def show_chart():
strategy = settings["Strategy"]
deltaDays = settings['deltaDays']
filename = settings['configFilename']
configjs = Settings.get_configjs(filename)
watch = settings["watch"]
dateset = gekkoWrapper.getAvailableDataset(watch)
daterange = coreFunctions.getRandomDateRange(dateset, deltaDays=deltaDays)
res = evolution_bayes.EvaluateRaw(watch, daterange, configjs[strategy], strategy)
#res = gekkoWrapper.httpPost(URL, gekkoConfig)
show_candles(res, configjs[strategy])
def show_chart():
strategy = settings["Strategy"]
deltaDays = settings['deltaDays']
filename = settings['configFilename']
configjs = Settings.get_configjs(filename)
watch = settings["watch"]
dateset = gekkoWrapper.getAvailableDataset(watch)
daterange = resultInterface.getRandomDateRange(dateset, deltaDays=deltaDays)
res = evolution_bayes.EvaluateRaw(watch, daterange, configjs[strategy], strategy)
#res = gekkoWrapper.httpPost(URL, gekkoConfig)
show_candles(res, configjs[strategy])
def gekko_bayesian(indicator=None):
print("")
global Strategy
Strategy = indicator
watch = settings["watch"]
global DatasetRange
DatasetRange = gekkoWrapper.getAvailableDataset(watch)
if indicator == None:
Strategy = settings['Strategy']
print("Starting search %s parameters" % Strategy)
bo = BayesianOptimization(gekko_search, copy.deepcopy(StratConfig))
# 1st Evaluate
print("")
print("Step 1: BayesianOptimization parameter search")
bo.maximize(init_points=settings['init_points'],
n_iter=settings['num_iter'])
max_val = bo.res['max']['max_val']
index = all_val.index(max_val)
s1 = stats[index]
# 2nd Evaluate
print("")
print("Step 2: testing searched parameters on random date")
chosenRange = gekkoWrapper.getAvailableDataset()
DateRange = gekkoWrapper.getDateRange(chosenRange,
deltaDays=settings['testDays'])
max_params = bo.res['max']['max_params'].copy()
#max_params["persistence"] = 1
print("Starting Second Evaluation")
gekko_search(**max_params)
s2 = stats[-1]
# 3rd Evaluate
print("")
print("Step 3: testing searched parameters on recent date")
watch = settings["watch"]
result = EvaluateRaw(watch, DateRange, max_params, Strategy)
if type(result['report']) == bool:
s3 = 0.
else:
s3 = result['report']['relativeProfit']
resultjson = expandGekkoStrategyParameters(max_params, Strategy)[Strategy]
# config.js like output
percentiles = np.array([0.25, 0.5, 0.75])
formatted_percentiles = [
str(int(round(x * 100))) + "%" for x in percentiles
]
stats_index = (['count', 'mean', 'std', 'min'] + formatted_percentiles +
['max'])
print("")
print("// " + '-' * 50)
print("// " + Strategy + ' Settings')
print("// " + '-' * 50)
print("// 1st Evaluate: %.3f" % s1[1])
for i in range(len(s1)):
print('// %s: %.3f' % (stats_index[i], s1[i]))
print("// " + '-' * 50)
print("// 2nd Evaluate: %.3f" % s2[1])
for i in range(len(s2)):
print('// %s: %.3f' % (stats_index[i], s2[i]))
print("// " + '-' * 50)
print("// 3rd Evaluate nearest date: %s to %s" %
(DateRange['from'], DateRange['to']))
print("// Evaluted Score: %f" % s3)
print("// " + '-' * 50)
print("config.%s = {%s};" %
(Strategy, json.dumps(resultjson, indent=2)[1:-1]))
print("// " + '-' * 50)
if settings["save"]:
paramsdf = pd.DataFrame.from_dict(bo.res["all"]["params"])
valuesdf = pd.DataFrame.from_dict(bo.res["all"]["values"])
paramsdf["target"] = valuesdf
watch = settings["watch"]
filename = "_".join([
watch["exchange"], watch["currency"], watch["asset"], Strategy,
datetime.datetime.now().strftime('%Y%m%d_%H%M%S'),
str(max_val)
])
save_dir = gsettings["save_dir"]
csv_filename = os.path.join(save_dir, filename) + "_bayes.csv"
json_filename = os.path.join(save_dir, filename) + "_config.json"
json2_filename = os.path.join(save_dir, filename) + "_response.json"
config = expandGekkoStrategyParameters(max_params, Strategy)
config["watch"] = watch
gekko_config = gekkoWrapper.createConfig(config, DateRange)
if not os.path.exists(save_dir):
os.mkdir(save_dir)
paramsdf.to_csv(csv_filename, index=False)
print("Saved: " + csv_filename)
f = open(json_filename, "w")
f.write(json.dumps(gekko_config, indent=2))
f.close()
print("Saved: " + json_filename)
f = open(json2_filename, "w")
f.write(json.dumps(result, indent=2))
f.close()
print("Saved: " + json2_filename)
if settings["show_chart"]:
chart.show_candles(result, max_params)
return max_params
dict_merge = lambda a, b: a.update(b) or a
gsettings = getSettings()['Global']
settings = getSettings()['bayesian']
Strategy = settings["Strategy"]
StratConfig = getSettings()["strategies"][Strategy]
percentiles = np.array([0.25, 0.5, 0.75])
all_val = []
stats = []
candleSize = 0
historySize = 0
watch = settings["watch"]
watch, DatasetRange = gekkoWrapper.getAvailableDataset(watch)
def expandGekkoStrategyParameters(IND, Strategy):
config = {}
IND = promoterz.utils.expandNestedParameters(IND)
config[Strategy] = IND
return config
def Evaluate(Strategy, parameters):
DateRange = gekkoWrapper.getRandomDateRange(
DatasetRange, deltaDays=settings['deltaDays'])
# Fix the shit below!
settings = getSettings()['bayesian']
bayesSettings = getSettings('bayesian')
Strategy = settings["Strategy"]
StratConfig = getSettings()["strategies"][Strategy]
percentiles = np.array([0.25, 0.5, 0.75])
all_val = []
stats = []
candleSize = 0
historySize = 0
watch = settings["watch"]
watch, DatasetRange = gekkoWrapper.getAvailableDataset(watch)
def expandGekkoStrategyParameters(IND, Strategy):
config = {}
IND = promoterz.utils.expandNestedParameters(IND)
config[Strategy] = IND
return config
def Evaluate(Strategy, parameters):
DateRange = gekkoWrapper.getRandomDateRange(DatasetRange, deltaDays=settings['deltaDays'])
params = expandGekkoStrategyParameters(parameters, Strategy)