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__author__ = 'Wray Buntine'
_VERSION = '0.1'

import numpy;
import random;

##########
#  globals
#
#  WARNING:  need to recode to remove dependence of beta on x-range!!!

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library(jsonlite)

scribble_creator <- function(folder) {
  points <- list.files(folder, full.names = TRUE)
  message(sprintf("%s fueron detectados", length(points)))
  Sys.sleep(2)
  for (index in seq_along(points)) {
    in_files <- list.files(points[index])
    jsonf <- in_files[grepl("cloud_segmentation", in_files)]
    js_list <- jsonlite::read_json(sprintf("%s/%s", points[index], jsonf))

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library(rgee)
library(rgeeExtra)

# Roy account
ee_Initialize("roy1")

# Load Planet, Sentinel-2, and Landsat-8
# ee_utils_dataset_display(planet)
planet <- ee$ImageCollection('projects/planet-nicfi/assets/basemaps/americas')
s2 <- ee$ImageCollection$Dataset$COPERNICUS_S2_SR

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library(jsonlite)
library(reticulate)
library(raster)

np <- import("numpy")

save_manual_labeling_scribble <- function(point, output) {
  points_x <- list.files(
    path = sprintf("%s/%s.iris/segmentation", point, basename(point)),
    pattern = "2_final\\.npy",

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library(jsonlite)
library(reticulate)
library(raster)

np <- import("numpy")

save_manual_labeling_scribble <- function(point, output) {
  points_x <- list.files(
    path = sprintf("%s/%s.iris/segmentation", point, basename(point)),
    pattern = "2_final\\.npy",

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library(jsonlite)

scribble_ano <- function(file) {
  segmentation_point <- jsonlite::read_json(file)  
  segmentation_point$classes <- list(
    list(
      name = "Clear",
      description = "All clear pixels, i.e. without cloud contamination or cloud shadows.",
      colour = c(255, 255, 255, 0),
      user_colour = c(0, 255, 255, 85)

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viz_patches <- function(pid) {
  metadata_list <- read.csv("https://storage.googleapis.com/flood_dataset/flood-training-metadata.csv")
  date <- metadata_list[metadata_list$chip_id %in% pid, 6][1]
  
  url <- sprintf("https://storage.googleapis.com/flood_dataset/%s.tif", pid)  
  local_tif <- tempfile(fileext = ".tif")
  download.file(url, local_tif)
  
  # BOX
  ee_extent <- local_tif %>% 

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#' Script to sample multiple layers by years 1990 - 2011 using a point dataset
#' @description Layers: Landsat spectral values; NDVI; NDMI; NBR; Elevation, Slope, Aspect.
#' 
#' PARAMETERS
#' 
#' 
library(rgee)
ee_Initialize()

USUptsNew <- ee$FeatureCollection("users/dougramsey/ForCaMF/PointData/USU_RandomPoints_NEW")

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library(rgee)
library(sf)
library(magick)

ee_Initialize()

mask <- system.file("shp/arequipa.shp", package = "rgee") %>% 
  st_read(quiet = TRUE) %>% 
  sf_as_ee()