def __init__(self,
validation,
test_days,
sampling_type=None): ## sampling_type can be 'prob' or 'max'
ur = probabilistic_rewards.uncertain_rewards(test_days)
task_prob, self.prob, self.clusters = ur.get_probabilistic_reward_model(
)
self.time_int = 48
self.int_duration = 1440 / self.time_int
if validation == True:
self.test_days = ur.test_days
self.test_tasks = ur.test_tasks
self.no_days = len(self.test_days)
### expected data
# self.test_rewards = []
# with open('/home/milan/workspace/strands_ws/src/battery_scheduler/data/exp_rewards', 'r') as f:
# for rew in f:
# self.test_rewards.append(float(rew[:-1]))
else:
self.no_days = 1 # no. of days to be tested, if not using validation
self.rewards, self.cl_ids, self.act_rewards = self.get_samples(
validation, sampling_type)
def __init__(self, init_battery, init_charging, test_days, pareto_point):
ur = probabilistic_rewards.uncertain_rewards(test_days)
self.task_prob, self.prob, self.clusters = ur.get_probabilistic_reward_model(
)
self.charge_model, self.discharge_model, self.gocharge_model = get_battery_model(
)
self.cl_id = []
self.sample_reward = []
self.actual_reward = []
self.exp_reward = []
self.no_int = ur.no_int
self.no_days = len(ur.test_days)
self.horizon = 48 ## in terms of intervals
self.no_simulations = 1
for z in range(self.no_int * self.no_days):
self.exp_reward.append(
sum(self.prob[z % self.no_int] * self.clusters))
print self.prob[z % self.no_int], self.clusters, sum(
self.prob[z % self.no_int] * self.clusters)
self.req_pareto_point = pareto_point
self.main_path = roslib.packages.get_pkg_dir('battery_scheduler')
self.path_mod = self.main_path + '/models/'
self.path_data = self.main_path + '/data/'
sg = generate_samples.sample_generator(True, test_days)
self.cl_id = []
for clid in sg.cl_ids:
if np.isnan(clid):
cl = None
else:
cl = int(clid)
self.cl_id.append(cl)
self.sample_reward = sg.rewards
self.actual_reward = sg.act_rewards
self.totalreward = np.zeros((self.no_days))
self.init_battery = init_battery
self.init_charging = init_charging
self.actions = []
self.obtained_rewards = []
self.battery = []
self.charging = []
self.time = []
self.pareto_point = []
self.simulate()
def __init__(self, init_battery, init_charging, test_days, pareto_point):
ur = probabilistic_rewards.uncertain_rewards(test_days)
self.task_prob, self.prob, self.clusters = ur.get_probabilistic_reward_model(
)
self.charge_model, self.discharge_model = get_battery_model()
self.cl_id = []
self.sample_reward = []
self.actual_reward = []
self.exp_reward = []
self.no_int = ur.no_int
self.no_days = len(ur.test_days)
self.horizon = 48 ## in terms of intervals
self.no_simulations = 1
for z in range(self.no_int * self.no_days):
self.exp_reward.append(
sum(self.prob[z % self.no_int] * self.clusters))
self.req_pareto_point = pareto_point
self.main_path = roslib.packages.get_pkg_dir('battery_scheduler')
self.path_rew = self.main_path + '/data/rhc2_sample_rewards'
self.path_mod = self.main_path + '/models/'
self.path_data = self.main_path + '/data/'
if not os.path.isfile(self.path_rew):
raise ValueError(
'Sample Rewards Not Generated. Generate rewards with generate_samples.py'
)
with open(self.path_rew, 'r') as f:
for line in f:
x = line.split(' ')
self.cl_id.append(int(float(x[0].strip())))
self.sample_reward.append(float(x[1].strip()))
self.actual_reward.append(float(x[2].strip()))
self.totalreward = np.zeros((self.no_days))
self.init_battery = init_battery
self.init_charging = init_charging
self.actions = []
self.obtained_rewards = []
self.battery = []
self.charging = []
self.time = []
self.pareto_point = []
def __init__(self, init_battery, init_charging, test_days, plan_id):
ur = probabilistic_rewards.uncertain_rewards(test_days)
self.task_prob, self.prob, self.clusters = ur.get_probabilistic_reward_model(
)
self.charge_model, self.discharge_model = get_battery_model()
self.cl_id = []
self.sample_reward = []
self.actual_reward = []
self.exp_reward = []
self.no_int = ur.no_int
self.no_days = len(ur.test_days)
self.no_simulations = 1
for z in range(self.no_int * self.no_days):
self.exp_reward.append(
sum(self.prob[z % self.no_int] * self.clusters))
#######################SPECIFY LOCATION ######################
self.main_path = '/home/milan/workspace/strands_ws/src/battery_scheduler'
self.path_rew = self.main_path + '/data/bcth_pareto_sample_rewards'
self.path_mod = self.main_path + '/models/'
self.path_data = self.main_path + '/data/'
if not os.path.isfile(self.path_rew):
raise ValueError(
'Sample Rewards Not Generated. Generate rewards with generate_samples.py'
)
with open(self.path_rew, 'r') as f:
for line in f:
x = line.split(' ')
self.cl_id.append(int(float(x[0].strip())))
self.sample_reward.append(float(x[1].strip()))
self.actual_reward.append(float(x[2].strip()))
self.avg_totalreward = np.zeros((self.no_days))
self.init_battery = init_battery
self.init_charging = init_charging
self.actions = []
self.obtained_rewards = []
self.battery = []
self.charging = []
self.time = []
self.plan_id = plan_id
def __init__(self, init_battery, init_charging, test_days):
self.current_battery = init_battery
self.current_charging = init_charging
self.charge_model, self.discharge_model = get_battery_model()
ur = probabilistic_rewards.uncertain_rewards(test_days)
self.task_prob, prob, clusters = ur.get_probabilistic_reward_model()
self.threshold = np.mean(clusters)
# self.threshold = 8000
self.test_rewards = []
with open(
roslib.packages.get_pkg_dir('battery_scheduler') +
'/data/rbc4_sample_rewards', 'r') as f:
for line in f:
self.test_rewards.append(float(line.split(' ')[2].strip()))
self.battery = []
self.charging = []
self.action = []
self.obtained_reward = []
self.time = []
def get_rewards_from_plan(self, fname):
print 'Reading Plan...'
file_name = roslib.packages.get_pkg_dir(
'battery_scheduler') + '/data/' + fname
rewards_obtained = []
with open(file_name, 'r') as f:
for line in f:
if 'time' not in line:
s = line.split(' ')
rewards_obtained.append(float(s[4]))
return rewards_obtained
if __name__ == '__main__':
pr = probabilistic_rewards.uncertain_rewards([])
probt, probm, rew_cl = pr.get_probabilistic_reward_model()
threshold = np.mean(rew_cl)
rbc3 = RuleBasedControl(70, 1, [
datetime(2017, 10, 10),
datetime(2017, 10, 11),
datetime(2017, 10, 12)
], threshold)
rbc3.get_plan('rbc3_101011101210_1')
np.random.seed(1)
rbc3 = RuleBasedControl(70, 1, [
datetime(2017, 10, 10),
datetime(2017, 10, 11),
datetime(2017, 10, 12)