R/drrobust.R

In XiaosuTong/drsstl: Spatial Seasonal Trend Loess analysis routine using divide and recombined

# nolint start
# drrobust <- function(input, output, vari, Clcontrol, zero.weight=1e-6) {
#
#   jobW <- list()
#   jobW$map <- expression({
#     lapply(seq_along(map.keys), function(r) {
#       n <- nrow(map.values[[r]])
#       mid1 <- floor(n / 2 + 1)
#       mid2 <- n - mid1 + 1
#       R.abs <- abs(map.values[[r]][, vari] - map.values[[r]]$trend - map.values[[r]]$seasonal)
#       h <- 3 * sum(sort(R.abs)[mid1:mid2])
#       h9 <- 0.999 * h
#       h1 <- 0.001 * h
#       w <- (1 - (R.abs / h)^2)^2
#       w[R.abs <= h1] <- 1
#       w[R.abs >= h9] <- 0
#       w[w == 0] <- zero.weight
#       w[is.na(w)] <- 1
#       map.values[[r]]$weight <- w
#       rhcollect(map.keys[[r]], map.values[[r]])
#     })
#   })
#   jobW$parameters <- list(
#     vari = vari, zero.weight = zero.weight
#   )
#   jobW$input <- rhfmt(input, type = "sequence")
#   jobW$output <- rhfmt(output, type = "sequence")
#   jobW$mapred <- list(
#     mapred.reduce.tasks = Clcontrol$reduceTask,  #cdh3,4
#     mapreduce.job.reduces = Clcontrol$reduceTask,  #cdh5
#     io.sort.mb = Clcontrol$io.sort,
#     rhipe_reduce_buff_size = 10000,
#     io.sort.spill.percent = Clcontrol$spill.percent
#   )
#   jobW$readback <- FALSE
#   jobW$jobname <- output
#   job.mr <- do.call("rhwatch", jobW)
#
# }
# nolint end