Build daily load-curve segments from a normalized panel — elcf4r_build_daily

Convert a long-format load table into one row per entity-day and one column per within-day time index. This is the matrix representation required by functional load-curve models and rolling benchmark scripts.

Usage

elcf4r_build_daily_segments(
  data,
  id_col = "entity_id",
  timestamp_col = "timestamp",
  value_col = "y",
  temp_col = "temp",
  carry_cols = NULL,
  expected_points_per_day = NULL,
  resolution_minutes = NULL,
  complete_days_only = TRUE,
  drop_na_value = TRUE,
  tz = "UTC"
)

Arguments

data: Data frame containing at least entity id, timestamp and load.
id_col: Name of the entity identifier column.
timestamp_col: Name of the timestamp column.
value_col: Name of the load column.
temp_col: Optional name of a temperature column used to derive day summaries.
carry_cols: Optional day-level columns to propagate into the returned covariate table. Their first non-missing value within each day is kept.
expected_points_per_day: Expected number of samples per day. If NULL, it is derived from resolution_minutes.
resolution_minutes: Sampling resolution in minutes. If NULL, it is inferred from timestamps or from a resolution_minutes column. Fractional minute values are allowed.
complete_days_only: If TRUE, incomplete or duplicated days are dropped from the output.
drop_na_value: If TRUE, days with missing load values are dropped.
tz: Time zone used to derive dates and within-day positions.

Value

A list with components segments, covariates, resolution_minutes and points_per_day.

Examples

id1 <- subset(
  elcf4r_iflex_example,
  entity_id == unique(elcf4r_iflex_example$entity_id)[1]
)
daily <- elcf4r_build_daily_segments(id1, carry_cols = "participation_phase")
dim(daily$segments)
#> [1] 14 24
names(daily$covariates)
#>  [1] "day_key"             "entity_id"           "date"               
#>  [4] "n_points"            "n_unique_index"      "has_duplicate_index"
#>  [7] "has_missing_value"   "dow"                 "month"              
#> [10] "temp_mean"           "temp_min"            "temp_max"           
#> [13] "participation_phase"