Check parameter values against logical rules

Applies parameter-specific and row-wise logical rules to benthos/epibenthos data, flagging measurements that violate defined conditions. This function replaces multiple deprecated check_*_logical() functions with a general, flexible implementation.

Usage

check_parameter_rules(
  data,
  param_conditions = get(".param_conditions", envir = asNamespace("SHARK4R")),
  rowwise_conditions = get(".rowwise_conditions", envir = asNamespace("SHARK4R")),
  return_df = FALSE,
  return_logical = FALSE,
  verbose = TRUE
)

Arguments

data

A data frame containing at least the columns parameter and value.

param_conditions

A named list of parameter-specific rules. Each element should be a list with:

condition

Function taking a numeric vector and returning a logical vector (TRUE = violation).

range_msg

Character string describing the expected range.

Defaults to SHARK4R:::.param_conditions defined in the package namespace.

rowwise_conditions

A named list of row-wise rules applied across multiple parameters. Each element should be a function taking the full data frame and returning a logical vector. Defaults to SHARK4R:::.rowwise_conditions defined in the package namespace.

return_df

Logical. If TRUE, problematic rows are returned as plain data.frames.

return_logical

Logical. If TRUE, problematic rows are returned as logical vectors. Overrides return_df.

verbose

Logical. If TRUE, messages will be displayed during execution. Defaults to TRUE.

Value

A named list of results for each parameter:

Logical vector

If return_logical = TRUE.

Data frame

If return_df = TRUE and violations exist.

DT datatable

If violations exist and return_df = FALSE.

NULL

If no violations exist for the parameter.

Invisible return.

Details

This function evaluates each parameter in param_conditions and rowwise_conditions. Only parameters present in the dataset are checked. Messages are printed indicating whether values are within expected ranges or which rows violate rules.

Examples

df <- data.frame(
  station_name = c("A1", "A2", "A3", "A4"),
  sample_date = as.Date("2023-05-01") + 0:3,
  sample_id = 101:104,
  parameter = c("Wet weight", "Wet weight", "Abundance", "BQIm"),
  value = c(0, 5, 0, 3)
)

# Check against default package rules
check_parameter_rules(df)
#> Parameter Wet weight, measurement(s) outside expected range: > 0
#> Parameter BQIm, row-wise logical check failed

# Return problematic rows as data.frame
check_parameter_rules(df, return_df = TRUE)
#> Parameter Wet weight, measurement(s) outside expected range: > 0
#> Parameter BQIm, row-wise logical check failed

# Return logical vectors for each parameter
check_parameter_rules(df, return_logical = TRUE)