Validate measure data — validate

Performs comprehensive validation checks on measure data, including axis monotonicity, duplicate detection, missing value detection, and spacing regularity.

Usage

validate_measure(
  x,
  checks = c("monotonic", "duplicates", "missing", "spacing"),
  tolerance = 1e-06,
  action = c("error", "warn", "message")
)

Arguments

x: A measure_tbl, measure_list, or data frame with measure column.
checks: Character vector of checks to perform. Default is all checks: "monotonic", "duplicates", "missing", "spacing".
tolerance: Numeric tolerance for spacing regularity check. Default is 1e-6.
action: What to do when validation fails: "error" (default), "warn", or "message".

Value

Invisibly returns a list with validation results. Each element is a list with valid (logical), message (character), and details.

Examples

# Create valid measure data
spec <- new_measure_tbl(location = 1:100, value = sin(1:100 / 10))
validate_measure(spec)

# Data with issues
spec_dup <- new_measure_tbl(location = c(1, 2, 2, 3), value = c(1, 2, 3, 4))
try(validate_measure(spec_dup))
#> Error in validate_measure(spec_dup) : Measure validation failed:
#> ✖ Duplicate locations found in 1 sample(s) Irregular spacing found in 1
#>   sample(s)

# Only check specific issues
validate_measure(spec, checks = c("monotonic", "missing"))