Arnaud Legoux Moving Average (ta.alma)

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Smooth price with an offsettable Gaussian weight distribution to control smoothing and response. floor=True rounds the weight center down and normalizes stably; the fixed backend weight direction is retained, without promising numerical parity with Pine.

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Run this example

This complete script uses bundled data. It observes the selected output without placing trades.

import numpy as np
from openbacktesting import Backtest, Strategy
from openbacktesting.test import GOOG

data = GOOG.copy()

class Example(Strategy):
    def init(self):
        self.value = self.ta.alma(self.close)
        self.latest_value = None

    def next(self):
        channel = self.value
        if channel.valid[-1]:
            self.latest_value = float(channel[-1])

result = Backtest(data, Example).run()
print(result["_strategy"].latest_value)

Call and parameters

self.ta.alma(
    source=None,
    *,
    length=10,
    sigma=6.0,
    distribution_offset=0.85,
    floor=False,
    inputs=None,
    backend=None,
    required_outputs=None,
)

Register in init(). Read the returned channel in next() after checking valid[-1].

Parameter	Meaning	Type	Default	Allowed values
length	Calculation window in observations.	int	10	Minimum: 1
sigma	Controls the ALMA Gaussian weight width.	float	6.0	Minimum: 1e-08
distribution_offset	Relative location of the ALMA weight center.	float	0.85	Minimum: 1e-08; Maximum: 1.0
floor	Round the ALMA weight center down when True.	bool	False	No additional constraints

source/named source arguments accept a column name or same-run single-channel handle. Alternatively, inputs maps each input below to a column or handle. backend selects a supported implementation; required_outputs selects channels for readiness diagnostics. See shared arguments and handles.

Inputs and outputs

Required inputs: close.

Channel	Meaning
alma	Arnaud Legoux Moving Average value

Reading values safely

Insufficient history or missing inputs can make a channel invalid. Check that channel's valid mask; ready is diagnostic and never suppresses next(). Multi-output results may have different valid channels on the same bar.

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