mirror of https://github.com/gsi-upm/soil
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7 Commits
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b0add8552e
| Author | SHA1 | Date |
|---|---|---|
J. Fernando Sánchez
|
b0add8552e | 5 years ago |
|
J. Fernando Sánchez
|
1cf85ea450 | 5 years ago |
|
J. Fernando Sánchez
|
c32e167fb8 | 5 years ago |
|
J. Fernando Sánchez
|
5f68b5321d | 5 years ago |
|
J. Fernando Sánchez
|
2a2843bd19 | 5 years ago |
|
J. Fernando Sánchez
|
d1006bd55c | 5 years ago |
|
J. Fernando Sánchez
|
9bc036d185 | 5 years ago |
@ -1,4 +1,7 @@
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test:
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quick-test:
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docker-compose exec dev python -m pytest -s -v
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.PHONY: test
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test:
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docker run -t -v $$PWD:/usr/src/app -w /usr/src/app python:3.7 python setup.py test
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.PHONY: test
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@ -0,0 +1,29 @@
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---
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vars:
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bounds:
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x1: [0, 1]
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x2: [1, 2]
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fixed:
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x3: ["a", "b", "c"]
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sampler: "SALib.sample.morris.sample"
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samples: 10
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template: |
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group: simple
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num_trials: 1
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interval: 1
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max_time: 2
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seed: "CompleteSeed!"
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dump: false
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network_params:
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generator: complete_graph
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n: 10
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network_agents:
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- agent_type: CounterModel
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weight: {{ x1 }}
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state:
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id: 0
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- agent_type: AggregatedCounter
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weight: {{ 1 - x1 }}
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environment_params:
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name: {{ x3 }}
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skip_test: true
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@ -1,8 +1,10 @@
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nxsim
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nxsim>=0.1.2
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simpy
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networkx>=2.0
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numpy
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matplotlib
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pyyaml
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pandas
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scipy
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pyyaml>=5.1
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pandas>=0.23
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scipy==1.2.1 # scipy 1.3.0rc1 is not compatible with salib
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SALib>=1.3
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Jinja2
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@ -1 +1 @@
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0.13.8
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0.14.0
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@ -1,18 +0,0 @@
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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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@ -0,0 +1,175 @@
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import os
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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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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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for name in names:
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mod = deserialize(name, known_modules=['soil.exporters'])
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exporters.append(mod(simulation, *args, **kwargs))
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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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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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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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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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'''Method to call when the simulation starts'''
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def end(self):
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'''Method to call when the simulation ends'''
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def trial_end(self, env):
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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 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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if not self.dry_run:
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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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class Gexf(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('{}.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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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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dfm = pd.DataFrame(self.means, columns=['metric', 'key', 'value'])
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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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@ -0,0 +1,201 @@
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import os
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import logging
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import ast
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import sys
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import importlib
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from glob import glob
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from itertools import product, chain
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import yaml
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import networkx as nx
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from jinja2 import Template
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logger = logging.getLogger('soil')
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logger.setLevel(logging.INFO)
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def load_network(network_params, dir_path=None):
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if network_params is None:
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return nx.Graph()
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path = network_params.get('path', None)
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if path:
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if dir_path and not os.path.isabs(path):
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path = os.path.join(dir_path, path)
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extension = os.path.splitext(path)[1][1:]
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kwargs = {}
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if extension == 'gexf':
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kwargs['version'] = '1.2draft'
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kwargs['node_type'] = int
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try:
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method = getattr(nx.readwrite, 'read_' + extension)
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except AttributeError:
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raise AttributeError('Unknown format')
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return method(path, **kwargs)
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net_args = network_params.copy()
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if 'generator' not in net_args:
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return nx.Graph()
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net_gen = net_args.pop('generator')
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if dir_path not in sys.path:
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sys.path.append(dir_path)
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method = deserializer(net_gen,
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known_modules=['networkx.generators',])
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return method(**net_args)
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def load_file(infile):
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with open(infile, 'r') as f:
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return list(chain.from_iterable(map(expand_template, load_string(f))))
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|
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def load_string(string):
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yield from yaml.load_all(string, Loader=yaml.FullLoader)
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||||
|
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|
||||
def expand_template(config):
|
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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.'))
|
||||
|
||||
template = Template(config['template'])
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||||
|
||||
sampler_name = config.get('sampler', 'SALib.sample.morris.sample')
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n_samples = int(config.get('samples', 100))
|
||||
sampler = deserializer(sampler_name)
|
||||
bounds = config['vars']['bounds']
|
||||
|
||||
problem = {
|
||||
'num_vars': len(bounds),
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||||
'names': list(bounds.keys()),
|
||||
'bounds': list(v for v in bounds.values())
|
||||
}
|
||||
samples = sampler(problem, n_samples)
|
||||
|
||||
lists = config['vars'].get('lists', {})
|
||||
names = list(lists.keys())
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||||
values = list(lists.values())
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combs = list(product(*values))
|
||||
|
||||
allnames = names + problem['names']
|
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allvalues = [(list(i[0])+list(i[1])) for i in product(combs, samples)]
|
||||
params = list(map(lambda x: dict(zip(allnames, x)), allvalues))
|
||||
|
||||
|
||||
blank_str = template.render({k: 0 for k in allnames})
|
||||
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')
|
||||
|
||||
confs = []
|
||||
for ps in params:
|
||||
string = template.render(ps)
|
||||
for c in load_string(string):
|
||||
yield c
|
||||
|
||||
|
||||
def load_files(*patterns, **kwargs):
|
||||
for pattern in patterns:
|
||||
for i in glob(pattern, **kwargs):
|
||||
for config in load_file(i):
|
||||
path = os.path.abspath(i)
|
||||
if 'dir_path' not in config:
|
||||
config['dir_path'] = os.path.dirname(path)
|
||||
yield config, path
|
||||
|
||||
|
||||
def load_config(config):
|
||||
if isinstance(config, dict):
|
||||
yield config, None
|
||||
else:
|
||||
yield from load_files(config)
|
||||
|
||||
|
||||
builtins = importlib.import_module('builtins')
|
||||
|
||||
def name(value, known_modules=[]):
|
||||
'''Return a name that can be imported, to serialize/deserialize an object'''
|
||||
if value is 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__':
|
||||
return tname
|
||||
if known_modules and modname in known_modules:
|
||||
return tname
|
||||
for kmod in known_modules:
|
||||
if not kmod:
|
||||
continue
|
||||
module = importlib.import_module(kmod)
|
||||
if hasattr(module, tname):
|
||||
return tname
|
||||
return '{}.{}'.format(modname, tname)
|
||||
|
||||
|
||||
def serializer(type_):
|
||||
if type_ != 'str' and hasattr(builtins, type_):
|
||||
return repr
|
||||
return lambda x: x
|
||||
|
||||
|
||||
def serialize(v, known_modules=[]):
|
||||
'''Get a text representation of an object.'''
|
||||
tname = name(v, known_modules=known_modules)
|
||||
func = serializer(tname)
|
||||
return func(v), tname
|
||||
|
||||
def deserializer(type_, known_modules=[]):
|
||||
if type(type_) != str: # Already deserialized
|
||||
return type_
|
||||
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_)
|
||||
return lambda x=None: ast.literal_eval(x) if x is not None else cls()
|
||||
# Otherwise, see if we can find the module and the class
|
||||
modules = known_modules or []
|
||||
options = []
|
||||
|
||||
for mod in modules:
|
||||
if mod:
|
||||
options.append((mod, type_))
|
||||
|
||||
if '.' in type_: # Fully qualified module
|
||||
module, type_ = type_.rsplit(".", 1)
|
||||
options.append ((module, type_))
|
||||
|
||||
errors = []
|
||||
for modname, tname in options:
|
||||
try:
|
||||
module = importlib.import_module(modname)
|
||||
cls = getattr(module, tname)
|
||||
return getattr(cls, 'deserialize', cls)
|
||||
except (ModuleNotFoundError, AttributeError) as ex:
|
||||
errors.append((modname, tname, ex))
|
||||
raise Exception('Could not find type {}. Tried: {}'.format(type_, errors))
|
||||
|
||||
|
||||
def deserialize(type_, value=None, **kwargs):
|
||||
'''Get an object from a text representation'''
|
||||
if not isinstance(type_, str):
|
||||
return type_
|
||||
des = deserializer(type_, **kwargs)
|
||||
if value is None:
|
||||
return des
|
||||
return des(value)
|
||||
@ -0,0 +1,110 @@
|
||||
import os
|
||||
import io
|
||||
import tempfile
|
||||
import shutil
|
||||
from time import time
|
||||
|
||||
from unittest import TestCase
|
||||
from soil import exporters
|
||||
from soil.utils import safe_open
|
||||
from soil import simulation
|
||||
|
||||
|
||||
class Dummy(exporters.Exporter):
|
||||
started = False
|
||||
trials = 0
|
||||
ended = False
|
||||
total_time = 0
|
||||
|
||||
def start(self):
|
||||
self.__class__.started = True
|
||||
|
||||
def trial_end(self, env):
|
||||
assert env
|
||||
self.__class__.trials += 1
|
||||
self.__class__.total_time += env.now
|
||||
|
||||
def end(self):
|
||||
self.__class__.ended = True
|
||||
|
||||
|
||||
class Exporters(TestCase):
|
||||
def test_basic(self):
|
||||
config = {
|
||||
'name': 'exporter_sim',
|
||||
'network_params': {},
|
||||
'agent_type': 'CounterModel',
|
||||
'max_time': 2,
|
||||
'num_trials': 5,
|
||||
'environment_params': {}
|
||||
}
|
||||
s = simulation.from_config(config)
|
||||
s.run_simulation(exporters=[Dummy], dry_run=True)
|
||||
assert Dummy.started
|
||||
assert Dummy.ended
|
||||
assert Dummy.trials == 5
|
||||
assert Dummy.total_time == 2*5
|
||||
|
||||
def test_distribution(self):
|
||||
'''The distribution exporter should write the number of agents in each state'''
|
||||
config = {
|
||||
'name': 'exporter_sim',
|
||||
'network_params': {
|
||||
'generator': 'complete_graph',
|
||||
'n': 4
|
||||
},
|
||||
'agent_type': 'CounterModel',
|
||||
'max_time': 2,
|
||||
'num_trials': 5,
|
||||
'environment_params': {}
|
||||
}
|
||||
output = io.StringIO()
|
||||
s = simulation.from_config(config)
|
||||
s.run_simulation(exporters=[exporters.Distribution], dry_run=True, exporter_params={'copy_to': output})
|
||||
result = output.getvalue()
|
||||
assert 'count' in result
|
||||
assert 'SEED,Noneexporter_sim_trial_3,1,,1,1,1,1' in result
|
||||
|
||||
def test_writing(self):
|
||||
'''Try to write CSV, GEXF, sqlite and YAML (without dry_run)'''
|
||||
n_trials = 5
|
||||
config = {
|
||||
'name': 'exporter_sim',
|
||||
'network_params': {
|
||||
'generator': 'complete_graph',
|
||||
'n': 4
|
||||
},
|
||||
'agent_type': 'CounterModel',
|
||||
'max_time': 2,
|
||||
'num_trials': n_trials,
|
||||
'environment_params': {}
|
||||
}
|
||||
output = io.StringIO()
|
||||
s = simulation.from_config(config)
|
||||
tmpdir = tempfile.mkdtemp()
|
||||
envs = s.run_simulation(exporters=[
|
||||
exporters.Default,
|
||||
exporters.CSV,
|
||||
exporters.Gexf,
|
||||
exporters.Distribution,
|
||||
],
|
||||
outdir=tmpdir,
|
||||
exporter_params={'copy_to': output})
|
||||
result = output.getvalue()
|
||||
|
||||
simdir = os.path.join(tmpdir, s.group or '', s.name)
|
||||
with open(os.path.join(simdir, '{}.dumped.yml'.format(s.name))) as f:
|
||||
result = f.read()
|
||||
assert result
|
||||
|
||||
try:
|
||||
for e in envs:
|
||||
with open(os.path.join(simdir, '{}.gexf'.format(e.name))) as f:
|
||||
result = f.read()
|
||||
assert result
|
||||
|
||||
with open(os.path.join(simdir, '{}.csv'.format(e.name))) as f:
|
||||
result = f.read()
|
||||
assert result
|
||||
finally:
|
||||
shutil.rmtree(tmpdir)
|
||||
Loading…
Reference in New Issue