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Process matrices and add derived columns

Source: R/synch_matrix_processing.R
matrix_process.Rd

Main function to process synchronization matrices from feeding and drinking data. Creates time-based matrices tracking animal activity, bin usage, and optionally feed amounts. Adds derived columns like total number of animals active, total bins occupied, and date information. Can handle both single data frame input or list of data frames.

Usage

matrix_process(
  data_list,
  type = c("feed", "drink", "feed_and_drink"),
  resolution = c("sec", "min"),
  id_col = id_col2(),
  start_col = start_col2(),
  end_col = end_col2(),
  bin_col = bin_col2(),
  start_weight_col = start_weight_col2(),
  end_weight_col = end_weight_col2(),
  bins_feed = bins_feed2(),
  bins_wat = bins_wat2()
)

Arguments

data_list

List of data frames to process or single data frame

type

Character, one of 'feed', 'drink', 'feed_and_drink'

resolution

Character, either "sec" (default) or "min" for time resolution

id_col

Animal ID column name (default current global value from id_col2())

start_col

Start time column name (default current global value from start_col2())

end_col

End time column name (default current global value from end_col2())

bin_col

Bin ID column name (default current global value from bin_col2())

start_weight_col

Start weight column name (default current global value from start_weight_col2())

end_weight_col

End weight column name (default current global value from end_weight_col2())

bins_feed

Integer vector of feed bins (default current global value from bins_feed2())

bins_wat

Integer vector of water bins (default current global value from bins_wat2())

Value

List containing processed matrices (structure depends on input type and format):

For feed type ("feed"):

  • synch_master_animal2: Time × Animal activity matrix

    • Rows: Time points (filtered to active periods only)

    • Columns: Time + Animal IDs + derived columns

    • Values in each cell: 1 = animal present, 0 = animal not present

    • Derived columns: total_animal_num, unoccupied_bin_num, date

  • synch_master_bin2: Time × Animal bin occupancy matrix

    • Rows: Time points (filtered to active periods only)

    • Columns: Time + Animal IDs + date column only

    • Values in each cell: Bin number animal is using (0 = not active)

    • Derived columns: date only

  • synch_master_feed2: Time × Bin feed amount matrix

    • Rows: Time points (filtered to active periods only)

    • Columns: Time + Bin numbers + derived columns

    • Values in each cell: Feed weight at each bin

    • Derived columns: totalFeed, date

For drink/feed_and_drink types ("drink", "feed_and_drink"):

  • synch_master_animal2: Same as above but for drinking activity

  • synch_master_bin2: Same as above but for water bin occupancy

Note: If input is a single data frame, returns individual matrices. If input is a list, returns lists of matrices (one per date).

Examples

# Create toy data with more realistic structure
toy_data <- list(
  day1 = data.frame(
    animal = c(1, 2),
    start = lubridate::ymd_hms(c("2023-01-01 10:00:00", "2023-01-01 10:00:01")),
    end = lubridate::ymd_hms(c("2023-01-01 10:00:02", "2023-01-01 10:00:03")),
    bin = c(1, 2),
    start_weight = c(10.5, 8.3),
    end_weight = c(10.2, 8.1)
  )
)


# Process with bin
result <- matrix_process(toy_data, type = "feed", 
                                  id_col = "animal", start_col = "start", 
                                  end_col = "end", bin_col = "bin",
                                  start_weight_col = "start_weight",
                                  end_weight_col = "end_weight",
                                  bins_feed = 1:2)
names(result)
#> [1] "synch_master_animal2" "synch_master_bin2"    "synch_master_feed2"