extracted climate data

.Rhistory

+install.packages("remotes")
+remotes::install_github("jalvesaq/colorout")
+??inout
+install.packages("splancs")
+?reclass
+?breaks
+?break
+?addPolygons
+library(leaflet)
+?addPolygons
+?colorBins
+?colorBin
+?addLegend
+library(sf)
+install.packages("sf")
+library(sf)
+?sf_interset
+?sf_intersect
+?intersect
+?st_intersection
+install.packages("rgeos")
+library(rgeos)
+?gIntersect
+?gOverlap
+?gOverlaps
+?pairs
+install.packages("queyras")
+shiny::runApp('PROJETS/SOCBIO_Yves/ASONB/gitlab-folder/exploHumanImpactData')
+?write.csv
+library(FD)
+?divc
+install.pacakges("rgdal")
+install.packages("rgdal")
+library(rgdal)
+install.packages("adespatial")
+library(adespatial)
+library(adespatial)
+library(sf)
+setwd("~/Documents/PROJETS/HISTFUNC/H3")
+library(remake)
+remake::make("herbivores")
+remake::make("herbivores")
+?pairs
+?extract
+install.packages("tidyverse")
+shiny::runApp('~/Documents/PROJETS/SOCBIO_Yves/ASONB/gitlab-folder/exploHumanImpactData')
+install.packages("PostgreSQL")
+install.packages("RPostgres")
+install.packages("rpostgis")
+install.packages("RPostgreSQL")
+sapply(list.files("R_fct"), function(x)source(paste0("R_fct/",x)))
+setwd("~/Documents/PROJETS/ZAA/AS/git_as_biomass")
+sapply(list.files("R_fct"), function(x)source(paste0("R_fct/",x)))
+require(RPostgreSQL)
+data = readRDS("data.rds")
+head(data$sites)
+dat_h_veg = merge(data$h, data$sites[,c("id_site", "ref_typoveg")], by.x = "ref_site", by.y ="id_site")
+str(dat_h_veg)
+summary(dat_h_veg$hmean)
+library(dplyr)
+# library(reshape)
+library(tidyr)
+library(ggplot2)
+dat_long <- dat_h_veg %>%
+select(hmean, hmad, ref_typoveg) %>%
+drop_na() %>%
+group_by(ref_typoveg) %>%
+summarize(hauteur=mean(hmean), var_inter=mad(hmean), var_intra = mean(hmad)) %>%
+gather(stat, value, hauteur:var_intra)
+ggplot(dat_long, aes(fill=stat, x=ref_typoveg, y=value)) +
+geom_bar(position = "dodge", stat = "identity") +
+facet_wrap(~stat, ncol = 1, scales = "free")
+head(dat_long)
+head(dat_h_veg)
+pl <- ggplot(dat_h_veg, aes(x = date_releve, y = hmean)) +
+geom_line(aes(color = ref_site), show.legend = FALSE) +
+facet_wrap(~ref_typoveg)
+pl + theme(legend.position = "none")
+head(dat_h_veg)
+ggplot(dat_h_veg, aes(x = ref_typoveg, y = hmean)) +
+geom_boxplot(stat = "identidy")
+ggplot(dat_h_veg, aes(x = ref_typoveg, y = hmean)) +
+geom_boxplot(stat = "identity")
+ggplot(dat_h_veg, aes(x = ref_typoveg, y = hmean)) +
+geom_boxplot()
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmean), y = hmean)) +
+geom_boxplot()
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmean, na.rm=TRUE), y = hmean)) +
+geom_boxplot()
+summary(dat_h_veg)
+dat_h_veg[which(is.na(dat_h_veg$hmad)),]
+dat_h_veg[which(is.na(dat_h_veg$hmad)),"ref_site"]
+unique(dat_h_veg[which(is.na(dat_h_veg$hmad)),"ref_site"])
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmean, na.rm=TRUE), y = hmean)) +
+geom_boxplot() +
+labs(y="Hauteur moyenne (est. biomasse)", x="Type vegetation",
+labs(y="Hauteur moyenne (est. biomasse)", x="Type vegetation")
+labs(y="Hauteur moyenne (est. biomasse)", x="Type vegetation")
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmean, na.rm=TRUE), y = hmean)) +
+geom_boxplot() +
+labs(y="Hauteur moyenne (est. biomasse)", x="Type vegetation")
+head(data)
+head(data$h)
+head(data$sites)
+tail(data$h)
+summary(data$h$hmean)
+data$h$ref_releve[which(is.na(data$h$hmean))]
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hsd, na.rm=TRUE), y = hsd)) +
+geom_boxplot() +
+labs(y="Hétérogénéité", x="Type vegetation")
+summary(data_h_veg$ref_typoveg)
+summary(dat_h_veg$ref_typoveg)
+table(dat_h_veg$ref_typoveg)
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hsd, na.rm=TRUE), y = hsd)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur", x="Type vegetation")
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hsd, na.rm=TRUE), y = hsd/hmean)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur", x="Type vegetation")
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad/hmean, na.rm=TRUE), y = hsd)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur", x="Type vegetation")
+ggplot(dat_h_veg, aes(x = hmad, y = hsd)) +
+geom_points()
+ggplot(dat_h_veg, aes(x = hmad, y = hsd)) +
+geom_point()
+ggplot(dat_h_veg, aes(x = date_releve, y = hsd)) +
+geom_line(aes(color = ref_site), show.legend = FALSE) +
+facet_wrap(~ref_typoveg)
+ggplot(dat_h_veg, aes(x = date_releve, y = hmad)) +
+geom_line(aes(color = ref_site), show.legend = FALSE) +
+facet_wrap(~ref_typoveg)
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad, na.rm=TRUE), y = hmad)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur", x="Type vegetation")
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad/hmean, na.rm=TRUE), y = hmad/hmean)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur", x="Type vegetation")
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad/hmean, na.rm=TRUE), y = hmad/hmean)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur (stand. moy.)", x="Type vegetation")
+head(dat_h_veg)
+head(dat_h_veg)
+dat_h_veg[which(dat_h_veg$ref_site=="BELRIV01"),]
+sapply(dat_h_veg$ref_releve, function(x){
+paste(strplit(x, "_")[-2])
+})
+sapply(dat_h_veg$ref_releve, function(x){
+paste(strsplit(x, "_")[-2])
+})
+sapply(dat_h_veg$ref_releve, function(x){
+paste(unlist(strsplit(x, "_")[-2]))
+})
+sapply(dat_h_veg$ref_releve, function(x){
+paste(unlist(strsplit(x, "_"))[-2])
+})
+lapply(dat_h_veg$ref_releve, function(x){
+paste(unlist(strsplit(x, "_"))[-2])
+})
+unlist(lapply(dat_h_veg$ref_releve, function(x){
+paste(unlist(strsplit(x, "_"))[-2], sep="_")
+}))
+sapply(dat_h_veg$ref_releve, function(x){
+paste(unlist(strsplit(x, "_"))[-2], sep="_")
+})
+x = dat_h_veg$ref_releve[1]
+strsplit(x, "_")
+strsplit(x, "_")[-2]
+strsplit(x, "_")[[1]][-2]
+sapply(dat_h_veg$ref_releve, function(x){
+paste(strsplit(x, "_")[[1]][-2], sep="_")
+})
+lapply(dat_h_veg$ref_releve, function(x){
+paste(strsplit(x, "_")[[1]][-2], sep="_")
+})
+x
+strsplit(x, "_")[[1]][-2]
+paste(strsplit(x, "_")[[1]][-2], sep="_")
+paste(strsplit(x, "_")[[1]][-2], sep="_", collapse = TRUE)
+x1 = strsplit(x, "_")[[1]][-2]
+paste(x1, sep="_")
+x1
+paste(x1, collapse="_")
+x1 =
+paste(strsplit(x, "_")[[1]][-2], collapse="_")
+x1 =
+paste(strsplit(x, "_")[[1]][-2], collapse="_")
+paste(strsplit(x, "_")[[1]][-2], collapse="_")
+lapply(dat_h_veg$ref_releve, function(x){
+paste(strsplit(x, "_")[[1]][-2], collapse="_")
+})
+dat_h_veg$releveL1L2 =
+unlist(lapply(dat_h_veg$ref_releve, function(x){
+paste(strsplit(x, "_")[[1]][-2], collapse="_")
+}))
+head(dat_h_veg)
+data = readRDS("data.rds")
+#==============================
+## dataframe ##
+#===============================
+head(data$sites)
+head(data$h)
+dat_h_veg = merge(data$h, data$sites[,c("id_site", "ref_typoveg")], by.x = "ref_site", by.y ="id_site")
+str(dat_h_veg)
+data = readRDS("data.rds")
+#==============================
+## dataframe ##
+#===============================
+head(data$sites)
+head(data$h)
+data = readRDS("data.rds")
+#==============================
+## dataframe ##
+#===============================
+head(data$sites)
+head(data$h)
+dat_h_veg = merge(data$h, data$sites[,c("id_site", "ref_typoveg")], by.x = "ref_site", by.y ="id_site")
+str(dat_h_veg)
+summary(dat_h_veg$hmean)
+dat_h_veg = unique(merge(data$h, data$sites[,c("id_site", "ref_typoveg")], by.x = "ref_site", by.y ="id_site"))
+length(unique(dat_h_veg$releve))
+dim(dat_h_veg)
+summary(dat_h_veg$hmean)
+head(data$otable)
+data$otable[which(is.na(data$otable$hauteur)),]
+summary(dat_h_veg$hmean)
+dat_long <- dat_h_veg %>%
+select(hmean, hmad, ref_typoveg) %>%
+drop_na() %>%
+group_by(ref_typoveg) %>%
+summarize(hauteur=mean(hmean), var_inter=mad(hmean), var_intra = mean(hmad)) %>%
+gather(stat, value, hauteur:var_intra)
+ggplot(dat_long, aes(fill=stat, x=ref_typoveg, y=value)) +
+geom_bar(position = "dodge", stat = "identity") +
+facet_wrap(~stat, ncol = 1, scales = "free")
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmean, na.rm=TRUE), y = hmean)) +
+geom_boxplot() +
+labs(y="Hauteur moyenne (est. biomasse)", x="Type vegetation")
+pl <- ggplot(dat_h_veg, aes(x = date_releve, y = hmean)) +
+geom_line(aes(color = ref_site), show.legend = FALSE) +
+facet_wrap(~ref_typoveg)
+pl + theme(legend.position = "none")
+head(dat_h_veg)
+#==============================
+## effet obs                ##
+#===============================
+dat_h_veg[which(is.duplicated(dat_h_releve)),]
+#==============================
+## effet obs                ##
+#===============================
+dat_h_veg[which(is.duplicated(dat_h_veg$releve)),]
+?is.duplicated
+??is.duplicated
+#==============================
+## effet obs                ##
+#===============================
+dat_h_veg[which(duplicated(dat_h_veg$releve)),]
+duplicated(dat_h_veg$releve
+duplicated(dat_h_veg$releve)
+duplicated(dat_h_veg$releve)
+### sd vs mad
+ggplot(dat_h_veg, aes(x = hmad, y = hsd)) +
+geom_point()
+### dans le temps
+ggplot(dat_h_veg, aes(x = date_releve, y = hmad)) +
+geom_line(aes(color = ref_site), show.legend = FALSE) +
+facet_wrap(~ref_typoveg)
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad, na.rm=TRUE), y = hmad)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur", x="Type vegetation")
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmad/hmean, na.rm=TRUE), y = hmad/hmean)) +
+geom_boxplot() +
+labs(y="Variation intra de hauteur (stand. moy.)", x="Type vegetation")
+calage = read.csv("../PNE_calage_reformat.csv")
+calage = read.csv("../PNE_calage_reformat.csv")
+head(calage)
+calage = read.csv("../PNE_calage_reformat.csv", sep= ";")
+head(calage)
+str(calage)
+calage %>% group_by(site) %>% summarize(hmean = mean(hauteur))
+str(calage)
+calage = read.csv("../PNE_calage_reformat.csv", sep= ";", dec = ",")
+str(calage)
+calage %>% group_by(site) %>% summarize(hmean = mean(hauteur))
+calage %>% group_by(site) %>% summarize(hmean = mean(hauteur, na.rm=TRUE))
+cal_mean = calage %>% group_by(site) %>% summarize(hmean = mean(hauteur, na.rm=TRUE))
+ggplot(cal_mean, aes(x = site, y = hmean)) +
+geom_boxplot()
+ggplot(cal_mean, aes(x = site, y = hmean)) +
+geom_point()
+head(calage)
+calage$releve = paste0(calage$site, calage$Releveur)
+cal_mean = calage %>% group_by(releve) %>% summarize(hmean = mean(hauteur, na.rm=TRUE))
+ggplot(cal_mean, aes(x = site, y = hmean)) +
+geom_point()
+ggplot(cal_mean, aes(x = releve, y = hmean)) +
+geom_point()
+ggplot(cal_mean, aes(x = releve, y = hmean)) +
+geom_point() +
+geom_boxplot()
+ggplot(cal_mean, aes(x = releve, y = hmean)) +
+geom_point()
+cal_mean
+cal_mean = calage %>% group_by(releve) %>% summarize(site = site, hmean = mean(hauteur, na.rm=TRUE))
+cal_mean
+ggplot(cal_mean, aes(x = site, y = hmean)) +
+geom_point() +
+geom_boxplot()
+ggplot(cal_mean, aes(x = site, y = hmean)) +
+geom_boxplot() +
+geom_point()
+cal_mean
+cal_mean %>% group_by(site) %>% summarize(hmad = hmad(hmean))
+cal_mean %>% group_by(site)
+calage %>% group_by(releve)
+cal_mean = unique(calage %>% group_by(releve) %>% summarize(site = site, hmean = mean(hauteur, na.rm=TRUE)))
+ggplot(cal_mean, aes(x = site, y = hmean)) +
+geom_boxplot() +
+geom_point()
+cal_mean %>% group_by(site)
+cal_mean %>% group_by(site) %>% summarize(hmad = hmad(hmean))
+cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean))
+cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean)/mean(hmean))
+cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean), hmad_st = mad(hmean)/mean(hmean))
+cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean), hmad_st = mad(hmean)/mean(hmean))
+ggplot(cal_mean, aes(x = reorder(site, hmean), y = hmean)) +
+geom_boxplot() +
+geom_point()
+cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean), hmad_st = mad(hmean)/mean(hmean))
+obs_error = cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean), hmad_st = mad(hmean)/mean(hmean))
+ggplot(obs_error, aes(x = site, y = hmad_st)) +
+geom_bar()
+ggplot(obs_error, aes(x = site, y = hmad_st)) +
+geom_bar(stat = "identity")
+obs_error = cal_mean %>% group_by(site) %>% summarize(hmad = mad(hmean), hmad_st = mad(hmean)/mean(hmean), hm = mean(hmean))
+ggplot(obs_error, aes(x = reorder(site, hm), y = hmad_st)) +
+geom_bar(stat = "identity")
+ggplot(cal_mean, aes(x = reorder(site, hmean), y = hmean)) +
+geom_boxplot() +
+geom_point()
+ggplot(obs_error, aes(x = reorder(site, hm), y = hmad_st)) +
+geom_bar(stat = "identity")
+ggplot(cal_mean, aes(x = reorder(site, hmean), y = hmean)) +
+geom_boxplot() +
+geom_point()
+ggplot(dat_h_veg, aes(x = reorder(ref_typoveg, hmean, na.rm=TRUE), y = hmean)) +
+geom_boxplot() +
+labs(y="Hauteur moyenne (est. biomasse)", x="Type vegetation")
+head(dat_h_veg)
+table(ref_typoveg)
+table(dat_h_veg$ref_typoveg)
+dat_h_veg[which(dat_h_veg$ref_typoveg=="EBOU"),]
+dat_h_veg[which(dat_h_veg$ref_typoveg=="HUM"),]
+head(cal_mean)
+cal_mean

.gitignore

+_DATA/*

R_fct/extract_meteo_data_fct.r

+extract_ncdat <- function(path, variables, NoPs){
+  nc.read = nc_open(path)
+  time<-ncvar_get(nc.read,"time")
+  tunits<-ncatt_get(nc.read,"time",attname="units")
+  tustr<-strsplit(tunits$value, " ")
+  dates<-as.Date(time,origin=unlist(tustr)[3])
+  nc.data = lapply(variables, function(x) ncvar_get(nc.read,x)[unique(NoPs),])
+  nc_close(nc.read)
+  return(list(data = abind(nc.data, along = 3), dates = dates))
+}
+
+
+calc_meteo_variables <- function(path_data_allslopes, year, days, NoPs, periods, tbase = 5.5){
+  # year = as.numeric(test$year[1])
+  # days = test$date_releve
+  # NoPs = test$NoP
+  variables = c("RN_ISBA", "TS_ISBA", "WSN_T_ISBA", "DSN_T_ISBA", "RAINF_ISBA", "TALB_ISBA")
+  # periods = c(30,60)
+
+  # library required
+  require(tidync)
+  require(ncmeta)
+  require(tidyr)
+  require(ncdf4)
+  require(ncdf4.helpers)
+  require(abind)
+
+  # check filepath dataset
+  if(!(length(list.files(path_data_allslopes)) > 0) ) stop("not able to connect to data path or empty path")
+
+  dat1 = extract_ncdat(paste0(path_data_allslopes, "/reanalysis/pro/PRO_",as.character(year),"080106_",as.character(year+1),"080106.nc"), variables, NoPs)
+  dat2 = extract_ncdat(paste0(path_data_allslopes, "/reanalysis/pro/PRO_",as.character(year-1),"080106_",as.character(year),"080106.nc"), variables, NoPs)
+
+  datAll = abind(dat2$data, dat1$data, along = 2)
+  datesAll = c(dat2$dates, dat1$dates)
+
+  output = array(data = NA, dim = list(length(days),8, length(periods)), dimnames = list(1:length(days), c("snowfree", "cumgdd", "frost", "gddspeed", "rainfall", "radiations", "albedo", "snowstock"), periods))
+
+  # releves loop
+  for (rel in 1:length(days)) {
+    # rel = 1
+    nop = which(NoPs[rel]%in%unique(NoPs))
+    d = which(days[rel]==datesAll)
+
+    for (p in 1:length(periods)){
+      # p = 1
+      temp = datAll[nop,(d-periods[p]):d, which(variables == "TS_ISBA")]-273.15
+      snow = datAll[nop,(d-periods[p]):d, which(variables == "DSN_T_ISBA")]
+      snowfree = snow==0
+      gdd = (temp - tbase)
+      gdd[gdd<0]=0
+
+      #### snowfree
+      output[rel, "snowfree", p] = sum(snowfree)
+      #### cumgdd (snowfree)
+      output[rel, "cumgdd", p] = sum(gdd[snowfree])
+      #### snowfreefrost
+      output[rel, "frost", p] =  sum(which(temp<0 & snowfree))
+      #### gddspeed
+      output[rel, "gddspeed", p] = mean(gdd[gdd>0])
+      #### rainfall
+      output[rel, "rainfall", p] = sum(datAll[nop,(d-periods[p]):d, which(variables == "RAINF_ISBA")])
+      #### radiations
+      output[rel, "radiations", p] = sum(datAll[nop,(d-periods[p]):d, which(variables == "RN_ISBA")])
+      #### albedo
+      output[rel, "albedo", p] = sum(datAll[nop,(d-periods[p]):d, which(variables == "TABL_ISBA")])
+      #### snowstock
+      output[rel, "snowstock", p] = max(datAll[nop,(d-periods[p]):d, which(variables == "WSN_T_ISBA")])
+
+
+    }
+  }
+
+
+  return(output)
+
+}
+
+
+#=============================================
+#--- build NoP raster functions
+#=============================================
+NoP_from_values <- function(x, safran_classes_complet, alti_field="ZS", slope_field="slope", aspect_field="aspect", massif_field="massif_num"){
+    num_point = safran_classes_complet[which(((safran_classes_complet[,alti_field] == x[alti_field] & safran_classes_complet[,slope_field] == x[slope_field]) & safran_classes_complet[,aspect_field]==x[aspect_field]) & safran_classes_complet[,massif_field]==x[massif_field]), "Number_of_points"]
+    if(length(num_point)==0) num_point=9999
+    return(num_point)
+}
+
+
+NoP_from_rasters <- function(r_alti, r_slope, r_aspect, r_massif, safran_classes_complet, parallel=FALSE, nclust=2){
+  if(resolution(r_alti)!=resolution(r_slope) || resolution(r_alti)!=resolution(r_aspect) || resolution(r_alti)!=resolution(r_massif)) stop("pb resolution")
+  if(projection(r_alti)!=projection(r_slope) || projection(r_alti)!=projection(r_aspect) || projection(r_alti)!=projection(r_aspect)) stop("pb proj")
+
+  crocus_alti <- cut(r_alti, breaks = seq(0, 5200, by = 300) , include.lowest = TRUE)
+  crocus_aspect <- cut(r_aspect, breaks = c(-1,seq(0, 360, by = 45)) , include.lowest = TRUE)
+  crocus_slope <- cut(r_slope, breaks = c(0, 10, 30, 90) , include.lowest = TRUE)
+
+  crocus_stack <- stack(crocus_alti, crocus_slope, crocus_aspect, crocus_massif_raster)
+  names(crocus_stack) <- c("altitude", "slope", "aspect", "massif")
+
+  corresp <- function(x, na.rm){
+    if(sum(is.na(x))==0){
+      num_point = safran_classes_complet[which(((sf4$cat_raster_alti == x[1] & safran_classes_complet$cat_raster_aspect == x[3]) & safran_classes_complet$cat_raster_slope==x[2]) & safran_classes_complet$massif_num==x[4]), "Number_of_points"]
+      }else num_point=NA
+      if(length(num_point)==0) num_point=9999
+      return(num_point)
+    }
+
+    if(parallel==TRUE){
+      library(doParallel)
+      beginCluster(n=nclust, type="SOCK")
+      cl = getCluster()
+      clusterExport(cl, "safran_classes_complet", envir=environment())
+      NoP = clusterR(crocus_stack, stackApply, args = list(indices=rep(1, 4), fun = corresp, na.rm=TRUE))
+      endCluster()
+
+      }else{
+        NoP <- stackApply(crocus_stack, indices=rep(1, 4),fun = corresp, na.rm=TRUE)
+
+      }
+
+
+      return(NoP)
+
+    }

meteo_data.r

-library(tidync)
-library(ncmeta)
-library(tidyr)
-library(raster)
-library(sp)
-#=============================================
-#--- Data input
-#=============================================
-
-sites <- readRDS("data_sites.rds
-sites <- sites[which(!is.na(sites$x)),]
-coordinates(sites)= cbind(sites$y, sites$x)
-proj4string(sites) = CRS("+proj=lcc +lat_1=49 +lat_2=44 +lat_0=46.5 +lon_0=3 +x_0=700000 +y_0=6600000 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs")
-
-
-NoP_raster = raster()
-
-plot(NoP_raster)
-points(sites)
-
-spTransform()
-
-extract()
-
-# path_data_allslopes = "/Volumes/infogeo/Meteo_France/SAFRAN_montagne-CROCUS_2019/alp_allslopes"
-path_data_allslopes = "/Volumes/ISA-RESEARCH/alp_allslopes"
-safran_classes <- read.table("safran_classes.txt", h=T, sep="\t")
-
-#=============================================
-#--- Extract function
-#=============================================
-# list of variables:
-# 
-extract_meteo <- function(path_data_allslopes, years, variables, NoP){
-
-  # library required
-  require(tidync)
-  require(ncmeta)
-  require(tidyr)
-
-  # check filepath dataset
-  if(!(length(list.files(path_data_allslopes)) > 0) ) stop("not able to connect to data path or empty path")
-
-  # temporal loop
-
-  for (y in years){
-    # read data and stock for a year y
-
-    pro_file = paste0(path_data_allslopes, "/reanalysis/pro/PRO_",as.character(y),"080106_",as.character(y+1),"080106.nc")
-
-    src <- tidync(pro_file)
-
-    data_y <- src %>% activate("D0,D3") %>% hyper_filter(Number_of_points = Number_of_points %in% NoP) %>% hyper_tibble(select_var = variables)
-
-    # TODO: compute values from data_y
-
-  }
-
-
- # build output
- # TODO!!
-
-  return(output)
-
-}

workflow2_climate.r

+
+#=============================================
+#--- Sites, extration NoP_raster
+# inputs: sites, NoP_raster
+# outputs: NoP for each site
+#=============================================
+library(tidyr)
+library(raster)
+library(sp)
+
+sites <- readRDS("data_sites.rds")
+head(sites)
+summary(sites$x)
+
+sites1 <- sites[which(sites$x<10),]
+coordinates(sites1)= c("x","y")
+proj4string(sites1) = CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")
+
+sites2 <- sites[which(sites$x>10),]
+coordinates(sites2)= c("x","y")