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