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99.3_scratch_TODO.R
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99.3_scratch_TODO.R
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#' ---
#' title: "Scratch File for Development"
#' author: "MS Patterson, [email protected]"
#' date: "`r format(Sys.time(), '%B %d, %Y')`"
#' output: github_document
#' ---
#'
#' ##TODO
#' 0. [x] **orig_strata:** More or less done when the collation is complete,
#' can be pulled out of that data.
#' 1. [x] **strata_totals:** exported with samples, needs to be processed and
#' converted into pixel counts. Trivial.
#' 2. [x] **Collate CEO outputs:** Bring together all samples, unify with original
#' data derived from GEE/MAE to get stratifying map classes and old validation
#' back into the file. Should be able to join on Lat/Long.
#' 3. [X] **map_label:** Data goes back into GEE to sample final maps.
#' Obviously constrained by existence of final maps.
#' 4. [X] **Process CEO outputs:** run through data prep scripts to get ref classes.
#' Will likely require updating the functions, again. Might have to wait on
#' this step for the actual maps to be output, to avoid another reclass on the
#' data. Potential chokepoint.
#' 5. [X] **ref_label:** Pull out of processed CEO data. Can be completed prior
#' to having final maps, but is potential chokepoint linked to processing.
#' 6. [X] **sample_totals:** Derived from a summary of the collatted CEO data.
#' 7. [X] **rfcodes:** Easy-peasy lemon squeezy. Reclass possible, though.
#' 8. [X] **pixel** = 30.
#' 9. [X] **totarea_pix:** Easy to get from total areas.
#' 10. [X] **Analyze:** Use new functions to rebalance sample and calculate
#' accuracies. Rejoice, maybe!
#' 11. [] **DREAD:** Reclass to improve accuracy and re-run.
#' 12. [] **Report:** Outline shortly, then simply fill in.
#'
#' Scratch area below:
#+ scratch
#setup
library(tidyverse)
source("00.1_functions_en.R")
source("00.3_area_est_functions_en.R")