Revision 0488d027
Added by Benoit Parmentier over 9 years ago
| climate/research/oregon/interpolation/global_run_scalingup_assessment_part2.R | ||
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#Analyses, figures, tables and data are also produced in the script. |
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#AUTHOR: Benoit Parmentier |
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#CREATED ON: 03/23/2014 |
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#MODIFIED ON: 05/26/2015
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#MODIFIED ON: 07/30/2015
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#Version: 4 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: analyses for run 10 global analyses,all regions 1500x4500km with additional tiles to increase overlap |
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interpolation_method <- c("gam_CAI") #PARAM2
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#out_suffix<-"run10_global_analyses_01282015" |
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#out_suffix <- "output_run10_1000x3000_global_analyses_02102015" |
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out_suffix <- "run10_1500x4500_global_analyses_pred_2010_05262015" #PARAM3
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out_dir <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_2010_05262015" #PARAM4
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out_suffix <- "run10_1500x4500_global_analyses_pred_2010_testelev_07302015" #PARAM3
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out_dir <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_2010_testelev_07302015" #PARAM4
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create_out_dir_param <- FALSE #PARAM 5 |
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mosaic_plot <- FALSE #PARAM6 |
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NA_flag_val <- NA_value |
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tile_size <- "1500x4500" #PARAM 11 |
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mulitple_region <- TRUE #PARAM 12
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multiple_region <- TRUE #PARAM 12
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region_name <- "world" #PARAM 13 |
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plot_region <- TRUE |
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#multiple regions? |
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if(mulitple_region==TRUE){
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if(multiple_region==TRUE){
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df_tile_processed$reg <- basename(dirname(as.character(df_tile_processed$path_NEX))) |
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tb <- merge(tb,df_tile_processed,by="tile_id") |
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#get the files |
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l_reg_name <- unique(df_tile_processed$reg) |
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l_reg_name <- c("reg5")
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#l_reg_name <- c("reg5")
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#lf_mosaics_reg5 <- mixedsort(list.files(path="/data/project/layers/commons/NEX_data/output_run10_global_analyses_11302014/mosaics/reg5", |
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# pattern="CAI_TMAX_clim_month_.*_mod1_all.tif", full.names=T)) |
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lf_mosaics_reg <- vector("list",length=length(l_reg_name))
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lf_world_pred <-list.files(path=file.path(out_dir,"mosaics"), |
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pattern=paste("^reg4.*.",".tif$",sep=""),full.names=T)
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l_reg_name <- unique(df_tile_processed$reg) |
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lf_world_pred <-list.files(path=file.path(out_dir,l_reg_name[[i]]), |
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pattern=paste(".tif$",sep=""),full.names=T)
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#mosaic_list_mean <- test_list |
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#out_rastnames <- "world_test_mosaic_20100101" |
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#lf_world_mask_reg[[i]] <- mclapply(1:length(lf_m),FUN=plot_daily_mosaics,list_param=list_param_plot_daily_mosaics,mc.preschedule=FALSE,mc.cores = 10) |
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} |
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############# NEW MASK AND DATA |
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## Plot areas and day predicted as first check |
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l_reg_name <- unique(df_tile_processed$reg) |
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#(subset(df_tile_processed$reg == l_reg_name[i],date) |
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for(i in 1:length(l_reg_name)){
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lf_world_pred <-list.files(path=file.path(out_dir,l_reg_name[[i]]), |
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pattern=paste(".tif$",sep=""),full.names=T)
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#mosaic_list_mean <- test_list |
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#out_rastnames <- "world_test_mosaic_20100101" |
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#out_path <- out_dir |
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#lf_world_pred <- list.files(pattern="world.*2010090.*.tif$") |
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#lf_raster_fname <- list.files(pattern="world.*2010*.*02162015.tif$",full.names=T) |
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lf_raster_fname <- lf_world_pred |
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prefix_str <- paste("Figure10_",l_reg_name[i],sep="")
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l_dates <- basename(lf_raster_fname) |
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tmp_name <- gsub(".tif","",l_dates)
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tmp_name <- gsub("gam_CAI_dailyTmax_predicted_mod1_0_1_","",tmp_name)
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#l_dates <- tmp_name |
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l_dates <- paste(l_reg_name[i],"_",tmp_name,sep="") |
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screenRast=TRUE |
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list_param_plot_screen_raster <- list(lf_raster_fname,screenRast,l_dates,out_dir,prefix_str,out_suffix) |
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names(list_param_plot_screen_raster) <- c("lf_raster_fname","screenRast","l_dates","out_dir_str","prefix_str","out_suffix_str")
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#undebug(plot_screen_raster_val) |
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#world_m_list1<- plot_screen_raster_val(1,list_param_plot_screen_raster) |
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#world_m_list <- mclapply(11:30, list_param=list_param_plot_screen_raster, plot_screen_raster_val,mc.preschedule=FALSE,mc.cores = num_cores) #This is the end bracket from mclapply(...) statement |
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world_m_list <- mclapply(1:length(l_dates), list_param=list_param_plot_screen_raster, plot_screen_raster_val,mc.preschedule=FALSE,mc.cores = num_cores) #This is the end bracket from mclapply(...) statement |
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#s_pred <- stack(lf_raster_fname) |
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#res_pix <- 1500 |
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#col_mfrow <- 3 |
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#row_mfrow <- 2 |
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#png(filename=paste("Figure10_levelplot_combined_",region_name,"_",out_suffix,".png",sep=""),
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# width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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#levelplot(s_pred,layers=1:6,col.regions=rev(terrain.colors(255)),cex=4) |
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#dev.off() |
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} |
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##################### END OF SCRIPT ###################### |
Also available in: Unified diff
assessment part2 with new mask and buffer being evaluated