Create regulariser object and MCMC particle regulariser #785
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… particle regularisation.
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Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## main #785 +/- ##
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+ Coverage 94.87% 94.89% +0.02%
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Files 176 179 +3
Lines 9757 9801 +44
Branches 1938 1942 +4
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+ Hits 9257 9301 +44
Misses 356 356
Partials 144 144
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sdhiscocks
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stonesoup/regulariser/particle.py
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| for detection in detections: | ||
| move_meas_likelihood.append(measurement_model.logpdf(detection, moved_particles)) | ||
| post_meas_likelihood.append(measurement_model.logpdf(detection, moved_particles)) |
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Just to save calling logpdf twice.
| for detection in detections: | |
| move_meas_likelihood.append(measurement_model.logpdf(detection, moved_particles)) | |
| post_meas_likelihood.append(measurement_model.logpdf(detection, moved_particles)) | |
| for detection in detections: | |
| likelihood = measurement_model.logpdf(detection, moved_particles) | |
| move_meas_likelihood.append(likelihood) | |
| post_meas_likelihood.append(likelihood) |
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Actually, is this an error, and they shouldn't be the same? From variable names looks like it should be posterior.
| for detection in detections: | |
| move_meas_likelihood.append(measurement_model.logpdf(detection, moved_particles)) | |
| post_meas_likelihood.append(measurement_model.logpdf(detection, moved_particles)) | |
| for detection in detections: | |
| move_meas_likelihood.append(measurement_model.logpdf(detection, moved_particles)) | |
| post_meas_likelihood.append(measurement_model.logpdf(detection, posterior)) |
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stonesoup/regulariser/particle.py
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| alpha = (move_meas_likelihood[max_likelihood_idx]*move_likelihood) / \ | ||
| (post_meas_likelihood[max_likelihood_idx]*post_likelihood) |
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move_likelihood and post_likelihood are from pdf, and move_meas_likelihood and post_meas_likelihood are using logpdf. Is this right?
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You are right, there is a mismatch between logpdf and pdf. I have changed the move_likelihood and post_likelihood to also be logpdf and changed the calculation of alpha accordingly.
remove copies Co-authored-by: Steven Hiscocks <sdhiscocks@dstl.gov.uk>
Co-authored-by: Steven Hiscocks <sdhiscocks@dstl.gov.uk>
Created the regulariser object for optional use with particle filters when impoverishment is a problem. This has included the class MCMCRegulariser that follows a particular implementation using the Metropolis-Hastings algorithm (referenced appropriately in the docs).