So trying to just get my head back into this. The contents of my config.toml
are below. I'm trying to run (what I understand to be):
cmosiman$ python main.py -u
/Users/cmosiman/.pyenv/versions/dragg/lib/python3.6/site-packages/pandas/compat/__init__.py:120: UserWarning: Could not import the lzma module. Your installed Python is incomplete. Attempting to use lzma compression will result in a RuntimeError.
warnings.warn(msg)
INFO:aggregator:Set the version write out to ['dn-wd-v4', 'dn-wd-v4-avg']
INFO:aggregator:Start: 2015-01-01T00:00:00; End: 2015-01-02T00:00:00; Number of hours: 24
INFO:aggregator:Made it to Aggregator Run
INFO:aggregator:Flushing Redis
INFO:aggregator:Homes looking ok!
INFO:aggregator:Performing baseline run for horizon: 6
multiprocess.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/Users/cmosiman/.pyenv/versions/dragg/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/Users/cmosiman/.pyenv/versions/dragg/lib/python3.6/site-packages/multiprocess/pool.py", line 44, in mapstar
return list(map(*args))
File "/Users/cmosiman/.pyenv/versions/dragg/lib/python3.6/site-packages/pathos/helpers/mp_helper.py", line 15, in <lambda>
func = lambda args: f(*args)
File "/Users/cmosiman/Github/dragg/dragg/mpc_calc.py", line 28, in manage_home
home.run_home()
File "/Users/cmosiman/Github/dragg/dragg/mpc_calc.py", line 716, in run_home
self.solve_type_problem()
File "/Users/cmosiman/Github/dragg/dragg/mpc_calc.py", line 692, in solve_type_problem
self.set_environmental_variables()
File "/Users/cmosiman/Github/dragg/dragg/mpc_calc.py", line 270, in set_environmental_variables
self.cast_redis_curr_rps()
File "/Users/cmosiman/Github/dragg/dragg/mpc_calc.py", line 684, in cast_redis_curr_rps
self.tracked_price[0] = self.reward_price[0]
IndexError: list index out of range
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "main.py", line 7, in <module>
a.run()
File "/Users/cmosiman/Github/dragg/dragg/aggregator.py", line 1174, in run
self.run_baseline()
File "/Users/cmosiman/Github/dragg/dragg/aggregator.py", line 875, in run_baseline
self.run_iteration()
File "/Users/cmosiman/Github/dragg/dragg/aggregator.py", line 819, in run_iteration
results = pool.map(manage_home, self.as_list)
File "/Users/cmosiman/.pyenv/versions/dragg/lib/python3.6/site-packages/pathos/multiprocessing.py", line 137, in map
return _pool.map(star(f), zip(*args)) # chunksize
File "/Users/cmosiman/.pyenv/versions/dragg/lib/python3.6/site-packages/multiprocess/pool.py", line 266, in map
return self._map_async(func, iterable, mapstar, chunksize).get()
File "/Users/cmosiman/.pyenv/versions/dragg/lib/python3.6/site-packages/multiprocess/pool.py", line 644, in get
raise self._value
IndexError: list index out of range
[community]
total_number_homes = [ 10, 0,]
homes_battery = [ 0, 0,]
homes_pv = [ 3, 0,]
homes_pv_battery = [ 0, 0,]
overwrite_existing = true
house_p_avg = 1.0
[simulation]
start_datetime = "2015-01-01 00"
end_datetime = "2015-01-02 00"
loop_days = true
random_seed = 12
n_nodes = 1
load_zone = "LZ_HOUSTON"
check_type = "all"
run_rbo_mpc = true
run_rl_agg = false
run_rl_simplified = false
checkpoint_interval = "daily"
[rl]
version = [ "dn-wd-v4", "dn-wd-v4-avg"]
[rl.parameters]
learning_rate = [ 0.01,]
discount_factor = [ 1.0,]
batch_size = [ 4, 32,]
exploration_rate = [ 0.01,]
twin_q = false
[rl.utility]
rl_agg_action_horizon = [ 6, 4,]
rl_agg_forecast_horizon = 1
base_price = 0.1
action_space = [ -1.0, 1.0,]
hourly_steps = [ 1,]
minutes_per_step = 120
tou_enabled = false
[rl.simplified]
response_rate = 0.3
offset = 0.2
[home.hvac]
r_dist = [ 6.8, 9.199999999999999,]
c_dist = [ 4.25, 5.75,]
p_cool_dist = [ 3.5, 3.5,]
p_heat_dist = [ 3.5, 3.5,]
temp_sp_dist = [ 18, 22,]
temp_deadband_dist = [ 2, 3,]
[home.wh]
r_dist = [ 18.7, 25.3,]
c_dist = [ 4.25, 5.75,]
p_dist = [ 2.5, 2.5,]
sp_dist = [ 45.5, 48.5,]
deadband_dist = [ 9, 12,]
size_dist = [ 200, 300,]
[home.battery]
max_rate = 5
capacity = 13.5
cap_bounds = [ 0.15, 0.85,]
charge_eff = 0.95
discharge_eff = 0.99
cons_penalty = 0.005
[home.pv]
area = 32
efficiency = 0.2
[home.hems]
prediction_horizon = [ 6,]
price_uncertainty = 0.3
sub_subhourly_steps = [ 4,]
solver = "GLPK_MI"
[rl.utility.tou]
shoulder_times = [ 9, 21,]
shoulder_price = 0.09
peak_times = [ 14, 18,]
peak_price = 0.13
[home.wh.waterdraws]
n_big_draw_dist = [ 2, 5,]
n_small_draw_dist = [ 0, 0,]
big_draw_size_dist = [ 25, 40,]
small_draw_size_dist = [ 7.5, 15.0,]