909 lines
21 KiB
Python
909 lines
21 KiB
Python
|
"""
|
|||
|
|
Momentum Indicators — Oscillators measuring speed and change of price movements.
|
|||
|
|
|
|||
|
|
Functions
|
|||
|
|
---------
|
|||
|
|
RSI — Relative Strength Index
|
|||
|
|
MOM — Momentum
|
|||
|
|
ROC — Rate of Change: ((price/prevPrice)-1)*100
|
|||
|
|
ROCP — Rate of Change Percentage: (price-prevPrice)/prevPrice
|
|||
|
|
ROCR — Rate of Change Ratio: price/prevPrice
|
|||
|
|
ROCR100 — Rate of Change Ratio 100 scale: (price/prevPrice)*100
|
|||
|
|
WILLR — Williams' %R
|
|||
|
|
AROON — Aroon (returns aroon_down, aroon_up)
|
|||
|
|
AROONOSC — Aroon Oscillator
|
|||
|
|
CCI — Commodity Channel Index
|
|||
|
|
MFI — Money Flow Index
|
|||
|
|
BOP — Balance Of Power
|
|||
|
|
STOCHF — Stochastic Fast
|
|||
|
|
STOCH — Stochastic
|
|||
|
|
STOCHRSI — Stochastic Relative Strength Index
|
|||
|
|
APO — Absolute Price Oscillator
|
|||
|
|
PPO — Percentage Price Oscillator
|
|||
|
|
CMO — Chande Momentum Oscillator
|
|||
|
|
PLUS_DM — Plus Directional Movement
|
|||
|
|
MINUS_DM — Minus Directional Movement
|
|||
|
|
PLUS_DI — Plus Directional Indicator
|
|||
|
|
MINUS_DI — Minus Directional Indicator
|
|||
|
|
DX — Directional Movement Index
|
|||
|
|
ADX — Average Directional Movement Index
|
|||
|
|
ADXR — Average Directional Movement Index Rating
|
|||
|
|
TRIX — 1-day Rate-Of-Change of Triple Smooth EMA
|
|||
|
|
ULTOSC — Ultimate Oscillator
|
|||
|
|
TRANGE — True Range (also in volatility)
|
|||
|
|
"""
|
|||
|
|
|
|||
|
|
from __future__ import annotations
|
|||
|
|
|
|||
|
|
import numpy as np
|
|||
|
|
from numpy.typing import ArrayLike
|
|||
|
|
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
adx as _adx,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
adxr as _adxr,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
apo as _apo,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
aroon as _aroon,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
aroonosc as _aroonosc,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
bop as _bop,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
cci as _cci,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
cmo as _cmo,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
dx as _dx,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
mfi as _mfi,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
minus_di as _minus_di,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
minus_dm as _minus_dm,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
mom as _mom,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
plus_di as _plus_di,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
plus_dm as _plus_dm,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
ppo as _ppo,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
roc as _roc,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
rocp as _rocp,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
rocr as _rocr,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
rocr100 as _rocr100,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
rsi as _rsi,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
stoch as _stoch,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
stochf as _stochf,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
stochrsi as _stochrsi,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
trix as _trix,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
ultosc as _ultosc,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._ferro_ta import (
|
|||
|
|
willr as _willr,
|
|||
|
|
)
|
|||
|
|
from ferro_ta._utils import _to_f64
|
|||
|
|
from ferro_ta.core.exceptions import _normalize_rust_error
|
|||
|
|
from ferro_ta.indicators.volatility import TRANGE
|
|||
|
|
|
|||
|
|
|
|||
|
|
def RSI(close: ArrayLike, timeperiod: int = 14) -> np.ndarray:
|
|||
|
|
"""Relative Strength Index.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of RSI values (0–100); leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _rsi(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def MOM(close: ArrayLike, timeperiod: int = 10) -> np.ndarray:
|
|||
|
|
"""Momentum.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 10).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of MOM values; leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _mom(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def ROC(close: ArrayLike, timeperiod: int = 10) -> np.ndarray:
|
|||
|
|
"""Rate of Change: ((price/prevPrice)-1)*100.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 10).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of ROC values; leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _roc(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def ROCP(close: ArrayLike, timeperiod: int = 10) -> np.ndarray:
|
|||
|
|
"""Rate of Change Percentage: (price-prevPrice)/prevPrice.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 10).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of ROCP values; leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _rocp(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def ROCR(close: ArrayLike, timeperiod: int = 10) -> np.ndarray:
|
|||
|
|
"""Rate of Change Ratio: price/prevPrice.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 10).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of ROCR values; leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _rocr(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def ROCR100(close: ArrayLike, timeperiod: int = 10) -> np.ndarray:
|
|||
|
|
"""Rate of Change Ratio 100 scale: (price/prevPrice)*100.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 10).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of ROCR100 values; leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _rocr100(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def WILLR(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Williams' %R.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of WILLR values (-100 to 0); leading ``timeperiod - 1`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _willr(_to_f64(high), _to_f64(low), _to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def AROON(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> tuple[np.ndarray, np.ndarray]:
|
|||
|
|
"""Aroon.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
tuple[numpy.ndarray, numpy.ndarray]
|
|||
|
|
``(aroondown, aroonup)`` — two arrays of equal length.
|
|||
|
|
Leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _aroon(_to_f64(high), _to_f64(low), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def AROONOSC(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Aroon Oscillator.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of AROONOSC values; leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _aroonosc(_to_f64(high), _to_f64(low), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def CCI(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Commodity Channel Index.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of CCI values; leading ``timeperiod - 1`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _cci(_to_f64(high), _to_f64(low), _to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def MFI(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
volume: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Money Flow Index.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
volume : array-like
|
|||
|
|
Sequence of volume values.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of MFI values (0–100); leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _mfi(
|
|||
|
|
_to_f64(high), _to_f64(low), _to_f64(close), _to_f64(volume), timeperiod
|
|||
|
|
)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def BOP(
|
|||
|
|
open: ArrayLike,
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Balance Of Power.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
open : array-like
|
|||
|
|
Sequence of open prices.
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of BOP values (-1 to 1).
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _bop(_to_f64(open), _to_f64(high), _to_f64(low), _to_f64(close))
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def STOCHF(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
fastk_period: int = 5,
|
|||
|
|
fastd_period: int = 3,
|
|||
|
|
) -> tuple[np.ndarray, np.ndarray]:
|
|||
|
|
"""Stochastic Fast.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
fastk_period : int, optional
|
|||
|
|
%K period (default 5).
|
|||
|
|
fastd_period : int, optional
|
|||
|
|
%D smoothing period (default 3).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
tuple[numpy.ndarray, numpy.ndarray]
|
|||
|
|
``(fastk, fastd)`` — two arrays of equal length.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _stochf(
|
|||
|
|
_to_f64(high), _to_f64(low), _to_f64(close), fastk_period, fastd_period
|
|||
|
|
)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def STOCH(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
fastk_period: int = 5,
|
|||
|
|
slowk_period: int = 3,
|
|||
|
|
slowd_period: int = 3,
|
|||
|
|
) -> tuple[np.ndarray, np.ndarray]:
|
|||
|
|
"""Stochastic.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
fastk_period : int, optional
|
|||
|
|
Fast %K period (default 5).
|
|||
|
|
slowk_period : int, optional
|
|||
|
|
Slow %K smoothing period (default 3).
|
|||
|
|
slowd_period : int, optional
|
|||
|
|
Slow %D smoothing period (default 3).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
tuple[numpy.ndarray, numpy.ndarray]
|
|||
|
|
``(slowk, slowd)`` — two arrays of equal length.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _stoch(
|
|||
|
|
_to_f64(high),
|
|||
|
|
_to_f64(low),
|
|||
|
|
_to_f64(close),
|
|||
|
|
fastk_period,
|
|||
|
|
slowk_period,
|
|||
|
|
slowd_period,
|
|||
|
|
)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def STOCHRSI(
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
fastk_period: int = 5,
|
|||
|
|
fastd_period: int = 3,
|
|||
|
|
) -> tuple[np.ndarray, np.ndarray]:
|
|||
|
|
"""Stochastic Relative Strength Index.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
RSI period (default 14).
|
|||
|
|
fastk_period : int, optional
|
|||
|
|
Stochastic %K period (default 5).
|
|||
|
|
fastd_period : int, optional
|
|||
|
|
Stochastic %D smoothing period (default 3).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
tuple[numpy.ndarray, numpy.ndarray]
|
|||
|
|
``(fastk, fastd)`` — two arrays of equal length.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _stochrsi(_to_f64(close), timeperiod, fastk_period, fastd_period)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def APO(
|
|||
|
|
close: ArrayLike,
|
|||
|
|
fastperiod: int = 12,
|
|||
|
|
slowperiod: int = 26,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Absolute Price Oscillator.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
fastperiod : int, optional
|
|||
|
|
Fast EMA period (default 12).
|
|||
|
|
slowperiod : int, optional
|
|||
|
|
Slow EMA period (default 26).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of APO values; leading ``slowperiod - 1`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _apo(_to_f64(close), fastperiod, slowperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def PPO(
|
|||
|
|
close: ArrayLike,
|
|||
|
|
fastperiod: int = 12,
|
|||
|
|
slowperiod: int = 26,
|
|||
|
|
signalperiod: int = 9,
|
|||
|
|
) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
|
|||
|
|
"""Percentage Price Oscillator.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
fastperiod : int, optional
|
|||
|
|
Fast EMA period (default 12).
|
|||
|
|
slowperiod : int, optional
|
|||
|
|
Slow EMA period (default 26).
|
|||
|
|
signalperiod : int, optional
|
|||
|
|
Signal EMA period (default 9).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]
|
|||
|
|
``(ppo, signal, histogram)`` — three arrays of equal length.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _ppo(_to_f64(close), fastperiod, slowperiod, signalperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def CMO(close: ArrayLike, timeperiod: int = 14) -> np.ndarray:
|
|||
|
|
"""Chande Momentum Oscillator.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Number of periods (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of CMO values (-100 to 100); leading ``timeperiod`` entries are ``NaN``.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _cmo(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def PLUS_DM(high: ArrayLike, low: ArrayLike, timeperiod: int = 14) -> np.ndarray:
|
|||
|
|
"""Plus Directional Movement.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Smoothing period (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of +DM values.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _plus_dm(_to_f64(high), _to_f64(low), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def MINUS_DM(high: ArrayLike, low: ArrayLike, timeperiod: int = 14) -> np.ndarray:
|
|||
|
|
"""Minus Directional Movement.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Smoothing period (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of -DM values.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _minus_dm(_to_f64(high), _to_f64(low), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def PLUS_DI(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Plus Directional Indicator.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Smoothing period (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of +DI values.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _plus_di(_to_f64(high), _to_f64(low), _to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def MINUS_DI(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Minus Directional Indicator.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Smoothing period (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of -DI values.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _minus_di(_to_f64(high), _to_f64(low), _to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def DX(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Directional Movement Index.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Smoothing period (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of DX values (0–100).
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _dx(_to_f64(high), _to_f64(low), _to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def ADX(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Average Directional Movement Index.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Smoothing period (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of ADX values (0–100).
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _adx(_to_f64(high), _to_f64(low), _to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def ADXR(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod: int = 14,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Average Directional Movement Index Rating.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
Smoothing period (default 14).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of ADXR values (0–100).
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _adxr(_to_f64(high), _to_f64(low), _to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def TRIX(close: ArrayLike, timeperiod: int = 30) -> np.ndarray:
|
|||
|
|
"""1-day Rate-Of-Change of a Triple Smooth EMA.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod : int, optional
|
|||
|
|
EMA period (default 30).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of TRIX values.
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _trix(_to_f64(close), timeperiod)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
def ULTOSC(
|
|||
|
|
high: ArrayLike,
|
|||
|
|
low: ArrayLike,
|
|||
|
|
close: ArrayLike,
|
|||
|
|
timeperiod1: int = 7,
|
|||
|
|
timeperiod2: int = 14,
|
|||
|
|
timeperiod3: int = 28,
|
|||
|
|
) -> np.ndarray:
|
|||
|
|
"""Ultimate Oscillator.
|
|||
|
|
|
|||
|
|
Parameters
|
|||
|
|
----------
|
|||
|
|
high : array-like
|
|||
|
|
Sequence of high prices.
|
|||
|
|
low : array-like
|
|||
|
|
Sequence of low prices.
|
|||
|
|
close : array-like
|
|||
|
|
Sequence of closing prices.
|
|||
|
|
timeperiod1 : int, optional
|
|||
|
|
First period (default 7).
|
|||
|
|
timeperiod2 : int, optional
|
|||
|
|
Second period (default 14).
|
|||
|
|
timeperiod3 : int, optional
|
|||
|
|
Third period (default 28).
|
|||
|
|
|
|||
|
|
Returns
|
|||
|
|
-------
|
|||
|
|
numpy.ndarray
|
|||
|
|
Array of ULTOSC values (0–100).
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
return _ultosc(
|
|||
|
|
_to_f64(high),
|
|||
|
|
_to_f64(low),
|
|||
|
|
_to_f64(close),
|
|||
|
|
timeperiod1,
|
|||
|
|
timeperiod2,
|
|||
|
|
timeperiod3,
|
|||
|
|
)
|
|||
|
|
except ValueError as e:
|
|||
|
|
_normalize_rust_error(e)
|
|||
|
|
|
|||
|
|
|
|||
|
|
__all__ = [
|
|||
|
|
"RSI",
|
|||
|
|
"MOM",
|
|||
|
|
"ROC",
|
|||
|
|
"ROCP",
|
|||
|
|
"ROCR",
|
|||
|
|
"ROCR100",
|
|||
|
|
"WILLR",
|
|||
|
|
"AROON",
|
|||
|
|
"AROONOSC",
|
|||
|
|
"CCI",
|
|||
|
|
"MFI",
|
|||
|
|
"BOP",
|
|||
|
|
"STOCHF",
|
|||
|
|
"STOCH",
|
|||
|
|
"STOCHRSI",
|
|||
|
|
"APO",
|
|||
|
|
"PPO",
|
|||
|
|
"CMO",
|
|||
|
|
"PLUS_DM",
|
|||
|
|
"MINUS_DM",
|
|||
|
|
"PLUS_DI",
|
|||
|
|
"MINUS_DI",
|
|||
|
|
"DX",
|
|||
|
|
"ADX",
|
|||
|
|
"ADXR",
|
|||
|
|
"TRIX",
|
|||
|
|
"ULTOSC",
|
|||
|
|
"TRANGE",
|
|||
|
|
]
|