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feat: add length->period kwargs alias across all 168 indicator functions for pandas-ta compat

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Miha Kralj
2026-03-02 10:00:29 -08:00
parent ae7207c3d8
commit 18694e337e
16 changed files with 211 additions and 168 deletions
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python/quantalib/errors.py
+22 -22
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@@ -39,7 +39,7 @@ __all__ = [
def huber(actual: object, predicted: object, period: int = 14, delta: float = 1.35, offset: int = 0, **kwargs) -> object:
"""Huber Loss."""
period = int(period)
period = int(kwargs.get("length", period))
delta = float(delta)
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
@@ -51,7 +51,7 @@ def huber(actual: object, predicted: object, period: int = 14, delta: float = 1.
def logcosh(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Log-Cosh Loss."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -62,7 +62,7 @@ def logcosh(actual: object, predicted: object, period: int = 14, offset: int = 0
def maape(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Mean Arctangent Absolute Percentage Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -73,7 +73,7 @@ def maape(actual: object, predicted: object, period: int = 14, offset: int = 0,
def mapd(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Mean Absolute Percentage Deviation."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -84,7 +84,7 @@ def mapd(actual: object, predicted: object, period: int = 14, offset: int = 0, *
def mase(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Mean Absolute Scaled Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -95,7 +95,7 @@ def mase(actual: object, predicted: object, period: int = 14, offset: int = 0, *
def mdae(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Median Absolute Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -106,7 +106,7 @@ def mdae(actual: object, predicted: object, period: int = 14, offset: int = 0, *
def mdape(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Median Absolute Percentage Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -117,7 +117,7 @@ def mdape(actual: object, predicted: object, period: int = 14, offset: int = 0,
def me(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Mean Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -128,7 +128,7 @@ def me(actual: object, predicted: object, period: int = 14, offset: int = 0, **k
def mpe(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Mean Percentage Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -139,7 +139,7 @@ def mpe(actual: object, predicted: object, period: int = 14, offset: int = 0, **
def mrae(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Mean Relative Absolute Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -150,7 +150,7 @@ def mrae(actual: object, predicted: object, period: int = 14, offset: int = 0, *
def msle(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Mean Squared Logarithmic Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -161,7 +161,7 @@ def msle(actual: object, predicted: object, period: int = 14, offset: int = 0, *
def pseudohuber(actual: object, predicted: object, period: int = 14, delta: float = 1.35, offset: int = 0, **kwargs) -> object:
"""Pseudo-Huber Loss."""
period = int(period)
period = int(kwargs.get("length", period))
delta = float(delta)
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
@@ -173,7 +173,7 @@ def pseudohuber(actual: object, predicted: object, period: int = 14, delta: floa
def quantileloss(actual: object, predicted: object, period: int = 14, quantile: float = 0.5, offset: int = 0, **kwargs) -> object:
"""Quantile Loss (Pinball Loss)."""
period = int(period)
period = int(kwargs.get("length", period))
quantile = float(quantile)
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
@@ -185,7 +185,7 @@ def quantileloss(actual: object, predicted: object, period: int = 14, quantile:
def rae(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Relative Absolute Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -196,7 +196,7 @@ def rae(actual: object, predicted: object, period: int = 14, offset: int = 0, **
def rmsle(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Root Mean Squared Logarithmic Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -207,7 +207,7 @@ def rmsle(actual: object, predicted: object, period: int = 14, offset: int = 0,
def rse(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Relative Squared Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -218,7 +218,7 @@ def rse(actual: object, predicted: object, period: int = 14, offset: int = 0, **
def rsquared(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""R-Squared (Coefficient of Determination)."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -229,7 +229,7 @@ def rsquared(actual: object, predicted: object, period: int = 14, offset: int =
def smape(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Symmetric Mean Absolute Percentage Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -240,7 +240,7 @@ def smape(actual: object, predicted: object, period: int = 14, offset: int = 0,
def theilu(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Theil U Statistic (Error)."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -251,7 +251,7 @@ def theilu(actual: object, predicted: object, period: int = 14, offset: int = 0,
def tukeybiweight(actual: object, predicted: object, period: int = 14, c: float = 4.685, offset: int = 0, **kwargs) -> object:
"""Tukey Biweight Loss."""
period = int(period)
period = int(kwargs.get("length", period))
c = float(c)
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
@@ -263,7 +263,7 @@ def tukeybiweight(actual: object, predicted: object, period: int = 14, c: float
def wmape(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Weighted Mean Absolute Percentage Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)
@@ -274,7 +274,7 @@ def wmape(actual: object, predicted: object, period: int = 14, offset: int = 0,
def wrmse(actual: object, predicted: object, period: int = 14, offset: int = 0, **kwargs) -> object:
"""Weighted Root Mean Squared Error."""
period = int(period)
period = int(kwargs.get("length", period))
offset = int(offset)
a, idx = _arr(actual); p, _ = _arr(predicted)
n = len(a)