Extract an rwl series from ring or sector profile data

This function builds a dendrochronological dplR rwl object (a data frame with years as row names and series IDs as column names) from annually resolved QWA data, ready for scaling (see scale_for_tucson()) and writing to .rwl with dplR::write.tucson(). Depending on the selected parameter, the function either uses ring-level measurements (e.g. mean ring width, mrw) or profile-level measurements at a given sector (aggregated cell parameters such as the 90th percentile lumen area, la_q90).

Duplicate rings (exclude_dupl) and user-defined ring exclusions (exclude_issues) are filtered out before constructing the final time series. These flag columns are read from df_rings, making it a required parameter, while prf_data (with the selected sector) is only required to extract a param from the profile data.

Series are grouped by woodpiece (each core/sample yields one series); thus the woodpiece_labels become the column names.

Usage

extract_rwl(df_rings, param, prf_data = NULL, sector = NULL)

Arguments

df_rings: A data frame containing ROXAS ring-level measurements and logical flag columns (the $rings component of a QWAdata object, after calling complete_QWAdata() to instantiate the flag columns).
param: Character string specifying the parameter to export: either a measurement column in df_rings, or an aggregated cell measurement in prf_data (e.g. "la_mean", "la_q90").
prf_data: A data frame containing ROXAS profile-level measurements (aggregated cell parameters via calculate_sector_profiles()). Only required when param is not a df_rings column.
sector: Integer specifying which sector to use when exporting a prf_data parameter. Required in that case, otherwise ignored.

Value

A dplR rwl object with the selected param data.

Examples

if (FALSE) { # \dontrun{
# Build an rwl object from mean ring width
extract_rwl(df_rings = QWA_data$rings,
           param = "mrw")

# Build an rwl object from a profile-level parameter
extract_rwl(df_rings = QWA_data$rings,
           param = "cwtrad_mean",
           prf_data = prf_sector,
           sector = 5)
} # }