Flag overly-gapfilled data — flux

Flags rows of data based on variables with associated _QC columns.

Usage

flux_qc(data, qc_vars, max_gapfilled = 0.5, operator = c("any", "all"))

Arguments

data: A data frame created by flux_read().
qc_vars: A character vector of column names with associated *_QC columns to use for flagging.
max_gapfilled: Numeric between 0 and 1; cutoff for the qc_flagged flag to be TRUE. Can be length 1 or the same length as qc_vars to supply a different threshold for each variable.
operator: How to flag data when multiple qc_vars are supplied? If "any", the row will be marked as bad if any of the QC vars indicate gap-filling above their max_gapfill threshold. If "all" then the row will be flagged only if all of the QC vars are above their max_gapfill.

Value

A tibble with the added columns p_gapfilled and qc_flagged. If operator = "any", qc_flagged = TRUE indicates that at least one of the supplied QC variables was more gapfilled than max_gapfilled and p_gapfilled will be the maximum proportion gapfilled across the QC vars for each row. If operator = "all", then qc_flagged = TRUE indicates that all of the supplied QC variables were more gapfilled than the thresholds supplies and p_gapfilled will be the minimum proportion gapfilled across all QC variables for each row.

Examples

if (FALSE) { # \dontrun{

# Flag rows where NEE_VUT_REF is more than 50% gapfilled
manifest <- flux_discover_files()
annual <- flux_read(manifest, resolution = "y")
annual_flagged <- flux_qc(
  annual,
  qc_vars = "NEE_VUT_REF",
  max_gapfilled = 0.5
)

# Use multiple variables each with a different threshold for QC
annual_flagged2 <- flux_qc(
  annual,
  qc_vars = c("NEE_VUT_REF", "TA_F"),
  max_gapfilled = c(0.4, 0.6)
)

# Same as above, but require *both* variables to be above their thresholds
# to consider that row a problem
annual_flagged2 <- flux_qc(
  annual,
  qc_vars = c("NEE_VUT_REF", "TA_F"),
  max_gapfilled = c(0.4, 0.6),
  operator = "all"
)

} # }