
Raise an exception otherwise.
"""
config = {
'network_params': {
'path': join(ROOT, 'test.gexf')
}
}
G = network.from_config(config['network_params'])
config = {"network_params": {"path": join(ROOT, "test.gexf")}}
G = network.from_config(config["network_params"])
assert G
assert len(G) == 2
with self.assertRaises(AttributeError):
config = {
'network_params': {
'path': join(ROOT, 'unknown.extension')
}
}
G = network.from_config(config['network_params'])
config = {"network_params": {"path": join(ROOT, "unknown.extension")}}
G = network.from_config(config["network_params"])
print(G)
def test_generate_barabasi(self):
@ -41,88 +33,73 @@ class TestNetwork(TestCase):
If no path is given, a generator and network parameters
should be used to generate a network
"""
cfg = {
'params': {
'generator': 'barabasi_albert_graph'
}
}
cfg = {"params": {"generator": "barabasi_albert_graph"}}
with self.assertRaises(Exception):
G = network.from_config(cfg)
cfg['params']['n'] = 100
cfg['params']['m'] = 10
cfg["params"]["n"] = 100
cfg["params"]["m"] = 10
G = network.from_config(cfg)
assert len(G) == 100
def test_save_geometric(self):
"""
There is a bug in networkx that prevents it from creating a GEXF file
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.NetworkEnvironment(topology=G)
f = io.BytesIO()
assert env.topologies['default']
network.dump_gexf(env.topologies['default'], f)
assert env.G
network.dump_gexf(env.G, f)
def test_networkenvironment_creation(self):
"""Networkenvironment should accept netconfig as parameters"""
model_params = {
'topologies': {
'default': {
'path': join(ROOT, 'test.gexf')
}
"topology": {"path": join(ROOT, "test.gexf")},
"agents": {
"topology": True,
"distribution": [
{
"agent_class": CustomAgent,
}
],
},
'agents': {
'topology': 'default',
'distribution': [{
'agent_class': CustomAgent,
}]
}
}
env = environment.Environment(**model_params)
assert env.topologies
assert env.G
env.step()
assert len(env.topologies['default']) == 2
assert len(env.G) == 2
assert len(env.agents) == 2
assert env.agents[1].count_agents(state_id='normal') == 2
assert env.agents[1].count_agents(state_id='normal', limit_neighbors=True) == 1
assert env.agents[1].count_agents(state_id="normal") == 2
assert env.agents[1].count_agents(state_id="normal", limit_neighbors=True) == 1
assert env.agents[0].neighbors == 1
def test_custom_agent_neighbors(self):
"""Allow for search of neighbors with a certain state_id"""
config = {
'model_params': {
'topologies': {
'default': {
'path': join(ROOT, 'test.gexf')
}
},
'agents': {
'topology': 'default',
'distribution': [
{
'weight': 1,
'agent_class': CustomAgent
}
]
}
"model_params": {
"topology": {"path": join(ROOT, "test.gexf")},
"agents": {
"topology": True,
"distribution": [{"weight": 1, "agent_class": CustomAgent}],
},
},
'max_time': 10,
"max_time": 10,
}
s = simulation.from_config(config)
env = s.run_simulation(dry_run=True)[0]
assert env.agents[1].count_agents(state_id='normal') == 2
assert env.agents[1].count_agents(state_id='normal', limit_neighbors=True) == 1
assert env.agents[1].count_agents(state_id="normal") == 2
assert env.agents[1].count_agents(state_id="normal", limit_neighbors=True) == 1
assert env.agents[0].neighbors == 1
def test_subgraph(self):
'''An agent should be able to subgraph the global topology'''
"""An agent should be able to subgraph the global topology"""
G = nx.Graph()
G.add_node(3)
G.add_edge(1, 2)
distro = agents.calculate_distribution(agent_class=agents.NetworkAgent)
aconfig = config.AgentConfig(distribution=distro, topology='default')
env = environment.Environment(name='Test', topologies={'default': G}, agents=aconfig)
aconfig = config.AgentConfig(distribution=distro, topology=True)
env = environment.Environment(name="Test", topology=G, agents=aconfig)
lst = list(env.network_agents)
a2 = env.find_one(node_id=2)