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J. Fernando Sánchez 2022-10-16 17:58:19 +02:00
parent d9947c2c52
commit 78833a9e08
26 changed files with 1254 additions and 899 deletions
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177
soil/__init__.py
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@ -22,58 +22,107 @@ from .utils import logger
from .time import *
def main(cfg='simulation.yml', exporters=None, parallel=None, output="soil_output", *, do_run=False, debug=False, **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=output or "soil_output",
help='folder to write results to. It defaults to the current directory.')
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(
"--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(
"-e",
"--exporter",
action="append",
default=[],
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.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.")
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
@ -81,14 +130,16 @@ def main(cfg='simulation.yml', exporters=None, parallel=None, output="soil_outpu
if parallel is None:
parallel = not args.synchronous
exporters = exporters or ['default', ]
exporters = exporters or [
"default",
]
for exp in args.exporter:
if exp not in exporters:
exporters.append(exp)
if args.csv:
exporters.append('csv')
exporters.append("csv")
if args.graph:
exporters.append('gexf')
exporters.append("gexf")
if os.getcwd() not in sys.path:
sys.path.append(os.getcwd())
@ -97,38 +148,38 @@ def main(cfg='simulation.yml', exporters=None, parallel=None, output="soil_outpu
if output is None:
output = args.output
logger.info('Loading config file: {}'.format(args.file))
logger.info("Loading config file: {}".format(args.file))
debug = debug or args.debug
if args.pdb or debug:
args.synchronous = True
res = []
try:
exp_params = {}
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,
dry_run=args.dry_run,
exporters=exporters,
parallel=parallel,
outdir=output,
exporter_params=exp_params,
**kwargs):
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:
@ -144,19 +195,21 @@ def main(cfg='simulation.yml', exporters=None, parallel=None, output="soil_outpu
if do_run:
res.append(sim.run())
else:
print('not running')
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
os.environ['SOIL_DEBUG'] = 'true'
os.environ["SOIL_DEBUG"] = "true"
set_trace()
return res
@ -165,5 +218,5 @@ def easy(cfg, debug=False, **kwargs):
return main(cfg, **kwargs)[0]
if __name__ == '__main__':
if __name__ == "__main__":
main(do_run=True)

4
soil/__main__.py
View File

@ -1,7 +1,9 @@
from . import main as init_main
def main():
init_main(do_run=True)
if __name__ == '__main__':
if __name__ == "__main__":
init_main(do_run=True)

3
soil/agents/BassModel.py
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

72
soil/agents/BigMarketModel.py
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]

14
soil/agents/CounterModel.py
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))

8
soil/agents/Geo.py
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)]

28
soil/agents/IndependentCascadeModel.py
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

166
soil/agents/ModelM2.py
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

64
soil/agents/SISaModel.py
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

100
soil/agents/SentimentCorrelationModel.py
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"]

330
soil/agents/__init__.py
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 isinstance(func, classmethod) 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():
@ -117,20 +120,22 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
def from_dict(cls, model, attrs, warn_extra=True):
ignored = {}
args = {}
for k, v in attrs.items():
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 }')
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)
@ -148,7 +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()
@ -156,7 +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
@ -169,7 +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
@ -186,9 +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):
@ -214,10 +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):
@ -225,7 +230,6 @@ class BaseAgent(MesaAgent, MutableMapping, metaclass=MetaAgent):
class NetworkAgent(BaseAgent):
def __init__(self, *args, topology, node_id, **kwargs):
super().__init__(*args, **kwargs)
@ -248,18 +252,21 @@ class NetworkAgent(BaseAgent):
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') 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
@ -272,7 +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):
@ -280,11 +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:
@ -294,11 +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
@ -348,32 +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)
@ -386,7 +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
@ -396,10 +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)
@ -414,23 +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.
@ -453,26 +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
@ -480,28 +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
@ -509,12 +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:
@ -525,7 +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)
@ -609,12 +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
@ -657,11 +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 = []
@ -694,7 +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)
@ -711,23 +745,25 @@ 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, topology: 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, topology=topology, random=random)
def _agents_from_config(cfg: config.AgentConfig,
topology: 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)
@ -737,7 +773,9 @@ def _agents_from_config(cfg: config.AgentConfig,
assigned_network = 0
if cfg.fixed is not None:
agents, assigned_total, assigned_network = _from_fixed(cfg.fixed, topology=cfg.topology, default=cfg)
agents, assigned_total, assigned_network = _from_fixed(
cfg.fixed, topology=cfg.topology, default=cfg
)
n = cfg.n
@ -749,46 +787,56 @@ def _agents_from_config(cfg: config.AgentConfig,
for d in cfg.distribution:
if d.strategy == config.Strategy.topology:
topo = d.topology if ('topology' in d.__fields_set__) else cfg.topology
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')
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')
raise ValueError(
f"Topology does not have enough free nodes to assign one to the agent"
)
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)
if networked:
new_agents = _from_distro(networked,
n= topo_size - assigned_network,
topology=topo,
default=cfg,
random=random)
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 - assigned_total
agents += _from_distro(total, n=remaining,
default=cfg,
random=random)
remaining = n - assigned_total
agents += _from_distro(total, n=remaining, default=cfg, random=random)
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 }')
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: bool, 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_total = 0
@ -799,12 +847,18 @@ def _from_fixed(lst: List[config.FixedAgentConfig], topology: bool, default: con
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'] = True
agent["topology"] = True
counts_network += 1
if not fixed.hidden:
counts_total += 1
@ -813,17 +867,21 @@ def _from_fixed(lst: List[config.FixedAgentConfig], topology: bool, default: con
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)
@ -836,29 +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)
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
@ -877,4 +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)

169
soil/config.py
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]] = {}
@ -38,7 +39,7 @@ class Topology(BaseModel):
class NetParams(BaseModel, extra=Extra.allow):
generator: Union[Callable, str]
n: int
n: int
class NetConfig(BaseModel):
@ -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()
@ -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('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)")
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):
@ -111,16 +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
@ -140,45 +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
topology = None
if 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
@ -186,80 +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'] = False
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'] = True
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'] = True
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['topology'] = topology
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)

2
soil/datacollection.py
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)

79
soil/debugging.py
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)
@ -29,12 +29,12 @@ def wrapcmd(func):
class Debug(pdb.Pdb):
def __init__(self, *args, skip_soil=False, **kwargs):
skip = kwargs.get('skip', [])
skip.append('soil')
skip = kwargs.get("skip", [])
skip.append("soil")
if skip_soil:
skip.append('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] "
@ -42,7 +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():
@ -52,20 +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('')
return self.do_continue("")
do_cs = do_continue_state
@wrapcmd
def do_soil_agent():
if not agent:
print('No agent available')
print("No agent available")
return
keys = None
@ -81,9 +81,9 @@ class Debug(pdb.Pdb):
do_aa = do_soil_agent
def do_break_state(self, arg: str, instances=None, temporary=False):
'''
"""
Break before a specified state is stepped into.
'''
"""
klass = None
state = arg
@ -95,39 +95,39 @@ class Debug(pdb.Pdb):
if tokens:
instances = list(eval(token) for token in tokens)
colon = state.find(':')
colon = state.find(":")
if colon > 0:
klass = state[:colon].rstrip()
state = state[colon+1:].strip()
state = state[colon + 1 :].strip()
print(klass, state, tokens)
klass = eval(klass,
self.curframe.f_globals,
self.curframe_locals)
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)]
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')
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}')
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
@ -135,38 +135,36 @@ 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) }'
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')
"""
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')
self.error("No current agent.")
self.error("Try this again when the debugger is stopped inside an agent")
return
arg = f'{agent.__class__.__name__}:{ arg } {agent.unique_id}'
arg = f"{agent.__class__.__name__}:{ arg } {agent.unique_id}"
return self.do_break_state(arg)
do_bss = do_break_state_self
@ -174,6 +172,7 @@ class Debug(pdb.Pdb):
debugger = None
def set_trace(frame=None, **kwargs):
global debugger
if debugger is None:

132
soil/environment.py
View File

@ -35,18 +35,20 @@ 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 {}
@ -75,27 +77,26 @@ class BaseEnvironment(Model):
)
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
@ -108,11 +109,10 @@ class BaseEnvironment(Model):
override = lst.override
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._agent_from_dict(agent) for agent in lst]
for a in new_agents:
self.schedule.add(a)
@ -122,8 +122,7 @@ class BaseEnvironment(Model):
setattr(agent, attr, value)
def _agent_dict_from_config(self, cfg):
return agentmod.from_config(cfg,
random=self.random)
return agentmod.from_config(cfg, random=self.random)
@property
def agents(self):
@ -131,7 +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))
@ -139,18 +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_class, unique_id=None, **kwargs):
a = None
if unique_id is None:
unique_id = self.next_id()
a = agent_class(model=self,
unique_id=unique_id,
**args)
a = agent_class(model=self, unique_id=unique_id, **args)
self.schedule.add(a)
return a
@ -163,16 +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)
@ -180,10 +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):
@ -197,13 +194,15 @@ class BaseEnvironment(Model):
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: Union[config.NetConfig, nx.Graph] = None, **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._set_topology(topology)
@ -211,37 +210,35 @@ class NetworkEnvironment(BaseEnvironment):
self.init_agents(agents)
def init_agents(self, *args, **kwargs):
'''Initialize the agents from a '''
"""Initialize the agents from a"""
super().init_agents(*args, **kwargs)
for agent in self.schedule._agents.values():
if hasattr(agent, 'node_id'):
if hasattr(agent, "node_id"):
self._init_node(agent)
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
"""
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)
return agentmod.from_config(cfg, topology=self.G, random=self.random)
def _agent_from_dict(self, agent, unique_id=None):
agent = dict(agent)
if not agent.get('topology', False):
if not agent.get("topology", False):
return super()._agent_from_dict(agent)
if unique_id is None:
unique_id = self.next_id()
node_id = agent.get('node_id', None)
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
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
@ -269,32 +266,33 @@ class NetworkEnvironment(BaseEnvironment):
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)
node_id = network.find_unassigned(
G=self.G, shuffle=True, random=self.random
)
if node_id in G.nodes:
self.G.nodes[node_id]['agent'] = None # Reserve
self.G.nodes[node_id]["agent"] = None # Reserve
else:
self.G.add_node(node_id)
a = self.add_agent(unique_id=unique_id, agent_class=agent_class, node_id=node_id, **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 agent_for_node_id(self, node_id):
return self.G.nodes[node_id].get('agent')
return self.G.nodes[node_id].get("agent")
def populate_network(self, agent_class, weights=None, **agent_params):
if not hasattr(agent_class, 'len'):
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:
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)
self.add_agent(node_id=node_id, agent_class=a_class, **agent_params)
Environment = NetworkEnvironment

127
soil/exporters.py
View File

@ -24,56 +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:
@ -86,102 +88,117 @@ 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:
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')
logger.info("NOT dumping results")
def trial_end(self, env):
if self.dry_run:
logger.info('Running in DRY_RUN mode, the database will NOT be created')
logger.info("Running in DRY_RUN mode, the database will NOT be created")
return
with timer('Dumping simulation {} trial {}'.format(self.simulation.name,
env.id)):
with timer(
"Dumping simulation {} trial {}".format(self.simulation.name, env.id)
):
fpath = os.path.join(self.outdir, f'{env.id}.sqlite')
engine = create_engine(f'sqlite:///{fpath}', echo=False)
fpath = os.path.join(self.outdir, f"{env.id}.sqlite")
engine = create_engine(f"sqlite:///{fpath}", echo=False)
dc = env.datacollector
for (t, df) in get_dc_dfs(dc):
df.to_sql(t, con=engine, if_exists='append')
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() }
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()
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)):
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 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
@ -189,7 +206,7 @@ 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
@ -198,7 +215,7 @@ 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:

41
soil/network.py
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)
@ -19,24 +20,28 @@ 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.fixed, config.Topology):
@ -49,17 +54,17 @@ def from_config(cfg: config.NetConfig, dir_path: str = None):
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
"""
# TODO: test
candidates = list(G.nodes(data=True))
if shuffle:
random.shuffle(candidates)
for next_id, data in candidates:
if 'agent' not in data:
if "agent" not in data:
node_id = next_id
break
@ -68,8 +73,14 @@ def find_unassigned(G, shuffle=False, random=random):
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")

83
soil/serialization.py
View File

@ -15,13 +15,14 @@ import networkx as nx
from jinja2 import Template
logger = logging.getLogger('soil')
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))))
@ -30,14 +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)
@ -49,9 +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)
@ -60,25 +62,25 @@ 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
@ -100,22 +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
@ -125,17 +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
@ -160,9 +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_)
@ -172,8 +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 = []
@ -181,7 +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_))
@ -190,32 +194,31 @@ 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))
def deserialize(type_, value=None, globs=None, **kwargs):
'''Get an object from a text representation'''
"""Get an object from a text representation"""
if not isinstance(type_, str):
return type_
if globs and type_ in globs:
des = globs[type_]
else:
des = deserializer(type_, **kwargs)
des = deserializer(type_, **kwargs)
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'''
#TODO: remove
print('SERIALIZATION', kwargs)
"""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

161
soil/simulation.py
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
@ -25,7 +25,7 @@ from .time import INFINITY
from .config import Config, convert_old
#TODO: change documentation for simulation
# TODO: change documentation for simulation
@dataclass
class Simulation:
"""
@ -36,15 +36,16 @@ class Simulation:
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
@ -56,14 +57,15 @@ class Simulation:
extra: Dict[str, Any] = field(default_factory=dict)
@classmethod
def from_dict(cls, env, **kwargs):
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
}
d = {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:
d.setdefault('extra', {}).update(ignored)
d.setdefault("extra", {}).update(ignored)
if ignored:
print(f'Warning: Ignoring these parameters (added to "extra"): { ignored }')
d.update(kwargs)
@ -74,24 +76,34 @@ class Simulation:
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=None,
exporters=None, 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)
outdir = outdir or self.outdir
logger.info('Using exporters: %s', exporters or [])
logger.info('Output directory: %s', 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:
@ -99,22 +111,28 @@ class Simulation:
if not exporter_params:
exporter_params = self.exporter_params
exporters = serialization.deserialize_all(exporters,
simulation=self,
known_modules=['soil.exporters', ],
dry_run=dry_run,
outdir=outdir,
**exporter_params)
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)):
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)
@ -128,11 +146,12 @@ class Simulation:
exporter.sim_end()
def get_env(self, trial_id=0, model_params=None, **kwargs):
'''Create an environment for a trial of the simulation'''
"""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(value.lsplit(":", 1)[1])
return reporters
params = self.model_params.copy()
@ -140,18 +159,22 @@ class Simulation:
params.update(model_params)
params.update(kwargs)
agent_reporters = deserialize_reporters(params.pop('agent_reporters', {}))
model_reporters = deserialize_reporters(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,
**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
@ -160,50 +183,58 @@ 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) }
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):
@ -215,15 +246,15 @@ def iter_from_config(*cfgs, **kwargs):
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)
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]

21
soil/time.py
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 getattr(agent, 'alive', True):
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}")

63
soil/utils.py
View File

@ -9,12 +9,12 @@ 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"
@ -23,38 +23,44 @@ logFormatter = logging.Formatter(logformat, timeformat)
consoleHandler = logging.StreamHandler()
consoleHandler.setFormatter(logFormatter)
logging.basicConfig(level=logging.INFO,
handlers=[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 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 and os.path.exists(path):
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))
stamp = strftime("%Y-%m-%d_%H.%M.%S", localtime(creation))
backup_dir = os.path.join(outdir, 'backup')
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))
newpath = os.path.join(
backup_dir, "{}@{}".format(os.path.basename(path), stamp)
)
copyfile(path, newpath)
return open(path, mode=mode, **kwargs)
@ -67,21 +73,23 @@ def open_or_reuse(f, *args, **kwargs):
except (AttributeError, TypeError):
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
@ -93,7 +101,7 @@ 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
@ -106,27 +114,28 @@ 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:

9
soil/version.py
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()

1
soil/visualization.py
View File

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

270
soil/web/__init__.py
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,
)

2
soil/web/__main__.py
View File

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

27
soil/web/run.py
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,
)