- class stonesoup.resampler.particle.SystematicResampler[source]
Resample the particles
ParticleStateor list of
Particle) – The particles or particle state to be resampled according to their weights
particle state – The particle state after resampling
- Return type
- class stonesoup.resampler.particle.ESSResampler(threshold: float = None, resampler: ~Resampler = <class 'SystematicResampler'>)[source]
This wrapper uses a
Resamplerto resample the particles inside an instant of
Particles, but only after checking if this is necessary by comparing Effective Sample Size (ESS) with a supplied threshold (numeric). Kish’s ESS is used, as recommended in Section 3.5 of this tutorial 1.
Doucet A., Johansen A.M., 2009, Tutorial on Particle Filtering and Smoothing: Fifteen years later, Handbook of Nonlinear Filtering, Vol. 12.
float, optional) – Threshold compared with ESS to decide whether to resample. Default is number of particles divided by 2, set in resample method
Resampler, optional) – Resampler to wrap, which is called when ESS below threshold
- threshold: float
Threshold compared with ESS to decide whether to resample. Default is number of particles divided by 2, set in resample method