def adjustcapasity(txl, history, dynamic=True):
"""
Rule function that applies the capacity change algorithm in the case of two intervention node systems. This is uses
a history variable that is cleared when the capacity is adjusted so that another five timesteps must pass before the
capacity can be changed again. This only modifies OpenIntervention if dynamic is true else only intervention is
modified.
:param txl: neo4j database write transaction
:param history: List of previous average times since discharge
:param dynamic: indicates if adjustment to OpenIntervention is needed
:return: history
"""
currenttimes = timesincedischarge(txl)
if not currenttimes and history:
currentav = history[-1]
elif not currenttimes:
currentav = 14
else:
currentav = mean(currenttimes)
history = history + [currentav]
# If it has been less than 20 time steps since last change do nothing
if len(history) < 20:
return history
else:
if history[-5] - history[-1] < -1 and history[-1] > 5:
if dynamic:
if intf.getnodevalue(
txl, "InterventionOpen", "cap",
uid="name") > 0 and dynamic:
intf.updatenode(
txl, "Intervention", "cap",
intf.getnodevalue(
txl, "Intervention", "cap", uid="name") + 1,
"name")
intf.updatenode(
txl, "InterventionOpen", "cap",
intf.getnodevalue(
txl, "InterventionOpen", "cap", uid="name") - 1,
"name")
else:
intf.updatenode(
txl, "Intervention", "cap",
intf.getnodevalue(txl, "Intervention", "cap", uid="name") +
1, "name")
return []
elif history[-5] - history[-1] > 0 and history[-1] < 5:
if intf.getnodevalue(txl, "Intervention", "cap", uid="name") > 0:
intf.updatenode(
txl, "Intervention", "cap",
intf.getnodevalue(txl, "Intervention", "cap", uid="name") -
1, "name")
if dynamic:
intf.updatenode(
txl, "InterventionOpen", "cap",
intf.getnodevalue(
txl, "InterventionOpen", "cap", uid="name") + 1,
"name")
return []
else:
return history
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
def learn(self, tx, choice):
"""
Agent is changed by node and can change node and edge it arrived by. This can include changes to decision
making parameters.
:param tx: neo4j database write transaction
:param choice: Chosen edge for move
:return: None
"""
super(FallAgent, self).learn(tx, choice)
# modify mob, conf, res and energy based on new node
if self.fall and self.fall != "Mild":
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) + ")"
if "modm" in choice.end_node:
self.mobility = self.positive(
npr.normal(choice.end_node["modm"], 0.05) + self.mobility)
intf.updateagent(tx, self.id, "mob", self.mobility)
# check for updates to wellbeing and log any changes
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 "modc" in choice.end_node:
self.confidence = self.positive(
npr.normal(choice.end_node["modc"], 0.05) + self.confidence)
intf.updateagent(tx, self.id, "conf", self.confidence)
if "modrc" in choice.end_node:
self.confidence_resources = self.positive(
npr.normal(choice.end_node["modrc"], 0.05) +
self.confidence_resources)
intf.updateagent(tx, self.id, "conf_res",
self.confidence_resources)
if "modrm" in choice.end_node:
self.mobility_resources = self.positive(
npr.normal(choice.end_node["modrm"], 0.05) + self.mobility)
intf.updateagent(tx, self.id, "mob_res", self.mobility_resources)
if "energy" in choice.end_node:
self.current_energy = npr.normal(choice.end_node["energy"],
0.05) + self.current_energy
intf.updateagent(tx, self.id, "energy", self.current_energy)
# log going into care
if choice.end_node["name"] == "Care":
clock = tx.run("MATCH (a:Clock) " "RETURN a.time").values()[0][0]
self.log = self.log + ", (Care, " + str(clock) + ")"
if "cap" in choice.end_node.keys():
intf.updatenode(tx, choice.end_node["name"], "load",
choice.end_node["load"] + 1, "name")
if self.view[0]["name"] == "Hos" and choice.end_node["name"] != "Hos":
clock = tx.run("MATCH (a:Clock) " "RETURN a.time").values()[0][0]
self.log = self.log + ", (Discharged, " + str(clock) + ")"
intf.updateagent(tx, self.id, "log", str(self.log))
def learn(self, tx, choice):
"""
Agent is changed by node and can change node and edge it arrived by. This can include changes to decision
making parameters.
:param tx: neo4j database write transaction
:param choice: Chosen edge for move
:return: None
"""
super(Patient, self).learn(tx, choice)
# modify mob, conf, res and energy based on new node
if self.fall and self.fall != "Mild":
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) + ")"
if "modm" in choice.end_node:
self.mobility = self.positive(
npr.normal(choice.end_node["modm"], 0.05) + self.mobility)
intf.updateagent(tx, self.id, "mob", self.mobility)
# check for updates to wellbeing and log any changes
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 choice.end_node:
self.mood = self.positive(
npr.normal(choice.end_node["modmood"], 0.05) + self.mood)
intf.updateagent(tx, self.id, "mood", self.mood)
if "energy" in choice.end_node:
self.current_energy = npr.normal(choice.end_node["energy"],
0.05) + self.current_energy
energy_change = self.current_energy - self.energy
intf.updateagent(tx, self.id, "energy", self.current_energy)
edge_types = ["social", "fall", "medical", "inactive"]
for i in range(len(edge_types)):
if choice["type"] == edge_types[i]:
if energy_change < 0:
self.inclination[i] = self.inclination[i] + 1
elif energy_change > 0:
self.inclination[i] = self.positive(
self.inclination[i] - 1)
# change to inclination based on mobility, energy and mood
if self.current_energy > 0.8:
self.inclination[0] = self.inclination[0] + 1
elif self.current_energy < 0.2:
self.inclination[3] = self.inclination[3] + 1
if self.mood > 0.8:
self.inclination[0] = self.inclination[0] - 1
self.inclination[3] = self.inclination[3] + 1
elif self.mood < 0.2:
self.inclination[0] = self.inclination[0] + 1
self.inclination[3] = self.inclination[3] - 1
if self.mobility < 0.4:
self.inclination[2] = self.inclination[2] + 1
self.inclination[3] = self.inclination[3] + 1
elif self.mobility > 0.8:
self.inclination[3] = self.inclination[3] - 1
intf.updateagent(tx, self.id, "inclination", self.inclination)
# log going into care
if choice.end_node["name"] == "Care":
clock = tx.run("MATCH (a:Clock) " "RETURN a.time").values()[0][0]
self.log = self.log + ", (Care, " + str(clock) + ")"
if "cap" in choice.end_node.keys():
intf.updatenode(tx, choice.end_node["name"], "load",
choice.end_node["load"] + 1, "name")
if self.view[0]["name"] == "Hos" and choice.end_node["name"] != "Hos":
clock = tx.run("MATCH (a:Clock) " "RETURN a.time").values()[0][0]
self.log = self.log + ", (Discharged, " + str(clock) + ")"
intf.updateagent(tx, self.id, "log", str(self.log))