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Custom Indicator Arnaud Legoux Moving Average (Vectorised or NanVec): Help Needed

Have anyone done an indicator on this that they would be willing to share? I'm interested in both Normal and Vectorised approaches.
(https://stackoverflow.com/questions/46990098/arnaudlegouxmovingaverageandnumpy)
I am not experienced in subclassing/inheritance in Python
Any help would be highly appreciated. Thx in advance!

Anybody has any custom indicator examples which includes numpy calculations? I would be appretiated if you share so i can figure out how to convert the code below.
def NPALMA(pnp_array, a) : length = a # just some number (6.0 is useful) sigma = 6 # sensisitivity (close to 1) or smoothness (close to 0) offset = 0.85 asize = length  1 m = offset * asize s = length / sigma dss = 2 * s * s alma = np.zeros(pnp_array.shape) wtd_sum = np.zeros(pnp_array.shape) for l in range(len(pnp_array)): if l >= asize: for i in range(length): im = i  m wtd = np.exp( (im * im) / dss) alma[l] += pnp_array[l  length + i] * wtd wtd_sum[l] += wtd alma[l] = alma[l] / wtd_sum[l] return alma

@EnderKina were you able to solve this?