def get_name(self, id_):
try:
for player in self.players:
if player[0] == id_:
return player[1]
log.error("get_name: could not find [%s] on list" % id_)
raise KeyError
except KeyError as e:
log.error(e)
return "ERROR"
def add_bid(self, id_, bid):
for player in self.players:
if player[0] == id_:
if player[2] < bid:
player[2] = bid
log.info("[%s][%s] changed bid from %s to %s" %
(player[0], player[1], player[2], bid))
yield
else:
log.warning(
"[%s][%s] tried to bid from %s to %s. Not cool, bro. Not cool."
% (player[0], player[1], player[2], bid))
yield
log.error("add_bid: could not find [%s] on list" % id_)
def medicines(self, args):
log.info("Export medicines")
# Get filename
if not "filename" in args:
log.error("No filename provided")
exit()
# log.info("Func medicines")
template_filename = "gui/templates/medicines_report.html"
html_string = inventory.medicines.utils.export_html(template_filename)
if "html" in args and args["html"]:
try:
with open(args["filename"].name + ".html", "w") as fdesc:
fdesc.write(html_string)
except IOError as error:
log.error("File not writable: %s", error)
try:
with open("gui/templates/report.css", "r") as fdesc:
css_string = fdesc.read()
except IOError as error:
log.error("CSS file not readable: %s", error)
exit()
inventory.medicines.utils.export_pdf(
pdf_filename=args["filename"].name,
html_string=html_string,
css_string=css_string)
def check_if_in(self, id_):
for player in self.players:
if player[0] == id_:
return True
log.error("check_if_in: could not find [%s] on list" % id_)
return False
dyn_reg2 = args.dyn_reg2
net_activation = args.net_activation
pre_process = args.pre_process
LengthOfCurve = args.LengthOfCurve
action_noise = args.action_noise
exp_group_dir = args.exp_group_dir
#TODO important
USE_PROB_PREDICT = args.mode # 'random'#'prob'
# param check
if dyn_batch_size > max_timestep:
assert log.error(
'Hyper param error: dyn_batch_size must not be more than max_timestep.'
)
# Exp paramaters
log_interval_policy = 100
exp_name = 'Train_policy'
num_exp = args.exp_num
log_name = 'train._{} _drop{}_nrd{}-EXP_{}'.format(exp_name, drop_p, n_rnd,
num_exp)
# Create log files
log_dir = utils.configure_log_dir(env_name,
txt=log_name,
No_time=False,
log_group=exp_group_dir)
logger = utils.Logger(log_dir, csvname='log')