| CharAnalysis | R Documentation |
Top-level wrapper that calls each analytical stage in sequence and returns all intermediate and final results as a single named list.
CharAnalysis(file_name = NULL)
file_name |
Path to the |
Named list with the following elements:
List of raw and resampled series. After Phase 2:
includes accIS (smoothed background) and peak
(C_peak, either residuals or ratios). After Phase 3: also includes
charPeaks ([N \times T] binary peak matrix),
charPeaksThresh, peaksTotal, and threshFRI.
After Phase 4: also includes peakInsig,
peakMagnitude, smoothedFireFrequ, peaksFrequ.
Pretreatment parameter list (possibly updated by
[char_pretreatment()] – e.g. yrInterp auto-set,
zoneDiv end-value corrected).
Smoothing parameter list.
Peak-analysis parameter list.
Results / output parameter list.
Character string: site name.
Integer matrix (nGaps x 2) of missing-value gap indices.
Threshold list returned by [char_thresh_global()] or
[char_thresh_local()]. Contains pos, neg, SNI,
GOF, and (after Phase 3) minCountP – the
[N \times T] matrix of Shuie-Bain p-values.
Post-processing list from [char_post_process()]: FRI
series, smoothed FRI curve, per-zone Weibull statistics, and the
assembled char_results output matrix (N \times 33).
Numeric matrix (N \times 33) matching the
MATLAB charResults output exactly (alias of
post$char_results).
[char_parameters()], [char_validate_params()], [char_pretreatment()], [char_smooth()], [char_thresh_global()], [char_thresh_local()], [char_peak_id()], [char_post_process()]
# Run the full pipeline on the bundled example dataset:
params_file <- system.file("validation", "CO_charParams.csv",
package = "CharAnalysis")
out <- CharAnalysis(params_file)
# Phase 2 outputs
head(data.frame(ageTop_i = out$charcoal$ybpI,
charAcc_i = out$charcoal$accI,
charBkg_i = out$charcoal$accIS,
charPeak_i = out$charcoal$peak))
# Phase 3 outputs
sum(out$charcoal$charPeaks[, ncol(out$charcoal$charPeaks)])
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