Source code for stonesoup.resampler.particle

# -*- coding: utf-8 -*-
import numpy as np

from .base import Resampler
from ..types.numeric import Probability
from ..types.particle import Particles

[docs]class SystematicResampler(Resampler):
[docs] def resample(self, particles): """Resample the particles Parameters ---------- particles : list of :class:`~.Particle` The particles to be resampled according to their weight Returns ------- particles : list of :class:`~.Particle` The resampled particles """ if not isinstance(particles, Particles): particles = Particles(particle_list=particles) n_particles = len(particles) weight = Probability(1/n_particles) log_weights = np.array([weight.log_value for weight in particles.weight]) weight_order = np.argsort(log_weights, kind='stable') max_log_value = log_weights[weight_order[-1]] with np.errstate(divide='ignore'): cdf = np.log(np.cumsum(np.exp(log_weights[weight_order] - max_log_value))) cdf += max_log_value # Pick random starting point u_i = np.random.uniform(0, 1 / n_particles) # Cycle through the cumulative distribution and copy the particle # that pushed the score over the current value u_j = u_i + (1 / n_particles) * np.arange(n_particles) index = weight_order[np.searchsorted(cdf, np.log(u_j))] new_particles = Particles(state_vector=particles.state_vector[:, index], weight=[weight]*n_particles, parent=Particles(state_vector=particles.state_vector[:, index], weight=particles.weight[index])) return new_particles