Revision d183bd8b
Added by Benoit Parmentier about 10 years ago
| climate/research/oregon/interpolation/global_run_scalingup_assessment_part1.R | ||
|---|---|---|
| 18 | 18 |
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| 19 | 19 |
#First source file: |
| 20 | 20 |
#source /nobackupp4/aguzman4/climateLayers/sharedModules/etc/environ.sh |
| 21 |
#MODULEPATH=$MODULEPATH:/nex/modules/files |
|
| 22 |
#module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex |
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| 23 |
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| 21 | 24 |
################################################################################################# |
| 22 | 25 |
|
| 23 | 26 |
### Loading R library and packages |
| ... | ... | |
| 832 | 835 |
}else{
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| 833 | 836 |
list_days <- 1:365 #should check for year in case it has 366, add later!! |
| 834 | 837 |
} |
| 835 |
###Make this a function later?? |
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| 836 |
for (i in 1:nb_mod){
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| 837 |
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list_tif_files_dates <- lf_pred_tif[[i]] |
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| 839 | 838 |
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| 840 |
mosaic_list_var <- list_tif_files_dates |
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| 841 |
out_rastnames_var <- l_out_rastnames_var[[i]] |
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##Use python code written by Alberto Guzman |
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| 842 | 840 |
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file_format <- ".tif"
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NA_flag_val <- -9999
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system("MODULEPATH=$MODULEPATH:/nex/modules/files")
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system("module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex")
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j<-1 #date index for loop |
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| 847 |
list_param_mosaic<-list(j,mosaic_list_var,out_rastnames_var,out_dir,file_format,NA_flag_val) |
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names(list_param_mosaic)<-c("j","mosaic_list","out_rastnames","out_path","file_format","NA_flag_val")
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| 849 |
#list_var_mosaiced <- mclapply(1:2,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 2) |
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list_var_mosaiced <- mclapply(list_days,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 2) |
|
| 851 |
#list_var_mosaiced <- mclapply(1:1,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 1) |
|
| 852 |
#list_var_mosaiced <- mclapply(1:365,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 2) |
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#mosaic for delt sufaces? |
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#mosoaic for clim months? |
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} |
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###################### |
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### mosaic clim monthly data...this will be a function later... |
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#Now get the clim surfaces: |
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month_l <- paste("clim_month_",1:12,sep="")
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#l_pattern_models <- lapply(c("_mod1_0_1","_mod2_0_1","_mod3_0_1","_mod_kr_0_1"),
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# FUN=function(x){paste(x,"_",month_l,sep="")})
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out_prefix_s <- paste(name_method,c("_mod1_0_01","_mod2_0_01","_mod3_0_01","_mod_kr_0_1"),sep="")
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dates_l #list of predicted dates |
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#l_out_rastnames_var <- paste(name_method,"predicted_mod1_0_01_",dates_l,sep="") |
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| 870 |
l_out_rastnames_var <- lapply(out_prefix_s, |
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| 871 |
FUN=function(x){paste(x,"_",month_l,sep="")})
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for (i in 1:nb_mod){
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#this should be the input param for the new function generated automatically... |
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list_tif_files_dates <- lf_clim_tif[[i]] |
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mosaic_list_var <- list_tif_files_dates |
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out_rastnames_var <- l_out_rastnames_var[[i]] |
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#file_format <- ".tif" |
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#NA_flag_val <- -9999 |
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j<-1 #date index for loop |
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list_param_mosaic<-list(j,mosaic_list_var,out_rastnames_var,out_dir,file_format,NA_flag_val) |
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names(list_param_mosaic)<-c("j","mosaic_list","out_rastnames","out_path","file_format","NA_flag_val")
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| 885 |
#list_var_mosaiced <- mclapply(1:2,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 2) |
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list_var_mosaiced <- mclapply(1:12,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 4) |
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| 887 |
} |
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module_path <- "" |
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module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/" |
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in_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg2/" |
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out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg2/mosaics" |
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###################### |
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#### NOW create mosaic images for daily delta prediction |
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#This should be a function!!! |
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date_l# <- paste("clim_month_",1:12,sep="")
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#l_pattern_models <- lapply(c("_mod1_0_1.*","_mod2_0_1.*","_mod3_0_1.*","_mod_kr_0_1.*"),
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# FUN=function(x){paste("*.",month_l,x,".*.tif",sep="")})
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#l_pattern_models <- lapply(c(".*delta_dailyTmax_mod1_del_0_1.*",".*delta_dailyTmax_mod2_del_0_1.*",".*delta_dailyTmax_mod3_del_0_1.*",".*delta_dailyTmax_mod_kr_del_0_1.*"),
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# FUN=function(x){paste(x,dates_l,".*.tif",sep="")})
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out_prefix_s <- paste(name_method,c("delta_mod1_0_01","delta_mod2_0_01","delta_mod3_0_01","delta_mod_kr_0_1"),sep="")
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dates_l #list of predicted dates |
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#l_out_rastnames_var <- paste(name_method,"predicted_mod1_0_01_",dates_l,sep="") |
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l_out_rastnames_var <- lapply(out_prefix_s, |
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FUN=function(x){paste(x,"_",dates_l,sep="")})
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#nb_mod <- 4 #this is set up earlier |
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##Add option to specify wich dates to mosaic?? |
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day_to_mosaic <- c("20100101","20100901")
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if (!is.null(day_to_mosaic)){
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list_days <-match(day_to_mosaic,dates_l) |
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}else{
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list_days <- 1:365 #should check for year in case it has 366, add later!! |
|
| 911 |
} |
|
| 912 |
###Make this a function later?? |
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for (i in 1:nb_mod){
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| 915 |
list_tif_files_dates <- lf_pred_tif[[i]] |
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mosaic_list_var <- list_tif_files_dates |
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| 917 |
out_rastnames_var <- l_out_rastnames_var[[i]] |
|
| 918 |
#this is be set up earlier... |
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| 919 |
#file_format <- ".tif" |
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#NA_flag_val <- -9999 |
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| 921 |
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| 922 |
j<-1 #date index for loop |
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| 923 |
list_param_mosaic<-list(j,mosaic_list_var,out_rastnames_var,out_dir,file_format,NA_flag_val) |
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names(list_param_mosaic)<-c("j","mosaic_list","out_rastnames","out_path","file_format","NA_flag_val")
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| 925 |
#list_var_mosaiced <- mclapply(1:2,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 2) |
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list_var_mosaiced <- mclapply(list_days,FUN=mosaic_m_raster_list,list_param=list_param_mosaic,mc.preschedule=FALSE,mc.cores = 2) |
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| 927 |
} |
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l_dates <- "20100101,20100102" |
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cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),
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in_dir_mosaics, |
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out_dir_mosaics, |
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"--date", l_dates,sep=" ") |
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system(cmd_str) |
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### Now find out how many files were predicted |
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# will be useful later on |
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###################################################### |
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####### PART 3: EXAMINE STATIONS AND MODEL FITTING ### |
| ... | ... | |
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Atlas_dir <- file.path("/data/project/layers/commons/NEX_data/",basename(out_dir),"mosaics")
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| 1060 | 987 |
Atlas_hostname <- "parmentier@atlas.nceas.ucsb.edu" |
| 1061 |
lf_reg4 <- list.files(path=file.path(dirname(in_dir_list[[2]]),"mosaics"),full.names=T) |
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lf_reg5 <- list.files(path=file.path(dirname(in_dir_list[[20]]),"mosaics"),full.names=T) |
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#lf_reg4 <- list.files(path=file.path(dirname(in_dir_list[[2]]),"mosaics"),full.names=T) |
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#lf_reg5 <- list.files(path=file.path(dirname(in_dir_list[[20]]),"mosaics"),full.names=T) |
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lf_reg2 <- list.files(path=file.path("/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg2","mosaics"),
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full.names=T) |
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| 1063 | 992 |
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#lf_cp_mosaics <- c(lf_reg4,lf_reg5) |
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filenames_NEX <- paste(lf_cp_mosaics,collapse=" ") #copy raster prediction object |
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cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,Atlas_dir,sep=":"), sep=" ")
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system(cmd_str) |
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#filenames_NEX <- paste(lf_cp_mosaics,collapse=" ") #copy raster prediction object
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#cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,Atlas_dir,sep=":"), sep=" ")
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#system(cmd_str)
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#since they have the same name, must place them in separate dir... |
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filenames_NEX <- paste(lf_reg4,collapse=" ") #copy raster prediction object
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cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,file.path(Atlas_dir,"reg4"),sep=":"), sep=" ")
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filenames_NEX <- paste(lf_reg2,collapse=" ") #copy raster prediction object
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cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,file.path(Atlas_dir,"reg2"),sep=":"), sep=" ")
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system(cmd_str) |
| 1073 | 1002 |
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filenames_NEX <- paste(lf_reg5,collapse=" ") #copy raster prediction object |
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cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,file.path(Atlas_dir,"reg5"),sep=":"), sep=" ")
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| 1003 |
############# COPY FILES USED FOR DIFFERENCES OF IMAGES |
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#copy mosaics from other tiles of 1,500x4,500 |
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lf_reg4_1500x4500 <- list.files(path="/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg4_1500x4500/",full.names=T) |
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| 1008 |
lf_reg5_1500x4500 <- list.files(path="/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg5_1500x4500/",full.names=T) |
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lf_reg4_1000x3000 <- list.files(path="/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg4_1000x3000/",full.names=T) |
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lf_reg5_1000x3000 <- list.files(path="/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg5_1000x3000/",full.names=T) |
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| 1012 |
Atlas_dir <- file.path("/data/project/layers/commons/NEX_data/",basename(out_dir),"mosaics")
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Atlas_hostname <- "parmentier@atlas.nceas.ucsb.edu" |
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#lf_reg4 <- list.files(path=file.path(dirname(in_dir_list[[2]]),"mosaics"),full.names=T) |
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| 1016 |
#copy reg5_1000x3000 |
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| 1017 |
filenames_NEX <- paste(lf_reg5_1000x3000,collapse=" ") #copy raster prediction object |
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| 1018 |
cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,file.path(Atlas_dir,"reg5_1000x3000"),sep=":"), sep=" ")
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| 1019 |
system(cmd_str) |
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| 1021 |
#copy reg4_1000x3000 |
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| 1022 |
filenames_NEX <- paste(lf_reg4_1000x3000,collapse=" ") #copy raster prediction object |
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| 1023 |
cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,file.path(Atlas_dir,"reg4_1000x3000"),sep=":"), sep=" ")
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| 1024 |
system(cmd_str) |
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| 1026 |
#copy reg4_1500x4500 |
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| 1027 |
filenames_NEX <- paste(lf_reg4_1500x4500,collapse=" ") #copy raster prediction object |
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| 1028 |
cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,file.path(Atlas_dir,"reg4_1500x4500"),sep=":"), sep=" ")
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| 1029 |
system(cmd_str) |
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| 1031 |
#copy reg5_1500x4500 |
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| 1032 |
filenames_NEX <- paste(lf_reg5_1500x4500,collapse=" ") #copy raster prediction object |
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| 1033 |
cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,file.path(Atlas_dir,"reg5_1500x4500"),sep=":"), sep=" ")
|
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system(cmd_str) |
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| 1078 |
###Copy shapefiles in the separate directories? |
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| 1079 |
#lf_cp_shp <- list.files(in_dir_shp, ".shp",full.names=T) |
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| 1080 |
#list_tile_scp <- 1:6 |
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| 1081 |
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| 1082 |
#for (j in 1:length(list_tile_scp)){
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| 1083 |
# tile_nb <- list_tile_scp[j] |
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| 1084 |
# |
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| 1085 |
# in_dir_tile <-dirname(df_tile_processed$shp_files[tile_nb]) |
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| 1086 |
# #/data/project/layers/commons/NEX_data/output_run2_05122014/output |
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| 1087 |
# #output_atlas_dir |
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| 1088 |
# #Atlas_dir <- file.path(file.path("/data/project/layers/commons/NEX_data/",basename(out_dir),"output"),in_dir_tile)
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| 1089 |
# Atlas_dir <- file.path(output_atlas_dir,as.character(df_tile_processed$tile_coord[j]),"/shapefiles") |
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| 1090 |
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| 1091 |
# Atlas_hostname <- "parmentier@atlas.nceas.ucsb.edu" |
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| 1092 |
# |
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| 1093 |
# lf_cp_shp_pattern <- gsub(".shp","*",lf_cp_shp)
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| 1094 |
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| 1095 |
#filenames_NEX <- paste(lf_cp_shp,collapse=" ") #copy raster prediction object |
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| 1096 |
# filenames_NEX <- paste(lf_cp_shp_pattern,collapse=" ") #copy raster prediction object |
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| 1097 |
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| 1098 |
# cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,Atlas_dir,sep=":"), sep=" ")
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| 1099 |
# system(cmd_str) |
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| 1100 |
#} |
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| 1101 |
|
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| 1102 |
#### FIRST COPY DATA FOR SPECIFIC TILES ##### |
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| 1103 |
#Copy specific tiles info back...This assumes that the tree structre |
|
| 1104 |
#has been created on ATLAS: |
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| 1105 |
#../$out_dir/ouput/tile_coord |
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| 1106 |
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| 1107 |
#list_tile_scp <- c(1,2) |
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| 1108 |
list_tile_scp <- 1:6 |
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| 1109 |
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| 1110 |
for (j in 1:length(list_tile_scp)){
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| 1111 |
tile_nb <- list_tile_scp[j] |
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| 1112 |
#nb_mod <- 3+1 #set up earlier |
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| 1113 |
date_selected <- c("20100101","20100102","20100103","20100103","20100901","20100902","20100903") #should be set up earlier
|
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| 1114 |
date_index <- c(1,2,3,244,245,246) #list_day?? |
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| 1115 |
#tile_nb <- 1 |
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| 1116 |
|
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| 1117 |
in_dir_tile <- basename(df_tile_processed$path_NEX[tile_nb]) |
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| 1118 |
#/data/project/layers/commons/NEX_data/output_run2_05122014/output |
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| 1119 |
#output_atlas_dir |
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| 1120 |
#Atlas_dir <- file.path(file.path("/data/project/layers/commons/NEX_data/",basename(out_dir),"output"),in_dir_tile)
|
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| 1121 |
Atlas_dir <- file.path(output_atlas_dir,in_dir_tile) |
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| 1122 |
Atlas_hostname <- "parmentier@atlas.nceas.ucsb.edu" |
|
| 1123 |
#filenames_NEX <- list_raster_obj_files[tile_nb] #copy raster prediction object |
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| 1124 |
#cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,Atlas_dir,sep=":"), sep=" ")
|
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| 1125 |
#system(cmd_str) |
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| 1126 |
|
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| 1127 |
#Now copy back tif for specific dates and tile (date 1 and date 244) |
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| 1128 |
#nb_mod <- 3+1 |
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| 1129 |
lf_cp_day <- vector("list",length=length(date_selected))
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| 1130 |
#Get relevant daily info |
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| 1131 |
for(i in 1:length(date_selected)){
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| 1132 |
#d |
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| 1133 |
index <- date_index[i] |
|
| 1134 |
#get all predicted tmax files for all models and specific date, tile |
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| 1135 |
lf_cp_pred_tif <- unlist(lapply(1:nb_mod,FUN=function(x){lf_pred_tif[[x]][[index]][[tile_nb]]}))
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| 1136 |
lf_cp_delta_tif <- unlist(lapply(1:nb_mod,FUN=function(x){lf_delta_tif[[x]][[index]][[tile_nb]]}))
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| 1137 |
lf_cp_day[[i]] <- unlist(c(unlist(lf_cp_pred_tif),unlist(lf_cp_delta_tif))) |
|
| 1138 |
} |
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| 1139 |
#get the monthly info... |
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| 1140 |
month_index <- 1:12 #can subset |
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| 1141 |
#month_index <- c(1,9) #can subset |
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| 1142 |
lf_cp_month <- vector("list",length=length(month_index))
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| 1143 |
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| 1144 |
for(i in 1:length(month_index)){
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| 1145 |
#d |
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| 1146 |
index <- month_index[i] |
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| 1147 |
#get all predicted tmax files for all models and specific date, tile |
|
| 1148 |
lf_cp_month[[i]] <- unlist(lapply(1:nb_mod,FUN=function(x){lf_clim_tif[[x]][[index]][[tile_nb]]}))
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| 1149 |
} |
|
| 1150 |
##Add RData object for specified tile... |
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| 1151 |
lf_cp_RData_tif <- c(lf_covar_obj[tile_nb],lf_covar_tif[tile_nb],list_raster_obj_files[[tile_nb]],lf_diagnostic_obj[[tile_nb]]) |
|
| 1152 |
#unlist(lf_cp_RData_tif) |
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| 1153 |
lf_cp <- unlist(c(lf_cp_day,lf_cp_month,lf_cp_RData_tif)) |
|
| 1154 |
#lf_cp <- c(unlist(c(lf_cp_day,lf_cp_month)),list_raster_obj_files[tile_nb]) |
|
| 1155 |
filenames_NEX <- paste(lf_cp,collapse=" ") |
|
| 1156 |
#filenames_NEX <- paste(list_tif_files_dates[[1]][[6]],list_tif_files_dates[[244]][[6]],lf_covar_tif[6]) #to get first date and tile 6 prediction mod1 |
|
| 1157 |
cmd_str <- paste("scp -p",filenames_NEX,paste(Atlas_hostname,Atlas_dir,sep=":"), sep=" ")
|
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| 1158 |
system(cmd_str) |
|
| 1159 |
} |
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| 1160 | 1036 |
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| 1161 | 1037 |
##################### END OF SCRIPT ###################### |
| 1162 | 1038 |
|
| 1163 | 1039 |
|
| 1164 | 1040 |
###Mosaic ... |
| 1165 |
#MODULEPATH=$MODULEPATH:/nex/modules/files |
|
| 1166 |
#module load pythonkits/gdal_1.10.0_python_2.7.3_nex |
|
| 1041 |
#python mosaicUsingGdalMerge.py /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/ /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaics/ |
|
| 1042 |
#specify which month you want to process with the '-m' option. |
|
| 1043 |
#To do select dates you can use the '--date' option and use the format YYYYMMDD, |
|
| 1044 |
#can do multiple dates at a time by separating them with a comma. |
|
| 1045 |
|
|
| 1046 |
#python mosaicUsingGdalMerge.py /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/ /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaics/ --date 20100101,20100102,20100103,20100104 |
|
| 1047 |
#python /nobackupp6/aguzman4/climateLayers/sharedCode/mosaicUsingGdalMerge.py /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg2/ /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg2/mosaics/ --date 20100101,20100102,20100103,20100104 |
|
| 1048 |
#python /nobackupp6/aguzman4/climateLayers/sharedCode/mosaicUsingGdalMerge.py /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg2/ /nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg2/mosaics/ --m 1" |
|
| 1049 |
|
|
| 1050 |
# cmd_str <- paste("python", module_path,"mosaicUsingGdalMerge.py",
|
|
| 1051 |
# "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/" |
|
| 1052 |
# "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaics/" |
|
| 1053 |
# "--date 20100101,20100102,20100103,20100104",sep=" ") |
|
| 1054 |
# cmd_str <- paste("python", module_path,"mosaicUsingGdalMerge.py",
|
|
| 1055 |
# "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/" |
|
| 1056 |
# "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaics/" |
|
| 1057 |
# "--date 20100101,20100102,20100103,20100104",sep=" ") |
|
| 1058 |
# |
|
| 1059 |
# system("MODULEPATH=$MODULEPATH:/nex/modules/files")
|
|
| 1060 |
# system("module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex")
|
|
| 1061 |
# |
|
| 1062 |
# module_path <- "" |
|
| 1063 |
#module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/" |
|
| 1064 |
#in_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/reg5/" |
|
| 1065 |
#out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/reg5/mosaics" |
|
| 1066 |
#l_dates <- "20100101,20100102,20100103,20100104,20100901,20100902,20100903,20100904" |
|
| 1067 |
#cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),
|
|
| 1068 |
# in_dir_mosaics, |
|
| 1069 |
# out_dir_mosaics, |
|
| 1070 |
# "--date", l_dates,sep=" ") |
|
| 1071 |
#system(cmd_str) |
|
| 1072 |
|
|
| 1073 |
#module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/" |
|
| 1074 |
#in_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/reg4/" |
|
| 1075 |
#out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/reg4/mosaics" |
|
| 1076 |
#l_dates <- "20100101,20100102,20100103,20100104,20100901,20100902,20100903,20100904" |
|
| 1077 |
#cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),
|
|
| 1078 |
# in_dir_mosaics, |
|
| 1079 |
# out_dir_mosaics, |
|
| 1080 |
# "--date", l_dates,sep=" ") |
|
| 1081 |
|
|
| 1082 |
system("MODULEPATH=$MODULEPATH:/nex/modules/files")
|
|
| 1083 |
system("module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex")
|
|
| 1084 |
|
|
| 1085 |
module_path <- "" |
|
| 1086 |
module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/" |
|
| 1087 |
in_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg4/" |
|
| 1088 |
out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg4/mosaicsMean" |
|
| 1089 |
out_dir_mosaics <- "/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg4_1000x3000" |
|
| 1090 |
#/nobackup/bparmen1//output_run10_global_analyses_12152014 |
|
| 1091 |
prefix_str <- "reg4_1000x300" |
|
| 1092 |
|
|
| 1093 |
#l_dates <- "20100101,20100102" |
|
| 1094 |
l_dates <- "20100101,20100102,20100103,20100104,20100301,20100501,20100701,20100901,20100902,20100903,20100904" |
|
| 1095 |
cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),
|
|
| 1096 |
in_dir_mosaics, |
|
| 1097 |
out_dir_mosaics, |
|
| 1098 |
prefix_str, |
|
| 1099 |
"--date", l_dates,sep=" ") |
|
| 1100 |
system(cmd_str) |
|
| 1101 |
|
|
| 1102 |
#reg5 100x3000 |
|
| 1103 |
|
|
| 1104 |
system("MODULEPATH=$MODULEPATH:/nex/modules/files")
|
|
| 1105 |
system("module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex")
|
|
| 1106 |
|
|
| 1107 |
module_path <- "" |
|
| 1108 |
module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/" |
|
| 1109 |
in_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/" |
|
| 1110 |
#out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaicsMean" |
|
| 1111 |
out_dir_mosaics <- "/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg5_1000x3000" |
|
| 1112 |
#/nobackup/bparmen1//output_run10_global_analyses_12152014 |
|
| 1113 |
prefix_str <- "reg5_1000x300" |
|
| 1114 |
|
|
| 1115 |
#l_dates <- "20100101,20100102" |
|
| 1116 |
l_dates <- "20100101,20100102,20100103,20100104,20100301,20100501,20100701,20100901,20100902,20100903,20100904" |
|
| 1117 |
cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),
|
|
| 1118 |
in_dir_mosaics, |
|
| 1119 |
out_dir_mosaics, |
|
| 1120 |
prefix_str, |
|
| 1121 |
"--date", l_dates,sep=" ") |
|
| 1122 |
system(cmd_str) |
|
| 1123 |
|
|
| 1124 |
#reg5 1500x4500 |
|
| 1125 |
|
|
| 1126 |
#system("MODULEPATH=$MODULEPATH:/nex/modules/files")
|
|
| 1127 |
#system("module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex")
|
|
| 1128 |
|
|
| 1129 |
module_path <- "" |
|
| 1130 |
module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/" |
|
| 1131 |
in_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/reg5/" |
|
| 1132 |
#out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaicsMean" |
|
| 1133 |
out_dir_mosaics <- "/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg5_1500x4500" |
|
| 1134 |
#/nobackup/bparmen1//output_run10_global_analyses_12152014 |
|
| 1135 |
prefix_str <- "reg5_1500x4500" |
|
| 1136 |
|
|
| 1137 |
#l_dates <- "20100101,20100102" |
|
| 1138 |
l_dates <- "20100101,20100102,20100103,20100104,20100301,20100501,20100701,20100901,20100902,20100903,20100904" |
|
| 1139 |
cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),
|
|
| 1140 |
in_dir_mosaics, |
|
| 1141 |
out_dir_mosaics, |
|
| 1142 |
prefix_str, |
|
| 1143 |
"--date", l_dates,sep=" ") |
|
| 1144 |
system(cmd_str) |
|
| 1167 | 1145 |
|
| 1146 |
##### |
|
| 1147 |
#reg4 1500x4500: NEED TO USE MOD2!!! in this specific case... |
|
| 1148 |
|
|
| 1149 |
#system("MODULEPATH=$MODULEPATH:/nex/modules/files")
|
|
| 1150 |
#system("module load /nex/modules/files/pythonkits/gdal_1.10.0_python_2.7.3_nex")
|
|
| 1151 |
|
|
| 1152 |
module_path <- "" |
|
| 1153 |
module_path <- "/nobackupp6/aguzman4/climateLayers/sharedCode/" |
|
| 1154 |
in_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1500x4500_km/reg4/" |
|
| 1155 |
#out_dir_mosaics <- "/nobackupp6/aguzman4/climateLayers/output1000x3000_km/reg5/mosaicsMean" |
|
| 1156 |
out_dir_mosaics <- "/nobackup/bparmen1//output_run10_global_analyses_12152014/mosaics/reg4_1500x4500" |
|
| 1157 |
#/nobackup/bparmen1//output_run10_global_analyses_12152014 |
|
| 1158 |
prefix_str <- "reg4_1500x4500" |
|
| 1159 |
mod_str <- "mod2" #use mod2 which corresponds to model with LST and elev |
|
| 1160 |
|
|
| 1161 |
#l_dates <- "20100101,20100102" |
|
| 1162 |
l_dates <- "20100101,20100102,20100103,20100104,20100301,20100501,20100701,20100901,20100902,20100903,20100904" |
|
| 1163 |
cmd_str <- paste("python", file.path(module_path,"mosaicUsingGdalMerge.py"),
|
|
| 1164 |
in_dir_mosaics, |
|
| 1165 |
out_dir_mosaics, |
|
| 1166 |
prefix_str, |
|
| 1167 |
"--mods", mod_str, |
|
| 1168 |
"--date", l_dates,sep=" ") |
|
| 1169 |
system(cmd_str) |
|
| 1168 | 1170 |
|
| 1171 |
###copy folder in mosaics... |
|
Also available in: Unified diff
run 10 NEX assessement generation of mosaics images and automated copy back to server