Safely delete individual feature measurements with all related data

**DANGER: This permanently deletes data from the database!**

This function safely deletes individual feature measurements (records in `data_traits_measures`) and their associated sub-features (`data_ind_measures_feat`) in the correct order to respect foreign key constraints: 1. Measurement features (`data_ind_measures_feat`) 2. Trait measurements (`data_traits_measures`)

**Individuals are preserved** — only the feature measurements are removed.

**Safety features:** - Dry-run mode to preview what will be deleted - Shows counts of all related data - Requires explicit confirmation (unless force = TRUE) - Uses database transactions (rollback on error) - Detailed logging of each step

Usage

safe_delete_individual_features(
  id_trait_measures = NULL,
  individual_ids = NULL,
  trait_ids = NULL,
  con = NULL,
  dry_run = TRUE,
  force = FALSE,
  verbose = TRUE
)

Arguments

id_trait_measures

Integer vector. Specific measurement ID(s) to delete (`id_trait_measures` from `data_traits_measures`). Takes precedence over `individual_ids` / `trait_ids`. Typically obtained from query_individual_features(..., include_measurement_ids = TRUE). Default NULL.

individual_ids

Integer vector. Delete all feature measurements belonging to these individual ID(s) (`id_n` from `data_individuals`). Can be combined with `trait_ids`. Default NULL.

trait_ids

Integer vector. Filter measurements to these trait ID(s) (`id_trait` from `traitlist`). Only used when `individual_ids` is provided. Default NULL (all traits).

con

Database connection. If NULL, will connect automatically.

dry_run

Logical. If TRUE, shows what would be deleted without deleting. Default TRUE for safety.

force

Logical. If TRUE, skips confirmation prompts. Default FALSE. **USE WITH EXTREME CAUTION!**

verbose

Logical. Show detailed progress? Default TRUE.

Value

List with deletion summary (invisible)

Examples

if (FALSE) { # \dontrun{
con <- call.mydb()

# STEP 1: Extract features and pick the ones to remove
feats <- query_individual_features(
  plot_ids = 42,
  include_measurement_ids = TRUE,
  format = "long"
)
ids_to_remove <- feats$id_trait_measures[feats$trait == "dbh" & feats$traitvalue < 0]

# STEP 2: Always do a dry-run first!
safe_delete_individual_features(id_trait_measures = ids_to_remove, dry_run = TRUE)

# STEP 3: Review output, then delete if sure
safe_delete_individual_features(id_trait_measures = ids_to_remove, dry_run = FALSE)

# Alternative: delete all features of specific trait(s) for given individuals
safe_delete_individual_features(
  individual_ids = c(1001, 1002),
  trait_ids = c(5),
  dry_run = TRUE
)
} # }