def test_tee_simple():
"Very simple check with stdout only"
chan = StringIO()
text = 'Hello'
tee = Tee(chan, channel='stdout')
print(text, file=chan)
nt.assert_equal(chan.getvalue(), text + "\n")
def tchan(self, channel, check='close'):
trap = StringIO()
chan = StringIO()
text = 'Hello'
std_ori = getattr(sys, channel)
setattr(sys, channel, trap)
tee = Tee(chan, channel=channel)
print(text, end='', file=chan)
setattr(sys, channel, std_ori)
trap_val = trap.getvalue()
nt.assert_equal(chan.getvalue(), text)
if check == 'close':
tee.close()
else:
del tee
def tchan(self, channel):
trap = StringIO()
chan = StringIO()
text = 'Hello'
std_ori = getattr(sys, channel)
setattr(sys, channel, trap)
tee = Tee(chan, channel=channel)
print(text, end='', file=chan)
trap_val = trap.getvalue()
self.assertEqual(chan.getvalue(), text)
tee.close()
setattr(sys, channel, std_ori)
assert getattr(sys, channel) == std_ori
def print_redirect(log_path: Union[Path, str], mode="a"):
try:
tee = Tee(log_path, mode=mode, channel="stdout")
yield tee
finally:
tee.close()
def __enter__(self):
self.orig_stream = getattr(sys, self.channel)
self.buffer = MyStringIO()
self.tee = Tee(self.buffer, channel=self.channel)
setattr(sys, self.channel, self.buffer if self.suppress else self.tee)
def _capture_on(self):
self.orig_stdout = sys.stdout
self.buffer = StringIO()
self.tee = Tee(self.buffer, 'stdout')
sys.stdout = self.buffer
df_for_cluster = util.pre_process(df)
tree = find_decision_point(df_for_cluster)
IM_tree = IM_tree.replace(" ", "")
fig_tree.create_tree(tree, config.silhouette)
sum_sil = 0.0
max_row = 0
for node in config.process_tree:
if node.sil == None:
continue
parent_log_rows = node.parent.log_rows if node.parent != -1 else node.log_rows
sum_sil += (node.sil * (node.log_rows / parent_log_rows))
max_row = node.row if node.row > max_row else max_row
total_sil = sum_sil / (max_row + 1)
with closing(Tee('log_file.txt', "a", channel="stdout")) as outputstream:
print("=============================================")
print(time.strftime("%d/%m/%Y %H:%M:%S"))
print("{} \nsilhouette threshold: {}".format(
config.data_file, config.silhouette_threshold))
print('IM tree: ', IM_tree)
print('tree: ', tree)
print(config.explain_operator)
print('sil: ', config.silhouette)
print('total_sil: ', total_sil)
fig_tree.create_tree_fig()
# activity_set = set(df['activity'].unique())
if path.exists(path1+"/States_SL.txt") == False:
print('', file=open(path1+"/States_SL.txt", "w"))
if path.exists(path1+"/States_TP.txt") == False:
print('', file=open(path1+"/States_TP.txt", "w"))
States_Market=path1+dash+"States_Market.txt"
States_Order=path1+dash+"States_Order.txt"
States_Possible=path1+dash+"States_Possible.txt"
States_isOpen=path1+dash+"States_isOpen.txt"
States_SL=path1+dash+"States_SL.txt"
States_TP=path1+dash+"States_TP.txt"
if True:#change from if to while to always loop
from IPython.utils.io import Tee
from contextlib import closing
with closing(Tee("outputfile.txt", "w", channel="stdout")) as outputstream:
try:
api_key = '4-H0Cb9XAKoBfNmCDO-yFlMf' # your api key
api_secret = 'LfpNu5iTL2UGgdknnbM0Do0Ws4edag8ckF70pb3UJNRkYkVM' # your api secret
#whenever bitmex_cli is used, 1 api useage instance is tracked by bitmex. Bitmex only allows 15 api calls per minute
bitmex_cli = bitmex1(test=False, api_key=api_key, api_secret=api_secret)#this wrapper used due to supporting leverage and the simplicity of creating market/limit orders. Also closes orders.
#creating dataframe that will be used to store candlestick data.
df=pd.DataFrame()
timep= df.append({'time':1}, ignore_index=True)
timep=timep.iloc[0:0]
openp= df.append({'open':1}, ignore_index=True)
openp=openp.iloc[0:0]
highp= df.append({'high':2}, ignore_index=True)
highp=highp.iloc[0:0]
lowp= df.append({'low':3}, ignore_index=True)
lowp=lowp.iloc[0:0]
help="Whether to show the GPU utilization on terminal")
parser.add_argument("--reverse")
args = parser.parse_args()
exp_id = args.id
tot_exps = args.tot_exps
n_trials = args.trials
gputil = args.print_gputil
gpus = tf.config.experimental.list_physical_devices('GPU')
if not os.path.exists('../terminal_logs'):
os.makedirs('../terminal_logs')
with closing(
Tee(f"../terminal_logs/exp{exp_id}.txt", "w",
channel="stderr")) as outputstream:
# with closing(Tee(f"../terminal_logs/exp{exp_id}_new_epochs.txt", "w", channel="stderr")) as outputstream:
if gputil:
monitor = Monitor(30)
# with StdoutTee(f"../terminal_logs/exp{exp_id}.txt"), StderrTee(f"../terminal_logs/exp{exp_id}_err.txt"):
if gpus:
try:
# Currently, memory growth needs to be the same across GPUs
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
logical_gpus = tf.config.experimental.list_logical_devices(
'GPU')
print(len(gpus), "Physical GPUs,", len(logical_gpus),
"Logical GPUs")
except RuntimeError as e:
# Memory growth must be set before GPUs have been initialized
