mirror of
https://github.com/gsi-upm/soil
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7d1c800490
* Graphs are not saved by default (not backwards compatible) * Modified newsspread examples * More granular options to save results (exporting to CSV and GEXF are now optional) * Updated tutorial to include exporting options * Removed references from environment to simulation * Added parallelism to simulations (can be turned off with a flag or argument).
82 lines
2.3 KiB
Python
82 lines
2.3 KiB
Python
from soil.agents import FSM, state, default_state, prob
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import logging
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class DumbViewer(FSM):
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'''
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A viewer that gets infected via TV (if it has one) and tries to infect
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its neighbors once it's infected.
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'''
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defaults = {
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'prob_neighbor_spread': 0.5,
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'prob_tv_spread': 0.1,
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}
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@default_state
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@state
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def neutral(self):
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if self['has_tv']:
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if prob(self.env['prob_tv_spread']):
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self.set_state(self.infected)
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@state
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def infected(self):
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for neighbor in self.get_neighboring_agents(state_id=self.neutral.id):
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if prob(self.env['prob_neighbor_spread']):
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neighbor.infect()
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def infect(self):
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self.set_state(self.infected)
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class HerdViewer(DumbViewer):
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'''
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A viewer whose probability of infection depends on the state of its neighbors.
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'''
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level = logging.DEBUG
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def infect(self):
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infected = self.count_neighboring_agents(state_id=self.infected.id)
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total = self.count_neighboring_agents()
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prob_infect = self.env['prob_neighbor_spread'] * infected/total
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self.debug('prob_infect', prob_infect)
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if prob(prob_infect):
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self.set_state(self.infected.id)
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class WiseViewer(HerdViewer):
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'''
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A viewer that can change its mind.
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'''
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defaults = {
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'prob_neighbor_spread': 0.5,
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'prob_neighbor_cure': 0.25,
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'prob_tv_spread': 0.1,
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}
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@state
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def cured(self):
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prob_cure = self.env['prob_neighbor_cure']
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for neighbor in self.get_neighboring_agents(state_id=self.infected.id):
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if prob(prob_cure):
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try:
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neighbor.cure()
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except AttributeError:
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self.debug('Viewer {} cannot be cured'.format(neighbor.id))
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def cure(self):
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self.set_state(self.cured.id)
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@state
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def infected(self):
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cured = max(self.count_neighboring_agents(self.cured.id),
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1.0)
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infected = max(self.count_neighboring_agents(self.infected.id),
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1.0)
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prob_cure = self.env['prob_neighbor_cure'] * (cured/infected)
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if prob(prob_cure):
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return self.cure()
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return self.set_state(super().infected)
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