def activate() -> None:
sample_size = sample_selector.get()
sample_size = int(sample_size) if sample_size else 5
all_schedules = schedule(RESULTS_PATH, QUERY_PATH)
to_dataframe(all_schedules).to_csv(ALL_SCHEDULES_PATH)
sample_schedules = coverage_sample(all_schedules, sample_size)
print(len(sample_schedules))
to_dataframe(sample_schedules).to_csv(SAMPLE_SCHEDULES_PATH)
if open_output.get():
subprocess.run(['start', SAMPLE_SCHEDULES_PATH], check=True, shell=True)
def main():
if len(sys.argv) < 1:
print("Please insert the name of the file you want to test on")
sys.exit()
if len(sys.argv) < 2:
print("Examples are being tested on forest implementation by default")
TEST_FILE = sys.argv[1]
START_TIME = time.time()
labels, data = util.load_raw_data(TEST_FILE)
A = np.array(labels)
labels = [row[0] for row in A]
df_labels, df_data = util.to_dataframe(labels, data)
algorithm = convert_arguments()
res = algorithm(df_labels, df_data)
print(res)
print(
"----------------------------------- TOTAL EXECUTION TIME -----------------------------------\n"
)
END_TIME = time.time()
print(END_TIME - START_TIME)
def main():
algorithm = convert_arguments()
START_TIME = time.time()
labels, data = util.load_raw_data_clean()
A = np.array(labels)
labels = [row[0] for row in A]
df_labels, df_data = util.to_dataframe(labels, data)
# Number of examples
N = df_labels.shape[0]
print(
"----------------------------------- LOADING COMPLETED -----------------------------------\n"
)
print(
"----------------------------------- CONFUSION_MATRIX ------------------------------------\n"
)
res = algorithm(df_labels, df_data, N)
print(res)
print(
"----------------------------------- TOTAL EXECUTION TIME -----------------------------------\n"
)
END_TIME = time.time()
print(END_TIME - START_TIME)
def activate() -> None:
courses = course_file.get()
query = query_file.get()
output_dir = output_folder.get()
output_full = output_dir + "/all_schedules.csv"
output_sample = output_dir + "/sample_schedules.csv"
sample_size = sample_selector.get()
sample_size = int(sample_size) if sample_size else 5
if not courses or not query or not output_dir:
text.config(fg="red", text="Missing one or more required fields.")
return
else:
text.config(fg="black", text="")
all_schedules = schedule(course_file.get(), query_file.get())
to_dataframe(all_schedules).to_csv(output_full)
sample_schedules = coverage_sample(all_schedules, sample_size)
to_dataframe(sample_schedules).to_csv(output_sample)
if open_output.get():
subprocess.run(['start', output_sample],
check=True,
shell=True)
# cluster
num_clusters=10
cluster = LandmarkAgglomerative(n_clusters=num_clusters, n_landmarks=200, linkage='ward', metric='euclidean')
cluster.fit(trajs)
ctraj = {}
for k, v in traj_dict.items():
v = v.copy(order='C')
v = cluster.partial_predict(v)
diff = nframes-v.shape[0]
v = np.append(v, np.zeros(diff)-1)
ctraj[k] = v
# Convert to DF for plotting and sampling.
df = to_dataframe(ctraj, nframes, dt=1)
# Plot trajectories
sample = df.sample(frac=0.1, axis=0)
sample.sort_values(by=['Prod_ID', 'Site_ID', 'Time_ps'], inplace=True)
g = sns.FacetGrid(sample, col='Prod_ID',hue='Site_ID', col_wrap=10)
g.map(plt.scatter, 'Time_ps', 'Trajectory', alpha=0.5)
g.set(ylim=(-0.5,num_clusters))
g.fig.tight_layout()
plt.savefig('figures/{}_cluster_trajectory.pdf'.format(feature))
# Plot histograms
g = sns.FacetGrid(sample, col='Prod_ID',hue='Site_ID', col_wrap=10)
g = g.map(plt.hist, 'Trajectory', bins=range(num_clusters), histtype='step', lw='5')
g.fig.tight_layout()
plt.savefig('figures/{}_cluster_hist.pdf'.format(feature))
def main():
symbol_conf=conf["symbol"]
ex=HistorialData(symbol_conf)
for symbol in symbol_conf.keys():
exchange=symbol_conf[symbol]["exchange"]
time_unit=symbol_conf[symbol]["time_unit"]
candles=symbol_conf[symbol]["candles"]
#get historical data from symbol and symbol identified
logger.debug("Get historical data %s:%s",exchange,symbol)
try:
data=ex.get_historical_data(symbol,exchange,time_unit,candles)
except Exception as e:
logger.error("Error in retrieving historical data for %s",symbol,exc_info=True)
continue
data=to_dataframe(data)
# Aplly strategy(s) to collected data
for st in symbol_conf[symbol]["strategies"]:
klass=globals()[st]
tatics=klass(data,symbol,symbol_conf[symbol],conf["indicators"],bruteforce=True)
result=tatics.launch()
if isinstance(result,list):
#check configuration and update with new parameters if having
if "indicators" in symbol_conf[symbol]:
# stochastic RSI parameters
if symbol_conf[symbol]["indicators"]["stoch_rsi"]["period"] != trading_result["period"]:
logger.info("Change stoch_rsi_period from %s to %s", str(symbol_conf[symbol]["indicators"]["stoch_rsi"]["period"]),str(trading_result["period"]))
symbol_conf[symbol]["indicators"]["stoch_rsi"]["period"] = int(trading_result["period"])
if symbol_conf[symbol]["indicators"]["stoch_rsi"]["fast_k"] != trading_result["fast_k_period"]:
logger.info("Change stoch_rsi_fast_k from %s to %s", str(symbol_conf[symbol]["indicators"]["stoch_rsi"]["fast_k"]),str(trading_result["fast_k_period"]))
symbol_conf[symbol]["indicators"]["stoch_rsi"]["fast_k"] = int(trading_result["fast_k_period"])
if symbol_conf[symbol]["indicators"]["stoch_rsi"]["fast_d"] != trading_result["fast_d_period"]:
logger.info("Change stoch_rsi_fast_d from %s to %s", str(symbol_conf[symbol]["indicators"]["stoch_rsi"]["fast_d"]),str(trading_result["fast_d_period"]))
symbol_conf[symbol]["indicators"]["stoch_rsi"]["fast_d"] = int(trading_result["fast_d_period"])
#selling indicators
if symbol_conf[symbol]["indicators"]["selling"]["rsi"] != trading_result["selling_rsi"]:
logger.info("Change selling_rsi from %s to %s", str(symbol_conf[symbol]["indicators"]["selling"]["rsi"]),str(trading_result["selling_rsi"]))
symbol_conf[symbol]["indicators"]["selling"]["rsi"] = int(trading_result["selling_rsi"])
if symbol_conf[symbol]["indicators"]["selling"]["rsi_bullish"] != trading_result["selling_rsi_bullish"]:
logger.info("Change selling_rsi_bullish from %s to %s", str(symbol_conf[symbol]["indicators"]["selling"]["rsi_bullish"]),str(trading_result["selling_rsi_bullish"]))
symbol_conf[symbol]["indicators"]["selling"]["rsi_bullish"] = int(trading_result["selling_rsi_bullish"])
if symbol_conf[symbol]["indicators"]["selling"]["fast_k"] != trading_result["selling_stoch_rsi"]:
logger.info("Change selling_stoch_rsi from %s to %s", str(symbol_conf[symbol]["indicators"]["selling"]["fast_k"]),str(trading_result["selling_stoch_rsi"]))
symbol_conf[symbol]["indicators"]["selling"]["rsi"] = int(trading_result["selling_rsi"])
#buying indicators
if symbol_conf[symbol]["indicators"]["buying"]["rsi"] != trading_result["buying_rsi"]:
logger.info("Change buying_rsi from %s to %s", str(symbol_conf[symbol]["indicators"]["buying"]["rsi"]),str(trading_result["buying_rsi"]))
symbol_conf[symbol]["indicators"]["buying"]["rsi"] = int(trading_result["buying_rsi"])
if symbol_conf[symbol]["indicators"]["buying"]["rsi_bullish"] != trading_result["buying_rsi_bullish"]:
logger.info("Change buying_rsi_bullish from %s to %s", str(symbol_conf[symbol]["indicators"]["buying"]["rsi_bullish"]),str(trading_result["buying_rsi_bullish"]))
symbol_conf[symbol]["indicators"]["buying"]["rsi_bullish"] = int(trading_result["buying_rsi_bullish"])
if symbol_conf[symbol]["indicators"]["buying"]["fast_k"] != trading_result["buying_stoch_rsi"]:
logger.info("Change buying_stoch_rsi from %s to %s", str(symbol_conf[symbol]["indicators"]["buying"]["fast_k"]),str(trading_result["buying_stoch_rsi"]))
symbol_conf[symbol]["indicators"]["buying"]["fast_k"] = int(trading_result["buying_stoch_rsi"])
if symbol_conf[symbol]["indicators"]["buying"]["confirmed_bullish"] != trading_result["buying_confirmed_pullish"]:
logger.info("Change buying_confirmed_pullish from %s to %s", str(symbol_conf[symbol]["indicators"]["buying"]["confirmed_bullish"]),str(trading_result["buying_confirmed_pullish"]))
symbol_conf[symbol]["indicators"]["buying"]["confirmed_bullish"] = int(trading_result["buying_confirmed_pullish"])
if symbol_conf[symbol]["indicators"]["buying"]["rsi_midpoint"] != trading_result["buying_rsi_midpoint"]:
logger.info("Change buying_rsi_midpoint from %s to %s", str(symbol_conf[symbol]["indicators"]["buying"]["rsi_midpoint"]),str(trading_result["buying_rsi_midpoint"]))
symbol_conf[symbol]["indicators"]["buying"]["rsi_midpoint"] = int(trading_result["buying_rsi_midpoint"])
if symbol_conf[symbol]["indicators"]["buying"]["macdhist"] != trading_result["buying_macdhist"]:
logger.info("Change buying_macdhist from %s to %s", str(symbol_conf[symbol]["indicators"]["buying"]["macdhist"]),str(trading_result["buying_macdhist"]))
symbol_conf[symbol]["indicators"]["buying"]["macdhist"] = int(trading_result["buying_macdhist"])
else:
indicators={"selling":{"rsi":int(trading_result["selling_rsi"]),"rsi_bullish":int(trading_result["selling_rsi_bullish"]), "fast_k":int(trading_result["selling_stoch_rsi"])},\
"buying":{"rsi":int(trading_result["buying_rsi"]),"rsi_bullish":int(trading_result["buying_rsi_bullish"]), "fast_k":int(trading_result["buying_stoch_rsi"]),\
"confirmed_bullish":int(trading_result["buying_confirmed_pullish"]),"rsi_midpoint":int(trading_result["buying_rsi_midpoint"]),\
"macdhist":int(trading_result["buying_macdhist"])},\
"stoch_rsi":{"period":int(trading_result["period"]),"fast_k":int(trading_result["fast_k_period"]),"fast_d":int(trading_result["fast_d_period"])}}
symbol_conf[symbol]["indicators"]=indicators
#Automatically update configuration file
conf["symbol"]=symbol_conf
with open('conf/conf_recommender.yml', 'w') as outfile:
yaml.dump(conf, outfile, default_flow_style=False)
def main():
symbol_conf = conf["symbol"]
ex = HistorialData(symbol_conf)
for symbol in symbol_conf.keys():
exchange = symbol_conf[symbol]["exchange"]
time_unit = symbol_conf[symbol]["time_unit"]
candles = symbol_conf[symbol]["candles"]
#get historical data from symbol and symbol identified
logger.debug("Get historical data %s:%s", exchange, symbol)
try:
data = ex.get_historical_data(symbol, exchange, time_unit, candles)
except Exception as e:
logger.error("Error in retrieving historical data for %s",
symbol,
exc_info=True)
continue
data = to_dataframe(data)
# Aplly strategy(s) to collected data
for st in symbol_conf[symbol]["strategies"]:
klass = globals()[st]
tatics = klass(data,
symbol,
symbol_conf[symbol],
conf["indicators"],
bruteforce=True)
result = tatics.launch()
if isinstance(result, list):
#check configuration and update with new parameters if having
if "indicators" in symbol_conf[symbol]:
# stochastic RSI parameters
if symbol_conf[symbol]["indicators"]["stoch_rsi"][
"period"] != trading_result["period"]:
logger.info(
"Change stoch_rsi_period from %s to %s",
str(symbol_conf[symbol]["indicators"]["stoch_rsi"]
["period"]), str(trading_result["period"]))
symbol_conf[symbol]["indicators"]["stoch_rsi"][
"period"] = int(trading_result["period"])
if symbol_conf[symbol]["indicators"]["stoch_rsi"][
"fast_k"] != trading_result["fast_k_period"]:
logger.info(
"Change stoch_rsi_fast_k from %s to %s",
str(symbol_conf[symbol]["indicators"]["stoch_rsi"]
["fast_k"]),
str(trading_result["fast_k_period"]))
symbol_conf[symbol]["indicators"]["stoch_rsi"][
"fast_k"] = int(trading_result["fast_k_period"])
if symbol_conf[symbol]["indicators"]["stoch_rsi"][
"fast_d"] != trading_result["fast_d_period"]:
logger.info(
"Change stoch_rsi_fast_d from %s to %s",
str(symbol_conf[symbol]["indicators"]["stoch_rsi"]
["fast_d"]),
str(trading_result["fast_d_period"]))
symbol_conf[symbol]["indicators"]["stoch_rsi"][
"fast_d"] = int(trading_result["fast_d_period"])
#selling indicators
if symbol_conf[symbol]["indicators"]["selling"][
"rsi"] != trading_result["selling_rsi"]:
logger.info(
"Change selling_rsi from %s to %s",
str(symbol_conf[symbol]["indicators"]["selling"]
["rsi"]), str(trading_result["selling_rsi"]))
symbol_conf[symbol]["indicators"]["selling"][
"rsi"] = int(trading_result["selling_rsi"])
if symbol_conf[symbol]["indicators"]["selling"][
"rsi_bullish"] != trading_result[
"selling_rsi_bullish"]:
logger.info(
"Change selling_rsi_bullish from %s to %s",
str(symbol_conf[symbol]["indicators"]["selling"]
["rsi_bullish"]),
str(trading_result["selling_rsi_bullish"]))
symbol_conf[symbol]["indicators"]["selling"][
"rsi_bullish"] = int(
trading_result["selling_rsi_bullish"])
if symbol_conf[symbol]["indicators"]["selling"][
"fast_k"] != trading_result["selling_stoch_rsi"]:
logger.info(
"Change selling_stoch_rsi from %s to %s",
str(symbol_conf[symbol]["indicators"]["selling"]
["fast_k"]),
str(trading_result["selling_stoch_rsi"]))
symbol_conf[symbol]["indicators"]["selling"][
"rsi"] = int(trading_result["selling_rsi"])
#buying indicators
if symbol_conf[symbol]["indicators"]["buying"][
"rsi"] != trading_result["buying_rsi"]:
logger.info(
"Change buying_rsi from %s to %s",
str(symbol_conf[symbol]["indicators"]["buying"]
["rsi"]), str(trading_result["buying_rsi"]))
symbol_conf[symbol]["indicators"]["buying"][
"rsi"] = int(trading_result["buying_rsi"])
if symbol_conf[symbol]["indicators"]["buying"][
"rsi_bullish"] != trading_result[
"buying_rsi_bullish"]:
logger.info(
"Change buying_rsi_bullish from %s to %s",
str(symbol_conf[symbol]["indicators"]["buying"]
["rsi_bullish"]),
str(trading_result["buying_rsi_bullish"]))
symbol_conf[symbol]["indicators"]["buying"][
"rsi_bullish"] = int(
trading_result["buying_rsi_bullish"])
if symbol_conf[symbol]["indicators"]["buying"][
"fast_k"] != trading_result["buying_stoch_rsi"]:
logger.info(
"Change buying_stoch_rsi from %s to %s",
str(symbol_conf[symbol]["indicators"]["buying"]
["fast_k"]),
str(trading_result["buying_stoch_rsi"]))
symbol_conf[symbol]["indicators"]["buying"][
"fast_k"] = int(trading_result["buying_stoch_rsi"])
if symbol_conf[symbol]["indicators"]["buying"][
"confirmed_bullish"] != trading_result[
"buying_confirmed_pullish"]:
logger.info(
"Change buying_confirmed_pullish from %s to %s",
str(symbol_conf[symbol]["indicators"]["buying"]
["confirmed_bullish"]),
str(trading_result["buying_confirmed_pullish"]))
symbol_conf[symbol]["indicators"]["buying"][
"confirmed_bullish"] = int(
trading_result["buying_confirmed_pullish"])
if symbol_conf[symbol]["indicators"]["buying"][
"rsi_midpoint"] != trading_result[
"buying_rsi_midpoint"]:
logger.info(
"Change buying_rsi_midpoint from %s to %s",
str(symbol_conf[symbol]["indicators"]["buying"]
["rsi_midpoint"]),
str(trading_result["buying_rsi_midpoint"]))
symbol_conf[symbol]["indicators"]["buying"][
"rsi_midpoint"] = int(
trading_result["buying_rsi_midpoint"])
if symbol_conf[symbol]["indicators"]["buying"][
"macdhist"] != trading_result["buying_macdhist"]:
logger.info(
"Change buying_macdhist from %s to %s",
str(symbol_conf[symbol]["indicators"]["buying"]
["macdhist"]),
str(trading_result["buying_macdhist"]))
symbol_conf[symbol]["indicators"]["buying"][
"macdhist"] = int(
trading_result["buying_macdhist"])
else:
indicators={"selling":{"rsi":int(trading_result["selling_rsi"]),"rsi_bullish":int(trading_result["selling_rsi_bullish"]), "fast_k":int(trading_result["selling_stoch_rsi"])},\
"buying":{"rsi":int(trading_result["buying_rsi"]),"rsi_bullish":int(trading_result["buying_rsi_bullish"]), "fast_k":int(trading_result["buying_stoch_rsi"]),\
"confirmed_bullish":int(trading_result["buying_confirmed_pullish"]),"rsi_midpoint":int(trading_result["buying_rsi_midpoint"]),\
"macdhist":int(trading_result["buying_macdhist"])},\
"stoch_rsi":{"period":int(trading_result["period"]),"fast_k":int(trading_result["fast_k_period"]),"fast_d":int(trading_result["fast_d_period"])}}
symbol_conf[symbol]["indicators"] = indicators
#Automatically update configuration file
conf["symbol"] = symbol_conf
with open('conf/conf_recommender.yml', 'w') as outfile:
yaml.dump(conf, outfile, default_flow_style=False)