## -----------------------------------------------------------------------------
library(openeo)

## ----include=FALSE------------------------------------------------------------
openeo:::demo_processes()

## -----------------------------------------------------------------------------
p = processes()

evi = function(data,context) {
  B08 = data[1]
  B04 = data[2]
  B02 = data[3]
  return((2.5 * (B08 - B04)) / sum(B08, 6 * B04, -7.5 * B02, 1))
}

## -----------------------------------------------------------------------------
as(evi,"Graph")

## ----eval=FALSE---------------------------------------------------------------
# library(sf)
# 
# p = processes()
# 
# bbox = st_bbox(c(xmin=16.1,
#                  xmax=16.6,
#                  ymax=48.6,
#                  ymin= 47.2), crs = 4326)
# 
# data = p$load_collection(id = "SENTINEL2_L2A_SENTINELHUB",
#                          spatial_extent = bbox,
#                          temporal_extent = list(
#                            "2018-04-01", "2018-05-01"
#                          ),
#                          bands=list("B08","B04","B02"))

## ----eval=FALSE---------------------------------------------------------------
# spectral_reduce = p$reduce_dimension(data = data, dimension = "bands",reducer = evi)

## ----eval=FALSE---------------------------------------------------------------
# temporal_reduce = p$reduce_dimension(data=spectral_reduce,dimension = "t", reducer = function(x,y){
#   min(x)
# })

## ----eval=FALSE---------------------------------------------------------------
# apply_linear_transform = p$apply(data=temporal_reduce,process = function(value,...) {
#   p$linear_scale_range(x = value,
#                            inputMin = -1,
#                            inputMax = 1,
#                            outputMin = 0,
#                            outputMax = 255)
# })

## ----eval=FALSE---------------------------------------------------------------
# result = p$save_result(data=apply_linear_transform,format="PNG")

## ----eval=FALSE---------------------------------------------------------------
# library(magrittr)
# 
# p = processes()
# 
# result2 = p$load_collection(id = "SENTINEL2_L2A_SENTINELHUB",
#                          spatial_extent = bbox,
#                          temporal_extent = list(
#                            "2018-04-01", "2018-05-01"
#                          ),
#                          bands=list("B08","B04","B02")) %>%
#   p$reduce_dimension(dimension = "bands",reducer = evi) %>%
#   p$reduce_dimension(dimension = "t", reducer = function(x,y){
#     min(x)
#   }) %>%
#   p$apply(process = function(value,...) {
#     p$linear_scale_range(x = value,
#                              inputMin = -1,
#                              inputMax = 1,
#                              outputMin = 0,
#                              outputMax = 255)
#   }) %>%
#   p$save_result(format="PNG")
# 

## ----paged.print=FALSE, eval=FALSE--------------------------------------------
# list_user_processes()

## ----eval=FALSE---------------------------------------------------------------
# validate_process(graph = evi)

## ----eval=FALSE---------------------------------------------------------------
# graph_id = create_user_process(graph = evi, id = "evi", summary = "EVI calculation on an array with 3 bands", description = "The EVI calculation is based on an array of 3 band values: blue, red, nir. In that order.")

## ----paged.print=FALSE, eval=FALSE--------------------------------------------
# list_user_processes()

## ----paged.print=FALSE, eval=FALSE--------------------------------------------
# evi_process = describe_user_process(id = "evi")
# class(evi_process)

## ----paged.print = FALSE, eval=FALSE------------------------------------------
# evi_process

## ----eval=FALSE---------------------------------------------------------------
# evi_graph = parse_graph(json = evi_process) # or use as(evi_process,"Graph")

## ----eval=FALSE---------------------------------------------------------------
# min_evi_graph_id = create_user_process( graph = result, id = "min_evi",summary="Minimum EVI calculation on Sentinel-2", description = "A preset process graph that will calculate the minimum NDVI on Sentinel-2 data, performs a linear scale into the value interval 0 to 255 in order to store the results as PNG.")

## ----paged.print = FALSE, eval=FALSE------------------------------------------
# list_user_processes()

## ----eval=FALSE---------------------------------------------------------------
# delete_user_process(id = min_evi_graph_id)

## ----eval=FALSE---------------------------------------------------------------
# p = processes()
# udps = user_processes()

## ----eval=FALSE---------------------------------------------------------------
# spectral_reduce$parameters$reducer = function(x,context) {
#   udps$evi(x)
# }
# 
# min_evi_graph = as(result,"Process")