Revision e5e3509c
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: 03/25/2015
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#MODIFIED ON: 04/15/2015
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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 and other tiles |
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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_03252015" #PARAM3
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out_dir <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_03252015" #PARAM4
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out_suffix <- "run10_1500x4500_global_analyses_pred_2003_04102015" #PARAM3
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out_dir <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_2003_04102015" #PARAM4
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create_out_dir_param <- FALSE #PARAM 5 |
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mosaic_plot <- FALSE #PARAM6 |
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#if daily mosaics NULL then mosaicas all days of the year |
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day_to_mosaic <- c("20100101","20100102","20100103","20100104","20100105",
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"20100301","20100302","20100303","20100304","20100305",
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"20100501","20100502","20100503","20100504","20100505",
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"20100701","20100702","20100703","20100704","20100705",
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"20100901","20100902","20100903","20100904","20100905",
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"20101101","20101102","20101103","20101104","20101105") #PARAM7
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day_to_mosaic <- c("20030101","20030102","20030103","20030104","20030105",
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"20030301","20030302","20030303","20030304","20030305",
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"20030501","20030502","20030503","20030504","20030505",
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"20030701","20030702","20030703","20030704","20030705",
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"20030901","20030902","20030903","20030904","20030905",
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"20031101","20031102","20031103","20031104","20031105") #PARAM7
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#CRS_locs_WGS84 <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #Station coords WGS84
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CRS_WGS84 <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #Station coords WGS84 #CONSTANT1
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| ... | ... | |
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mulitple_region <- TRUE #PARAM 12 |
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region_name <- "world" #PARAM 13 |
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plot_region <- FALSE |
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plot_region <- TRUE |
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num_cores <- 10 #PARAM 14 |
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########################## START SCRIPT ############################## |
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} |
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## Number of tiles with information: |
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sum(df_tile_processed$metrics_v) #188,number of tiles with raster object
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length(df_tile_processed$metrics_v) #214,number of tiles in the region
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sum(df_tile_processed$metrics_v)/length(df_tile_processed$metrics_v) #87.85% of tiles with info
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sum(df_tile_processed$metrics_v) #20,number of tiles with raster object
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length(df_tile_processed$metrics_v) #25,number of tiles in the region
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sum(df_tile_processed$metrics_v)/length(df_tile_processed$metrics_v) #80 of tiles with info
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#coordinates |
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#coordinates(summary_metrics_v) <- c("lon","lat")
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##################################################### |
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#### Figure 9: plotting mosaics of regions ########### |
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## plot mosaics... |
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#l_reg_name <- unique(df_tile_processed$reg) |
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#lf_mosaics_reg5 <- mixedsort(list.files(path="/data/project/layers/commons/NEX_data/output_run10_global_analyses_11302014/mosaics/reg5", |
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# pattern="CAI_TMAX_clim_month_.*_mod1_all.tif", full.names=T)) |
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#lf_mosaics_reg <- vector("list",length=length(l_reg_name))
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#for(i in 1:length(l_reg_name)){
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# lf_mosaics_reg[[i]] <- try(mixedsort( |
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# list.files( |
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# path=file.path(out_dir,"mosaics"), |
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# #pattern="reg6_.*._CAI_TMAX_clim_month_.*._mod1_all_mean.tif", |
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# pattern=paste(l_reg_name[i],".*._CAI_TMAX_clim_month_.*._mod1_all_mean.tif",sep=""), |
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# full.names=T)) |
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# ) |
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#} |
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#First collect file names |
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#names(lf_mosaics_reg) <- l_reg_name |
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#This part should be automated... |
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#lf_m_mask_reg6_1000x3000 <- mclapply(1:length(lf_m),FUN=plot_daily_mosaics,list_param=list_param_plot_daily_mosaics,mc.preschedule=FALSE,mc.cores = 10) |
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if(plot_region==TRUE){
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#get the files |
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l_reg_name <- unique(df_tile_processed$reg) |
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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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for(i in 1:length(l_reg_name)){
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lf_mosaics_reg[[i]] <- try(mixedsort( |
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list.files( |
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path=file.path(out_dir,"mosaics"), |
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#pattern="reg6_.*._CAI_TMAX_clim_month_.*._mod1_all_mean.tif", |
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pattern=paste(l_reg_name[i],".*._CAI_TMAX_clim_month_.*._mod1_all_mean.tif",sep=""), |
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full.names=T)) |
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) |
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} |
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#now mask and potl |
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lf_mosaics_mask_reg <- vector("list",length=length(l_reg_name))
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for(i in 1:length(l_reg_name)){
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d |
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# |
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lf_m <- lf_mosaics_reg[[i]] |
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out_dir_str <- out_dir |
| ... | ... | |
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#lapply() |
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list_param_plot_daily_mosaics <- list(lf_m=lf_m,reg_name=reg_name,out_dir_str=out_dir_str,out_suffix=out_suffix,l_dates=day_to_mosaic) |
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#lf_m_mask_reg4_1500x4500 <- mclapply(1:2,FUN=plot_daily_mosaics,list_param=list_param_plot_daily_mosaics,mc.preschedule=FALSE,mc.cores = 6) |
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#lf_mosaics_mask_reg[[i]] <- lapply(1:1,FUN=plot_daily_mosaics,list_param=list_param_plot_daily_mosaics) |
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lf_mosaics_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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lf_mosaics_mask_reg[[i]] <- mclapply(1:length(lf_m),FUN=plot_daily_mosaics,list_param=list_param_plot_daily_mosaics,mc.preschedule=FALSE,mc.cores = num_cores)
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} |
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} |
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Also available in: Unified diff
assessment part2, first test for year 2003 predictions in reg5 Africa