本文整理汇总了Python中talib.HT_DCPERIOD属性的典型用法代码示例。如果您正苦于以下问题：Python talib.HT_DCPERIOD属性的具体用法？Python talib.HT_DCPERIOD怎么用？Python talib.HT_DCPERIOD使用的例子？那么恭喜您, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类talib的用法示例。
在下文中一共展示了talib.HT_DCPERIOD属性的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: ht_dcperiod
# 需要导入模块: import talib [as 别名]
# 或者: from talib import HT_DCPERIOD [as 别名]
def ht_dcperiod(candles: np.ndarray, source_type="close", sequential=False) -> Union[float, np.ndarray]:
"""
HT_DCPERIOD - Hilbert Transform - Dominant Cycle Period
:param candles: np.ndarray
:param source_type: str - default: "close"
:param sequential: bool - default=False
:return: float | np.ndarray
"""
if not sequential and len(candles) > 240:
candles = candles[-240:]
source = get_candle_source(candles, source_type=source_type)
res = talib.HT_DCPERIOD(source)
return res if sequential else res[-1] 示例2: HT_DCPERIOD
# 需要导入模块: import talib [as 别名]
# 或者: from talib import HT_DCPERIOD [as 别名]
def HT_DCPERIOD(Series):
res = talib.HT_DCPERIOD(Series.values)
return pd.Series(res, index=Series.index) 示例3: technical_indicators_df
# 需要导入模块: import talib [as 别名]
# 或者: from talib import HT_DCPERIOD [as 别名]
def technical_indicators_df(self, daily_data):
"""
Assemble a dataframe of technical indicator series for a single stock
"""
o = daily_data['Open'].values
c = daily_data['Close'].values
h = daily_data['High'].values
l = daily_data['Low'].values
v = daily_data['Volume'].astype(float).values
# define the technical analysis matrix
# Most data series are normalized by their series' mean
ta = pd.DataFrame()
ta['MA5'] = tb.MA(c, timeperiod=5) / tb.MA(c, timeperiod=5).mean()
ta['MA10'] = tb.MA(c, timeperiod=10) / tb.MA(c, timeperiod=10).mean()
ta['MA20'] = tb.MA(c, timeperiod=20) / tb.MA(c, timeperiod=20).mean()
ta['MA60'] = tb.MA(c, timeperiod=60) / tb.MA(c, timeperiod=60).mean()
ta['MA120'] = tb.MA(c, timeperiod=120) / tb.MA(c, timeperiod=120).mean()
ta['MA5'] = tb.MA(v, timeperiod=5) / tb.MA(v, timeperiod=5).mean()
ta['MA10'] = tb.MA(v, timeperiod=10) / tb.MA(v, timeperiod=10).mean()
ta['MA20'] = tb.MA(v, timeperiod=20) / tb.MA(v, timeperiod=20).mean()
ta['ADX'] = tb.ADX(h, l, c, timeperiod=14) / tb.ADX(h, l, c, timeperiod=14).mean()
ta['ADXR'] = tb.ADXR(h, l, c, timeperiod=14) / tb.ADXR(h, l, c, timeperiod=14).mean()
ta['MACD'] = tb.MACD(c, fastperiod=12, slowperiod=26, signalperiod=9)[0] / \
tb.MACD(c, fastperiod=12, slowperiod=26, signalperiod=9)[0].mean()
ta['RSI'] = tb.RSI(c, timeperiod=14) / tb.RSI(c, timeperiod=14).mean()
ta['BBANDS_U'] = tb.BBANDS(c, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)[0] / \
tb.BBANDS(c, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)[0].mean()
ta['BBANDS_M'] = tb.BBANDS(c, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)[1] / \
tb.BBANDS(c, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)[1].mean()
ta['BBANDS_L'] = tb.BBANDS(c, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)[2] / \
tb.BBANDS(c, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)[2].mean()
ta['AD'] = tb.AD(h, l, c, v) / tb.AD(h, l, c, v).mean()
ta['ATR'] = tb.ATR(h, l, c, timeperiod=14) / tb.ATR(h, l, c, timeperiod=14).mean()
ta['HT_DC'] = tb.HT_DCPERIOD(c) / tb.HT_DCPERIOD(c).mean()
ta["High/Open"] = h / o
ta["Low/Open"] = l / o
ta["Close/Open"] = c / o
self.ta = ta 示例4: HT_DCPERIOD
# 需要导入模块: import talib [as 别名]
# 或者: from talib import HT_DCPERIOD [as 别名]
def HT_DCPERIOD(series):
return _series_to_series(series, talib.HT_DCPERIOD) 示例5: HT_DCPERIOD
# 需要导入模块: import talib [as 别名]
# 或者: from talib import HT_DCPERIOD [as 别名]
def HT_DCPERIOD(data, **kwargs):
_check_talib_presence()
prices = _extract_series(data)
return talib.HT_DCPERIOD(prices, **kwargs)