def react(self, tx):
"""
If the agent now has more social bonds than they can manage we drop new non carer friends then those not used
recently and finally reduce the carers from most recent.
:param tx: neo4j write transaction
:return: None
"""
super(Patient, self).react(tx)
self.contacts = intf.agentcontacts(tx, self.id, "Agent")
carers = self.contacts + intf.agentcontacts(tx, self.id, "Agent",
"Carer")
if len(self.contacts) > self.social:
while len(carers) > self.social:
carer_drop = None
latest_time = 0
for carer in carers:
if carer["created"] > latest_time:
carer_drop = carer
latest_time = carer["created"]
intf.deletecontact(tx, self.id, carer_drop.end_node["id"],
"Agent", "Carer")
if len(carers) == self.social:
for contact in contacts:
intf.deletecontact(tx, self.id, contact.end_node["id"],
"Agent", "Agent")
if len(carers) + len(contacts) > self.social:
for contact in contacts:
if len(carers) + len(contacts) > self.social:
if intf.gettime() - contact['created'] < 5:
intf.deletecontact(tx, self.id,
contact.end_node["id"], "Agent",
"Agent")
oldest_usage = 0
contact_drop = None
while len(carers) + len(contacts) > self.social:
for contact in contacts:
if intf.gettime() - contact["usage"] > oldest_usage:
contact_drop = contact
oldest_usage = intf.gettime() - contact["usage"]
intf.deletecontact(tx, self.id, contact_drop.end_node["id"],
"Agent", "Agent")
def update(self, tx):
"""
Check agent contacts compare list with co-located agents and update co-located contacts with new last usage
:param tx: neo4j database write transaction
:return: None
"""
super(Patient, self).update(tx)
# Update existing com links with latest co-location
self.contacts = intf.agentcontacts(tx, self.id, "Patient")
if self.contacts and self.colocated:
update = [
contact for contact in self.contacts
if contact in self.colocated
]
for contact in update:
intf.updatecontactedge(tx, contact.end_node["id"], self.id,
"last_usage", intf.gettime())
def listen(self, tx):
"""
If the agent has a new social link check if the new friend has a link to a carer if they do for a random carer
they form a link with a .5 chance.
:param tx: neo4j write transaction
:return: None
"""
super(Patient, self).listen(tx)
if self.contacts:
carers = intf.agentcontacts(tx, self.contacts.end_node["id"],
"Agent", "Carer")
carers = [carer for carer in carers if carer["carer"]]
carer = npr.sample(carers)
if npr.random(1) < 0.5:
intf.createedge(
self.id, carer.end_node["id"], 'Patient', 'Carer',
'SOCIAL:FRIEND', 'created: ' + intf.gettime() +
', usage: ' + intf.gettime() + ', carer: True')
def payment(self, tx):
"""
Modifies chosen edge and agent. These include mobility, confidence and energy modifications.
:param tx: neo4j database write transaction
:return: None
"""
super(Patient, self).payment(tx)
# Deduct energy used on edge
if "energy" in self.choice.keys():
if "energy" in self.choice.end_node.keys():
if self.choice["energy"] + self.choice.end_node[
"energy"] > self.current_energy:
# Check for carers
carers = intf.agentcontacts(tx, self.id, "Agent", "Carer")
# Check for sufficient energy
for carer in carers:
print(carer)
if carer.end_node["energy"] >= self.choice["energy"]:
intf.updatenode(tx,
carer.end_node["id"],
"energy",
carer.end_node["energy"] -
self.choice["energy"],
label='Carer')
self.current_energy = self.current_energy + self.choice[
"energy"]
intf.updateagent(tx, self.id, "energy",
self.current_energy)
intf.updatecontactedge(tx, self.id,
carer.end_node["id"],
"usage", intf.gettime(tx),
"Agent", "Carer")
break
else:
return False
self.current_energy = npr.normal(self.choice["energy"],
0.05) + self.current_energy
intf.updateagent(tx, self.id, "energy", self.current_energy)
# mod variables based on edges
if "modm" in self.choice:
self.mobility = self.positive(
npr.normal(self.choice["modm"], 0.05) + self.mobility)
intf.updateagent(tx, self.id, "mob", self.mobility)
if self.mobility == 0:
if self.wellbeing != "Fallen":
self.wellbeing = "Fallen"
intf.updateagent(tx, self.id, "wellbeing", self.wellbeing)
clock = tx.run("MATCH (a:Clock) "
"RETURN a.time").values()[0][0]
self.log = self.log + ", (Fallen, " + str(clock) + ")"
elif self.mobility > 1:
if self.wellbeing != "Healthy":
self.wellbeing = "Healthy"
intf.updateagent(tx, self.id, "wellbeing", self.wellbeing)
clock = tx.run("MATCH (a:Clock) "
"RETURN a.time").values()[0][0]
self.log = self.log + ", (Healthy, " + str(clock) + ")"
elif self.mobility <= 1:
if self.wellbeing == "Healthy":
self.wellbeing = "At risk"
intf.updateagent(tx, self.id, "wellbeing", self.wellbeing)
clock = tx.run("MATCH (a:Clock) "
"RETURN a.time").values()[0][0]
self.log = self.log + ", (At risk, " + str(clock) + ")"
if "modmood" in self.choice:
self.mood = self.positive(
npr.normal(self.choice["modmood"], 0.05) + self.mood)
intf.updateagent(tx, self.id, "mood", self.mood)
return True