Normalize structured interpretation sources — interpret

interpret_records normalizes interpretation inputs from one or more structured sources into traceable evidence, estimate, header, note, prior, and footnote records. It is intended for downstream packages that already own the domain-specific ordering and wording of an interpretation, but want BayesTools to consistently extract table rows, preserve Bayes-factor metadata, and carry traceability information.

interpret_records(
  sources,
  plan,
  output = c("records", "text"),
  missing = c("error", "skip", "warn"),
  method = NULL,
  digits = 3
)

interpret_tables(sources, spec, ...)

Arguments

sources: named list of interpretation sources. Each source can be a data.frame/BayesTools_table, or a list with entries data, optional type, and optional per-source schema. Supported source types are "table", "record", and "records". Table schemas can define columns such as row, BF, central, lower, upper, and metadata such as BF_orientation, BF_scale, BF_name, BF_bound_operator, lower_prob, upper_prob, units, and conditioning. interval_level is not accepted as input; normalized estimate records derive it from upper_prob - lower_prob, or retain NA when endpoint probabilities are unknown.
plan: ordered list specifying which records to create. Plan items can have kind = "evidence", "estimate", "pair", "test_estimate", "for_each", "header", "note", "prior", or "footnote". Pair items contain evidence and/or estimate references. Dynamic "for_each" items generate records from source row order.
output: whether to return normalized "records" or a simple generic "text" rendering. Downstream packages should usually request "records" and render domain-specific text themselves.
missing: how missing optional sources or rows should be handled.
method: optional method name used only by the generic text renderer.
digits: number of digits used only by the generic text renderer.
spec: alias for plan used by interpret_tables.
...: additional arguments passed from interpret_tables to interpret_records.

Value

interpret_records returns a data frame with class "BayesTools_interpret_records" when output = "records", or a character vector when output = "text". Evidence records keep the supplied BF_value and BF_scale; BF_canonical_value is the Bayes factor on the natural scale in the canonical orientation (0 or Inf for a log-scale value beyond the double range). The text rendering classifies and prints a log-scale value from its logarithm, so such values keep their evidence strength and are printed as exp(<log>). interpret_tables is a convenience wrapper around interpret_records.