def abstract_example():
sma = Function('sma')
input_arrays = sma.get_input_arrays()
for key in input_arrays.keys():
input_arrays[key] = idata
sma.set_input_arrays(input_arrays)
odata = sma(30) # timePeriod=30, specified as an arg
bbands = Function('bbands', input_arrays)
bbands.set_function_parameters(timePeriod=20, nbDevUp=2, nbDevDown=2)
upper, middle, lower = bbands() # multiple output values unpacked (these will always have the correct order)
kama = Function('kama').run(input_arrays) # alternative run() calling method.
plot(odata, upper, middle, lower, kama)
def abstract_example():
sma = Function("sma")
input_arrays = sma.get_input_arrays()
for key in input_arrays.keys():
input_arrays[key] = idata
sma.set_input_arrays(input_arrays)
odata = sma(30) # timePeriod=30, specified as an arg
bbands = Function("bbands", input_arrays)
bbands.parameters = {"timeperiod": 20, "nbdevup": 2, "nbdevdn": 2}
upper, middle, lower = bbands() # multiple output values unpacked (these will always have the correct order)
kama = Function("kama").run(input_arrays) # alternative run() calling method.
plot(odata, upper, middle, lower, kama)
def abstract_example():
sma = Function('sma')
input_arrays = sma.get_input_arrays()
for key in input_arrays.keys():
input_arrays[key] = idata
sma.set_input_arrays(input_arrays)
odata = sma(30) # timePeriod=30, specified as an arg
bbands = Function('bbands', input_arrays)
bbands.parameters = {'timeperiod': 20, 'nbdevup': 2, 'nbdevdn': 2}
upper, middle, lower = bbands(
) # multiple output values unpacked (these will always have the correct order)
kama = Function('kama').run(
input_arrays) # alternative run() calling method.
plot(odata, upper, middle, lower, kama)
class Talib(CleanerBase):
def __init__(self,
ind: str,
params: dict,
frequency: str = None,
buffer_day: int = 5) -> None:
super().__init__(None, buffer_day, frequency)
self.indicator = Function(ind)
self.indicator.set_parameters(params)
self.rolling_window = self.indicator.lookback + 1
self.data = defaultdict(dict) # type:dict[str,dict[str,deque]]
@staticmethod
def _check_nan(value: float):
if isnan(value):
raise Exception(
'rolling_window should be longer. Because nan is generated!')
def _data_proxy(self, ticker: str) -> dict:
key = f'{ticker}_{self.frequency}'
return {
'open': array(self.data[key]['open']),
'high': array(self.data[key]['high']),
'low': array(self.data[key]['low']),
'close': array(self.data[key]['close']),
'volume': array(self.data[key]['volume'])
}
def calculate(self, ticker: str) -> dict:
self.indicator.set_input_arrays(self._data_proxy(ticker))
value = list(self.indicator.outputs)
if len(self.indicator.output_names) > 1:
[self._check_nan(i[-1]) for i in value]
return {
k: v[-1]
for k, v in zip(self.indicator.output_names, value)
}
self._check_nan(value[-1])
return value[-1]
class Talib(op.CleanerBase):
counter = count(1)
def __init__(self, ind: str, params: dict,
buffer_day: int, frequency: str) -> None:
name = f"{ind}_{next(self.counter)}"
self.indicator = Function(ind)
self.indicator.set_parameters(params)
rolling_window = self.indicator.lookback+1
super().__init__(name, rolling_window, buffer_day, frequency)
self.save_to_env(self)
self.data = self.get_data()
@staticmethod
def _check_nan(value: float):
if isnan(value):
raise Exception(
'rolling_window should be longer. Because nan is generated!')
def _data_proxy(self, ticker: str) -> dict:
key = f'{ticker}_{self.frequency}'
return {'open': array(self.data[key].open),
'high': array(self.data[key].high),
'low': array(self.data[key].low),
'close': array(self.data[key].close),
'volume': array(self.data[key].volume)}
def calculate(self, ticker: str) -> dict:
self.indicator.set_input_arrays(self._data_proxy(ticker))
value = list(self.indicator.outputs)
if len(self.indicator.output_names) > 1:
[self._check_nan(i[-1]) for i in value]
return {k: v[-1]
for k, v in zip(self.indicator.output_names, value)}
self._check_nan(value[-1])
return value[-1]
