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Merge branch 'mesa'

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This commit is contained in:
J. Fernando Sánchez
2023-04-21 15:19:21 +02:00
parent bf481f0f88 302075a65d
commit 4e296e0cf1
113 changed files with 8457 additions and 12300 deletions
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24
examples/newsspread/NewsSpread.ipynb
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@@ -80,11 +80,11 @@
"max_time: 300\r\n",
"name: Sim_all_dumb\r\n",
"network_agents:\r\n",
"- agent_type: DumbViewer\r\n",
"- agent_class: DumbViewer\r\n",
" state:\r\n",
" has_tv: false\r\n",
" weight: 1\r\n",
"- agent_type: DumbViewer\r\n",
"- agent_class: DumbViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" weight: 1\r\n",
@@ -104,19 +104,19 @@
"max_time: 300\r\n",
"name: Sim_half_herd\r\n",
"network_agents:\r\n",
"- agent_type: DumbViewer\r\n",
"- agent_class: DumbViewer\r\n",
" state:\r\n",
" has_tv: false\r\n",
" weight: 1\r\n",
"- agent_type: DumbViewer\r\n",
"- agent_class: DumbViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" weight: 1\r\n",
"- agent_type: HerdViewer\r\n",
"- agent_class: HerdViewer\r\n",
" state:\r\n",
" has_tv: false\r\n",
" weight: 1\r\n",
"- agent_type: HerdViewer\r\n",
"- agent_class: HerdViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" weight: 1\r\n",
@@ -136,12 +136,12 @@
"max_time: 300\r\n",
"name: Sim_all_herd\r\n",
"network_agents:\r\n",
"- agent_type: HerdViewer\r\n",
"- agent_class: HerdViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" state_id: neutral\r\n",
" weight: 1\r\n",
"- agent_type: HerdViewer\r\n",
"- agent_class: HerdViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" state_id: neutral\r\n",
@@ -163,12 +163,12 @@
"max_time: 300\r\n",
"name: Sim_wise_herd\r\n",
"network_agents:\r\n",
"- agent_type: HerdViewer\r\n",
"- agent_class: HerdViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" state_id: neutral\r\n",
" weight: 1\r\n",
"- agent_type: WiseViewer\r\n",
"- agent_class: WiseViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" weight: 1\r\n",
@@ -189,12 +189,12 @@
"max_time: 300\r\n",
"name: Sim_all_wise\r\n",
"network_agents:\r\n",
"- agent_type: WiseViewer\r\n",
"- agent_class: WiseViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" state_id: neutral\r\n",
" weight: 1\r\n",
"- agent_type: WiseViewer\r\n",
"- agent_class: WiseViewer\r\n",
" state:\r\n",
" has_tv: true\r\n",
" weight: 1\r\n",

138
examples/newsspread/NewsSpread.yml
View File

@@ -1,138 +0,0 @@
---
default_state: {}
load_module: newsspread
environment_agents: []
environment_params:
prob_neighbor_spread: 0.0
prob_tv_spread: 0.01
interval: 1
max_time: 300
name: Sim_all_dumb
network_agents:
- agent_type: DumbViewer
state:
has_tv: false
weight: 1
- agent_type: DumbViewer
state:
has_tv: true
weight: 1
network_params:
generator: barabasi_albert_graph
n: 500
m: 5
num_trials: 50
---
default_state: {}
load_module: newsspread
environment_agents: []
environment_params:
prob_neighbor_spread: 0.0
prob_tv_spread: 0.01
interval: 1
max_time: 300
name: Sim_half_herd
network_agents:
- agent_type: DumbViewer
state:
has_tv: false
weight: 1
- agent_type: DumbViewer
state:
has_tv: true
weight: 1
- agent_type: HerdViewer
state:
has_tv: false
weight: 1
- agent_type: HerdViewer
state:
has_tv: true
weight: 1
network_params:
generator: barabasi_albert_graph
n: 500
m: 5
num_trials: 50
---
default_state: {}
load_module: newsspread
environment_agents: []
environment_params:
prob_neighbor_spread: 0.0
prob_tv_spread: 0.01
interval: 1
max_time: 300
name: Sim_all_herd
network_agents:
- agent_type: HerdViewer
state:
has_tv: true
state_id: neutral
weight: 1
- agent_type: HerdViewer
state:
has_tv: true
state_id: neutral
weight: 1
network_params:
generator: barabasi_albert_graph
n: 500
m: 5
num_trials: 50
---
default_state: {}
load_module: newsspread
environment_agents: []
environment_params:
prob_neighbor_spread: 0.0
prob_tv_spread: 0.01
prob_neighbor_cure: 0.1
interval: 1
max_time: 300
name: Sim_wise_herd
network_agents:
- agent_type: HerdViewer
state:
has_tv: true
state_id: neutral
weight: 1
- agent_type: WiseViewer
state:
has_tv: true
weight: 1
network_params:
generator: barabasi_albert_graph
n: 500
m: 5
num_trials: 50
---
default_state: {}
load_module: newsspread
environment_agents: []
environment_params:
prob_neighbor_spread: 0.0
prob_tv_spread: 0.01
prob_neighbor_cure: 0.1
interval: 1
max_time: 300
name: Sim_all_wise
network_agents:
- agent_type: WiseViewer
state:
has_tv: true
state_id: neutral
weight: 1
- agent_type: WiseViewer
state:
has_tv: true
weight: 1
network_params:
generator: barabasi_albert_graph
n: 500
m: 5
network_params:
generator: barabasi_albert_graph
n: 500
m: 5
num_trials: 50

86
examples/newsspread/newsspread.py
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@@ -1,86 +0,0 @@
from soil.agents import FSM, state, default_state, prob
import logging
class DumbViewer(FSM):
'''
A viewer that gets infected via TV (if it has one) and tries to infect
its neighbors once it's infected.
'''
defaults = {
'prob_neighbor_spread': 0.5,
'prob_tv_spread': 0.1,
}
@default_state
@state
def neutral(self):
if self['has_tv']:
if prob(self.env['prob_tv_spread']):
return self.infected
@state
def infected(self):
for neighbor in self.get_neighboring_agents(state_id=self.neutral.id):
if prob(self.env['prob_neighbor_spread']):
neighbor.infect()
def infect(self):
'''
This is not a state. It is a function that other agents can use to try to
infect this agent. DumbViewer always gets infected, but other agents like
HerdViewer might not become infected right away
'''
self.set_state(self.infected)
class HerdViewer(DumbViewer):
'''
A viewer whose probability of infection depends on the state of its neighbors.
'''
def infect(self):
'''Notice again that this is NOT a state. See DumbViewer.infect for reference'''
infected = self.count_neighboring_agents(state_id=self.infected.id)
total = self.count_neighboring_agents()
prob_infect = self.env['prob_neighbor_spread'] * infected/total
self.debug('prob_infect', prob_infect)
if prob(prob_infect):
self.set_state(self.infected)
class WiseViewer(HerdViewer):
'''
A viewer that can change its mind.
'''
defaults = {
'prob_neighbor_spread': 0.5,
'prob_neighbor_cure': 0.25,
'prob_tv_spread': 0.1,
}
@state
def cured(self):
prob_cure = self.env['prob_neighbor_cure']
for neighbor in self.get_neighboring_agents(state_id=self.infected.id):
if prob(prob_cure):
try:
neighbor.cure()
except AttributeError:
self.debug('Viewer {} cannot be cured'.format(neighbor.id))
def cure(self):
self.set_state(self.cured.id)
@state
def infected(self):
cured = max(self.count_neighboring_agents(self.cured.id),
1.0)
infected = max(self.count_neighboring_agents(self.infected.id),
1.0)
prob_cure = self.env['prob_neighbor_cure'] * (cured/infected)
if prob(prob_cure):
return self.cured
return self.set_state(super().infected)

134
examples/newsspread/newsspread_sim.py Normal file
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@@ -0,0 +1,134 @@
from soil.agents import FSM, NetworkAgent, state, default_state, prob
from soil.parameters import *
import logging
from soil.environment import Environment
class DumbViewer(FSM, NetworkAgent):
"""
A viewer that gets infected via TV (if it has one) and tries to infect
its neighbors once it's infected.
"""
has_been_infected: bool = False
has_tv: bool = False
@default_state
@state
def neutral(self):
if self.has_tv:
if self.prob(self.get("prob_tv_spread")):
return self.infected
if self.has_been_infected:
return self.infected
@state
def infected(self):
for neighbor in self.get_neighbors(state_id=self.neutral.id):
if self.prob(self.get("prob_neighbor_spread")):
neighbor.infect()
def infect(self):
"""
This is not a state. It is a function that other agents can use to try to
infect this agent. DumbViewer always gets infected, but other agents like
HerdViewer might not become infected right away
"""
self.has_been_infected = True
class HerdViewer(DumbViewer):
"""
A viewer whose probability of infection depends on the state of its neighbors.
"""
def infect(self):
"""Notice again that this is NOT a state. See DumbViewer.infect for reference"""
infected = self.count_neighbors(state_id=self.infected.id)
total = self.count_neighbors()
prob_infect = self.get("prob_neighbor_spread") * infected / total
self.debug("prob_infect", prob_infect)
if self.prob(prob_infect):
self.has_been_infected = True
class WiseViewer(HerdViewer):
"""
A viewer that can change its mind.
"""
@state
def cured(self):
prob_cure = self.get("prob_neighbor_cure")
for neighbor in self.get_neighbors(state_id=self.infected.id):
if self.prob(prob_cure):
try:
neighbor.cure()
except AttributeError:
self.debug("Viewer {} cannot be cured".format(neighbor.id))
def cure(self):
self.has_been_cured = True
@state
def infected(self):
if self.has_been_cured:
return self.cured
cured = max(self.count_neighbors(self.cured.id), 1.0)
infected = max(self.count_neighbors(self.infected.id), 1.0)
prob_cure = self.get("prob_neighbor_cure") * (cured / infected)
if self.prob(prob_cure):
return self.cured
class NewsSpread(Environment):
ratio_dumb: probability = 1,
ratio_herd: probability = 0,
ratio_wise: probability = 0,
prob_tv_spread: probability = 0.1,
prob_neighbor_spread: probability = 0.1,
prob_neighbor_cure: probability = 0.05,
def init(self):
self.populate_network([DumbViewer, HerdViewer, WiseViewer],
[self.ratio_dumb, self.ratio_herd, self.ratio_wise])
from itertools import product
from soil import Simulation
# We want to investigate the effect of different agent distributions on the spread of news.
# To do that, we will run different simulations, with a varying ratio of DumbViewers, HerdViewers, and WiseViewers
# Because the effect of these agents might also depend on the network structure, we will run our simulations on two different networks:
# one with a small-world structure and one with a connected structure.
counter = 0
for [r1, r2] in product([0, 0.5, 1.0], repeat=2):
for (generator, netparams) in {
"barabasi_albert_graph": {"m": 5},
"erdos_renyi_graph": {"p": 0.1},
}.items():
print(r1, r2, 1-r1-r2, generator)
# Create new simulation
netparams["n"] = 500
Simulation(
name='newspread_sim',
model=NewsSpread,
parameters=dict(
ratio_dumb=r1,
ratio_herd=r2,
ratio_wise=1-r1-r2,
network_generator=generator,
network_params=netparams,
prob_neighbor_spread=0,
),
iterations=5,
max_steps=300,
dump=False,
).run()
counter += 1
# Run all the necessary instances
print(f"A total of {counter} simulations were run.")