R/combine_observations.R

In Xcertainty: Estimating Lengths and Uncertainty from Photogrammetric Imagery

#' Combine parsed observations into a single parsed object
#' 
#' Combine parsed observations, such as calibration and observation (whale) data into a single parsed object. 
#' This combined, single parsed object can then be used as the data input for one of the samplers.
#' 
#' @example examples/example_parse_observations.R
#' 
#' @param ... Parsed datasets to combine (i.e., outputs from 
#'   \code{Xcertainty::parsed_observations})
#' 
#' @return outputs a list with four elements: 
#' \describe{
#'  \item{pixel_counts}{a tibble containing the measurements in pixels 
#'  linked with Subject, Measurement description, Image, and the Timepoint}
#'  \item{training_objects}{a tibble containing the Subject, Measurement, Length, 
#'  and Timepoint. NULL if no training objects were included}
#'  \item{prediction_objects}{a tibble containing the Subject, Measurement, and 
#'  Timepoint. NULL if no prediction data included}
#'  \item{image_info}{a tibble containing the Image, Barometer, Laser, FocalLength,
#'  ImageWidth, SensorWidth, and UAS}
#'  }
#' 
#' @export
#' 
combine_observations = function(...) {
  
  # collect arguments
  x = list(...)
  
  # validate input
  for(i in seq_along(x)) {
    if(!inherits(x[[i]], 'obs.parsed')) {
      stop(paste('Argument', i, 'is not output from parse_observations()'))
    }
  }
  
  # combine arguments
  res = list(
    pixel_counts = do.call(rbind, lapply(x, function(x) x$pixel_counts)),
    training_objects = do.call(rbind, lapply(x, function(x) x$training_objects)),
    prediction_objects = do.call(rbind, lapply(x, function(x) x$prediction_objects)),
    image_info = do.call(rbind, lapply(x, function(x) x$image_info))
  )
  
  #
  # validate combined data
  #

  validate_pixel_counts(res$pixel_counts)

  if(!is.null(res$training_objects)) {
    validate_training_objects(res$training_objects)
  }
  
  if(!is.null(res$prediction_objects)) {
    validate_prediction_objects(res$prediction_objects)
  }
  
  validate_image_info(res$image_info)

  # package results
  class(res) = 'obs.parsed'
  res
}