def make_planting_decision(self, activities, farm):
all_activities = dict(self.eutopia.latest_activity_count)
total_activities = float(sum(all_activities.values()))
if total_activities > 0:
for k, v in all_activities.items():
all_activities[k] /= total_activities
if self.preferences.get('follow_local', 0) != 0:
local_activities = self.eutopia.get_activity_count(farm.neighbours)
total_activities = float(sum(local_activities.values()))
if total_activities > 0:
for k, v in local_activities.items():
local_activities[k] /= total_activities
best = None
for activity in activities:
total = 0
for pref, weight in self.preferences.items():
if pref == 'follow_society':
total += all_activities.get(activity.name, 0) * weight
elif pref == 'follow_local':
if weight != 0:
total += local_activities.get(activity.name,
0) * weight
else:
total += activity.get_product(pref, farm) * weight
# TODO: improve choice algorithm
# - maybe by allowing different sensitivities to risk
# on different income dimensions
if best is None or total > best_total:
best = activity
best_total = total
return best
def step(self):
for farm in self.farms:
activity = self.make_planting_decision(eutopia.activities.activities, farm)
money = activity.get_product('money', farm)
self.bank_balance += money
farm.last_activity = activity
def step(self):
for farm in self.farms:
# changed to self.eutopia to make it work with the sim version that is passed to Family21
activity = self.make_planting_decision(self.eutopia.activities.activities, farm)
money = activity.get_product('money', farm)
self.bank_balance += money
farm.last_activity = activity
def step(self):
for farm in self.farms:
# changed to self.eutopia to make it work with the sim version that is passed to Family21
activity = self.make_planting_decision(self.eutopia.activities.activities, farm)
money = activity.get_product('money', farm)
self.bank_balance += money
farm.last_activity = activity
def make_planting_decision(self, activities, farm):
best = None
for activity in activities:
total = 0
for pref, weight in self.preferences.items():
total += activity.get_product(pref, farm) * weight
# TODO: improve choice algorithm
# - maybe by allowing different sensitivities to risk
# on different income dimensions
if best is None or total > best_total:
best = activity
best_total = total
return best
def make_planting_decision(self, activities, farm):
all_activities = dict(self.eutopia.latest_activity_count)
total_activities = float(sum(all_activities.values()))
if total_activities > 0:
for k,v in all_activities.items():
all_activities[k]/=total_activities
if self.preferences.get('follow_local', 0) != 0:
local_activities = self.eutopia.get_activity_count(farm.neighbours)
total_activities = float(sum(local_activities.values()))
if total_activities > 0:
for k,v in local_activities.items():
local_activities[k]/=total_activities
best = None
for activity in activities:
total = 0
for pref, weight in self.preferences.items():
if pref=='follow_society':
total += all_activities.get(activity.name,0) * weight
elif pref=='follow_local':
if weight != 0:
total += local_activities.get(activity.name,0) * weight
else:
total += activity.get_product(pref, farm) * weight
# TODO: improve choice algorithm
# - maybe by allowing different sensitivities to risk
# on different income dimensions
if best is None or total > best_total:
best = activity
best_total = total
return best
