mirror of https://github.com/gsi-upm/soil
WIP: exporters
J. Fernando Sánchez
5 years ago
parent
9bc036d185
commit
d1006bd55c
@ -1,18 +0,0 @@
|
||||
from . import BaseAgent
|
||||
|
||||
import os.path
|
||||
import matplotlib
|
||||
import matplotlib.pyplot as plt
|
||||
import networkx as nx
|
||||
|
||||
|
||||
class DrawingAgent(BaseAgent):
|
||||
"""
|
||||
Agent that draws the state of the network.
|
||||
"""
|
||||
|
||||
def step(self):
|
||||
# Outside effects
|
||||
f = plt.figure()
|
||||
nx.draw(self.env.G, node_size=10, width=0.2, pos=nx.spring_layout(self.env.G, scale=100), ax=f.add_subplot(111))
|
||||
f.savefig(os.path.join(self.env.get_path(), "graph-"+str(self.env.now)+".png"))
|
||||
@ -1,43 +1,174 @@
|
||||
from .serialization import deserialize
|
||||
import os
|
||||
import time
|
||||
from io import BytesIO
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import networkx as nx
|
||||
import pandas as pd
|
||||
|
||||
from .serialization import deserialize
|
||||
from .utils import open_or_reuse, logger, timer
|
||||
|
||||
|
||||
def for_sim(simulation, names, dir_path=None):
|
||||
from . import utils
|
||||
|
||||
|
||||
def for_sim(simulation, names, *args, **kwargs):
|
||||
'''Return the set of exporters for a simulation, given the exporter names'''
|
||||
exporters = []
|
||||
for name in names:
|
||||
mod = deserialize(name, known_modules=['soil.exporters'])
|
||||
exporters.append(mod(simulation))
|
||||
exporters.append(mod(simulation, *args, **kwargs))
|
||||
return exporters
|
||||
|
||||
class DryRunner(BytesIO):
|
||||
def __init__(self, fname, *args, copy_to=None, **kwargs):
|
||||
super().__init__(*args, **kwargs)
|
||||
self.__fname = fname
|
||||
self.__copy_to = copy_to
|
||||
|
||||
def write(self, txt):
|
||||
if self.__copy_to:
|
||||
self.__copy_to.write('{}:::{}'.format(self.__fname, txt))
|
||||
try:
|
||||
super().write(txt)
|
||||
except TypeError:
|
||||
super().write(bytes(txt, 'utf-8'))
|
||||
|
||||
class Base:
|
||||
def close(self):
|
||||
logger.info('**Not** written to {} (dry run mode):\n\n{}\n\n'.format(self.__fname,
|
||||
self.getvalue().decode()))
|
||||
super().close()
|
||||
|
||||
def __init__(self, simulation):
|
||||
|
||||
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.sim = simulation
|
||||
outdir = outdir or os.getcwd()
|
||||
self.outdir = os.path.join(outdir,
|
||||
simulation.group or '',
|
||||
simulation.name)
|
||||
self.dry_run = dry_run
|
||||
self.copy_to = copy_to
|
||||
|
||||
def start(self):
|
||||
pass
|
||||
'''Method to call when the simulation starts'''
|
||||
|
||||
def end(self):
|
||||
pass
|
||||
'''Method to call when the simulation ends'''
|
||||
|
||||
def env(self):
|
||||
pass
|
||||
def trial_end(self, env):
|
||||
'''Method to call when a trial ends'''
|
||||
|
||||
def output(self, f, mode='w', **kwargs):
|
||||
if self.dry_run:
|
||||
f = DryRunner(f, copy_to=self.copy_to)
|
||||
else:
|
||||
try:
|
||||
if not os.path.isabs(f):
|
||||
f = os.path.join(self.outdir, f)
|
||||
except TypeError:
|
||||
pass
|
||||
return open_or_reuse(f, mode=mode, **kwargs)
|
||||
|
||||
class Dummy(Base):
|
||||
|
||||
class Default(Exporter):
|
||||
'''Default exporter. Writes CSV and sqlite results, as well as the simulation YAML'''
|
||||
|
||||
def start(self):
|
||||
with open(os.path.join(self.sim.outdir, 'dummy')) as f:
|
||||
f.write('simulation started @ {}'.format(time.time()))
|
||||
if not self.dry_run:
|
||||
logger.info('Dumping results to %s', self.outdir)
|
||||
self.sim.dump_yaml(outdir=self.outdir)
|
||||
else:
|
||||
logger.info('NOT dumping results')
|
||||
|
||||
def trial_end(self, env):
|
||||
if not self.dry_run:
|
||||
with timer('Dumping simulation {} trial {}'.format(self.sim.name,
|
||||
env.name)):
|
||||
with self.output('{}.sqlite'.format(env.name), mode='wb') as f:
|
||||
env.dump_sqlite(f)
|
||||
|
||||
|
||||
class CSV(Exporter):
|
||||
def trial_end(self, env):
|
||||
if not self.dry_run:
|
||||
with timer('[CSV] Dumping simulation {} trial {}'.format(self.sim.name,
|
||||
env.name)):
|
||||
with self.output('{}.csv'.format(env.name)) as f:
|
||||
env.dump_csv(f)
|
||||
|
||||
|
||||
def env(self, env):
|
||||
with open(os.path.join(self.sim.outdir, 'dummy-trial-{}'.format(env.name))) as f:
|
||||
class Gexf(Exporter):
|
||||
def trial_end(self, env):
|
||||
if not self.dry_run:
|
||||
with timer('[CSV] Dumping simulation {} trial {}'.format(self.sim.name,
|
||||
env.name)):
|
||||
with self.output('{}.gexf'.format(env.name), mode='wb') as f:
|
||||
env.dump_gexf(f)
|
||||
|
||||
|
||||
class Dummy(Exporter):
|
||||
|
||||
def start(self):
|
||||
with self.output('dummy', 'w') as f:
|
||||
f.write('simulation started @ {}\n'.format(time.time()))
|
||||
|
||||
def trial_end(self, env):
|
||||
with self.output('dummy', 'w') as f:
|
||||
for i in env.history_to_tuples():
|
||||
f.write(','.join(i))
|
||||
f.write(','.join(map(str, i)))
|
||||
f.write('\n')
|
||||
|
||||
def end(self):
|
||||
with self.output('dummy', 'a') as f:
|
||||
f.write('simulation ended @ {}\n'.format(time.time()))
|
||||
|
||||
|
||||
class Distribution(Exporter):
|
||||
'''
|
||||
Write the distribution of agent states at the end of each trial,
|
||||
the mean value, and its deviation.
|
||||
'''
|
||||
|
||||
def start(self):
|
||||
self.means = []
|
||||
self.counts = []
|
||||
|
||||
def trial_end(self, env):
|
||||
df = env[None, None, None].df()
|
||||
ix = df.index[-1]
|
||||
attrs = df.columns.levels[0]
|
||||
vc = {}
|
||||
stats = {}
|
||||
for a in attrs:
|
||||
t = df.loc[(ix, a)]
|
||||
try:
|
||||
self.means.append(('mean', a, t.mean()))
|
||||
except TypeError:
|
||||
for name, count in t.value_counts().iteritems():
|
||||
self.counts.append(('count', a, name, count))
|
||||
|
||||
def end(self):
|
||||
with open(os.path.join(self.sim.outdir, 'dummy')) as f:
|
||||
f.write('simulation ended @ {}'.format(time.time()))
|
||||
dfm = pd.DataFrame(self.means, columns=['metric', 'key', 'value'])
|
||||
dfc = pd.DataFrame(self.counts, columns=['metric', 'key', 'value', 'count'])
|
||||
dfm = dfm.groupby(by=['key']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
|
||||
dfc = dfc.groupby(by=['key', 'value']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
|
||||
with self.output('counts.csv') as f:
|
||||
dfc.to_csv(f)
|
||||
with self.output('metrics.csv') as f:
|
||||
dfm.to_csv(f)
|
||||
|
||||
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.name)) as f:
|
||||
f.savefig(f)
|
||||
|
||||
Loading…
Reference in New Issue