Help on customized indicator Thx!

Hello,
I am totally new to the community and also a fresh user of backtrader. I am trying to develop an indicator which I found in Tradingview. However I found it a bit difficult to do so.
The logic of the indicator is as the following:
Momentum Adjusted Moving Average (MaMA)
The idea is to adjust the prices with the momentum and calculate the moving average using the adjusted prices.
First, we calculate the momentum and acceleration:
Mom = Price_now  Price_prev Acceleration = Mom_now  Mom_prev
Then we calculate a probability value using a few past bars:
Probability = N_increase / N
where N_increase is the number of bars whose price is increased comparing to the previous one, and N the total number of bars in the calculation window.
Next we can calculate the adjusted price as:
Adj = Price_now + Probability * (Mom + 0.5 * Acceleration)
and finally calculate the moving average of Adj.
The strategy involving this indicator can be as simple as an MA crossover strategy.
I was wondering that if anyone would show me an example of how to implement this indicator in Backtrader ? I tried something like this but it somehow goes into an endless run...
class MaMA(bt.Indicator): lines = ('MaMA', ) params = { "momLength": 34, "maLength": 55, "pLength": 13} def __init__(self): max_length = max(self.p.momLength*2, self.p.maLength, self.p.pLength) self.addminperiod(max_length) def next(self): momentum = bt.ind.Momentum(self.datas[0].close, period=self.params.momLength) accelerate = bt.ind.Momentum(momentum, period=self.params.momLength) prob_change = bt.ind.Momentum(self.datas[0].close, period=1) probability = math.fsum(prob_change.get(size=self.p.pLength) > 0) / self.p.pLength adjusted_close = self.datas[0].close + ( momentum + accelerate*0.5 ) * probability self.lines.MaMA = bt.ind.SMA(adjusted_close, period=self.params.maLength)
Highly appreciate for any advice/suggestions! Thx in adv!

@sky_aka41 I think you are pretty close. I tried this all in a strategy (not a custom indicator) and it seems to be working.
Note I changed the
prob_change
andprobability
expressions slightly.class St(bt.Strategy): params = (("momLength", 34), ("maLength", 55), ("pLength", 13)) def __init__(self) : self.momentum = bt.ind.Momentum(self.datas[0].close, period=self.p.momLength) self.accelerate = bt.ind.Momentum(self.momentum, period=self.p.momLength) self.prob_change = bt.ind.Momentum(self.datas[0].close, period=1) > 0 self.probability = bt.ind.SumN(self.prob_change) / self.p.pLength self.adjusted_close = self.datas[0].close + (self.momentum + self.accelerate*0.5 ) * self.probability self.lines.MaMA = bt.ind.SMA(self.adjusted_close, period=self.p.maLength)