timescales.sim.sim_branching

timescales.sim.sim_branching(n_seconds, fs, tau, lambda_h, lambda_a=None, mean=None, variance=None)

Simulate a branching Poisson process.

Parameters

n_secondsfloat

Length of the signal, in seconds.

fsfloat

Sampling rate, in hz.

taufloat

Timescale, in seconds. Determines branching parameter, m.

lambda_hfloat

Poisson lambda constant.

lamda_afloat

Initial Poisson lambda weight. If None, default to (tau * fs) * lambda_h.

meanfloat, optional, default: None

Mean to normalize signal to.

variancefloat, optional, default: None

Variance to normalize signal to.

Returns

sig1d array

Timseries containing timescale process.

Notes

Simplified implentation based on MR. Estimator:

• https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249447

• https://github.com/Priesemann-Group/mrestimator