def test_get_ups_and_downs(data, parameter, expected):
"""
Test get ups and down functionality.
"""
assert get_ups_and_downs(
data,
parameter) == expected, f"Expected ups and downs to be: {expected}."
def get_rsi(self, prices: int = 14, parameter: str = 'close', shift: int = 0, round_value: bool = True,
update: bool = True) -> float:
"""
Returns relative strength index.
:param update: Boolean for whether function should call API and get latest data or not.
:param prices: Amount of prices to iterate through.
:param parameter: Parameter to use for iterations. By default, it's close.
:param shift: Amount of prices to shift prices by.
:param round_value: Boolean that determines whether final value is rounded or not.
:return: Final relative strength index.
"""
if not self.is_valid_average_input(shift, prices):
raise ValueError('Invalid input specified.')
if shift > 0:
updateDict = False
data = self.data
shift -= 1
else:
updateDict = True
data = self.data + [self.get_current_data()] if update else self.get_total_non_updated_data()
start = len(data) - 500 - prices - shift if len(data) > 500 + prices + shift else 0
ups, downs = get_ups_and_downs(data=data[start:len(data) - shift], parameter=parameter)
averageUp, averageDown = self.helper_get_ema(ups, downs, prices)
rs = averageUp / averageDown
rsi = 100 - 100 / (1 + rs)
if shift == 0 and updateDict:
self.rsi_data[prices] = rsi
if round_value:
return round(rsi, self.precision)
return rsi
def get_rsi(self, data: list, prices: int, parameter: str = 'close', shift: int = 0,
round_value: bool = False) -> float:
"""
Returns relative strength index.
:param data: Data values.
:param prices: Amount of prices to iterate through.
:param parameter: Parameter to use for iterations. By default, it's close.
:param shift: Amount of prices to shift prices by.
:param round_value: Boolean that determines whether final value is rounded or not.
:return: Final relative strength index.
"""
if shift > 0 and prices in self.rsi_dictionary:
rsi = self.rsi_dictionary[prices]['close'][-shift][0]
elif prices in self.rsi_dictionary:
alpha = 1 / prices
difference = data[-1][parameter] - data[-2][parameter]
if difference > 0:
up = difference * alpha + self.rsi_dictionary[prices]['close'][-1][1] * (1 - alpha)
down = self.rsi_dictionary[prices]['close'][-1][2] * (1 - alpha)
else:
up = self.rsi_dictionary[prices]['close'][-1][1] * (1 - alpha)
down = -difference * alpha + self.rsi_dictionary[prices]['close'][-1][2] * (1 - alpha)
rsi = 100 if down == 0 else 100 - 100 / (1 + up / down)
self.rsi_dictionary[prices]['close'].append((rsi, up, down))
else:
if shift > 0:
data = data[:-shift]
ups, downs = get_ups_and_downs(data=data, parameter=parameter)
rsi = self.helper_get_ema(ups, downs, prices)
return round(rsi, self.precision) if round_value else rsi
def test_get_ups_and_downs(data, parameter, expected):
assert get_ups_and_downs(
data,
parameter) == expected, f"Expected ups and downs to be: {expected}."
