Convert priors / MCMC samples to parameter sample chains
Source:R/get.parameter.samples.R
get.parameter.samples.RdConvert priors / MCMC samples to parameter sample chains
Value
Named list with 5 elements: trait.samples, sa.samples,
ensemble.samples, runs.samples, env.samples. Returned invisibly.
Details
Upstream contract (reads from each PFT's outdir):
post.distns.Rdataorprior.distns.RdataPosterior (or prior) distribution summaries produced by
run.meta.analysis.pft. A data frame with columnsdistn,parama,paramb,n.trait.mcmc.Rdata(Optional) MCMC chain samples from the meta-analysis. Named list of
mcmc.listobjects, one per trait. If present, samples are drawn from the chains directly; otherwise, independent samples are drawn frompost.distns.
File-based side effects (saved to settings$outdir):
samples.RdataWhen
save_to_disk = TRUE, bundles 5 objects:trait.samples— Named list (PFT -> trait -> numeric vector of lengthiterations). Raw MCMC or prior-sampled values.sa.samples— Named list (PFT -> matrix[n_quantiles x n_traits]). Quantile-based samples for sensitivity analysis.ensemble.samples— Named list (PFT -> data frame[ensemble.size x n_traits]). Subsampled parameter sets for ensemble runs.env.samples— Currently empty list (reserved for environmental samples).runs.samples— Currently empty list (reserved for run metadata).
Downstream contract: samples.Rdata is loaded by run.write.configs
(in PEcAn.workflow) to generate model configuration files. It is also
loaded by get.results and run.sensitivity.analysis to retrieve
sample metadata for post-processing. This implicit file-based coupling is
a refactoring target.